WRAP publications sorted by year
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Panyard, D., K. Kim, B. Darst, Y. Deming, X. Zhong, Y. Wu, H. Kang, C. Carlsson, S. Johnson, S. Asthana, C. Engelman, and Q. Lu. “Cerebrospinal Fluid Metabolomics Identifies 19 Brain-Related Phenotype associations.”. Communications Biology, Vol. 4, no. 1, 2021, p. 63.
The study of metabolomics and disease has enabled the discovery of new risk factors, diagnostic markers, and drug targets. For neurological and psychiatric phenotypes, the cerebrospinal fluid (CSF) is of particular importance. However, the CSF metabolome is difficult to study on a large scale due to the relative complexity of the procedure needed to collect the fluid. Here, we present a metabolome-wide association study (MWAS), which uses genetic and metabolomic data to impute metabolites into large samples with genome-wide association summary statistics. We conduct a metabolome-wide, genome-wide association analysis with 338 CSF metabolites, identifying 16 genotype-metabolite associations (metabolite quantitative trait loci, or mQTLs). We then build prediction models for all available CSF metabolites and test for associations with 27 neurological and psychiatric phenotypes, identifying 19 significant CSF metabolite-phenotype associations. Our results demonstrate the feasibility of MWAS to study omic data in scarce sample types.
Van, H., E. Jonaitis, T. Betthauser, R. Batrla, N. Wild, G. Kollmorgen, U. Andreasson, O. Okonkwo, B. Bendlin, S. Asthana, C. Carlsson, S. Johnson, H. Zetterberg, and K. Blennow. “, 2020.
This study examines the utility of a multipanel of cerebrospinal fluid (CSF) biomarkers complementing Alzheimer’s disease (AD) biomarkers in a clinical research sample. We compared biomarkers across groups defined by clinical diagnosis and pTau181 /Aβ42 status (+/-) and explored their value in predicting cognition.
Bruno, D., K. Mueller, T. Betthauser, N. Chin, C. Engelman, B. Christian, R. Koscik, and S. Johnson. “Serial Position Effects in the Logical Memory Test: Loss of Primacy Predicts Amyloid positivity.”. Journal of Neuropsychology, 2020.
Story recall is a frequently used neuropsychological test of episodic memory with clinical populations and for screening participants in drug trials for Alzheimer’s disease. However, it is unclear at this stage which underlying mechanisms confer the test its sensitivity. In this paper, we examined serial position effects, that is, better recall for items learned early and late on a list, in story recall, and their usefulness to predict early changes associated with neurodegenerative markers.
Reyes, A., E. Kaestner, E. Edmonds, M. Christina, Z. Wang, D. Drane, V. Punia, R. Busch, B. Hermann, C. McDonald, and D. Alzheimer’s. “Diagnosing Cognitive Disorders in Older Adults With epilepsy.”. Epilepsia, 2020.
To characterize the nature and prevalence of cognitive disorders in older adults with temporal lobe epilepsy (TLE) and compare their cognitive profiles to patients with amnestic mild cognitive impairment (ie, aMCI).
Luo, J., F. Agboola, E. Grant, C. Masters, M. Albert, S. Johnson, E. McDade, J. Vöglein, A. Fagan, T. Benzinger, P. Massoumzadeh, J. Hassenstab, R. Bateman, J. Morris, R. Perrin, J. Chhatwal, M. Jucker, B. Ghetti, C. Cruchaga, N. Graff-Radford, P. Schofield, H. Mori, and C. Xiong. “Sequence of Alzheimer Disease Biomarker Changes in Cognitively Normal Adults: A Cross-Sectional study.”. Neurology, Vol. 95, no. 23, 2020, pp. e3104-e3116.
To determine the ordering of changes in Alzheimer disease (AD) biomarkers among cognitively normal individuals.
Patterns of decreased resting cerebral blood flow (CBF) within the inferior temporal gyri, angular gyri, and posterior cingulate are a feature of aging and Alzheimer’s disease (AD) and have shown to be predictive of cognitive decline among older adults. Fitness and physical activity are both associated with many indices of brain health and may positively influence CBF, however, the majority of research to date has examined these measures in isolation, leaving the potential independent associations unknown. The purpose of this study was to determine the unique contributions of fitness and physical activity when predicting CBF in cognitively healthy adults at risk for AD. One hundred participants (63% female) from the Wisconsin Registry for Alzheimer’s Prevention underwent a maximal exercise test, physical activity monitoring, and a 3-D arterial spin labeling magnetic resonance imaging scan. For the entire sample, fitness was significantly associated with CBF while accounting for physical activity, age, gender, APOE ε4, family history of AD, education, and handedness (p = .026). Further, fitness explained significantly more variance than the combined effect of the covariates on CBF (R2 change = .059; p = .047). These results appear to be gender dependent, our data suggest fitness level, independent of physical activity, is associated with greater CBF in regions that are known to decline with age and AD for female (p = .011), but not male participants.
Zuelsdorff, M., O. Okonkwo, D. Norton, L. Barnes, K. Graham, L. Clark, M. Wyman, S. Benton, A. Gee, N. Lambrou, S. Johnson, and C. Gleason. “, Vol. 73, no. 2, 2020, pp. 671-82.
It is well-documented that African Americans have elevated risk for cognitive impairment and dementia in late life, but reasons for the racial disparities remain unknown. Stress processes have been linked to premature age-related morbidity, including Alzheimer’s and related dementias (ADRD), and plausibly contribute to social disparities in cognitive aging.
Pomponio, R., G. Erus, M. Habes, J. Doshi, D. Srinivasan, E. Mamourian, V. Bashyam, I. Nasrallah, T. Satterthwaite, Y. Fan, L. Launer, C. Masters, P. Maruff, C. Zhuo, H. Völzke, S. Johnson, J. Fripp, N. Koutsouleris, D. Wolf, R. Gur, R. Gur, J. Morris, M. Albert, H. Grabe, S. Resnick, R. Bryan, D. Wolk, R. Shinohara, H. Shou, and C. Davatzikos. “Harmonization of Large MRI Datasets for the Analysis of Brain Imaging Patterns Throughout the lifespan.”. NeuroImage, Vol. 208, 2020, p. 116450.
As medical imaging enters its information era and presents rapidly increasing needs for big data analytics, robust pooling and harmonization of imaging data across diverse cohorts with varying acquisition protocols have become critical. We describe a comprehensive effort that merges and harmonizes a large-scale dataset of 10,477 structural brain MRI scans from participants without a known neurological or psychiatric disorder from 18 different studies that represent geographic diversity. We use this dataset and multi-atlas-based image processing methods to obtain a hierarchical partition of the brain from larger anatomical regions to individual cortical and deep structures and derive age trends of brain structure through the lifespan (3-96 years old). Critically, we present and validate a methodology for harmonizing this pooled dataset in the presence of nonlinear age trends. We provide a web-based visualization interface to generate and present the resulting age trends, enabling future studies of brain structure to compare their data with this reference of brain development and aging, and to examine deviations from ranges, potentially related to disease.
Betthauser, T., R. Koscik, E. Jonaitis, S. Allison, K. Cody, C. Erickson, H. Rowley, C. Stone, K. Mueller, L. Clark, C. Carlsson, N. Chin, S. Asthana, B. Christian, and S. Johnson. “Amyloid and Tau Imaging Biomarkers Explain Cognitive Decline from Late Middle-age.”. Brain : A Journal of Neurology, Vol. 143, no. 1, 2020, pp. 320-35.
This study investigated differences in retrospective cognitive trajectories between amyloid and tau PET biomarker stratified groups in initially cognitively unimpaired participants sampled from the Wisconsin Registry for Alzheimer’s Prevention. One hundred and sixty-seven initially unimpaired individuals (baseline age 59 ± 6 years; 115 females) were stratified by elevated amyloid-β and tau status based on 11C-Pittsburgh compound B (PiB) and 18F-MK-6240 PET imaging. Mixed effects models were used to determine if longitudinal cognitive trajectories based on a composite of cognitive tests including memory and executive function differed between biomarker groups. Secondary analyses investigated group differences for a variety of cross-sectional health and cognitive tests, and associations between 18F-MK-6240, 11C-PiB, and age. A significant group × age interaction was observed with post hoc comparisons indicating that the group with both elevated amyloid and tau pathophysiology were declining approximately three times faster in retrospective cognition compared to those with just one or no elevated biomarkers. This result was robust against various thresholds and medial temporal lobe regions defining elevated tau. Participants were relatively healthy and mostly did not differ between biomarker groups in health factors at the beginning or end of study, or most cognitive measures at study entry. Analyses investigating association between age, MK-6240 and PiB indicated weak associations between age and 18F-MK-6240 in tangle-associated regions, which were negligible after adjusting for 11C-PiB. Strong associations, particularly in entorhinal cortex, hippocampus and amygdala, were observed between 18F-MK-6240 and global 11C-PiB in regions associated with Braak neurofibrillary tangle stages I-VI. These results suggest that the combination of pathological amyloid and tau is detrimental to cognitive decline in preclinical Alzheimer’s disease during late middle-age. Within the Alzheimer’s disease continuum, middle-age health factors likely do not greatly influence preclinical cognitive decline. Future studies in a larger preclinical sample are needed to determine if and to what extent individual contributions of amyloid and tau affect cognitive decline. 18F-MK-6240 shows promise as a sensitive biomarker for detecting neurofibrillary tangles in preclinical Alzheimer’s disease.
Hunt, J., W. Buckingham, A. Kim, J. Oh, N. Vogt, E. Jonaitis, T. Hunt, M. Zuelsdorff, R. Powell, D. Norton, R. Rissman, S. Asthana, O. Okonkwo, S. Johnson, A. Kind, and B. Bendlin. “Association of Neighborhood-Level Disadvantage With Cerebral and Hippocampal Volume.”. JAMA Neurology, Vol. 77, no. 4, 2020, pp. 451-60.
Identifying risk factors for brain atrophy during the aging process can help direct new preventive approaches for dementia and cognitive decline. The association of neighborhood socioeconomic disadvantage with brain volume in this context is not well known.
Agelink, van, V. de, B. Schmand, J. Murre, J. Staaks, C. ANDI, and H. Huizenga. “The Factor Structure of Cognitive Functioning in Cognitively Healthy Participants: A Meta-Analysis and Meta-Analysis of Individual Participant Data.”. Neuropsychology Review, Vol. 30, no. 1, 2020, pp. 51-96.
Many neuropsychologists are of the opinion that the multitude of cognitive tests may be grouped into a much smaller number of cognitive domains. However, there is little consensus on how many domains exist, what these domains are, nor on which cognitive tests belong to which domain. This incertitude can be solved by factor analysis, provided that the analysis includes a broad range of cognitive tests that have been administered to a very large number of people. In this article, two such factor analyses were performed, each combining multiple studies. However, because it was not possible to obtain complete multivariate data on more than the most common test variables in the field, not all possible domains were examined here. The first analysis was a factor meta-analysis of correlation matrices combining data of 60,398 healthy participants from 52 studies. Several models from the literature were fitted, of which a version based on the Cattell-Horn-Carroll (CHC) model was found to describe the correlations better than the others. The second analysis was a factor analysis of the Advanced Neuropsychological Diagnostics Infrastructure (ANDI) database, combining scores of 11,881 participants from 54 Dutch and Belgian studies not included in the first meta-analysis. Again, the model fit was better for the CHC model than for other models. Therefore, we conclude that the CHC model best characterizes both cognitive domains and which test belongs to each domain. Therefore, although originally developed in the intelligence literature, the CHC model deserves more attention in neuropsychology.
Zemla, J., K. Cao, K. Mueller, and J. Austerweil. “SNAFU: The Semantic Network and Fluency Utility.”. Behavior Research Methods, Vol. 52, no. 4, 2020, pp. 1681-99.
The verbal fluency task-listing words from a category or words that begin with a specific letter-is a common experimental paradigm that is used to diagnose memory impairments and to understand how we store and retrieve knowledge. Data from the verbal fluency task are analyzed in many different ways, often requiring manual coding that is time intensive and error-prone. Researchers have also used fluency data from groups or individuals to estimate semantic networks-latent representations of semantic memory that describe the relations between concepts-that further our understanding of how knowledge is encoded. However computational methods used to estimate networks are not standardized and can be difficult to implement, which has hindered widespread adoption. We present SNAFU: the Semantic Network and Fluency Utility, a tool for estimating networks from fluency data and automatizing traditional fluency analyses, including counting cluster switches and cluster sizes, intrusions, perseverations, and word frequencies. In this manuscript, we provide a primer on using the tool, illustrate its application by creating a semantic network for foods, and validate the tool by comparing results to trained human coders using multiple datasets.
Clinical evidence shows vascular factors may co-occur and complicate the expression of Alzheimer’s disease (AD); yet, the pathologic mechanisms and involvement of different compartments of the vascular network are not well understood. Diseases such as arteriosclerosis diminish vascular compliance and will lead to arterial stiffness, a well-established risk factor for cardiovascular morbidity. Arterial stiffness can be assessed using pulse wave velocity (PWV); however, this is usually done from carotid-to-femoral artery ratios. To probe the brain vasculature, intracranial PWV measures would be ideal. In this study, high temporal resolution 4D flow MRI was used to assess transcranial PWV in 160 subjects including AD, mild cognitive impairment (MCI), healthy controls, and healthy subjects with apolipoprotein ɛ4 positivity (APOE4+) and parental history of AD dementia (FH+). High temporal resolution imaging was achieved by high temporal binning of retrospectively gated data using a local-low rank approach. Significantly higher transcranial PWV in AD dementia and MCI subjects was found when compared to old-age-matched controls (AD vs. old-age-matched controls: P <0.001, AD vs. MCI: P = 0.029, MCI vs. old-age-matched controls P = 0.013). Furthermore, vascular changes were found in clinically healthy middle-age adults with APOE4+ and FH+ indicating significantly higher transcranial PWV compared to controls (P <0.001). DOI: 10.1177/0271678X20910302
Koscik, R., T. Betthauser, E. Jonaitis, S. Allison, L. Clark, B. Hermann, K. Cody, J. Engle, T. Barnhart, C. Stone, N. Chin, C. Carlsson, S. Asthana, B. Christian, and S. Johnson. “, Vol. 12, no. 1, 2020, p. e12007.
This study applies a novel algorithm to longitudinal amyloid positron emission tomography (PET) imaging to identify age-heterogeneous amyloid trajectory groups, estimate the age and duration (chronicity) of amyloid positivity, and investigate chronicity in relation to cognitive decline and tau burden.
Studies have suggested associations between self-reported engagement in health behaviors and reduced risk of cognitive decline. Most studies explore these relationships using one health behavior, often cross-sectionally or with dementia as the outcome. In this study, we explored whether several individual self-reported health behaviors were associated with cognitive decline when considered simultaneously, using data from the Wisconsin Registry for Alzheimer’s Prevention (WRAP), an Alzheimer’s disease risk-enriched cohort who were non-demented and in late midlife at baseline.
Zuelsdorff, M., J. Larson, J. Hunt, A. Kim, R. Koscik, W. Buckingham, C. Gleason, S. Johnson, S. Asthana, R. Rissman, B. Bendlin, and A. Kind. “, Vol. 6, no. 1, 2020, p. e12039.
Residence in a disadvantaged neighborhood associates with adverse health exposures and outcomes, and may increase risk for cognitive impairment and dementia. Utilization of a publicly available, geocoded disadvantage metric could facilitate efficient integration of social determinants of health into models of cognitive aging.
Raghavan, N., L. Dumitrescu, E. Mormino, E. Mahoney, A. Lee, Y. Gao, M. Bilgel, D. Goldstein, T. Harrison, C. Engelman, A. Saykin, C. Whelan, J. Liu, W. Jagust, M. Albert, S. Johnson, H. Yang, K. Johnson, P. Aisen, S. Resnick, R. Sperling, J. De, J. Schneider, D. Bennett, M. Schrag, B. Vardarajan, T. Hohman, R. Mayeux, and D. Alzheimer’s. “Association Between Common Variants in RBFOX1, an RNA-Binding Protein, and Brain Amyloidosis in Early and Preclinical Alzheimer Disease.”. JAMA Neurology, 2020.
Genetic studies of Alzheimer disease have focused on the clinical or pathologic diagnosis as the primary outcome, but little is known about the genetic basis of the preclinical phase of the disease.
Bashyam, V., G. Erus, J. Doshi, M. Habes, I. Nasralah, M. Truelove-Hill, D. Srinivasan, L. Mamourian, R. Pomponio, Y. Fan, L. Launer, C. Masters, P. Maruff, C. Zhuo, H. Völzke, S. Johnson, J. Fripp, N. Koutsouleris, T. Satterthwaite, D. Wolf, R. Gur, R. Gur, J. Morris, M. Albert, H. Grabe, S. Resnick, R. Bryan, D. Wolk, H. Shou, and C. Davatzikos. “MRI Signatures of Brain Age and Disease over the Lifespan Based on a Deep Brain Network and 14 468 Individuals worldwide.”. Brain : A Journal of Neurology, Vol. 143, no. 7, 2020, pp. 2312-24.
Deep learning has emerged as a powerful approach to constructing imaging signatures of normal brain ageing as well as of various neuropathological processes associated with brain diseases. In particular, MRI-derived brain age has been used as a comprehensive biomarker of brain health that can identify both advanced and resilient ageing individuals via deviations from typical brain ageing. Imaging signatures of various brain diseases, including schizophrenia and Alzheimer’s disease, have also been identified using machine learning. Prior efforts to derive these indices have been hampered by the need for sophisticated and not easily reproducible processing steps, by insufficiently powered or diversified samples from which typical brain ageing trajectories were derived, and by limited reproducibility across populations and MRI scanners. Herein, we develop and test a sophisticated deep brain network (DeepBrainNet) using a large (n = 11 729) set of MRI scans from a highly diversified cohort spanning different studies, scanners, ages and geographic locations around the world. Tests using both cross-validation and a separate replication cohort of 2739 individuals indicate that DeepBrainNet obtains robust brain-age estimates from these diverse datasets without the need for specialized image data preparation and processing. Furthermore, we show evidence that moderately fit brain ageing models may provide brain age estimates that are most discriminant of individuals with pathologies. This is not unexpected as tightly-fitting brain age models naturally produce brain-age estimates that offer little information beyond age, and loosely fitting models may contain a lot of noise. Our results offer some experimental evidence against commonly pursued tightly-fitting models. We show that the moderately fitting brain age models obtain significantly higher differentiation compared to tightly-fitting models in two of the four disease groups tested. Critically, we demonstrate that leveraging DeepBrainNet, along with transfer learning, allows us to construct more accurate classifiers of several brain diseases, compared to directly training classifiers on patient versus healthy control datasets or using common imaging databases such as ImageNet. We, therefore, derive a domain-specific deep network likely to reduce the need for application-specific adaptation and tuning of generic deep learning networks. We made the DeepBrainNet model freely available to the community for MRI-based evaluation of brain health in the general population and over the lifespan.
Talamonti, D., R. Koscik, S. Johnson, and D. Bruno. “Temporal Contiguity and Ageing: The Role of Memory Organization in Cognitive decline.”. Journal of Neuropsychology, 2020.
The temporal contiguity effect is the tendency to form associations between items presented in nearby study positions. In the present study, we explored whether temporal contiguity predicted conversion to cognitively unimpaired-declining (CUD) status from a baseline of unimpaired older adults. Data from 419 participants were drawn from the Wisconsin Registry of Alzheimer’s Prevention (WRAP) data set and analysed with binary logistic regressions. Temporal contiguity was calculated using the Rey Auditory Verbal Learning Test. Other predictors included age, years of education, sex, APOE-ε4 status, and other measures of memory recall. Lower temporal contiguity predicted conversion to CUD after accounting for covariates. These findings support the hypothesis that temporal organization in memory is related to cognitive decline and suggest that temporal contiguity may be used for studies of early detection.
Morris, J., G. Zhang, R. Dougherty, J. Mahnken, C. John, S. Lose, D. Cook, J. Burns, E. Vidoni, and O. Okonkwo. “, Vol. 12, no. 1, 2020, p. e12058.
Individuals with Alzheimer’s disease (AD) broadly exhibit lower cardiorespiratory fitness (CRF) compared to cognitively healthy older adults. Other factors, such as increasing age and female sex, are also known to track with lower CRF levels. However, it is unclear how these factors together with AD diagnosis and genetic risk (apolipoprotein e4 ; APOE4) collectively affect CRF.
Due to advances in the early detection of Alzheimer’s disease (AD) biomarkers including beta-amyloid (Aβ), neuropsychological measures that are sensitive to concurrent, subtle changes in cognition are critically needed. Story recall tasks have shown sensitivity to early memory declines in persons with mild cognitive impairment (MCI) and early stage dementia, as well as in persons with autosomal dominantly inherited AD up to 10 years prior to a dementia diagnosis. However, the evidence is inconclusive regarding relationships between evidence of Aβ and story recall measures. Because story recall tasks require the encoding and delayed retrieval of several lexical-semantic categories, such as proper names, verbs, and numerical expressions, and because lexical categories have been shown to be differentially impaired in persons with MCI, we focused on item-level analyses of lexical-semantic retrieval from a quintessential story recall task, Logical Memory from the Wechsler Memory Scale-Revised. Our objective was to investigate whether delayed recall of lexical categories (proper names, verbs and/or numerical expressions), as well as the traditional total score measure, was associated with “preclinical AD,” or cognitively unimpaired adults with positive Aβ deposition on positron emission tomography (PET) neuroimaging using Pittsburgh Compound B (PiB). We developed an item-level scoring system, in which we parsed items into lexical categories and examined the immediate and delayed recall of these lexical categories from 217 cognitively unimpaired participants from the Wisconsin Registry for Alzheimer’s Prevention (WRAP). We performed binary logistic regression models with story recall score as predictor and Aβ status (positive/negative) as the outcome. Using baseline Logical Memory data, proper names from delayed story recall were significantly associated with Aβ status, such that participants who recalled more proper names were less likely to be classified as PiB(+) (odds ratio = .58, p = .01). None of the other story recall variables, including total score, were associated with PiB status. Secondary analyses determined that immediate recall of proper names was not significantly associated with Aβ, suggesting a retrieval deficit rather than that of encoding. The present findings suggest that lexical semantic retrieval measures from existing story recall tasks may be sensitive to Aβ deposition, and may provide added utility to a widely-used, long-standing neuropsychological test for early detection of cognitive decline on the AD continuum.
Alzheimer’s disease (AD) is characterized by substantial neurodegeneration, including both cortical atrophy and loss of underlying white matter fiber tracts. Understanding longitudinal alterations to white matter may provide new insights into trajectories of brain change in both healthy aging and AD, and fluid biomarkers may be particularly useful in this effort. To examine this, 151 late-middle-aged participants enriched with risk for AD with at least one lumbar puncture and two diffusion tensor imaging (DTI) scans were selected for analysis from two large observational and longitudinally followed cohorts. Cerebrospinal fluid (CSF) was assayed for biomarkers of AD-specific pathology (phosphorylated-tau/Aβ42 ratio), axonal degeneration (neurofilament light chain protein, NFL), dendritic degeneration (neurogranin), and inflammation (chitinase-3-like protein 1, YKL-40). Linear mixed effects models were performed to test the hypothesis that biomarkers for AD, neurodegeneration, and inflammation, or two-year change in those biomarkers, would be associated with worse white matter health overall and/or progressively worsening white matter health over time. At baseline in the cingulum, phosphorylated-tau/Aβ42 was associated with higher mean diffusivity (MD) overall (intercept) and YKL-40 was associated with increases in MD over time. Two-year change in neurogranin was associated with higher mean diffusivity and lower fractional anisotropy overall (intercepts) across white matter in the entire brain and in the cingulum. These findings suggest that biomarkers for AD, neurodegeneration, and inflammation are potentially important indicators of declining white matter health in a cognitively healthy, late-middle-aged cohort.
Zuelsdorff, M., R. Koscik, O. Okonkwo, P. Peppard, B. Hermann, M. Sager, S. Johnson, and C. Engelman. “Social Support and Verbal Interaction Are Differentially Associated With Cognitive Function in Midlife and Older age.”. Neuropsychology, Development, and Cognition. Section B, Aging, Neuropsychology and Cognition, Vol. 26, no. 2, 2019, pp. 144-60.
Social engagement is associated with healthy aging and preserved cognition. Two dimensions of engagement, verbal interactions and perceived support, likely impact cognition via distinct mechanistic pathways. We explored the cognitive benefit of each construct among enrollees (N = 1,052, mean age = 60.2 years) in the Wisconsin Registry for Alzheimer’s Prevention study, who provide neuropsychological and sociobehavioral data at two-year intervals. Outcomes included six cognitive factor scores representing key domains of executive function and memory. Key predictors included self-reported perceived social support and weekly verbal interaction. Results indicated that after adjusting for lifestyle covariates, social support was positively associated with Speed and Flexibility and that verbal interactions were associated with Verbal Learning and Memory. These findings suggest that support, which may buffer stress, and verbal interaction, an accessible, aging-friendly form of environmental enrichment, are uniquely beneficial. Both are integral in the design of clinical and community interventions and programs that promote successful aging.
Betthauser, T., K. Cody, M. Zammit, D. Murali, A. Converse, T. Barnhart, C. Stone, H. Rowley, S. Johnson, and B. Christian. “In Vivo Characterization and Quantification of Neurofibrillary Tau PET Radioligand 18F-MK-6240 in Humans from Alzheimer Disease Dementia to Young Controls.”. Journal of Nuclear Medicine : Official Publication, Society of Nuclear Medicine, Vol. 60, no. 1, 2019, pp. 93-99.
Tau PET imaging has potential for elucidating changes in the deposition of neuropathological tau aggregates that are occurring during the progression of Alzheimer disease (AD). This work investigates in vivo kinetics, quantification strategies, and imaging characteristics of a novel tau PET radioligand 18F-MK-6240 in humans. Methods: Fifty-one individuals ranging from cognitively normal young controls to persons with dementia underwent T1-weighted MRI as well as 11C-PiB and 18F-MK-6240 PET imaging. PET data were coregistered to the MRI, and time-activity curves were extracted from regions of interest to assess 18F-MK-6240 kinetics. The pons and inferior cerebellum were investigated as potential reference regions. Reference tissue methods (Logan graphical analysis [LGA] and multilinear reference tissue method [MRTM2]) were investigated for quantification of 18F-MK-6240 distribution volume ratios (DVRs) in a subset of 19 participants. Stability of DVR methods was evaluated using truncated scan durations. SUV ratio (SUVR) estimates were compared with DVR estimates to determine the optimal timing window for SUVR analysis. Parametric SUVR images were used to identify regions of potential off-target binding and to compare binding patterns with neurofibrillary tau staging established in neuropathology literature. Results: SUVs in the pons and the inferior cerebellum indicated consistent clearance across all 51 subjects. LGA and MRTM2 DVR estimates were similar, with LGA slightly underestimating DVR compared with MRTM2. DVR estimates remained stable when truncating the scan duration to 60 min. SUVR determined 70-90 min after injection of 18F-MK-6240 indicated linearity near unity when compared with DVR estimates and minimized potential spill-in from uptake outside the brain. 18F-MK-6240 binding patterns in target regions were consistent with neuropathological neurofibrillary tau staging. Off-target binding regions included the ethmoid sinus, clivus, meninges, substantia nigra, but not the basal ganglia or choroid plexus. Conclusion:18F-MK-6240 is a promising PET radioligand for in vivo imaging of neurofibrillary tau aggregates in AD with minimal off-target binding in the human brain.
Characterizing Alzheimer’s disease (AD) at pre-clinical stages is crucial for initiating early treatment strategies. It is widely accepted that amyloid accumulation is a primary pathological event in AD. Also, loss of connectivity between brain regions is suspected of contributing to cognitive decline, but studies that test these associations using either local (i.e., individual edges) or global (i.e., modularity) connectivity measures may be limited. In this study, we utilized data acquired from 139 cognitively unimpaired participants. Sixteen gray matter (GM) regions known to be affected by AD were selected for analysis. For each of the 16 regions, the effect of amyloid burden, measured using Pittsburgh Compound B (PiB) positron emission tomography, on each of the 1761 brain network connections derived from diffusion tensor imaging (DTI) connecting 162 GM regions, was investigated. Applying our unique multiresolution statistical analysis called the Wavelet Connectivity Signature (WaCS), this study demonstrates the relationship between amyloid burden and structural brain connectivity as assessed with DTI. Our statistical analysis using WaCS shows that in 15 of 16 GM regions, statistically significant relationships between amyloid burden in those regions and structural connectivity networks were observed. After applying multiple testing correction, 10 unique structural brain connections were found to be significantly associated with amyloid accumulation. For 7 of those 10 network connections, the decrease in their network connection strength indexed by fractional anisotropy was, in turn, associated with lower cognitive function, providing evidence that AD-related structural connectivity loss is a correlate of cognitive decline.
Clark, L., R. Koscik, S. Allison, S. Berman, D. Norton, C. Carlsson, T. Betthauser, B. Bendlin, B. Christian, N. Chin, S. Asthana, and S. Johnson. “, Vol. 15, no. 3, 2019, pp. 418-2.
This study tested if central obesity, hypertension, or depressive symptoms moderated the relationship between β-amyloid (Aβ) and longitudinal cognitive performance in late middle-aged adults enriched for Alzheimer’s disease (AD) risk.
A major challenge in cognitive aging is differentiating preclinical disease-related cognitive decline from changes associated with normal aging. Neuropsychological test authors typically publish single time-point norms, referred to here as unconditional reference values. However, detecting significant change requires longitudinal, or conditional reference values, created by modeling cognition as a function of prior performance. Our objectives were to create, depict, and examine preliminary validity of unconditional and conditional reference values for ages 40-75 years on neuropsychological tests.
Kim, W., A. Racine, N. Adluru, S. Hwang, K. Blennow, H. Zetterberg, C. Carlsson, S. Asthana, R. Koscik, S. Johnson, B. Bendlin, and V. Singh. “Cerebrospinal Fluid Biomarkers of Neurofibrillary Tangles and Synaptic Dysfunction Are Associated With Longitudinal Decline in White Matter Connectivity: A Multi-Resolution Graph analysis.”. NeuroImage. Clinical, Vol. 21, 2019, p. 101586.
In addition to the development of beta amyloid plaques and neurofibrillary tangles, Alzheimer’s disease (AD) involves the loss of connecting structures including degeneration of myelinated axons and synaptic connections. However, the extent to which white matter tracts change longitudinally, particularly in the asymptomatic, preclinical stage of AD, remains poorly characterized. In this study we used a novel graph wavelet algorithm to determine the extent to which microstructural brain changes evolve in concert with the development of AD neuropathology as observed using CSF biomarkers. A total of 118 participants with at least two diffusion tensor imaging (DTI) scans and one lumbar puncture for CSF were selected from two observational and longitudinally followed cohorts. CSF was assayed for pathology specific to AD (Aβ42 and phosphorylated-tau), neurodegeneration (total-tau), axonal degeneration (neurofilament light chain protein; NFL), and synaptic degeneration (neurogranin). Tractography was performed on DTI scans to obtain structural connectivity networks with 160 nodes where the nodes correspond to specific brain regions of interest (ROIs) and their connections were defined by DTI metrics (i.e., fractional anisotropy (FA) and mean diffusivity (MD)). For the analysis, we adopted a multi-resolution graph wavelet technique called Wavelet Connectivity Signature (WaCS) which derives higher order representations from DTI metrics at each brain connection. Our statistical analysis showed interactions between the CSF measures and the MRI time interval, such that elevated CSF biomarkers and longer time were associated with greater longitudinal changes in white matter microstructure (decreasing FA and increasing MD). Specifically, we detected a total of 17 fiber tracts whose WaCS representations showed an association between longitudinal decline in white matter microstructure and both CSF p-tau and neurogranin. While development of neurofibrillary tangles and synaptic degeneration are cortical phenomena, the results show that they are also associated with degeneration of underlying white matter tracts, a process which may eventually play a role in the development of cognitive decline and dementia.
Prior research has identified numerous genetic (including sex), education, health, and lifestyle factors that predict cognitive decline. Traditional model selection approaches (e.g., backward or stepwise selection) attempt to find one model that best fits the observed data, risking interpretations that only the selected predictors are important. In reality, several predictor combinations may fit similarly well but result in different conclusions (e.g., about size and significance of parameter estimates). In this study, we describe an alternative method, Information-Theoretic (IT) model averaging, and apply it to characterize a set of complex interactions in a longitudinal study on cognitive decline.
Darst, B., R. Koscik, K. Hogan, S. Johnson, and C. Engelman. “Longitudinal Plasma Metabolomics of Aging and sex.”. Aging, Vol. 11, no. 4, 2019, pp. 1262-8.
Understanding how metabolites are longitudinally influenced by age and sex could facilitate the identification of metabolomic profiles and trajectories that indicate disease risk. We investigated the metabolomics of age and sex using longitudinal plasma samples from the Wisconsin Registry for Alzheimer’s Prevention (WRAP), a cohort of participants who were dementia free at enrollment. Metabolomic profiles were quantified for 2,344 fasting plasma samples among 1,212 participants, each with up to three study visits. Of 1,097 metabolites tested, 623 (56.8%) were associated with age and 695 (63.4%) with sex after correcting for multiple testing. Approximately twice as many metabolites were associated with age in stratified analyses of women versus men, and 68 metabolite trajectories significantly differed by sex, most notably including sphingolipids, which tended to increase in women and decrease in men with age. Using genome-wide genotyping, we also report the heritabilities of metabolites investigated, which ranged dramatically (0.2-99.2%); however, the median heritability of 36.2% suggests that many metabolites are highly influenced by a complex combination of genomic and environmental influences. These findings offer a more profound description of the aging process and may inform many new hypotheses regarding the role metabolites play in healthy and accelerated aging.
Characterization of longitudinal trajectories of biomarkers implicated in sporadic Alzheimer’s disease (AD) in decades before clinical diagnosis is important for disease prevention and monitoring.
Law, L., K. Sprecher, R. Dougherty, D. Edwards, R. Koscik, C. Gallagher, C. Carlsson, H. Zetterberg, K. Blennow, S. Asthana, M. Sager, B. Hermann, S. Johnson, D. Cook, B. Bendlin, and O. Okonkwo. “, Vol. 69, no. 1, 2019, pp. 111-2.
Previous studies indicate that cardiorespiratory fitness (CRF) and sleep are each favorably associated with Alzheimer’s disease (AD) pathophysiology, including reduced amyloid-β (Aβ) and tau pathology. However, few studies have examined CRF and sleep in the same analysis.
Merluzzi, A., N. Vogt, D. Norton, E. Jonaitis, L. Clark, C. Carlsson, S. Johnson, S. Asthana, K. Blennow, H. Zetterberg, and B. Bendlin. “, Vol. 5, 2019, pp. 129-38.
Neurodegeneration appears to be the biological mechanism most proximate to cognitive decline in Alzheimer’s disease. We test whether t-tau and alternative biomarkers of neurodegeneration-neurogranin and neurofilament light protein (NFL)-add value in predicting subclinical cognitive decline.
Although Alzheimer’s disease (AD) is highly heritable, genetic variants are known to be associated with AD only explain a small proportion of its heritability. Genetic factors may only convey disease risk in individuals with certain environmental exposures, suggesting that a multiomics approach could reveal underlying mechanisms contributing to complex traits, such as AD. We developed an integrated network to investigate relationships between metabolomics, genomics, and AD risk factors using Wisconsin Registry for Alzheimer’s Prevention participants. Analyses included 1,111 non-Hispanic Caucasian participants with whole blood expression for 11,376 genes (imputed from dense genome-wide genotyping), 1,097 fasting plasma metabolites, and 17 AD risk factors. A subset of 155 individuals also had 364 fastings cerebral spinal fluid (CSF) metabolites. After adjusting each of these 12,854 variables for potential confounders, we developed an undirected graphical network, representing all significant pairwise correlations upon adjusting for multiple testing. There were many instances of genes being indirectly linked to AD risk factors through metabolites, suggesting that genes may influence AD risk through particular metabolites. Follow-up analyses suggested that glycine mediates the relationship between carbamoyl-phosphate synthase 1 and measures of cardiovascular and diabetes risk, including body mass index, waist-hip ratio, inflammation, and insulin resistance. Further, 38 CSF metabolites explained more than 60% of the variance of CSF levels of tau, a detrimental protein that accumulates in the brain of AD patients and is necessary for its diagnosis. These results further our understanding of underlying mechanisms contributing to AD risk while demonstrating the utility of generating and integrating multiple omics data types.
Several neurodegeneration (N) metrics using structural MRI are used for the purpose of Alzheimer’s disease (AD)-related staging, including hippocampal volume, global atrophy, and an “AD signature” composite consisting of thickness or volumetric estimates derived from regions impacted early in AD. This study sought to determine if less user-intensive estimates of global atrophy and hippocampal volume were equivalent to a thickness-based AD signature from FreeSurfer for defining N across the AD continuum (i.e., individuals who are amyloid-positive (A+)).
O’Grady, J., D. Dean, K. Yang, C. Canda, S. Hoscheidt, E. Starks, A. Merluzzi, S. Hurley, N. Davenport, O. Okonkwo, R. Anderson, S. Asthana, S. Johnson, A. Alexander, and B. Bendlin. “Elevated Insulin and Insulin Resistance Are Associated With Altered Myelin in Cognitively Unimpaired Middle-Aged Adults.”. Obesity (Silver Spring, Md.), Vol. 27, no. 9, 2019, pp. 1464-71.
Insulin regulates metabolism and influences neural health. Insulin resistance (IR) and type II diabetes have been identified as risk factors for Alzheimer disease (AD). Evidence has also suggested that myelinated white matter alterations may be involved in the pathophysiology of AD; however, it is unknown whether insulin or IR affect the underlying myelin microstructure. The relationships between insulin, IR, and myelin were examined, with the hypothesis that IR would be associated with reduced myelin.
Dumitrescu, L., L. Barnes, M. Thambisetty, G. Beecham, B. Kunkle, W. Bush, K. Gifford, L. Chibnik, S. Mukherjee, J. De, W. Kukull, P. Crane, S. Resnick, C. Keene, T. Montine, G. Schellenberg, Y. Deming, M. Chao, M. Huentelman, E. Martin, K. Hamilton-Nelson, L. Shaw, J. Trojanowski, E. Peskind, C. Cruchaga, M. Pericak-Vance, A. Goate, N. Cox, J. Haines, H. Zetterberg, K. Blennow, E. Larson, S. Johnson, M. Albert, D. Alzheimer’s, D. Bennett, J. Schneider, A. Jefferson, and T. Hohman. “”. Brain : A Journal of Neurology, Vol. 142, no. 9, 2019, pp. 2581-9.
Autopsy measures of Alzheimer’s disease neuropathology have been leveraged as endophenotypes in previous genome-wide association studies (GWAS). However, despite evidence of sex differences in Alzheimer’s disease risk, sex-stratified models have not been incorporated into previous GWAS analyses. We looked for sex-specific genetic associations with Alzheimer’s disease endophenotypes from six brain bank data repositories. The pooled dataset included 2701 males and 3275 females, the majority of whom were diagnosed with Alzheimer’s disease at autopsy (70%). Sex-stratified GWAS were performed within each dataset and then meta-analysed. Loci that reached genome-wide significance (P < 5 × 10-8) in stratified models were further assessed for sex interactions. Additional analyses were performed in independent datasets leveraging cognitive, neuroimaging and CSF endophenotypes, along with age-at-onset data. Outside of the APOE region, one locus on chromosome 7 (rs34331204) showed a sex-specific association with neurofibrillary tangles among males (P = 2.5 × 10-8) but not females (P = 0.85, sex-interaction P = 2.9 × 10-4). In follow-up analyses, rs34331204 was also associated with hippocampal volume, executive function, and age-at-onset only among males. These results implicate a novel locus that confers male-specific protection from tau pathology and highlight the value of assessing genetic associations in a sex-specific manner. DOI: 10.1093/brain/awz206
Xiong, C., J. Luo, F. Agboola, Y. Li, M. Albert, S. Johnson, R. Koscik, C. Masters, A. Soldan, V. Villemagne, Q. Li, E. McDade, A. Fagan, P. Massoumzadeh, T. Benzinger, J. Hassenstab, R. Bateman, J. Morris, and I. Dominantly. “, Vol. 15, no. 11, 2019, pp. 1448-57.
Large longitudinal biomarkers database focusing on middle age is needed for Alzheimer’s disease (AD) prevention.
Guerrero, J., N. Adluru, B. Bendlin, H. Goldsmith, S. Schaefer, R. Davidson, S. Kecskemeti, H. Zhang, and A. Alexander. “Optimizing the Intrinsic Parallel Diffusivity in NODDI: An Extensive Empirical evaluation.”. PloS One, Vol. 14, no. 9, 2019, p. e0217118.
NODDI is widely used in parameterizing microstructural brain properties. The model includes three signal compartments: intracellular, extracellular, and free water. The neurite compartment intrinsic parallel diffusivity (d∥) is set to 1.7 μm2⋅ms-1, though the effects of this assumption have not been extensively explored. This work investigates the optimality of d∥ = 1.7 μm2⋅ms-1 under varying imaging protocol, age groups, sex, and tissue type in comparison to other biologically plausible values of d∥.
Jonaitis, E., R. Koscik, L. Clark, Y. Ma, T. Betthauser, S. Berman, S. Allison, K. Mueller, B. Hermann, H. Van, B. Christian, B. Bendlin, K. Blennow, H. Zetterberg, C. Carlsson, S. Asthana, and S. Johnson. “, Vol. 11, 2019, pp. 74-84.
Longitudinal cohort studies of cognitive aging must confront several sources of within-person variability in scores. In this article, we compare several neuropsychological measures in terms of longitudinal error variance and relationships with biomarker-assessed brain amyloidosis (Aβ).
Aerobic exercise has been associated with reduced burden of brain and cognitive changes related to Alzheimer’s disease (AD). However, it is unknown whether exercise training in asymptomatic individuals harboring risk for AD improves outcomes associated with AD. We investigated the effect of 26 weeks of supervised aerobic treadmill exercise training on brain glucose metabolism and cognition among 23 late-middle-aged adults from a cohort enriched with familial and genetic risk of AD. They were randomized to Usual Physical Activity (PA) or Enhanced PA conditions. Usual PA received instruction about maintaining an active lifestyle. Enhanced PA completed a progressive exercise training program consisting of 3 sessions of treadmill walking per week for 26 weeks. By week seven, participants exercised at 70- 80% heart rate reserve for 50 minutes per session to achieve 150 minutes of moderate intensity activity per week in accordance with public health guidelines. Before and after the intervention, participants completed a graded treadmill test to assess VO2peak as a measure of cardiorespiratory fitness (CRF), wore an accelerometer to measure free-living PA, underwent 18F-fluorodeoxyglucose positron emission tomography imaging to assess brain glucose metabolism, and a neuropsychological battery to assess episodic memory and executive function. VO2peak increased, sedentary behavior decreased, and moderate-to-vigorous PA increased significantly in the Enhanced PA group as compared to Usual PA. Glucose metabolism in the posterior cingulate cortex (PCC) did not change significantly in Enhanced PA relative to Usual PA. However, change in PCC glucose metabolism correlated positively with change in VO2peak. Executive function, but not episodic memory, was significantly improved after Enhanced PA relative to Usual PA. Improvement in executive function correlated with increased VO2peak. Favorable CRF adaptation after 26 weeks of aerobic exercise training was associated with improvements in PCC glucose metabolism and executive function, important markers of AD.
Hwang, S., R. Mehta, H. Kim, S. Johnson, and V. Singh. “Sampling-Free Uncertainty Estimation in Gated Recurrent Units With Applications to Normative Modeling in Neuroimaging.”. Uncertainty in Artificial Intelligence : Proceedings of the ... Conference. Conference on Uncertainty in Artificial Intelligence, Vol. 2019, 2019.
There has recently been a concerted effort to derive mechanisms in vision and machine learning systems to offer uncertainty estimates of the predictions they make. Clearly, there are benefits to a system that is not only accurate but also has a sense for when it is not. Existing proposals center around Bayesian interpretations of modern deep architectures – these are effective but can often be computationally demanding. We show how classical ideas in the literature on exponential families on probabilistic networks provide an excellent starting point to derive uncertainty estimates in Gated Recurrent Units (GRU). Our proposal directly quantifies uncertainty deterministically, without the need for costly sampling-based estimation. We show that while uncertainty is quite useful by itself in computer vision and machine learning, we also demonstrate that it can play a key role in enabling statistical analysis with deep networks in neuroimaging studies with normative modeling methods. To our knowledge, this is the first result describing sampling-free uncertainty estimation for powerful sequential models such as GRUs.
Zhen, X., R. Chakraborty, N. Vogt, B. Bendlin, and V. Singh. “Dilated Convolutional Neural Networks for Sequential Manifold-Valued Data.”. Proceedings. IEEE International Conference on Computer Vision, Vol. 2019, 2019, pp. 10620-3.
Efforts are underway to study ways via which the power of deep neural networks can be extended to non-standard data types such as structured data (e.g., graphs) or manifold-valued data (e.g., unit vectors or special matrices). Often, sizable empirical improvements are possible when the geometry of such data spaces are incorporated into the design of the model, architecture, and the algorithms. Motivated by neuroimaging applications, we study formulations where the data are sequential manifold-valued measurements. This case is common in brain imaging, where the samples correspond to symmetric positive definite matrices or orientation distribution functions. Instead of a recurrent model which poses computational/technical issues, and inspired by recent results showing the viability of dilated convolutional models for sequence prediction, we develop a dilated convolutional neural network architecture for this task. On the technical side, we show how the modules needed in our network can be derived while explicitly taking the Riemannian manifold structure into account. We show how the operations needed can leverage known results for calculating the weighted Fréchet Mean (wFM). Finally, we present scientific results for group difference analysis in Alzheimer’s disease (AD) where the groups are derived using AD pathology load: here the model finds several brain fiber bundles that are related to AD even when the subjects are all still cognitively healthy.
Hwang, S., Z. Tao, W. Kim, and V. Singh. “Conditional Recurrent Flow: Conditional Generation of Longitudinal Samples With Applications to Neuroimaging.”. Proceedings. IEEE International Conference on Computer Vision, Vol. 2019, 2019, pp. 10691-00.
We develop a conditional generative model for longitudinal image datasets based on sequential invertible neural networks. Longitudinal image acquisitions are common in various scientific and biomedical studies where often each image sequence sample may also come together with various secondary (fixed or temporally dependent) measurements. The key goal is not only to estimate the parameters of a deep generative model for the given longitudinal data, but also to enable evaluation of how the temporal course of the generated longitudinal samples are influenced as a function of induced changes in the (secondary) temporal measurements (or events). Our proposed formulation incorporates recurrent subnetworks and temporal context gating, which provide a smooth transition in a temporal sequence of generated data that can be easily informed or modulated by secondary temporal conditioning variables. We show that the formulation works well despite the smaller sample sizes common in these applications. Our model is validated on two video datasets and a longitudinal Alzheimer’s disease (AD) dataset for both quantitative and qualitative evaluations of the generated samples. Further, using our generated longitudinal image samples, we show that we can capture the pathological progressions in the brain that turn out to be consistent with the existing literature, and could facilitate various types of downstream statistical analysis.
Social activity is associated with healthy aging and preserved cognition. Such activity includes a confluence of social support and verbal interaction, each influencing cognition through rarely parsed, mechanistically distinct pathways. We created a novel verbal interaction measure for the Wisconsin Registry for Alzheimer’s Prevention (WRAP) and assessed reliability of resultant data, a first step toward mechanism-driven examination of social activity as a modifiable predictor of cognitive health.
Gleason, C., D. Norton, E. Anderson, M. Wahoske, D. Washington, E. Umucu, R. Koscik, N. Dowling, S. Johnson, C. Carlsson, S. Asthana, and D. Alzheimer’s. “, Vol. 61, no. 1, 2018, pp. 79-89.
Alzheimer’s disease (AD) biomarkers are emerging as critically important for disease detection and monitoring. Most biomarkers are obtained through invasive, resource-intense procedures. A cognitive marker, intra-individual cognitive variability (IICV) may provide an alternative or adjunct marker of disease risk for individuals unable or disinclined to undergo lumbar puncture.
While it is well known that discourse-related language functions are impaired in the dementia phase of Alzheimer’s Disease (AD), the presymptomatic temporal course of discourse dysfunction are not known earlier in the course of AD. To conduct discourse-related studies in this phase of AD, validated psychometric instruments are needed. This study investigates the latent structure, validity, and test-retest stability of discourse measures in a late-middle-aged normative group who are relatively free from sporadic AD risk factors.
Dougherty, R., J. Lindheimer, A. Stegner, R. Van, O. Okonkwo, and D. Cook. “, Vol. 61, no. 2, 2018, pp. 601-1.
Cardiorespiratory fitness (CRF) is routinely investigated in older adults; however, the most appropriate CRF measure to use for this population has received inadequate attention. This study aimed to 1) evaluate the reliability and validity of the oxygen uptake efficiency slope (OUES) as a sub-maximal measurement of CRF; 2) examine demographic, risk-factor, and exercise testing differences in older adults who satisfied standardized criteria for a peak oxygen consumption (V̇O2peak) test compared to those who did not; and 3) determine the difference between directly measured V̇O2peak values and OUES-predicted V̇O2peak values. One hundred ten enrollees from the Wisconsin Registry for Alzheimer’s Prevention participated in this study. Participants performed a graded maximal exercise test and wore an accelerometer for 7 days. For each participant, the OUES was calculated at 75%, 90%, and 100% of exercise duration. V̇O2peak was recorded at peak effort, and one week of physical activity behavior was measured. OUES values calculated at separate relative exercise durations displayed excellent reliability (ICC = 0.995; p < 0.001), and were strongly correlated with V̇O2peak (rrange = 0.801-0.909; p < 0.001). As hypothesized, participants who did not satisfy V̇O2peak criteria were significantly older than those who satisfied criteria (p = 0.049) and attained a directly measured V̇O2peak that was 2.31 mL·kg·min-1 less than the value that was predicted by OUES V̇O2peak (p = 0.003). Older adults are less likely to satisfy V̇O2peak criteria, which results in an underestimation of their CRF. Without adhering to standardized criteria, V̇O2peak measurement error may lead to misinterpretation of CRF and age-related associations. Here, we conclude that OUES is a reliable, valid measurement of CRF which does not require achievement of standardized criteria. DOI: 10.3233/JAD-170576
Johnson, S., R. Koscik, E. Jonaitis, L. Clark, K. Mueller, S. Berman, B. Bendlin, C. Engelman, O. Okonkwo, K. Hogan, S. Asthana, C. Carlsson, B. Hermann, and M. Sager. “, Vol. 10, 2018, pp. 130-42.
The Wisconsin Registry for Alzheimer’s Prevention is a longitudinal observational cohort study enriched with persons with a parental history (PH) of probable Alzheimer’s disease (AD) dementia. Since late 2001, Wisconsin Registry for Alzheimer’s Prevention has enrolled 1561 people at a mean baseline age of 54 years. Participants return for a second visit 4 years after baseline, and subsequent visits occur every 2 years. Eighty-one percent (1270) of participants remain active in the study at a current mean age of 64 and 9 years of follow-up. Serially assessed cognition, self-reported medical and lifestyle histories (e.g., diet, physical and cognitive activity, sleep, and mood), laboratory tests, genetics, and linked studies comprising molecular imaging, structural imaging, and cerebrospinal fluid data have yielded many important findings. In this cohort, PH of probable AD is associated with 46% apolipoprotein E (APOE) ε4 positivity, more than twice the rate of 22% among persons without PH. Subclinical or worse cognitive decline relative to internal normative data has been observed in 17.6% of the cohort. Twenty-eight percent exhibit amyloid and/or tau positivity. Biomarker elevations, but not APOE or PH status, are associated with cognitive decline. Salutary health and lifestyle factors are associated with better cognition and brain structure and lower AD pathophysiologic burden. Of paramount importance is establishing the amyloid and tau AD endophenotypes to which cognitive outcomes can be linked. Such data will provide new knowledge on the early temporal course of AD pathophysiology and inform the design of secondary prevention clinical trials.
Recent studies have found an association between functional variants in TREM2 and PLD3 and Alzheimer’s disease (AD), but their effect on cognitive function is unknown. We examined the effect of these variants on cognitive function in 1449 participants from the Wisconsin Registry for Alzheimer’s Prevention, a longitudinal study of initially asymptomatic adults, aged 36-73 years at baseline, enriched for a parental history of AD. A comprehensive cognitive test battery was performed at up to 5 visits. A factor analysis resulted in 6 cognitive factors that were standardized into z scores (∼N [0, 1]); the mean of these z scores was also calculated. In linear mixed models adjusted for age, gender, practice effects, and self-reported race/ethnicity, PLD3 V232M carriers had significantly lower mean z scores (p = 0.02) and lower z scores for story recall (p = 0.04), visual learning and memory (p = 0.049), and speed and flexibility (p = 0.02) than noncarriers. TREM2 R47H carriers had marginally lower z scores for speed and flexibility (p = 0.06). In conclusion, a functional variant in PLD3 was associated with significantly lower cognitive function in individuals carrying the variant than in noncarriers.
Bettcher, B., S. Johnson, R. Fitch, K. Casaletto, K. Heffernan, S. Asthana, H. Zetterberg, K. Blennow, C. Carlsson, J. Neuhaus, B. Bendlin, and J. Kramer. “, Vol. 62, no. 1, 2018, pp. 385-97.
Inflammatory markers have been shown to predict neurocognitive outcomes in aging adults; however, the degree to which peripheral markers mirror the central nervous system remains unknown. We investigated the association between plasma and cerebrospinal fluid (CSF) markers of inflammation, and explored whether these markers independently predict CSF indicators of Alzheimer’s disease (AD) pathology or neuronal damage. Plasma and CSF samples were analyzed for inflammatory markers in a cohort of asymptomatic older adults (n = 173). CSF samples were analyzed for markers of AD pathology (Aβ42, phosphorylated tau [p-tau], sAβPPβ) or neuronal damage (total tau; neurofilament light chain) (n = 147). Separate linear models for each analyte were conducted with CSF and plasma levels entered simultaneously as predictors and markers of AD pathology or neuronal damage as outcome measures. Strong associations were noted between CSF and plasma MIP-1β levels, and modest associations were observed for remaining analytes. With respect to AD pathology, higher levels of plasma and CSF IL-8, CSF MIP-1β, and CSF IP-10 were associated with higher levels of p-tau. Higher levels of CSF IL-8 were associated with higher levels of CSF Aβ42. Higher CSF sAβPPβ levels were associated with higher plasma markers only (IL-8; MCP-1). In terms of neuronal injury, higher levels of plasma and CSF IL-8, CSF IP-10, and CSF MIP-1β were associated with higher levels of CSF total tau. Exploratory analyses indicated that CSF Aβ42 modifies the relationship between plasma inflammatory levels and CSF tau levels. Results suggest that both plasma and CSF inflammatory markers independently relay integral information about AD pathology and neuronal damage.
Neuroinflammation is a potential factor speculated to underlie Alzheimer’s disease (AD) etiopathogenesis and progression. The overwhelming focus in this area of research to date has been on the chronic upregulation of pro-inflammatory cytokines to understand how neuroinflammatory mechanisms contribute to neurodegeneration. Yet, it is important to understand the pleiotropic roles of these cytokines in modulating neuroinflammation in which they cannot be labeled as a strictly “good” or “bad” biomarker phenotype. As such, biomarkers with more precise functions are needed to better understand how neuroinflammation impacts the brain in AD. Neuronal pentraxins are a concentration- dependent group of pro- or anti- inflammatory cytokines. There is contradictory evidence of these pentraxins as being both neuroprotective and potentially detrimental in AD. Potential neuroprotective examples include their ability to predict AD-related outcomes such as cognition, memory function and synaptic refinement. This review will briefly outline the basis of AD and subsequently summarize findings for neuropathological mechanisms of neuroinflammation, roles for traditional pro-and anti-inflammatory cytokines, and data found thus far on the neuronal pentraxins.
Surgery and anaesthesia might affect cognition in middle-aged people without existing cognitive dysfunction. We measured memory and executive function in 964 participants, mean age 54 years, and again four years later, by when 312 participants had had surgery and 652 participants had not. Surgery between tests was associated with a decline in immediate memory by one point (out of a maximum of 30), p = 0.013: memory became abnormal in 77 out of 670 participants with initially normal memory, 21 out of 114 (18%) of whom had had surgery compared with 56 out of 556 (10%) of those who had not, p = 0.02. The number of operations was associated with a reduction in immediate memory on retesting, beta coefficient (SE) 0.08 (0.03), p = 0.012. Working memory decline was also associated with longer cumulative operations, beta coefficient (SE) -0.01 (0.00), p = 0.028. A reduction in cognitive speed and flexibility was associated with worse ASA physical status, beta coefficient (SE) 0.55 (0.22) and 0.37 (0.17) for ASA 1 and 2 vs. 3, p = 0.035. However, a decline in working memory was associated with better ASA physical status, beta coefficient (SE) -0.48 (0.21) for ASA 1 vs. 3, p = 0.01.
Villeneuve, S., J. Vogel, J. Gonneaud, B. Pichet, P. Rosa-Neto, S. Gauthier, R. Bateman, A. Fagan, J. Morris, T. Benzinger, S. Johnson, J. Breitner, J. Poirier, and E. Presymptomatic. “Proximity to Parental Symptom Onset and Amyloid-β Burden in Sporadic Alzheimer Disease.”. JAMA Neurology, Vol. 75, no. 5, 2018, pp. 608-19.
Alzheimer disease (AD) develops during several decades. Presymptomatic individuals might be the best candidates for clinical trials, but their identification is challenging because they have no symptoms.
Bruno, D., R. Koscik, J. Woodard, N. Pomara, and S. Johnson. “The Recency Ratio As Predictor of Early MCI.”. International Psychogeriatrics, Vol. 30, no. 12, 2018, pp. 1883-8.
ABSTRACTObjectives:Individuals with Alzheimer’s disease (AD) present poor immediate primacy recall accompanied by intact or exaggerated recency, which then tends to decline after a delay. Bruno et al. (Journal of Clinical and Experimental Neuropsychology, Vol. 38, 2016, pp. 967-973) have shown that higher ratio scores between immediate and delayed recency (i.e. the recency ratio; Rr) are associated with cognitive decline in high-functioning older individuals. We tested whether Rr predicted conversion to early mild cognitive impairment (early MCI) from a cognitively healthy baseline.
The neuropsychological profile of people with mild cognitive impairment (MCI) and Alzheimer’s disease (AD) dementia includes a history of decline in memory and other cognitive domains, including language. While language impairments have been well described in AD dementia, language features of MCI are less well understood. Connected speech and language analysis is the study of an individual’s spoken discourse, usually elicited by a target stimulus, the results of which can facilitate understanding of how language deficits typical of MCI and AD dementia manifest in everyday communication. Among discourse genres, picture description is a constrained task that relies less on episodic memory and more on semantic knowledge and retrieval, within the cognitive demands of a communication context. Understanding the breadth of evidence across the continuum of cognitive decline will help to elucidate the areas of strength and need in terms of using this method as an evaluative tool for both cognitive changes and everyday functional communication.
Hohman, T., L. Dumitrescu, L. Barnes, M. Thambisetty, G. Beecham, B. Kunkle, K. Gifford, W. Bush, L. Chibnik, S. Mukherjee, J. De, W. Kukull, P. Crane, S. Resnick, C. Keene, T. Montine, G. Schellenberg, J. Haines, H. Zetterberg, K. Blennow, E. Larson, S. Johnson, M. Albert, D. Bennett, J. Schneider, A. Jefferson, and D. Alzheimer’s. “Sex-Specific Association of Apolipoprotein E With Cerebrospinal Fluid Levels of Tau.”. JAMA Neurology, Vol. 75, no. 8, 2018, pp. 989-98.
The strongest genetic risk factor for Alzheimer disease (AD), the apolipoprotein E (APOE) gene, has a stronger association among women compared with men. Yet limited work has evaluated the association between APOE alleles and markers of AD neuropathology in a sex-specific manner.
Deming, Y., L. Dumitrescu, L. Barnes, M. Thambisetty, B. Kunkle, K. Gifford, W. Bush, L. Chibnik, S. Mukherjee, J. De, W. Kukull, M. Huentelman, P. Crane, S. Resnick, C. Keene, T. Montine, G. Schellenberg, J. Haines, H. Zetterberg, K. Blennow, E. Larson, S. Johnson, M. Albert, A. Moghekar, A. Del, M. Fernandez, J. Budde, J. Hassenstab, A. Fagan, M. Riemenschneider, R. Petersen, L. Minthon, M. Chao, D. Van, V. Lee, L. Shaw, J. Trojanowski, E. Peskind, G. Li, L. Davis, J. Sealock, N. Cox, D. Alzheimer’s, D. Alzheimer, A. Goate, D. Bennett, J. Schneider, A. Jefferson, C. Cruchaga, and T. Hohman. “”. Acta Neuropathologica, Vol. 136, no. 6, 2018, pp. 857-72.
Cerebrospinal fluid (CSF) levels of amyloid-β 42 (Aβ42) and tau have been evaluated as endophenotypes in Alzheimer’s disease (AD) genetic studies. Although there are sex differences in AD risk, sex differences have not been evaluated in genetic studies of AD endophenotypes. We performed sex-stratified and sex interaction genetic analyses of CSF biomarkers to identify sex-specific associations. Data came from a previous genome-wide association study (GWAS) of CSF Aβ42 and tau (1527 males, 1509 females). We evaluated sex interactions at previous loci, performed sex-stratified GWAS to identify sex-specific associations, and evaluated sex interactions at sex-specific GWAS loci. We then evaluated sex-specific associations between prefrontal cortex (PFC) gene expression at relevant loci and autopsy measures of plaques and tangles using data from the Religious Orders Study and Rush Memory and Aging Project. In Aβ42, we observed sex interactions at one previous and one novel locus: rs316341 within SERPINB1 (p = 0.04) and rs13115400 near LINC00290 (p = 0.002). These loci showed stronger associations among females (β = - 0.03, p = 4.25 × 10-8; β = 0.03, p = 3.97 × 10-8) than males (β = - 0.02, p = 0.009; β = 0.01, p = 0.20). Higher levels of expression of SERPINB1, SERPINB6, and SERPINB9 in PFC was associated with higher levels of amyloidosis among females (corrected p values < 0.02) but not males (p > 0.38). In total tau, we observed a sex interaction at a previous locus, rs1393060 proximal to GMNC (p = 0.004), driven by a stronger association among females (β = 0.05, p = 4.57 × 10-10) compared to males (β = 0.02, p = 0.03). There was also a sex-specific association between rs1393060 and tangle density at autopsy (pfemale = 0.047; pmale = 0.96), and higher levels of expression of two genes within this locus were associated with lower tangle density among females (OSTN p = 0.006; CLDN16 p = 0.002) but not males (p ≥ 0.32). Results suggest a female-specific role for SERPINB1 in amyloidosis and for OSTN and CLDN16 in tau pathology. Sex-specific genetic analyses may improve understanding of AD’s genetic architecture.
Several chronic illnesses have demonstrated relationships to cognitive decline in the context of aging. However, researchers have largely ignored the effects of multi-morbidity in the context of Alzheimer’s disease and related dementias (ADRD) risk. The purpose of this study is to examine the relationship between multiple chronic conditions (MCC) and cognitive decline.
Vesperman, C., V. Pozorski, R. Dougherty, L. Law, E. Boots, J. Oh, C. Gallagher, C. Carlsson, H. Rowley, Y. Ma, B. Bendlin, S. Asthana, M. Sager, B. Hermann, S. Johnson, D. Cook, and O. Okonkwo. “, Vol. 10, no. 1, 2018, p. 97.
Age is the cardinal risk factor for Alzheimer’s disease (AD), and white matter hyperintensities (WMH), which are more prevalent with increasing age, may contribute to AD. Higher cardiorespiratory fitness (CRF) has been shown to be associated with cognitive health and decreased burden of AD-related brain alterations in older adults. Accordingly, the aim of this study was to determine whether CRF attenuates age-related accumulation of WMH in middle-aged adults at risk for AD.
Madrid, A., K. Hogan, L. Papale, L. Clark, S. Asthana, S. Johnson, and R. Alisch. “, Vol. 66, no. 3, 2018, pp. 927-34.
Differentially methylated positions (DMPs) between persons with and without late-onset Alzheimer’s disease (LOAD) were observed at 477 of 769,190 loci in a plurality of genes. Of these, 17 were shared with DMPs identified using clinical LOAD markers analyzed independently as continuous variables comprising Rey Auditory Verbal Learning Test scores, cerebrospinal fluid total tau (t-tau) and phosphorylated tau 181 (p-tau181) levels, and t-tau/Aβ1-42 (Aβ42), p-tau181/Aβ42, and Aβ42/Aβ1-40 (Aβ40) ratios. In patients with LOAD, 12 of the shared 17 DMPs were hypomethylated in B3GALT4 (Beta-1,3-galatcosyltransferase 4) (EC 184.108.40.206), and 5 were hypomethylated in ZADH2 (Prostaglandin reductase 3) (EC 220.127.116.11).
Besser, L., W. Kukull, D. Knopman, H. Chui, D. Galasko, S. Weintraub, G. Jicha, C. Carlsson, J. Burns, J. Quinn, R. Sweet, K. Rascovsky, M. Teylan, D. Beekly, G. Thomas, M. Bollenbeck, S. Monsell, C. Mock, X. Zhou, N. Thomas, E. Robichaud, M. Dean, J. Hubbard, M. Jacka, K. Schwabe-Fry, J. Wu, C. Phelps, J. Morris, and W. Neuropsychology. “”. Alzheimer Disease and Associated Disorders, Vol. 32, no. 4, 2018, pp. 351-8.
In 2015, the US Alzheimer’s Disease Centers (ADC) implemented Version 3 of the Uniform Data Set (UDS). This paper describes the history of Version 3 development and the UDS data that are freely available to researchers.
Vogt, N., K. Romano, B. Darst, C. Engelman, S. Johnson, C. Carlsson, S. Asthana, K. Blennow, H. Zetterberg, B. Bendlin, and F. Rey. “, Vol. 10, no. 1, 2018, p. 124.
Trimethylamine N-oxide (TMAO), a small molecule produced by the metaorganismal metabolism of dietary choline, has been implicated in human disease pathogenesis, including known risk factors for Alzheimer’s disease (AD), such as metabolic, cardiovascular, and cerebrovascular disease.
Darst, B., R. Koscik, A. Racine, J. Oh, R. Krause, C. Carlsson, H. Zetterberg, K. Blennow, B. Christian, B. Bendlin, O. Okonkwo, K. Hogan, B. Hermann, M. Sager, S. Asthana, S. Johnson, and C. Engelman. “, Vol. 55, no. 2, 2017, pp. 473-84.
Polygenic risk scores (PRSs) have been used to combine the effects of variants with small effects identified by genome-wide association studies. We explore the potential for using pathway-specific PRSs as predictors of early changes in Alzheimer’s disease (AD)-related biomarkers and cognitive function. Participants were from the Wisconsin Registry for Alzheimer’s Prevention, a longitudinal study of adults who were cognitively asymptomatic at enrollment and enriched for a parental history of AD. Using genes associated with AD in the International Genomics of Alzheimer’s Project’s meta-analysis, we identified clusters of genes that grouped into pathways involved in amyloid-β (Aβ) deposition and neurodegeneration: Aβ clearance, cholesterol metabolism, and immune response. Weighted pathway-specific and overall PRSs were developed and compared to APOE alone. Mixed models were used to assess whether each PRS was associated with cognition in 1,200 individuals, cerebral Aβ deposition measured using amyloid ligand (Pittsburgh compound B) positron emission imaging in 168 individuals, and cerebrospinal fluid Aβ deposition, neurodegeneration, and tau pathology in 111 individuals, with replication performed in an independent sample. We found that PRSs including APOE appeared to be driven by the inclusion of APOE, suggesting that the pathway-specific PRSs used here were not more predictive than an overall PRS or APOE alone. However, pathway-specific PRSs could prove to be useful as more knowledge is gained on the genetic variants involved in specific biological pathways of AD.
Dean, D., S. Hurley, S. Kecskemeti, J. O’Grady, C. Canda, N. Davenport-Sis, C. Carlsson, H. Zetterberg, K. Blennow, S. Asthana, M. Sager, S. Johnson, A. Alexander, and B. Bendlin. “Association of Amyloid Pathology With Myelin Alteration in Preclinical Alzheimer Disease.”. JAMA Neurology, Vol. 74, no. 1, 2017, pp. 41-49.
The accumulation of aggregated β-amyloid and tau proteins into plaques and tangles is a central feature of Alzheimer disease (AD). While plaque and tangle accumulation likely contributes to neuron and synapse loss, disease-related changes to oligodendrocytes and myelin are also suspected of playing a role in development of AD dementia. Still, to our knowledge, little is known about AD-related myelin changes, and even when present, they are often regarded as secondary to concomitant arteriosclerosis or related to aging.
Betthauser, T., P. Lao, D. Murali, T. Barnhart, S. Furumoto, N. Okamura, C. Stone, S. Johnson, and B. Christian. “In Vivo Comparison of Tau Radioligands 18F-THK-5351 and 18F-THK-5317.”. Journal of Nuclear Medicine : Official Publication, Society of Nuclear Medicine, Vol. 58, no. 6, 2017, pp. 996-1002.
This study compared the in vivo imaging characteristics of tau PET ligands 18F-THK-5351 and 18F-THK-5317 in the context of Alzheimer disease (AD). Additionally, reference tissue distribution volume ratio (DVR) estimation methods and SUV ratio (SUVR) timing windows were evaluated to determine the optimal strategy for specific binding quantification. Methods: Twenty-eight subjects (mean age ± SD, 71 ± 7 y) underwent either dynamic 90-min 18F-THK-5317 or 18F-THK-5351 PET scans. Bland-Altman plots were used to compare the simplified reference tissue method, multilinear reference tissue method (MRTM2), and Logan reference tissue DVR estimates and to assess temporal stability of SUVR windows using cerebellar gray matter as a reference region. In vivo kinetics and DVR estimates were directly compared for 10 subjects who underwent both 18F-THK-5317 and 18F-THK-5351 PET scans. Results: THK-5351 exhibited faster cerebellar gray matter clearance, faster cortical white matter clearance, and higher DVR estimates in AD tau-associated regions of interest than THK-5317. The MRTM2 method produced the most reliable DVR estimates for both tracers, particularly when scan duration was shortened to 60 min. SUVR stability was observed 50-70 min after injection for both tracers. Parametric images revealed differences between MRTM2, Logan, and SUVR binding in white matter regions for THK-5317. Conclusion: THK-5317 and THK-5351 show promise for in vivo detection of AD tau. THK-5351 has more favorable pharmacokinetics and imaging characteristics than THK-5317.
Law, L., S. Schultz, E. Boots, J. Einerson, R. Dougherty, J. Oh, C. Korcarz, D. Edwards, R. Koscik, N. Dowling, C. Gallagher, B. Bendlin, C. Carlsson, S. Asthana, B. Hermann, M. Sager, S. Johnson, D. Cook, J. Stein, and O. Okonkwo. “, Vol. 56, no. 1, 2017, pp. 351-9.
The objective of this study was to examine the association of chronotropic response (CR) and heart rate (HR) recovery- two indices of cardiovascular function within the context of a graded exercise test- with cognitive performance in a cognitively healthy, late-middle-aged cohort at risk for Alzheimer’s disease (AD). Ninety participants (age = 63.52±5.86 years; 65.6% female) from the Wisconsin Registry for Alzheimer’s Prevention participated in this study. They underwent graded exercise testing and a comprehensive neuropsychological assessment that assessed the following four cognitive domains: Immediate Memory, Verbal & Learning Memory, Working Memory, and Speed & Flexibility. Regression analyses, adjusted for age, sex, and education, were used to examine the association between CR, HR recovery, and cognition. We found significant associations between CR and cognitive performance in the domains of Immediate Memory, Verbal Learning & Memory, and Speed & Flexibility. In contrast, HR recovery was not significantly associated with cognitive function. The association between CR and cognition persisted even after controlling for HR recovery. Together, these findings indicatethat, in a cognitively normal, late-middle-aged cohort, CR is a stronger correlate of cognitive performance than HR recovery. Overall, this study reinforces the idea that cardiovascular health plays an important role in cognitive function, specifically in a cohort at risk for AD; and that interventions that promote vascular health may be a viable pathway to preventing or slowing cognitive decline due to AD.
Karrasch, M., P. Tiitta, B. Hermann, J. Joutsa, S. Shinnar, J. Rinne, A. Anttinen, and M. Sillanpää. “Cognitive Outcome in Childhood-Onset Epilepsy: A Five-Decade Prospective Cohort Study.”. Journal of the International Neuropsychological Society : JINS, Vol. 23, no. 4, 2017, pp. 332-40.
Little is known about the very long-term cognitive outcome in patients with childhood-onset epilepsy. The aim of this unique prospective population-based cohort study was to examine cognitive outcomes in aging participants with childhood-onset epilepsy (mean onset age=5.3 years) five decades later (mean age at follow-up=56.5 years).
Dougherty, R., S. Schultz, E. Boots, L. Ellingson, J. Meyer, R. Van, A. Stegner, D. Edwards, J. Oh, J. Einerson, C. Korcarz, R. Koscik, M. Dowling, C. Gallagher, C. Carlsson, H. Rowley, B. Bendlin, S. Asthana, B. Hermann, M. Sager, J. Stein, S. Johnson, O. Okonkwo, and D. Cook. “”. Brain and Behavior, Vol. 7, no. 3, 2017, p. e00625.
Cardiorespiratory fitness (CRF) has been shown to be related to brain health in older adults. In individuals at risk for developing Alzheimer’s disease (AD), CRF may be a modifiable risk factor that could attenuate anticipated declines in brain volume and episodic memory. The objective of this study was to determine the association between CRF and both hippocampal volume and episodic memory in a cohort of cognitively healthy older adults with familial and/or genetic risk for Alzheimer’s disease (AD).
Schultz, S., E. Boots, B. Darst, H. Zetterberg, K. Blennow, D. Edwards, R. Koscik, C. Carlsson, C. Gallagher, B. Bendlin, S. Asthana, M. Sager, K. Hogan, B. Hermann, D. Cook, S. Johnson, C. Engelman, and O. Okonkwo. “Cardiorespiratory Fitness Alters the Influence of a Polygenic Risk Score on Biomarkers of AD.”. Neurology, Vol. 88, no. 17, 2017, pp. 1650-8.
To examine whether a polygenic risk score (PRS) derived from APOE4, CLU, and ABCA7 is associated with CSF biomarkers of Alzheimer disease (AD) pathology and whether higher cardiorespiratory fitness (CRF) modifies the association between the PRS and CSF biomarkers.
Nicholas, C., S. Hoscheidt, L. Clark, A. Racine, S. Berman, R. Koscik, D. Maritza, S. Asthana, B. Christian, M. Sager, and S. Johnson. “Positive Affect Predicts Cerebral Glucose Metabolism in Late Middle-Aged adults.”. Social Cognitive and Affective Neuroscience, Vol. 12, no. 6, 2017, pp. 993-1000.
Positive affect is associated with a number of health benefits; however, few studies have examined the relationship between positive affect and cerebral glucose metabolism, a key energy source for neuronal function and a possible index of brain health. We sought to determine if positive affect was associated with cerebral glucose metabolism in late middle-aged adults (n = 133). Participants completed the positive affect subscale of the Center for Epidemiological Studies Depression Scale at two time points over a two-year period and underwent 18F-fluorodeoxyglucose-positron emission tomography scanning. After controlling for age, sex, perceived health status, depressive symptoms, anti-depressant use, family history of Alzheimer’s disease, APOE ε4 status and interval between visits, positive affect was associated with greater cerebral glucose metabolism across para-/limbic, frontal, temporal and parietal regions. Our findings provide evidence that positive affect in late midlife is associated with greater brain health in regions involved in affective processing and also known to be susceptible to early neuropathological processes. The current findings may have implications for interventions aimed at increasing positive affect to attenuate early neuropathological changes in at-risk individuals.
Dougherty, R., S. Schultz, T. Kirby, E. Boots, J. Oh, D. Edwards, C. Gallagher, C. Carlsson, B. Bendlin, S. Asthana, M. Sager, B. Hermann, B. Christian, S. Johnson, D. Cook, and O. Okonkwo. “, Vol. 58, no. 4, 2017, pp. 1089-97.
The objective of this study was to investigate the relationship between accelerometer-measured physical activity (PA) and glucose metabolism in asymptomatic late-middle-aged adults. Ninety-three cognitively healthy late-middle-aged adults from the Wisconsin Registry for Alzheimer’s Prevention participated in this cross-sectional study. They underwent 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) imaging and wore an accelerometer (ActiGraph GT3X+) to measure free-living PA. Accelerometer data yielded measures of light (LPA), moderate (MPA), and vigorous (VPA) intensity PA. FDG-PET images were scaled to the cerebellum and pons, and cerebral glucose metabolic rate was extracted from specific regions of interest (ROIs) known to be hypometabolic in AD, i.e., hippocampus, posterior cingulate, inferior temporal cortex, and angular gyrus. Regression analyses were utilized to examine the association between PA and glucose metabolism, while adjusting for potential confounds. There were associations between MPA and glucose metabolism in all ROIs examined. In contrast, LPA was not associated with glucose uptake in any ROI and VPA was only associated with hippocampal FDG uptake. Secondary analyses did not reveal associations between sedentary time and glucose metabolism in any of the ROIs. Exploratory voxel-wise analysis identified additional regions where MPA was significantly associated with glucose metabolism including the precuneus, supramarginal gyrus, amygdala, and middle frontal gyrus. These findings suggest that the intensity of PA is an important contributor to neuronal function in a late-middle-aged cohort, with MPA being the most salient. Prospective studies are necessary for fully elucidating the link between midlife engagement in PA and later life development of AD.
Willette, A., J. Webb, M. Lutz, B. Bendlin, A. Wennberg, J. Oh, A. Roses, R. Koscik, B. Hermann, N. Dowling, S. Asthana, S. Johnson, and D. Alzheimer’s. “, Vol. 13, no. 11, 2017, pp. 1217-25.
Family history (FH) of Alzheimer’s disease (AD) affects mitochondrial function and may modulate effects of translocase of the outer mitochondrial membrane 40 kDa (TOMM40) rs10524523 (‘523) poly-T length on memory decline.
Gross, A., J. Hassenstab, S. Johnson, L. Clark, S. Resnick, M. Kitner-Triolo, C. Masters, P. Maruff, J. Morris, A. Soldan, C. Pettigrew, and M. Albert. “, Vol. 8, 2017, pp. 147-55.
We established a method for diagnostic harmonization across multiple studies of preclinical Alzheimer’s disease and validated the method by examining its relationship with clinical status and cognition.
Sprecher, K., R. Koscik, C. Carlsson, H. Zetterberg, K. Blennow, O. Okonkwo, M. Sager, S. Asthana, S. Johnson, R. Benca, and B. Bendlin. “Poor Sleep Is Associated With CSF Biomarkers of Amyloid Pathology in Cognitively Normal adults.”. Neurology, Vol. 89, no. 5, 2017, pp. 445-53.
To determine the relationship between sleep quality and CSF markers of Alzheimer disease (AD) pathology in late midlife.
The purpose of this study was to investigate the longitudinal trajectory of self- and informant-subjective cognitive complaints (SCC), and to determine if SCC predict longitudinal changes in objective measures (OM) of cognitive function.
Bilgel, M., R. Koscik, Y. An, J. Prince, S. Resnick, S. Johnson, and B. Jedynak. “, Vol. 59, no. 4, 2017, pp. 1335-47.
Investigation of the temporal trajectories of currently used neuropsychological tests is critical to identifying earliest changing measures on the path to dementia due to Alzheimer’s disease (AD). We used the Progression Score (PS) method to characterize the temporal trajectories of measures of verbal memory, executive function, attention, processing speed, language, and mental status using data spanning normal cognition, mild cognitive impairment, and AD from 1,661 participants with a total of 7,839 visits (age at last visit 77.6 SD 9.2) in the Baltimore Longitudinal Study of Aging (BLSA) and 1510 participants with a total of 3,473 visits (age at last visit 59.5 SD 7.4) in the Wisconsin Registry for Alzheimer’s Prevention (WRAP). This method aligns individuals in time based on the similarity of their longitudinal measurements to reveal temporal trajectories. As a validation of our methodology, we explored the associations between the individualized cognitive progression scores (Cog-PS) computed by our method and clinical diagnosis. Digit span tests were the first to show declines in both data sets, and were detected mainly among cognitively normal individuals. These were followed by tests of verbal memory, which were in turn followed by Trail Making Tests, Boston Naming Test, and Mini-Mental State Examination. Differences in Cog-PS across the clinical diagnosis and APOEɛ4 groups were statistically significant, highlighting the potential use of Cog-PS as individualized indicators of disease progression. Identifying cognitive measures that are changing in preclinical AD can lead to the development of novel cognitive tests that are finely tuned to detecting earliest changes.
Berman, S., R. Koscik, L. Clark, K. Mueller, L. Bluder, J. Galvin, and S. Johnson. “, Vol. 1, no. 1, 2017, pp. 9-13.
The Quick Dementia Rating System (QDRS) and Clinical Dementia Rating Scale (CDR) assess global cognitive and functional decline. We evaluated whether the shorter QDRS was a valid screen for problems identified by the CDR in individuals with minimal clinical abnormalities. Agreement between QDRS-Global and CDR-Global was assessed for 54 participants from the Wisconsin Registry for Alzheimer’s Prevention. Resource-savings achieved by adopting an “administer CDR-only-if-QDRS-Global>0” approach were estimated based on 238 subsequent participants. Agreement statistics (concordance = 88.9%) supported use of the QDRS as an initial informant report and modifying center protocol to administer CDRs only when QDRS>0 reduced CDR assessments by 79.8%.
Neu, S., J. Pa, W. Kukull, D. Beekly, A. Kuzma, P. Gangadharan, L. Wang, K. Romero, S. Arneric, A. Redolfi, D. Orlandi, G. Frisoni, R. Au, S. Devine, S. Auerbach, A. Espinosa, M. Boada, A. Ruiz, S. Johnson, R. Koscik, J. Wang, W. Hsu, Y. Chen, and A. Toga. “Apolipoprotein E Genotype and Sex Risk Factors for Alzheimer Disease: A Meta-analysis.”. JAMA Neurology, Vol. 74, no. 10, 2017, pp. 1178-89.
It is unclear whether female carriers of the apolipoprotein E (APOE) ε4 allele are at greater risk of developing Alzheimer disease (AD) than men, and the sex-dependent association of mild cognitive impairment (MCI) and APOE has not been established.
Hermann, B., M. Sager, R. Koscik, K. Young, and K. Nakamura. “Vascular, Inflammatory, and Metabolic Factors Associated With Cognition in Aging Persons With Chronic epilepsy.”. Epilepsia, Vol. 58, no. 11, 2017, pp. e152-e156.
We examined cognition in aging persons with chronic epilepsy; characterized targeted vascular, inflammatory, and metabolic risk factors associated with abnormal cognitive aging in the general population; and examined associations between cognition and vascular, inflammatory, and metabolic health. Participants included 40 persons with chronic localization-related epilepsy and 152 controls, aged 54.6 and 55.3, respectively. Participants underwent neuropsychological assessment, clinical examination, and fasting blood evaluation for quantification of vascular status (systolic and diastolic blood pressure, obesity/body mass index [BMI], total and high-density lipoprotein [HDL] cholesterol level, and homocysteine), inflammatory markers (high sensitivity C-reactive protein [hs-CRP], and interleukin-6 [IL-6]), and metabolic status (insulin resistance [Homeostatic Model Assessment of Insulin Resistance (HOMA-IR)], glucose). Epilepsy participants exhibited impairment across all cognitive factor scores (all p’s < 0.0001); abnormalities in BMI (p = 0.049), hs-CRP (p = 0.046), HOMA-IR (p = 0.0040), and fasting glucose (p = 0.03), with significant relationships between higher HOMA-IR with poorer Immediate Memory (p = 0.03) and Visuospatial Ability (0.03); elevated hs-CRP with poorer Visuospatial (p = 0.035) and Verbal Ability (p = 0.06); elevated BMI with poorer Speed/Flexibility (p = 0.04), Visuospatial (p = 0.001) and Verbal Ability (p = 0.02); and lower HDL with poorer Verbal Learning/Delayed Memory (p = 0.01), Speed/Flexibility (p = 0.043), and Working Memory (p = 0.008). Aging persons with chronic epilepsy exhibit multiple abnormalities in metabolic, inflammatory, and vascular health that are associated with poorer cognitive function. DOI: 10.1111/epi.13891
Casaletto, K., F. Elahi, B. Bettcher, J. Neuhaus, B. Bendlin, S. Asthana, S. Johnson, K. Yaffe, C. Carlsson, K. Blennow, H. Zetterberg, and J. Kramer. “Neurogranin, a Synaptic Protein, Is Associated With Memory Independent of Alzheimer biomarkers.”. Neurology, Vol. 89, no. 17, 2017, pp. 1782-8.
To determine the association between synaptic functioning as measured via neurogranin in CSF and cognition relative to established Alzheimer disease (AD) biomarkers in neurologically healthy older adults.
Betthauser, T., P. Ellison, D. Murali, P. Lao, T. Barnhart, S. Furumoto, N. Okamura, S. Johnson, J. Engle, R. Nickles, and B. Christian. “Characterization of the Radiosynthesis and Purification of [18F]THK-5351, a PET Ligand for Neurofibrillary tau.”. Applied Radiation and Isotopes : Including Data, Instrumentation and Methods for Use in Agriculture, Industry and Medicine, Vol. 130, 2017, pp. 230-7.
This work characterizes the radiochemical synthesis, purification, and formulation of [18F]THK-5351, a tau PET radioligand, and develops an automated radiosynthesis routine (ELIXYS, Sofie Biosciences). Nucleophilic radiofluorination reaction was complete by 7min at 110°C with radiochemical yields proportional to precursor mass (0.1-0.5mg). Optimized HPLC purification produced radiotracer product with no chemical impurities observed on analytical HPLC in formulation. Automated radiosynthesis (ELIXYS), HPLC purification and formulation was completed in 86min producing formulated product suitable for human research use.
Alzheimer’s disease (AD) is the most common form of dementia. However, the etiopathogenesis of this devastating disease is not fully understood. Recent studies in rodents suggest that alterations in the gut microbiome may contribute to amyloid deposition, yet the microbial communities associated with AD have not been characterized in humans. Towards this end, we characterized the bacterial taxonomic composition of fecal samples from participants with and without a diagnosis of dementia due to AD. Our analyses revealed that the gut microbiome of AD participants has decreased microbial diversity and is compositionally distinct from control age- and sex-matched individuals. We identified phylum- through genus-wide differences in bacterial abundance including decreased Firmicutes, increased Bacteroidetes, and decreased Bifidobacterium in the microbiome of AD participants. Furthermore, we observed correlations between levels of differentially abundant genera and cerebrospinal fluid (CSF) biomarkers of AD. These findings add AD to the growing list of diseases associated with gut microbial alterations, as well as suggest that gut bacterial communities may be a target for therapeutic intervention.
Changes to everyday spoken language (“connected language”) are evident in persons with AD dementia, yet little is known about when these changes are first detectable on the continuum of cognitive decline. The aim of this study was to determine if participants with very early, subclinical memory declines were also showing declines in connected language. We analyzed connected language samples obtained from a simple picture description task at two time points in 264 participants from the Wisconsin Registry for Alzheimer’s Prevention (WRAP). In parallel, participants were classified as either “Cognitively Healthy” or “Early Mild Cognitive Impairment” based on longitudinal neuropsychological test performance. Linear mixed effects models were used to analyze language parameters that were extracted from the connected language samples using automated feature extraction. Participants with eMCI status declined faster in features of speech fluency and semantic content than those who were cognitively stable. Measures of lexical diversity and grammatical complexity were not associated with eMCI status in this group. These findings provide novel insights about the relationship between cognitive decline and everyday language, using a quick, inexpensive, and performance-based method.
Ithapu, V., R. Kondor, S. Johnson, and V. Singh. “The Incremental Multiresolution Matrix Factorization Algorithm.”. Proceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol. 2017, 2017, pp. 692-01.
Multiresolution analysis and matrix factorization are foundational tools in computer vision. In this work, we study the interface between these two distinct topics and obtain techniques to uncover hierarchical block structure in symmetric matrices – an important aspect in the success of many vision problems. Our new algorithm, the incremental multiresolution matrix factorization, uncovers such structure one feature at a time, and hence scales well to large matrices. We describe how this multiscale analysis goes much farther than what a direct “global” factorization of the data can identify. We evaluate the efficacy of the resulting factorizations for relative leveraging within regression tasks using medical imaging data. We also use the factorization on representations learned by popular deep networks, providing evidence of their ability to infer semantic relationships even when they are not explicitly trained to do so. We show that this algorithm can be used as an exploratory tool to improve the network architecture, and within numerous other settings in vision.
Kim, W., M. Jalal, S. Hwang, S. Johnson, and V. Singh. “Online Graph Completion: Multivariate Signal Recovery in Computer Vision.”. Proceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol. 2017, 2017, pp. 5019-27.
The adoption of “human-in-the-loop” paradigms in computer vision and machine learning is leading to various applications where the actual data acquisition (e.g., human supervision) and the underlying inference algorithms are closely interwined. While classical work in active learning provides effective solutions when the learning module involves classification and regression tasks, many practical issues such as partially observed measurements, financial constraints and even additional distributional or structural aspects of the data typically fall outside the scope of this treatment. For instance, with sequential acquisition of partial measurements of data that manifest as a matrix (or tensor), novel strategies for completion (or collaborative filtering) of the remaining entries have only been studied recently. Motivated by vision problems where we seek to annotate a large dataset of images via a crowdsourced platform or alternatively, complement results from a state-of-the-art object detector using human feedback, we study the “completion” problem defined on graphs, where requests for additional measurements must be made sequentially. We design the optimization model in the Fourier domain of the graph describing how ideas based on adaptive submodularity provide algorithms that work well in practice. On a large set of images collected from Imgur, we see promising results on images that are otherwise difficult to categorize. We also show applications to an experimental design problem in neuroimaging.
Kim, H., N. Adluru, H. Suri, B. Vemuri, S. Johnson, and V. Singh. “Riemannian Nonlinear Mixed Effects Models: Analyzing Longitudinal Deformations in Neuroimaging.”. Proceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol. 2017, 2017, pp. 5777-86.
Statistical machine learning models that operate on manifold-valued data are being extensively studied in vision, motivated by applications in activity recognition, feature tracking and medical imaging. While non-parametric methods have been relatively well studied in the literature, efficient formulations for parametric models (which may offer benefits in small sample size regimes) have only emerged recently. So far, manifold-valued regression models (such as geodesic regression) are restricted to the analysis of cross-sectional data, i.e., the so-called “fixed effects” in statistics. But in most “longitudinal analysis” (e.g., when a participant provides multiple measurements, over time) the application of fixed effects models is problematic. In an effort to answer this need, this paper generalizes non-linear mixed effects model to the regime where the response variable is manifold-valued, i.e., f : Rd → ℳ. We derive the underlying model and estimation schemes and demonstrate the immediate benefits such a model can provide – both for group level and individual level analysis – on longitudinal brain imaging data. The direct consequence of our results is that longitudinal analysis of manifold-valued measurements (especially, the symmetric positive definite manifold) can be conducted in a computationally tractable manner.
Clark, L., A. Racine, R. Koscik, O. Okonkwo, C. Engelman, C. Carlsson, S. Asthana, B. Bendlin, R. Chappell, C. Nicholas, H. Rowley, J. Oh, B. Hermann, M. Sager, B. Christian, and S. Johnson. “, Vol. 12, no. 7, 2016, pp. 805-14.
The present study investigated the relationship between beta-amyloid (Aβ) and cognition in a late middle-aged cohort at risk for Alzheimer’s disease (AD).
Melah, K., S. Lu, S. Hoscheidt, A. Alexander, N. Adluru, D. Destiche, C. Carlsson, H. Zetterberg, K. Blennow, O. Okonkwo, C. Gleason, N. Dowling, L. Bratzke, H. Rowley, M. Sager, S. Asthana, S. Johnson, and B. Bendlin. “, Vol. 50, no. 3, 2016, pp. 873-86.
The immune response in Alzheimer’s disease (AD) involves activation of microglia which may remove amyloid-β (Aβ). However, overproduction of inflammatory compounds may exacerbate neural damage in AD. AD pathology accumulates years before diagnosis, yet the extent to which neuroinflammation is involved in the earliest disease stages is unknown.
Ly, M., N. Adluru, D. Destiche, S. Lu, J. Oh, S. Hoscheidt, A. Alexander, O. Okonkwo, H. Rowley, M. Sager, S. Johnson, and B. Bendlin. “Fornix Microstructure and Memory Performance Is Associated With Altered Neural Connectivity During Episodic Recognition.”. Journal of the International Neuropsychological Society : JINS, Vol. 22, no. 2, 2016, pp. 191-04.
The purpose of this study was to assess whether age-related differences in white matter microstructure are associated with altered task-related connectivity during episodic recognition.
Racine, A., R. Koscik, C. Nicholas, L. Clark, O. Okonkwo, J. Oh, A. Hillmer, D. Murali, T. Barnhart, T. Betthauser, C. Gallagher, H. Rowley, N. Dowling, S. Asthana, B. Bendlin, K. Blennow, H. Zetterberg, C. Carlsson, B. Christian, and S. Johnson. “, Vol. 2, 2016, pp. 27-38.
Biomarkers are urgently needed for the critical yet understudied preclinical stage of Alzheimer’s disease (AD).
Hoscheidt, S., E. Starks, J. Oh, H. Zetterberg, K. Blennow, R. Krause, C. Gleason, L. Puglielli, C. Atwood, C. Carlsson, S. Asthana, S. Johnson, and B. Bendlin. “, Vol. 52, no. 4, 2016, pp. 1373-83.
Type 2 diabetes is associated with an increased risk for Alzheimer’s disease (AD). Regulation of normal insulin function may be important in reducing the prevalence of dementia due to AD, particularly in individuals who harbor genetic risk for or have a parental family history of AD. The relationship between insulin resistance (IR) and AD pathology remains poorly understood, particularly in midlife prior to the onset of clinical metabolic disease or cognitive decline.
Clark, L., R. Koscik, C. Nicholas, O. Okonkwo, C. Engelman, L. Bratzke, K. Hogan, K. Mueller, B. Bendlin, C. Carlsson, S. Asthana, M. Sager, B. Hermann, and S. Johnson. “”. Archives of Clinical Neuropsychology : The Official Journal of the National Academy of Neuropsychologists, Vol. 31, no. 7, 2016, pp. 675-88.
Detecting cognitive decline in presymptomatic Alzheimer’s disease (AD) and early mild cognitive impairment (MCI) is challenging, but important for treatments targeting AD-related neurodegeneration. The current study aimed to investigate the utility and performance of internally developed robust norms and standard norms in identifying cognitive impairment in late middle-age (baseline age range = 36-68; M = 54).
Merluzzi, A., D. Dean, N. Adluru, G. Suryawanshi, O. Okonkwo, J. Oh, B. Hermann, M. Sager, S. Asthana, H. Zhang, S. Johnson, A. Alexander, and B. Bendlin. “Age-Dependent Differences in Brain Tissue Microstructure Assessed With Neurite Orientation Dispersion and Density imaging.”. Neurobiology of Aging, Vol. 43, 2016, pp. 79-88.
Human aging is accompanied by progressive changes in executive function and memory, but the biological mechanisms underlying these phenomena are not fully understood. Using neurite orientation dispersion and density imaging, we sought to examine the relationship between age, cellular microstructure, and neuropsychological scores in 116 late middle-aged, cognitively asymptomatic participants. Results revealed widespread increases in the volume fraction of isotropic diffusion and localized decreases in neurite density in frontal white matter regions with increasing age. In addition, several of these microstructural alterations were associated with poorer performance on tests of memory and executive function. These results suggest that neurite orientation dispersion and density imaging is capable of measuring age-related brain changes and the neural correlates of poorer performance on tests of cognitive functioning, largely in accordance with published histological findings and brain-imaging studies of people of this age range. Ultimately, this study sheds light on the processes underlying normal brain development in adulthood, knowledge that is critical for differentiating healthy aging from changes associated with dementia.
Racine, A., R. Koscik, S. Berman, C. Nicholas, L. Clark, O. Okonkwo, H. Rowley, S. Asthana, B. Bendlin, K. Blennow, H. Zetterberg, C. Gleason, C. Carlsson, and S. Johnson. “Biomarker Clusters Are Differentially Associated With Longitudinal Cognitive Decline in Late midlife.”. Brain : A Journal of Neurology, Vol. 139, no. Pt 8, 2016, pp. 2261-74.
The ability to detect preclinical Alzheimer’s disease is of great importance, as this stage of the Alzheimer’s continuum is believed to provide a key window for intervention and prevention. As Alzheimer’s disease is characterized by multiple pathological changes, a biomarker panel reflecting co-occurring pathology will likely be most useful for early detection. Towards this end, 175 late middle-aged participants (mean age 55.9 ± 5.7 years at first cognitive assessment, 70% female) were recruited from two longitudinally followed cohorts to undergo magnetic resonance imaging and lumbar puncture. Cluster analysis was used to group individuals based on biomarkers of amyloid pathology (cerebrospinal fluid amyloid-β42/amyloid-β40 assay levels), magnetic resonance imaging-derived measures of neurodegeneration/atrophy (cerebrospinal fluid-to-brain volume ratio, and hippocampal volume), neurofibrillary tangles (cerebrospinal fluid phosphorylated tau181 assay levels), and a brain-based marker of vascular risk (total white matter hyperintensity lesion volume). Four biomarker clusters emerged consistent with preclinical features of (i) Alzheimer’s disease; (ii) mixed Alzheimer’s disease and vascular aetiology; (iii) suspected non-Alzheimer’s disease aetiology; and (iv) healthy ageing. Cognitive decline was then analysed between clusters using longitudinal assessments of episodic memory, semantic memory, executive function, and global cognitive function with linear mixed effects modelling. Cluster 1 exhibited a higher intercept and greater rates of decline on tests of episodic memory. Cluster 2 had a lower intercept on a test of semantic memory and both Cluster 2 and Cluster 3 had steeper rates of decline on a test of global cognition. Additional analyses on Cluster 3, which had the smallest hippocampal volume, suggest that its biomarker profile is more likely due to hippocampal vulnerability and not to detectable specific volume loss exceeding the rate of normal ageing. Our results demonstrate that pathology, as indicated by biomarkers, in a preclinical timeframe is related to patterns of longitudinal cognitive decline. Such biomarker patterns may be useful for identifying at-risk populations to recruit for clinical trials.
Dougherty, R., L. Ellingson, S. Schultz, E. Boots, J. Meyer, J. Lindheimer, R. Van, A. Stegner, D. Edwards, J. Oh, R. Koscik, M. Dowling, C. Gallagher, C. Carlsson, H. Rowley, B. Bendlin, S. Asthana, B. Hermann, M. Sager, S. Johnson, O. Okonkwo, and D. Cook. “, Vol. 4, 2016, pp. 14-7.
Physical activity (PA) is associated with brain health in older adults. However, it is unknown whether the current physical activity recommendations (PAR) impart substantive benefit. The objective of this study was to compare temporal lobe volumes between older adults who met PAR and those who did not.
Racine, A., L. Clark, S. Berman, R. Koscik, K. Mueller, D. Norton, C. Nicholas, K. Blennow, H. Zetterberg, B. Jedynak, M. Bilgel, C. Carlsson, B. Christian, S. Asthana, and S. Johnson. “, Vol. 54, no. 4, 2016, pp. 1395-08.
It is not known whether computerized cognitive assessments, like the CogState battery, are sensitive to preclinical cognitive changes or pathology in people at risk for Alzheimer’s disease(AD). In 469 late middle-aged participants from the Wisconsin Registry for Alzheimer’s Prevention(mean age 63.8±7 years at testing; 67% female; 39% APOE4+), we examined relationships between a CogState abbreviated battery(CAB) of seven tests and demographic characteristics, traditional paper-based neuropsychological tests as well as a composite cognitive impairment index, cognitive impairment status(determined by consensus review), and biomarkers for amyloid and tau(CSF phosphorylated-tau/Aβ42 and global PET-PiB burden) and neural injury(CSF neurofilament light protein). CSF and PET-PiB were collected in n = 71 and n = 91 participants, respectively, approximately four years prior to CAB testing. For comparison, we examined three traditional tests of delayed memory in parallel. Similar to studies in older samples, the CAB was less influenced by demographic factors than traditional tests. CAB tests were generally correlated with most paper-based cognitive tests examined and mapped onto the same cognitive domains. Greater composite cognitive impairment index was associated with worse performance on all CAB tests. Cognitively impaired participants performed significantly worse compared to normal controls on all but one CAB test. Poorer One Card Learning test performance was associated with higher levels of CSF phosphorylated-tau/Aβ42. These results support the use of the CogState battery as measures of early cognitive impairment in studies of people at risk for AD.
Mueller, K., R. Koscik, L. Turkstra, S. Riedeman, A. LaRue, L. Clark, B. Hermann, M. Sager, and S. Johnson. “, Vol. 54, no. 4, 2016, pp. 1539-50.
Connected language is often impaired among people with Alzheimer’s disease (AD), yet little is known about when language difficulties first emerge on the path to a clinical diagnosis. The objective of this study was to determine whether individuals with psychometric (preclinical) evidence of amnestic mild cognitive impairment (pMCI) showed deficits in connected language measures. Participants were 39 pMCI and 39 cognitively healthy (CH) adults drawn from the Wisconsin Registry for Alzheimer’s Prevention, who were matched for age, literacy, and sex. Participants completed a connected language task in which they described the Cookie Theft picture from the Boston Diagnostic Aphasia Examination. Language samples were analyzed across three language domains: content, syntactic complexity, and speech fluency. Paired t-tests were used to compare CH and pMCI groups on all variables, and Cohen’s d effect sizes were calculated for each comparison. The CH and pMCI groups differed significantly on measures of content (e.g., CH group produced more semantic units, more unique words and had larger idea density, on average, than the pMCI group). The picture description findings are consistent with previous retrospective studies showing semantic language differences in adults with autopsy-confirmed AD. Given that these comparisons are between cognitively healthy and pMCI individuals (before a clinical MCI diagnosis), these findings may represent subtle language difficulty in spontaneous speech, and may be predictive of larger language changes over time.
Alterations to myelin may be a core pathological feature of neurodegenerative diseases. Although white matter microstructural differences have been described in Parkinson’s disease (PD), it is unknown whether such differences include alterations of the brain’s myelin content. Thus, the objective of the current study is to measure and compare brain myelin content between PD patients and age-matched controls. In this cross-sectional study, 63 participants from the Longitudinal MRI in Parkinson’s Disease study underwent brain MRI, Unified Parkinson’s Disease Rating Scale (UPDRS) scoring, and cognitive asessments. Subjects were imaged with the mcDEPSOT (multi-component driven equilibrium single pulse observation of T1 and T2), a multicomponent relaxometry technique that quantifies longitudinal and transverse relaxation rates (R1 and R2, respectively) and the myelin water fraction (VFM), a surrogate for myelin content. A voxel-wise approach was used to compare R1, R2, and VFM measures between PD and control groups, and to evaluate relationships with age as well as disease duration, UPDRS scores, and daily levodopa equivalent dose. PD subjects had higher VFM than controls in frontal and temporal white matter and bilateral thalamus. Greater age was strongly associated with lower VFM in both groups, while an age-by-group interaction suggested a slower rate of VFM decline in the left putamen with aging in PD. Within the PD group, measures of disease severity, including UPDRS, daily levodopa equivalent dose, and disease duration, were observed to be related with myelin content in diffuse brain regions. The age-by-group interaction suggests that either PD or dopaminergic therapies allay observed age-related myelin changes. The relationships between VFM and disease severity measures suggests that VFM may provide a surrogate marker for microstructural changes related to Parkinson’s disease.
Kim, H., B. Smith, N. Adluru, C. Dyer, S. Johnson, and V. Singh. “Abundant Inverse Regression Using Sufficient Reduction and Its Applications.”. Computer Vision - ECCV ... : ... European Conference on Computer Vision : Proceedings. European Conference on Computer Vision, Vol. 9907, 2016, pp. 570-84.
Statistical models such as linear regression drive numerous applications in computer vision and machine learning. The landscape of practical deployments of these formulations is dominated by forward regression models that estimate the parameters of a function mapping a set of p covariates,
, to a response variable, y. The less known alternative, Inverse Regression, offers various benefits that are much less explored in vision problems. The goal of this paper is to show how Inverse Regression in the “abundant” feature setting (i.e., many subsets of features are associated with the target label or response, as is the case for images), together with a statistical construction called Sufficient Reduction, yields highly flexible models that are a natural fit for model estimation tasks in vision. Specifically, we obtain formulations that provide relevance of individual covariates used in prediction, at the level of specific examples/samples – in a sense, explaining why a particular prediction was made. With no compromise in performance relative to other methods, an ability to interpret why a learning algorithm is behaving in a specific way for each prediction, adds significant value in numerous applications. We illustrate these properties and the benefits of Abundant Inverse Regression (AIR) on three distinct applications.
Kim, W., S. Hwang, N. Adluru, S. Johnson, and V. Singh. “Adaptive Signal Recovery on Graphs via Harmonic Analysis for Experimental Design in Neuroimaging.”. Computer Vision - ECCV ... : ... European Conference on Computer Vision : Proceedings. European Conference on Computer Vision, Vol. 9910, 2016, pp. 188-05.
Consider an experimental design of a neuroimaging study, where we need to obtain p measurements for each participant in a setting where p‘ (< p) are cheaper and easier to acquire while the remaining (p – p‘) are expensive. For example, the p‘ measurements may include demographics, cognitive scores or routinely offered imaging scans while the (p – p‘) measurements may correspond to more expensive types of brain image scans with a higher participant burden. In this scenario, it seems reasonable to seek an “adaptive” design for data acquisition so as to minimize the cost of the study without compromising statistical power. We show how this problem can be solved via harmonic analysis of a band-limited graph whose vertices correspond to participants and our goal is to fully recover a multi-variate signal on the nodes, given the full set of cheaper features and a partial set of more expensive measurements. This is accomplished using an adaptive query strategy derived from probing the properties of the graph in the frequency space. To demonstrate the benefits that this framework can provide, we present experimental evaluations on two independent neuroimaging studies and show that our proposed method can reliably recover the true signal with only partial observations directly yielding substantial financial savings.
Hwang, S., N. Adluru, M. Collins, S. Ravi, B. Bendlin, S. Johnson, and V. Singh. “Coupled Harmonic Bases for Longitudinal Characterization of Brain Networks.”. Proceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol. 2016, 2016, pp. 2517-25.
There is a great deal of interest in using large scale brain imaging studies to understand how brain connectivity evolves over time for an individual and how it varies over different levels/quantiles of cognitive function. To do so, one typically performs so-called tractography procedures on diffusion MR brain images and derives measures of brain connectivity expressed as graphs. The nodes correspond to distinct brain regions and the edges encode the strength of the connection. The scientific interest is in characterizing the evolution of these graphs over time or from healthy individuals to diseased. We pose this important question in terms of the Laplacian of the connectivity graphs derived from various longitudinal or disease time points – quantifying its progression is then expressed in terms of coupling the harmonic bases of a full set of Laplacians. We derive a coupled system of generalized eigenvalue problems (and corresponding numerical optimization schemes) whose solution helps characterize the full life cycle of brain connectivity evolution in a given dataset. Finally, we show a set of results on a diffusion MR imaging dataset of middle aged people at risk for Alzheimer’s disease (AD), who are cognitively healthy. In such asymptomatic adults, we find that a framework for characterizing brain connectivity evolution provides the ability to predict cognitive scores for individual subjects, and for estimating the progression of participant’s brain connectivity into the future.
Intraindividual cognitive variability (IICV) has been shown to differentiate between groups with normal cognition, mild cognitive impairment (MCI), and dementia. This study examined whether baseline IICV predicted subsequent mild to moderate cognitive impairment in a cognitively normal baseline sample.
Ravi, S., V. Ithapu, S. Johnson, and V. Singh. “Experimental Design on a Budget for Sparse Linear Models and Applications.”. JMLR Workshop and Conference Proceedings, Vol. 48, 2016, pp. 583-92.
Budget constrained optimal design of experiments is a well studied problem. Although the literature is very mature, not many strategies are available when these design problems appear in the context of sparse linear models commonly encountered in high dimensional machine learning. In this work, we study this budget constrained design where the underlying regression model involves a ℓ1-regularized linear function. We propose two novel strategies: the first is motivated geometrically whereas the second is algebraic in nature. We obtain tractable algorithms for this problem which also hold for a more general class of sparse linear models. We perform a detailed set of experiments, on benchmarks and a large neuroimaging study, showing that the proposed models are effective in practice. The latter experiment suggests that these ideas may play a small role in informing enrollment strategies for similar scientific studies in the future.
Consider samples from two different data sources [Formula: see text] and [Formula: see text]. We only observe their transformed versions [Formula: see text] and [Formula: see text], for some known function class h(·) and g(·). Our goal is to perform a statistical test checking if Psource = Ptarget while removing the distortions induced by the transformations. This problem is closely related to domain adaptation, and in our case, is motivated by the need to combine clinical and imaging based biomarkers from multiple sites and/or batches – a fairly common impediment in conducting analyses with much larger sample sizes. We address this problem using ideas from hypothesis testing on the transformed measurements, wherein the distortions need to be estimated in tandem with the testing. We derive a simple algorithm and study its convergence and consistency properties in detail, and provide lower-bound strategies based on recent work in continuous optimization. On a dataset of individuals at risk for Alzheimer’s disease, our framework is competitive with alternative procedures that are twice as expensive and in some cases operationally infeasible to implement.
Willette, A., S. Johnson, A. Birdsill, M. Sager, B. Christian, L. Baker, S. Craft, J. Oh, E. Statz, B. Hermann, E. Jonaitis, R. Koscik, R. La, S. Asthana, and B. Bendlin. “, Vol. 11, no. 5, 2015, pp. 504-510.e1.
Insulin resistance (IR) increases Alzheimer’s disease (AD) risk. IR is related to greater amyloid burden post-mortem and increased deposition within areas affected by early AD. No studies have examined if IR is associated with an in vivo index of amyloid in the human brain in late middle-aged participants at risk for AD.
Cardiorespiratory fitness (CRF) is an objective measure of habitual physical activity (PA), and has been linked to increased brain structure and cognition. The gold standard method for measuring CRF is graded exercise testing (GXT), but GXT is not feasible in many settings. The objective of this study was to examine whether a non-exercise estimate of CRF is related to gray matter (GM) volumes, white matter hyperintensities (WMH), cognition, objective and subjective memory function, and mood in a middle-aged cohort at risk for Alzheimer’s disease (AD). Three hundred and fifteen cognitively healthy adults (mean age =58.58 years) enrolled in the Wisconsin Registry for Alzheimer’s Prevention underwent structural MRI scanning, cognitive testing, anthropometric assessment, venipuncture for laboratory tests, and completed a self-reported PA questionnaire. A subset (n = 85) underwent maximal GXT. CRF was estimated using a previously validated equation incorporating sex, age, body-mass index, resting heart rate, and self-reported PA. Results indicated that the CRF estimate was significantly associated with GXT-derived peak oxygen consumption, validating its use as a non-exercise CRF measure in our sample. Support for this finding was seen in significant associations between the CRF estimate and several cardiovascular risk factors. Higher CRF was associated with greater GM volumes in several AD-relevant brain regions including the hippocampus, amygdala, precuneus, supramarginal gyrus, and rostral middle frontal gyrus. Increased CRF was also associated with lower WMH and better cognitive performance in Verbal Learning & Memory, Speed & Flexibility, and Visuospatial Ability. Lastly, CRF was negatively correlated with self- and informant-reported memory complaints, and depressive symptoms. Together, these findings suggest that habitual participation in physical activity may provide protection for brain structure and cognitive function, thereby decreasing future risk for AD.
Nicholas, C., O. Okonkwo, B. Bendlin, J. Oh, S. Asthana, H. Rowley, B. Hermann, M. Sager, and S. Johnson. “Posteromedial Hyperactivation During Episodic Recognition Among People With Memory Decline: Findings from the WRAP study.”. Brain Imaging and Behavior, Vol. 9, no. 4, 2015, pp. 690-02.
Episodic memory decline is one of the earliest preclinical symptoms of AD, and has been associated with an upregulation in the BOLD response in the prodromal stage (e.g. MCI) of AD. In a previous study, we observed upregulation in cognitively normal (CN) subjects with subclinical episodic memory decline compared to non-decliners. In light of this finding, we sought to determine if a separate cohort of Decliners will show increased brain activation compared to Stable subjects during episodic memory processing, and determine whether the BOLD effect was influenced by cerebral blood flow (CBF) or gray matter volume (GMV). Individuals were classified as a “Decliner” if scores on the Rey Auditory Verbal Learning Test (RAVLT) consistently fell ≥ 1.5 SD below expected intra- or inter-individual levels. FMRI was used to compare activation during a facial recognition memory task in 90 Stable (age = 59.1) and 34 Decliner (age = 62.1, SD = 5.9) CN middle-aged adults and 10 MCI patients (age = 72.1, SD = 9.4). Arterial spin labeling and anatomical T1 MRI were used to measure resting CBF and GMV, respectively. Stables and Decliners performed similarly on the episodic recognition memory task and significantly better than MCI patients. Compared to Stables, Decliners showed increased BOLD signal in the left precuneus on the episodic memory task that was not explained by CBF or GMV, familial AD risk factors, or neuropsychological measures. These findings suggest that subtle changes in the BOLD signal reflecting altered neural function may be a relatively early phenomenon associated with memory decline.
This study tested the hypothesis that frequent participation in cognitively-stimulating activities, specifically those related to playing games and puzzles, is beneficial to brain health and cognition among middle-aged adults at increased risk for Alzheimer’s disease (AD). Three hundred twenty-nine cognitively normal, middle-aged adults (age range, 43.2-73.8 years) enrolled in the Wisconsin Registry for Alzheimer’s Prevention (WRAP) participated in this study. They reported their current engagement in cognitive activities using a modified version of the Cognitive Activity Scale (CAS), underwent a structural MRI scan, and completed a comprehensive cognitive battery. FreeSurfer was used to derive gray matter (GM) volumes from AD-related regions of interest (ROIs), and composite measures of episodic memory and executive function were obtained from the cognitive tests. Covariate-adjusted least squares analyses were used to examine the association between the Games item on the CAS (CAS-Games) and both GM volumes and cognitive composites. Higher scores on CAS-Games were associated with greater GM volumes in several ROIs including the hippocampus, posterior cingulate, anterior cingulate, and middle frontal gyrus. Similarly, CAS-Games scores were positively associated with scores on the Immediate Memory, Verbal Learning & Memory, and Speed & Flexibility domains. These findings were not modified by known risk factors for AD. In addition, the Total score on the CAS was not as sensitive as CAS-Games to the examined brain and cognitive measures. For some individuals, participation in cognitive activities pertinent to game playing may help prevent AD by preserving brain structures and cognitive functions vulnerable to AD pathophysiology.
Jones, J., D. Jackson, K. Chambers, K. Dabbs, D. Hsu, C. Stafstrom, M. Seidenberg, and B. Hermann. “Children With Epilepsy and Anxiety: Subcortical and Cortical differences.”. Epilepsia, Vol. 56, no. 2, 2015, pp. 283-90.
Using a hypothesis-driven approach, subcortical and cortical regions implicated in anxiety disorders in the general population were examined in children with recent-onset epilepsy with versus without anxiety compared to controls. This study reports frequency of anxiety disorders while examining familial, clinical, and demographic variables associated with anxiety in children with epilepsy.
Darst, B., R. Koscik, B. Hermann, R. La, M. Sager, S. Johnson, and C. Engelman. “, Vol. 45, no. 4, 2015, pp. 1149-55.
Cognitive decline is one of the hallmark features of Alzheimer’s disease, but many studies struggle to find strong associations between cognitive function and genetic variants. In order to identify which aspects of cognition are more likely to have a strong genetic component, we assessed the heritability of various cognitive functions related to Alzheimer’s disease in 303 initially asymptomatic middle-aged adult siblings with a parental history of Alzheimer’s disease from the Wisconsin Registry for Alzheimer’s Prevention. Participants underwent extensive cognitive testing, and six cognitive factors were identified via factor analysis. Working Memory and Visual Learning & Memory had the highest heritability (52% and 41%, respectively). Inclusion of APOE allele counts did not notably change heritability estimates, indicating that there are likely additional genetic variants contributing to cognition. These findings suggest that future genetic studies should focus on the cognitive domains of Working Memory and Visual Learning & Memory.
Starks, E., O. Patrick, S. Hoscheidt, A. Racine, C. Carlsson, H. Zetterberg, K. Blennow, O. Okonkwo, L. Puglielli, S. Asthana, N. Dowling, C. Gleason, R. Anderson, N. Davenport-Sis, L. DeRungs, M. Sager, S. Johnson, and B. Bendlin. “, Vol. 46, no. 2, 2015, pp. 525-33.
Insulin resistance (IR) is linked with the occurrence of pathological features observed in Alzheimer’s disease (AD), including neurofibrillary tangles and amyloid plaques. However, the extent to which IR is associated with AD pathology in the cognitively asymptomatic stages of preclinical AD remains unclear.
Almeida, R., S. Schultz, B. Austin, E. Boots, N. Dowling, C. Gleason, B. Bendlin, M. Sager, B. Hermann, H. Zetterberg, C. Carlsson, S. Johnson, S. Asthana, and O. Okonkwo. “Effect of Cognitive Reserve on Age-Related Changes in Cerebrospinal Fluid Biomarkers of Alzheimer Disease.”. JAMA Neurology, Vol. 72, no. 6, 2015, pp. 699-06.
Although advancing age is the strongest risk factor for the development of symptomatic Alzheimer disease (AD), recent studies have shown that there are individual differences in susceptibility to age-related alterations in the biomarkers of AD pathophysiology.
Schultz, S., J. Oh, R. Koscik, N. Dowling, C. Gallagher, C. Carlsson, B. Bendlin, A. LaRue, B. Hermann, H. Rowley, S. Asthana, M. Sager, S. Johnson, and O. Okonkwo. “, Vol. 1, no. 1, 2015, pp. 33-40.
Subjective memory complaints (SMCs) represent an individual’s perception of subtle changes in memory in the absence of objective impairment in memory. However, it is not fully known whether persons with SMCs harbor brain alterations related to Alzheimer’s disease (AD) or whether they indeed demonstrate poorer cognitive performance.
In the last five years, a consensus has developed that Alzheimer’s disease (AD) may begin years before overt cognitive impairment. Accordingly, the focus has shifted to identifying preclinical disease in order to match treatments to those most likely to benefit. Subtle cognitive changes, including reduced benefit from practice, may be one such preclinical sign. In this study, we explore cognitive aging trajectories within a large cohort of clinically intact late middle-aged adults.
This study examined the relationship between phonemic and semantic (category) verbal fluency and cognitive status in the Wisconsin Registry for Alzheimer’s Prevention (WRAP), a longitudinal cohort enriched for family history of Alzheimer’s disease. Participants were 283 WRAP subjects (age 53.1[6.5] years at baseline); who had completed three waves of assessment, over ∼6 years and met psychometric criteria either for “cognitively healthy” (CH) or for psychometric amnestic mild cognitive impairment (aMCI) using an approach that did not consider fluency scores. CH and aMCI groups differed significantly on phonemic total scores, category total scores, phonemic switching, and category mean cluster size. These results suggest that measures of both phonemic and semantic fluency yield lower scores in persons with evidence of psychometric aMCI compared with those who are CH. Differences have not previously been reported in a group this young, and provide evidence for the importance of including multiple verbal fluency tests targeting preclinical Alzheimer’s disease.
There is significant interest, both from basic and applied research perspectives, in understanding how structural/functional connectivity changes can explain behavioral symptoms and predict decline in neurodegenerative diseases such as Alzheimer’s disease (AD). The first step in most such analyses is to encode the connectivity information as a graph; then, one may perform statistical inference on various ‘global’ graph theoretic summary measures (e.g., modularity, graph diameter) and/or at the level of individual edges (or connections). For AD in particular, clear differences in connectivity at the dementia stage of the disease (relative to healthy controls) have been identified. Despite such findings, AD-related connectivity changes in preclinical disease remain poorly characterized. Such preclinical datasets are typically smaller and group differences are weaker. In this paper, we propose a new multi-resolution method for performing statistical analysis of connectivity networks/graphs derived from neuroimaging data. At the high level, the method occupies the middle ground between the two contrasts – that is, to analyze global graph summary measures (global) or connectivity strengths or correlations for individual edges similar to voxel based analysis (local). Instead, our strategy derives a Wavelet representation at each primitive (connection edge) which captures the graph context at multiple resolutions. We provide extensive empirical evidence of how this framework offers improved statistical power by analyzing two distinct AD datasets. Here, connectivity is derived from diffusion tensor magnetic resonance images by running a tractography routine. We first present results showing significant connectivity differences between AD patients and controls that were not evident using standard approaches. Later, we show results on populations that are not diagnosed with AD but have a positive family history risk of AD where our algorithm helps in identifying potentially subtle differences between patient groups. We also give an easy to deploy open source implementation of the algorithm for use within studies of connectivity in AD and other neurodegenerative disorders.
Sprecher, K., B. Bendlin, A. Racine, O. Okonkwo, B. Christian, R. Koscik, M. Sager, S. Asthana, S. Johnson, and R. Benca. “Amyloid Burden Is Associated With Self-Reported Sleep in Nondemented Late Middle-Aged adults.”. Neurobiology of Aging, Vol. 36, no. 9, 2015, pp. 2568-76.
Midlife may be an ideal window for intervention in Alzheimer’s disease (AD). To determine whether sleep is associated with early signs of AD neuropathology (amyloid deposition) in late midlife, we imaged brain amyloid deposits using positron emission tomography with [C-11]Pittsburgh Compound B (PiB), and assessed sleep with the Epworth Sleepiness Scale and the Medical Outcomes Study Sleep Scale in 98 cognitively healthy adults (aged 62.4 ± 5.7 years) from the Wisconsin Registry for Alzheimer’s Prevention. We used multiple regressions to test the extent to which sleep scores predicted regional amyloid burden. Participants reporting less adequate sleep, more sleep problems, and greater somnolence on the Medical Outcomes Study had greater amyloid burden in AD-sensitive brain regions (angular gyrus, frontal medial orbital cortex, cingulate gyrus, and precuneus). Amyloid was not associated with reported sleep amount, symptoms of sleep-disordered breathing, trouble falling asleep, or Epworth Sleepiness Scale. Poor sleep may be a risk factor for AD and a potential early marker of AD or target for preventative interventions in midlife.
Boots, E., S. Schultz, R. Almeida, J. Oh, R. Koscik, M. Dowling, C. Gallagher, C. Carlsson, H. Rowley, B. Bendlin, S. Asthana, M. Sager, B. Hermann, S. Johnson, and O. Okonkwo. “”. Archives of Clinical Neuropsychology : The Official Journal of the National Academy of Neuropsychologists, Vol. 30, no. 7, 2015, pp. 634-42.
Higher occupational attainment has previously been associated with increased Alzheimer’s disease (AD) neuropathology when individuals are matched for cognitive function, indicating occupation could provide cognitive reserve. We examined whether occupational complexity (OCC) associates with decreased hippocampal volume and increased whole-brain atrophy given comparable cognitive function in middle-aged adults at risk for AD. Participants (n = 323) underwent structural MRI, cognitive evaluation, and work history assessment. Three complexity ratings (work with data, people, and things) were obtained, averaged across up to 3 reported jobs, weighted by years per job, and summed to create a composite OCC rating. Greater OCC was associated with decreased hippocampal volume and increased whole-brain atrophy when matched for cognitive function; results remained substantively unchanged after adjusting for several demographic, AD risk, vascular, mental health, and socioeconomic characteristics. These findings suggest that, in people at risk for AD, OCC may confer resilience to the adverse effects of neuropathology on cognition.
Doherty, B., S. Schultz, J. Oh, R. Koscik, N. Dowling, T. Barnhart, D. Murali, C. Gallagher, C. Carlsson, B. Bendlin, A. LaRue, B. Hermann, H. Rowley, S. Asthana, M. Sager, B. Christian, S. Johnson, and O. Okonkwo. “, Vol. 1, no. 2, 2015, pp. 160-9.
There is a growing interest in understanding how amyloid-β (Aβ) accumulation in preclinical Alzheimer’s disease relates to brain morphometric measures and cognition. Existing investigations in this area have been primarily conducted in older cognitively-normal (CN) individuals. Therefore, not much is known about the associations between Aβ burden, cortical thickness, and cognition in midlife. We examined this question in 109, CN, late-middle-aged adults (mean age=60.72±5.65 years) from the Wisconsin Registry for Alzheimer’s Prevention. They underwent Pittsburgh Compound B (PiB) and anatomical magnetic resonance (MR) imaging, and a comprehensive cognitive exam. Blinded visual rating of the PiB scans was used to classify the participants as Aβ+ or Aβ-. Cortical thickness measurements were derived from the MR images. The Aβ+ group exhibited significant thinning of the entorhinal cortex and accelerated age-associated thinning of the parahippocampal gyrus compared with the Aβ- group. The Aβ+ group also had numerically lower, but nonsignificant, test scores on all cognitive measures, and significantly faster age-associated cognitive decline on measures of Speed & Flexibility, Verbal Ability, and Visuospatial Ability. Our findings suggest that early Aβ aggregation is associated with deleterious changes in brain structure and cognitive function, even in midlife, and that the temporal lag between Aβ deposition and the inception of neurodegenerative/cognitive changes might be narrower than currently thought.
Willette, A., B. Bendlin, E. Starks, A. Birdsill, S. Johnson, B. Christian, O. Okonkwo, R. La, B. Hermann, R. Koscik, E. Jonaitis, M. Sager, and S. Asthana. “Association of Insulin Resistance With Cerebral Glucose Uptake in Late Middle-Aged Adults at Risk for Alzheimer Disease.”. JAMA Neurology, Vol. 72, no. 9, 2015, pp. 1013-20.
Converging evidence suggests that Alzheimer disease (AD) involves insulin signaling impairment. Patients with AD and individuals at risk for AD show reduced glucose metabolism, as indexed by fludeoxyglucose F 18-labeled positron emission tomography (FDG-PET).
Schultz, S., E. Boots, R. Almeida, J. Oh, J. Einerson, C. Korcarz, D. Edwards, R. Koscik, M. Dowling, C. Gallagher, B. Bendlin, B. Christian, H. Zetterberg, K. Blennow, C. Carlsson, S. Asthana, B. Hermann, M. Sager, S. Johnson, J. Stein, and O. Okonkwo. “Cardiorespiratory Fitness Attenuates the Influence of Amyloid on Cognition.”. Journal of the International Neuropsychological Society : JINS, Vol. 21, no. 10, 2015, pp. 841-50.
The aim of this study was to examine cross-sectionally whether higher cardiorespiratory fitness (CRF) might favorably modify amyloid-β (Aβ)-related decrements in cognition in a cohort of late-middle-aged adults at risk for Alzheimer’s disease (AD). Sixty-nine enrollees in the Wisconsin Registry for Alzheimer’s Prevention participated in this study. They completed a comprehensive neuropsychological exam, underwent 11C Pittsburgh Compound B (PiB)-PET imaging, and performed a graded treadmill exercise test to volitional exhaustion. Peak oxygen consumption (VO2peak) during the exercise test was used as the index of CRF. Forty-five participants also underwent lumbar puncture for collection of cerebrospinal fluid (CSF) samples, from which Aβ42 was immunoassayed. Covariate-adjusted regression analyses were used to test whether the association between Aβ and cognition was modified by CRF. There were significant VO2peak*PiB-PET interactions for Immediate Memory (p=.041) and Verbal Learning & Memory (p=.025). There were also significant VO2peak*CSF Aβ42 interactions for Immediate Memory (p<.001) and Verbal Learning & Memory (p<.001). Specifically, in the context of high Aβ burden, that is, increased PiB-PET binding or reduced CSF Aβ42, individuals with higher CRF exhibited significantly better cognition compared with individuals with lower CRF. In a late-middle-aged, at-risk cohort, higher CRF is associated with a diminution of Aβ-related effects on cognition. These findings suggest that exercise might play an important role in the prevention of AD. DOI: 10.1017/S1355617715000843
Kim, W., B. Bendlin, M. Chung, S. Johnson, and V. Singh. “Statistical Inference Models for Image Datasets With Systematic Variations.”. Proceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol. 2015, 2015, pp. 4795-03.
Statistical analysis of longitudinal or cross sectional brain imaging data to identify effects of neurodegenerative diseases is a fundamental task in various studies in neuroscience. However, when there are systematic variations in the images due to parameter changes such as changes in the scanner protocol, hardware changes, or when combining data from multi-site studies, the statistical analysis becomes problematic. Motivated by this scenario, the goal of this paper is to develop a unified statistical solution to the problem of systematic variations in statistical image analysis. Based in part on recent literature in harmonic analysis on diffusion maps, we propose an algorithm which compares operators that are resilient to the systematic variations. These operators are derived from the empirical measurements of the image data and provide an efficient surrogate to capturing the actual changes across images. We also establish a connection between our method to the design of wavelets in non-Euclidean space. To evaluate the proposed ideas, we present various experimental results on detecting changes in simulations as well as show how the method offers improved statistical power in the analysis of real longitudinal PIB-PET imaging data acquired from participants at risk for Alzheimer’s disease (AD).
Kim, W., S. Ravi, S. Johnson, O. Okonkwo, and V. Singh. “On Statistical Analysis of Neuroimages With Imperfect Registration.”. Proceedings. IEEE International Conference on Computer Vision, Vol. 2015, 2015, pp. 666-74.
A variety of studies in neuroscience/neuroimaging seek to perform statistical inference on the acquired brain image scans for diagnosis as well as understanding the pathological manifestation of diseases. To do so, an important first step is to register (or co-register) all of the image data into a common coordinate system. This permits meaningful comparison of the intensities at each voxel across groups (e.g., diseased versus healthy) to evaluate the effects of the disease and/or use machine learning algorithms in a subsequent step. But errors in the underlying registration make this problematic, they either decrease the statistical power or make the follow-up inference tasks less effective/accurate. In this paper, we derive a novel algorithm which offers immunity to local errors in the underlying deformation field obtained from registration procedures. By deriving a deformation invariant representation of the image, the downstream analysis can be made more robust as if one had access to a (hypothetical) far superior registration procedure. Our algorithm is based on recent work on scattering transform. Using this as a starting point, we show how results from harmonic analysis (especially, non-Euclidean wavelets) yields strategies for designing deformation and additive noise invariant representations of large 3-D brain image volumes. We present a set of results on synthetic and real brain images where we achieve robust statistical analysis even in the presence of substantial deformation errors; here, standard analysis procedures significantly under-perform and fail to identify the true signal.
Hwang, S., M. Collins, S. Ravi, V. Ithapu, N. Adluru, S. Johnson, and V. Singh. “A Projection Free Method for Generalized Eigenvalue Problem With a Nonsmooth Regularizer.”. Proceedings. IEEE International Conference on Computer Vision, Vol. 2015, 2015, pp. 1841-9.
Eigenvalue problems are ubiquitous in computer vision, covering a very broad spectrum of applications ranging from estimation problems in multi-view geometry to image segmentation. Few other linear algebra problems have a more mature set of numerical routines available and many computer vision libraries leverage such tools extensively. However, the ability to call the underlying solver only as a “black box” can often become restrictive. Many ‘human in the loop’ settings in vision frequently exploit supervision from an expert, to the extent that the user can be considered a subroutine in the overall system. In other cases, there is additional domain knowledge, side or even partial information that one may want to incorporate within the formulation. In general, regularizing a (generalized) eigenvalue problem with such side information remains difficult. Motivated by these needs, this paper presents an optimization scheme to solve generalized eigenvalue problems (GEP) involving a (nonsmooth) regularizer. We start from an alternative formulation of GEP where the feasibility set of the model involves the Stiefel manifold. The core of this paper presents an end to end stochastic optimization scheme for the resultant problem. We show how this general algorithm enables improved statistical analysis of brain imaging data where the regularizer is derived from other ‘views’ of the disease pathology, involving clinical measurements and other image-derived representations.
Cerebral blood flow (CBF) provides an indication of the metabolic status of the cortex and may have utility in elucidating preclinical brain changes in persons at risk for Alzheimer’s disease (AD) and related diseases. In this study, we investigated CBF in 327 well-characterized adults including patients with AD (n = 28), patients with amnestic mild cognitive impairment (aMCI, n = 23), older cognitively normal (OCN, n = 24) adults, and asymptomatic middle-aged adults (n = 252) with and without a family history (FH) of AD. Compared with the asymptomatic cohort, AD patients displayed significant hypoperfusion in the precuneus, posterior cingulate, lateral parietal cortex, and the hippocampal region. Patients with aMCI exhibited a similar but less marked pattern of hypoperfusion. Perfusion deficits within the OCN adults were primarily localized to the inferior parietal lobules. Asymptomatic participants with a maternal FH of AD showed hypoperfusion in hippocampal and parietofrontal regions compared with those without a FH of AD or those with only a paternal FH of AD. These observations persisted when gray matter volume was included as a voxel-wise covariate. Our findings suggest that having a mother with AD might confer a particular risk for AD-related cerebral hypoperfusion in midlife. In addition, they provide further support for the potential utility of arterial spin labeling for the measurement of AD-related neurometabolic dysfunction, particularly in situations where [18F]fluorodeoxyglucose imaging is infeasible or clinically contraindicated.
Ly, M., E. Canu, G. Xu, J. Oh, D. McLaren, N. Dowling, A. Alexander, M. Sager, S. Johnson, and B. Bendlin. “Midlife Measurements of White Matter Microstructure Predict Subsequent Regional White Matter Atrophy in Healthy adults.”. Human Brain Mapping, Vol. 35, no. 5, 2014, pp. 2044-54.
Although age-related brain changes are becoming better understood, midlife patterns of change are still in need of characterization, and longitudinal studies are lacking. The aim of this study was to determine if baseline fractional anisotropy (FA), obtained from diffusion tensor imaging (DTI) predicts volume change over a 4-year interval.
White matter hyperintensities (WMH) of presumed vascular origin, as seen on T2-weighted fluid attenuated inversion recovery magnetic resonance imaging, are known to increase with age and are elevated in Alzheimer’s disease (AD). The cognitive implications of these common markers are not well understood. Previous research has primarily focused on global measures of WMH burden and broad localizations that contain multiple white matter tracts. The aims of this study were to determine the pattern of WMH accumulation with age, risk for AD, and the relationship with cognitive function utilizing a voxel-wise analysis capable of identifying specific white matter regions. A total of 349 participants underwent T1-weighted and high-resolution T2-weighted fluid attenuated inversion recovery magnetic resonance imaging and neuropsychological testing. Increasing age and lower cognitive speed and flexibility (a component of executive function), were both significantly associated with regional WMH throughout the brain. When age was controlled, lower cognitive speed and flexibility was independently associated with WMH in the superior corona radiata. Apolipoprotein E ε4 and parental family history of AD were not associated with higher burden of WMH. The results contribute to a larger body of literature suggesting that white matter measures are linked with processing speed, and illustrate the utility of voxel-wise analysis in understanding the effect of lesion location on cognitive function.
Johnson, S., B. Christian, O. Okonkwo, J. Oh, S. Harding, G. Xu, A. Hillmer, D. Wooten, D. Murali, T. Barnhart, L. Hall, A. Racine, W. Klunk, C. Mathis, B. Bendlin, C. Gallagher, C. Carlsson, H. Rowley, B. Hermann, N. Dowling, S. Asthana, and M. Sager. “”. Neurobiology of Aging, Vol. 35, no. 3, 2014, pp. 576-84.
To determine the relationship between amyloid burden and neural function in healthy adults at risk for Alzheimer’s Disease (AD), we used multimodal imaging with [C-11]Pittsburgh compound B positron emission tomography, [F-18]fluorodeoxyglucose, positron emission tomography , and magnetic resonance imaging, together with cognitive measurement in 201 subjects (mean age, 60.1 years; range, 46-73 years) from the Wisconsin Registry for Alzheimer’s Prevention. Using a qualitative rating, 18% of the samples were strongly positive Beta-amyloid (Aβ+), 41% indeterminate (Aβi), and 41% negative (Aβ-). Aβ+ was associated with older age, female sex, and showed trends for maternal family history of AD and APOE4. Relative to the Aβ- group, Aβ+ and Aβi participants had increased glucose metabolism in the bilateral thalamus; Aβ+ participants also had increased metabolism in the bilateral superior temporal gyrus. Aβ+ participants exhibited increased gray matter in the lateral parietal lobe bilaterally relative to the Aβ- group, and no areas of significant atrophy. Cognitive performance and self report cognitive and affective symptoms did not differ between groups. Amyloid burden can be identified in adults at a mean age of 60 years and is accompanied by glucometabolic increases in specific areas, but not atrophy or cognitive loss. This asymptomatic stage may be an opportune window for intervention to prevent progression to symptomatic AD.
Recent studies have found an association between a variant in triggering receptor expressed on myeloid cells 2 (TREM2) (rs75932628-T) and both Alzheimer’s disease (AD) and cognitive function in individuals aged 80-100 years. The role of TREM2 in younger, asymptomatic individuals is unknown. We examined this variant in 1148 participants from the Wisconsin Registry for Alzheimer’s Prevention, a longitudinal study of middle-aged adults enriched for a parental history of AD. Thirteen individuals carried the T risk allele. Carriers were more likely to have a parental history of AD (100% of carriers vs. 70% of noncarriers; p = 0.01) and, among the parental history subset, families with a TREM2 carrier had a younger maternal age of AD onset than noncarriers (67.9 vs. 75.6 years; p = 0.03). There was no significant association between TREM2 carrier status and cognitive function or decline. In conclusion, the association between TREM2 and both parental history of AD and younger maternal age of AD onset provide additional support for the role of TREM2 in AD and illustrate the importance of considering family history in AD study design.
Precise detection and quantification of white matter hyperintensities (WMH) observed in T2-weighted Fluid Attenuated Inversion Recovery (FLAIR) Magnetic Resonance Images (MRI) is of substantial interest in aging, and age-related neurological disorders such as Alzheimer’s disease (AD). This is mainly because WMH may reflect co-morbid neural injury or cerebral vascular disease burden. WMH in the older population may be small, diffuse, and irregular in shape, and sufficiently heterogeneous within and across subjects. Here, we pose hyperintensity detection as a supervised inference problem and adapt two learning models, specifically, Support Vector Machines and Random Forests, for this task. Using texture features engineered by texton filter banks, we provide a suite of effective segmentation methods for this problem. Through extensive evaluations on healthy middle-aged and older adults who vary in AD risk, we show that our methods are reliable and robust in segmenting hyperintense regions. A measure of hyperintensity accumulation, referred to as normalized effective WMH volume, is shown to be associated with dementia in older adults and parental family history in cognitively normal subjects. We provide an open source library for hyperintensity detection and accumulation (interfaced with existing neuroimaging tools), that can be adapted for segmentation problems in other neuroimaging studies.
It is difficult to reliably detect the earliest signs of Alzheimer’s disease (AD)-associated cognitive impairment. Our aim was to compare 3 psychometric methods of identifying amnestic mild cognitive impairment (aMCI) in a middle-aged longitudinal cohort enriched for AD risk.
Okonkwo, O., J. Oh, R. Koscik, E. Jonaitis, C. Cleary, N. Dowling, B. Bendlin, A. Larue, B. Hermann, T. Barnhart, D. Murali, H. Rowley, C. Carlsson, C. Gallagher, S. Asthana, M. Sager, B. Christian, and S. Johnson. “”. Journal of the International Neuropsychological Society : JINS, Vol. 20, no. 4, 2014, pp. 422-33.
The relative influence of amyloid burden, neuronal structure and function, and prior cognitive performance on prospective memory decline among asymptomatic late middle-aged individuals at risk for Alzheimer’s disease (AD) is currently unknown. We investigated this using longitudinal cognitive data from 122 middle-aged adults (21 “Decliners” and 101 “Stables”) enrolled in the Wisconsin Registry for Alzheimer’s Prevention who underwent multimodality neuroimaging [11C-Pittsburgh Compound B (PiB), 18F-fluorodeoxyglucose (FDG), and structural/functional magnetic resonance imaging (fMRI)] 5.7 ± 1.4 years (range = 2.9-8.9) after their baseline cognitive assessment. Covariate-adjusted regression analyses revealed that the only imaging measure that significantly distinguished Decliners from Stables (p = .027) was a Neuronal Function composite derived from FDG and fMRI. In contrast, several cognitive measures, especially those that tap episodic memory, significantly distinguished the groups (p’s<.05). Complementary receiver operating characteristic curve analyses identified the Brief Visuospatial Memory Test-Revised (BVMT-R) Total (.82 ± .05, p < .001), the BVMT-R Delayed Recall (.73 ± .06, p = .001), and the Reading subtest from the Wide-Range Achievement Test-III (.72 ± .06, p = .002) as the top three measures that best discriminated the groups. These findings suggest that early memory test performance might serve a more clinically pivotal role in forecasting future cognitive course than is currently presumed. DOI: 10.1017/S1355617714000113
Jackson, D., J. Lin, K. Chambers, A. Kessler-Jones, J. Jones, D. Hsu, C. Stafstrom, M. Seidenberg, and B. Hermann. “Birth Weight and Cognition in Children With epilepsy.”. Epilepsia, Vol. 55, no. 6, 2014, pp. 901-8.
Birth weight is an important indicator of prenatal environment, and subtle variations of birth weight within the normal range have been associated with differential risk for cognitive and behavioral problems. Therefore, we aimed to determine if there are differences in birth weight between full-term children with uncomplicated new/recent-onset epilepsies and typically developing healthy controls. We further examined the relationships between birth weight and childhood/adolescent cognition, behavior, and academic achievement.
Some cognitively healthy individuals develop brain amyloid accumulation, suggestive of incipient Alzheimer’s disease (AD), but the effect of amyloid on other potentially informative imaging modalities, such as Diffusion Tensor Imaging (DTI), in characterizing brain changes in preclinical AD requires further exploration. In this study, a sample (N = 139, mean age 60.6, range 46 to 71) from the Wisconsin Registry for Alzheimer’s Prevention (WRAP), a cohort enriched for AD risk factors, was recruited for a multimodal imaging investigation that included DTI and [C-11]Pittsburgh Compound B (PiB) positron emission tomography (PET). Participants were grouped as amyloid positive (Aβ+), amyloid indeterminate (Aβi), or amyloid negative (Aβ-) based on the amount and pattern of amyloid deposition. Regional voxel-wise analyses of four DTI metrics, fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (Da), and radial diffusivity (Dr), were performed based on amyloid grouping. Three regions of interest (ROIs), the cingulum adjacent to the corpus callosum, hippocampal cingulum, and lateral fornix, were selected based on their involvement in the early stages of AD. Voxel-wise analysis revealed higher FA among Aβ+ compared to Aβ- in all three ROIs and in Aβi compared to Aβ- in the cingulum adjacent to the corpus callosum. Follow-up exploratory whole-brain analyses were consistent with the ROI findings, revealing multiple regions where higher FA was associated with greater amyloid. Lower fronto-lateral gray matter MD was associated with higher amyloid burden. Further investigation showed a negative correlation between MD and PiB signal, suggesting that Aβ accumulation impairs diffusion. Interestingly, these findings in a largely presymptomatic sample are in contradistinction to relationships reported in the literature in symptomatic disease stages of Mild Cognitive Impairment and AD, which usually show higher MD and lower FA. Together with analyses showing that cognitive function in these participants is not associated with any of the four DTI metrics, the present results suggest an early relationship between PiB and DTI, which may be a meaningful indicator of the initiating or compensatory mechanisms of AD prior to cognitive decline.
Little is still known about the effects of risk factors for Alzheimer’s disease (AD) on white matter microstructure in cognitively healthy adults. The purpose of this cross-sectional study was to assess the effect of two well-known risk factors for AD, parental family history and APOE4 genotype.
Cellular studies suggest sphingolipids may cause or accelerate amyloid-beta (Aβ) and tau pathology but in vivo human studies are lacking. We determined cerebrospinal fluid levels of sphingolipids (ceramides and sphingomyelins), amyloid-beta (Aβ1-42, AβX-38, AβX-40, and AβX-42) and tau (T-tau and p-tau181) in 91 cognitively normal individuals, aged 36-69 years, with a parental history of Alzheimer’s disease. The 18-carbon acyl chain length ceramide species was associated with AβX-38 (r = 0.312, p = 0.003), AβX-40 (r = 0.327, p = 0.002), and T-tau (r = 0.313, p = 0.003) but not with AβX-42 (r = 0.171, p = 0.106) or p-tau (r = 0.086, p = 0.418). All sphingomyelin species correlated (most p < 0.001) with all Aβ species and T-tau; many also correlated with p-tau. Results remained in regression models after controlling for age and APOE genotype. These results suggest in vivo relationships between cerebrospinal fluid ceramides and sphingomyelins and Aβ and tau levels in cognitively normal individuals at increased risk for Alzheimer's disease, indicating these sphingolipids may be associated with early pathogenesis. DOI: 10.1016/j.neurobiolaging.2014.05.019
Okonkwo, O., S. Schultz, J. Oh, J. Larson, D. Edwards, D. Cook, R. Koscik, C. Gallagher, N. Dowling, C. Carlsson, B. Bendlin, A. LaRue, H. Rowley, B. Christian, S. Asthana, B. Hermann, S. Johnson, and M. Sager. “Physical Activity Attenuates Age-Related Biomarker Alterations in Preclinical AD.”. Neurology, Vol. 83, no. 19, 2014, pp. 1753-60.
To examine whether engagement in physical activity might favorably alter the age-dependent evolution of Alzheimer disease (AD)-related brain and cognitive changes in a cohort of at-risk, late-middle-aged adults.
Kim, H., N. Adluru, B. Bendlin, S. Johnson, B. Vemuri, and V. Singh. “Canonical Correlation Analysis on Riemannian Manifolds and Its Applications.”. Computer Vision - ECCV ... : ... European Conference on Computer Vision : Proceedings. European Conference on Computer Vision, Vol. 8690, 2014, pp. 251-67.
Canonical correlation analysis (CCA) is a widely used statistical technique to capture correlations between two sets of multi-variate random variables and has found a multitude of applications in computer vision, medical imaging and machine learning. The classical formulation assumes that the data live in a pair of vector spaces which makes its use in certain important scientific domains problematic. For instance, the set of symmetric positive definite matrices (SPD), rotations and probability distributions, all belong to certain curved Riemannian manifolds where vector-space operations are in general not applicable. Analyzing the space of such data via the classical versions of inference models is rather sub-optimal. But perhaps more importantly, since the algorithms do not respect the underlying geometry of the data space, it is hard to provide statistical guarantees (if any) on the results. Using the space of SPD matrices as a concrete example, this paper gives a principled generalization of the well known CCA to the Riemannian setting. Our CCA algorithm operates on the product Riemannian manifold representing SPD matrix-valued fields to identify meaningful statistical relationships on the product Riemannian manifold. As a proof of principle, we present results on an Alzheimer’s disease (AD) study where the analysis task involves identifying correlations across diffusion tensor images (DTI) and Cauchy deformation tensor fields derived from T1-weighted magnetic resonance (MR) images.
Kim, H., N. Adluru, M. Collins, M. Chung, B. Bendlin, S. Johnson, R. Davidson, and V. Singh. “Multivariate General Linear Models (MGLM) on Riemannian Manifolds With Applications to Statistical Analysis of Diffusion Weighted Images.”. Proceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Vol. 2014, 2014, pp. 2705-12.
Linear regression is a parametric model which is ubiquitous in scientific analysis. The classical setup where the observations and responses, i.e., (xi , yi ) pairs, are Euclidean is well studied. The setting where yi is manifold valued is a topic of much interest, motivated by applications in shape analysis, topic modeling, and medical imaging. Recent work gives strategies for max-margin classifiers, principal components analysis, and dictionary learning on certain types of manifolds. For parametric regression specifically, results within the last year provide mechanisms to regress one real-valued parameter, xi ∈ R, against a manifold-valued variable, yi ∈ . We seek to substantially extend the operating range of such methods by deriving schemes for multivariate multiple linear regression -a manifold-valued dependent variable against multiple independent variables, i.e., f : R
→ . Our variational algorithm efficiently solves for multiple geodesic bases on the manifold concurrently via gradient updates. This allows us to answer questions such as: what is the relationship of the measurement at voxel y to disease when conditioned on age and gender. We show applications to statistical analysis of diffusion weighted images, which give rise to regression tasks on the manifold GL(n)/O(n) for diffusion tensor images (DTI) and the Hilbert unit sphere for orientation distribution functions (ODF) from high angular resolution acquisition. The companion open-source code is available on nitrc.org/projects/riem_mglm.
Willette, A., G. Xu, S. Johnson, A. Birdsill, E. Jonaitis, M. Sager, B. Hermann, R. La, S. Asthana, and B. Bendlin. “Insulin Resistance, Brain Atrophy, and Cognitive Performance in Late Middle-Aged adults.”. Diabetes Care, Vol. 36, no. 2, 2013, pp. 443-9.
Insulin resistance dysregulates glucose uptake and other functions in brain areas affected by Alzheimer disease. Insulin resistance may play a role in Alzheimer disease etiopathogenesis. This longitudinal study examined whether insulin resistance among late middle-aged, cognitively healthy individuals was associated with 1) less gray matter in Alzheimer disease-sensitive brain regions and 2) worse cognitive performance.
Walker, N., D. Jackson, K. Dabbs, J. Jones, D. Hsu, C. Stafstrom, R. Sheth, M. Koehn, M. Seidenberg, and B. Hermann. “Is Lower IQ in Children With Epilepsy Due to Lower Parental IQ? A Controlled Comparison study.”. Developmental Medicine and Child Neurology, Vol. 55, no. 3, 2013, pp. 278-82.
The aim of this study was to determine the relationship between parent and child Full-scale IQ (FSIQ) in children with epilepsy and in typically developing comparison children and to examine parent-child IQ differences by epilepsy characteristics.
Jackson, D., K. Dabbs, N. Walker, J. Jones, D. Hsu, C. Stafstrom, M. Seidenberg, and B. Hermann. “The Neuropsychological and Academic Substrate of new/Recent-Onset epilepsies.”. The Journal of Pediatrics, Vol. 162, no. 5, 2013, pp. 1047-53.e1.
To characterize neuropsychological and academic status in children, ages 8-18 years, with new-/recent-onset idiopathic generalized epilepsy (IGE) and idiopathic localization-related epilepsy (ILRE) compared with healthy controls.
Engelman, C., R. Koscik, E. Jonaitis, O. Okonkwo, B. Hermann, R. La, and M. Sager. “, Vol. 36, no. 4, 2013, pp. 749-57.
The strongest genetic factor for late-onset Alzheimer’s disease (AD) is APOE; nine additional susceptibility genes have recently been identified. The effect of these genes is often assumed to be additive and polygenic scores are formed as a summary measure of risk. However, interactions between these genes are likely to be important. We sought to examine the role of interactions between the nine recently identified AD susceptibility genes and APOE in cognitive function and decline in 1,153 participants from the Wisconsin Registry for Alzheimer’s Prevention, a longitudinal study of middle-aged adults enriched for a parental history of AD. Participants underwent extensive cognitive testing at baseline and up to two additional visits approximately 4 and 6 years later. The influence of the interaction between APOE and each of 14 single nucleotide polymorphisms (SNPs) in the nine recently identified genes on three cognitive factor scores (Verbal Learning and Memory, Working Memory, and Immediate Memory) was examined using linear mixed models adjusting for age, gender, and ancestry. Interactions between the APOE ε4 allele and both of the genotyped ABCA7 SNPs, rs3764650 and rs3752246, were associated with all three cognitive factor scores (p-values ≤ 0.01). Both of these genes are in the cholesterol metabolism pathway leading to AD. This research supports the importance of considering non-additive effects of AD susceptibility genes.
Birdsill, A., C. Carlsson, A. Willette, O. Okonkwo, S. Johnson, G. Xu, J. Oh, C. Gallagher, R. Koscik, E. Jonaitis, B. Hermann, A. LaRue, H. Rowley, S. Asthana, M. Sager, and B. Bendlin. “Low Cerebral Blood Flow Is Associated With Lower Memory Function in Metabolic syndrome.”. Obesity (Silver Spring, Md.), Vol. 21, no. 7, 2013, pp. 1313-20.
Metabolic syndrome (MetS)–a cluster of cardiovascular risk factors–is linked with cognitive decline and dementia. However, the brain changes underlying this link are presently unknown. In this study, we tested the relationship between MetS, cerebral blood flow (CBF), white matter hyperintensity burden, and gray matter (GM) volume in cognitively healthy late middle-aged adults. Additionally, the extent to which MetS was associated with cognitive performance was assessed.
To examine the associations of stressful experiences and social support with cognitive function in a sample of middle-aged adults with a family history of Alzheimer’s disease (AD).
Cognitive activity is thought to provide some protection against dementia, but the mechanism and timing of these effects are unknown. Data for this study were drawn from the Wisconsin Registry for Alzheimer’s Prevention (WRAP), an at-risk middle-aged sample (mean age = 54 years) enriched for parental family history of Alzheimer’s disease (AD). We had two main aims: (a) to determine the relative contribution of three facets of cognitive activity-education, occupational complexity with data, and cognitive leisure activities-to WRAP participants’ cognitive performance; and (b) to assess for interactions between genetic risk factors and cognitive activity in explaining cognitive performance. Results from mixed effects models indicate that some of the variance usually attributed to education may be more closely accounted for by cognitive activities later in life. Overall, our analyses suggest cautious optimism for cognitive activities, especially game playing, as a strategy for preserving cognitive strengths in midlife.
Hypercholesterolemia in midlife increases risk for Alzheimer’s disease (AD) and contributes to cerebrovascular dysregulation – an early finding in preclinical AD pathology. Statins improve vascular reactivity, but it is unknown if they increase regional cerebral blood flow (CBF) in individuals at risk for AD.
Ries, M., D. McLaren, B. Bendlin, Guofanxu, H. Rowley, R. Birn, E. Kastman, M. Sager, S. Asthana, and S. Johnson. “Medial Prefrontal Functional Connectivity--Relation to Memory Self-Appraisal Accuracy in Older Adults With and Without Memory disorders.”. Neuropsychologia, Vol. 50, no. 5, 2012, pp. 603-11.
It is tentatively estimated that 25% of people with early Alzheimer’s disease (AD) show impaired awareness of disease-related changes in their own cognition. Research examining both normative self-awareness and altered awareness resulting from brain disease or injury points to the central role of the medial prefrontal cortex (MPFC) in generating accurate self-appraisals. The current project builds on this work – examining changes in MPFC functional connectivity that correspond to impaired self-appraisal accuracy early in the AD time course. Our behavioral focus was self-appraisal accuracy for everyday memory function, and this was measured using the Memory Function Scale of the Memory Awareness Rating Scale – an instrument psychometrically validated for this purpose. Using regression analysis of data from people with healthy memory (n=12) and people with impaired memory due to amnestic mild cognitive impairment or early AD (n=12), we tested the hypothesis that altered MPFC functional connectivity – particularly with other cortical midline structures and dorsolateral prefrontal cortex – explains variation in memory self-appraisal accuracy. We spatially constrained (i.e., explicitly masked) our regression analyses to those regions that work in conjunction with the MPFC to evoke self-appraisals in a normative group. This empirically derived explicit mask was generated from the result of a psychophysiological interaction analysis of fMRI self-appraisal task data in a separate, large group of cognitively healthy individuals. Results of our primary analysis (i.e., the regression of memory self-appraisal accuracy on MPFC functional connectivity) were generally consistent with our hypothesis: people who were less accurate in making memory self-appraisals showed attenuated functional connectivity between the MPFC seed region and proximal areas within the MPFC (including subgenual anterior cingulate cortex), bilateral dorsolateral prefrontal cortex, bilateral caudate, and left posterior hippocampus. Contrary to our expectations, MPFC functional connectivity with the posterior cingulate was not significantly related to accuracy of memory self-appraisals. Results reported here corroborate findings of variable memory self-appraisal accuracy during the earliest emergence of AD symptoms and reveal alterations in MPFC functional connectivity that correspond to impaired memory self-appraisal.
Identification of preclinical Alzheimer’s disease (AD) is an essential first step in developing interventions to prevent or delay disease onset. In this study, we examine the hypothesis that deeper analyses of traditional cognitive tests may be useful in identifying subtle but potentially important learning and memory differences in asymptomatic populations that differ in risk for developing Alzheimer’s disease. Subjects included 879 asymptomatic higher-risk persons (middle-aged children of parents with AD) and 355 asymptotic lower-risk persons (middle-aged children of parents without AD). All were administered the Rey Auditory Verbal Learning Test at baseline. Using machine learning approaches, we constructed a new measure that exploited finer differences in memory strategy than previous work focused on serial position and subjective organization. The new measure, based on stochastic gradient descent, provides a greater degree of statistical separation (p = 1.44 × 10-5) than previously observed for asymptomatic family history and non-family history groups, while controlling for apolipoprotein epsilon 4, age, gender, and education level. The results of our machine learning approach support analyzing memory strategy in detail to probe potential disease onset. Such distinct differences may be exploited in asymptomatic middle-aged persons as a potential risk factor for AD.
Okonkwo, O., G. Xu, N. Dowling, B. Bendlin, A. Larue, B. Hermann, R. Koscik, E. Jonaitis, H. Rowley, C. Carlsson, S. Asthana, M. Sager, and S. Johnson. “Family History of Alzheimer Disease Predicts Hippocampal Atrophy in Healthy Middle-Aged adults.”. Neurology, Vol. 78, no. 22, 2012, pp. 1769-76.
To evaluate the longitudinal influence of family history (FH) of Alzheimer disease (AD) and apolipoprotein E ε4 allele (APOE4) on brain atrophy and cognitive decline over 4 years among asymptomatic middle-aged individuals.
Cerebrospinal fluid (CSF) biomarkers T-Tau and Aβ(42) are linked with Alzheimer’s disease (AD), yet little is known about the relationship between CSF biomarkers and structural brain alteration in healthy adults. In this study we examined the extent to which AD biomarkers measured in CSF predict brain microstructure indexed by diffusion tensor imaging (DTI) and volume indexed by T1-weighted imaging. Forty-three middle-aged adults with parental family history of AD received baseline lumbar puncture and MRI approximately 3.5 years later. Voxel-wise image analysis methods were used to test whether baseline CSF Aβ(42), total tau (T-Tau), phosphorylated tau (P-Tau) and neurofilament light protein predicted brain microstructure as indexed by DTI and gray matter volume indexed by T1-weighted imaging. T-Tau and T-Tau/Aβ(42) were widely correlated with indices of brain microstructure (mean, axial, and radial diffusivity), notably in white matter regions adjacent to gray matter structures affected in the earliest stages of AD. None of the CSF biomarkers were related to gray matter volume. Elevated P-Tau and P-Tau/Aβ(42) levels were associated with lower recognition performance on the Rey Auditory Verbal Learning Test. Overall, the results suggest that CSF biomarkers are related to brain microstructure in healthy adults with elevated risk of developing AD. Furthermore, the results clearly suggest that early pathological changes in AD can be detected with DTI and occur not only in cortex, but also in white matter.
Wharton, W., J. Stein, C. Korcarz, J. Sachs, S. Olson, H. Zetterberg, M. Dowling, S. Ye, C. Gleason, G. Underbakke, L. Jacobson, S. Johnson, M. Sager, S. Asthana, and C. Carlsson. “, Vol. 32, no. 1, 2012, pp. 147-56.
Research shows that certain antihypertensives taken during midlife confer Alzheimer’s disease (AD) related benefits in later life. We conducted a clinical trial to evaluate the extent to which the angiotensin converting enzyme inhibitor (ACE-I), ramipril, affects AD biomarkers including cerebrospinal fluid (CSF) amyloid-β (Aβ) levels and ACE activity, arterial function, and cognition in participants with a parental history of AD. This four month randomized, double-blind, placebo-controlled, pilot clinical trial evaluated the effects of ramipril, a blood-brain-barrier crossing ACE-I, in cognitively healthy individuals with mild, or Stage I hypertension. Fourteen participants were stratified by gender and apolipoprotein E ε4 (APOE ε4) status and randomized to receive 5 mg of ramipril or matching placebo daily. Participants were assessed at baseline and month 4 on measures of CSF Aβ(1-42) and ACE activity, arterial function, and cognition. Participants were middle-aged (mean 54 y) and highly educated (mean 15.4 y), and included 50% men and 50% APOE ε4 carriers. While results did not show a treatment effect on CSF Aβ(1-42) (p = 0.836), data revealed that ramipril can inhibit CSF ACE activity (p = 0.009) and improve blood pressure, however, there were no differences between groups in arterial function or cognition. In this study, ramipril therapy inhibited CSF ACE activity and improved blood pressure, but did not influence CSF Aβ1-42. While larger trials are needed to confirm our CSF Aβ results, it is possible that prior research reporting benefits of ACE-I during midlife may be attributed to alternative mechanisms including improvements in cerebral blood flow or the prevention of angiotensin II-mediated inhibition of acetylcholine.
Naylor, M., J. Karlawish, S. Arnold, A. Khachaturian, Z. Khachaturian, V. Lee, M. Baumgart, S. Banerjee, C. Beck, K. Blennow, R. Brookmeyer, K. Brunden, K. Buckwalter, M. Comer, K. Covinsky, L. Feinberg, G. Frisoni, C. Green, R. Guimaraes, L. Gwyther, F. Hefti, M. Hutton, C. Kawas, D. Kent, L. Kuller, K. Langa, R. Mahley, K. Maslow, C. Masters, D. Meier, P. Neumann, S. Paul, R. Petersen, M. Sager, M. Sano, D. Schenk, H. Soares, R. Sperling, S. Stahl, D. van, Y. Stern, D. Weir, D. Wolk, and J. Trojanowski. “, Vol. 8, no. 5, 2012, pp. 445-52.
To address the pending public health crisis due to Alzheimer’s disease (AD) and related neurodegenerative disorders, the Marian S. Ware Alzheimer Program at the University of Pennsylvania held a meeting entitled “State of the Science Conference on the Advancement of Alzheimer’s Diagnosis, Treatment and Care,” on June 21-22, 2012. The meeting comprised four workgroups focusing on Biomarkers; Clinical Care and Health Services Research; Drug Development; and Health Economics, Policy, and Ethics. The workgroups shared, discussed, and compiled an integrated set of priorities, recommendations, and action plans, which are presented in this article.
The cognitive effects of postmenopausal hormone therapy (HT) have been studied extensively, but little is known about the relationship between premenopausal hormone use and cognition. Hormonal contraceptive use vs. nonuse may be a potential factor influencing cognitive processes in midlife. The aim of this study is to explore the effect of modification of hormone milieu through use of hormonal contraception in premenopausal women and midlife cognitive function.
Johnson, S., R. La, B. Hermann, G. Xu, R. Koscik, E. Jonaitis, B. Bendlin, K. Hogan, A. Roses, A. Saunders, M. Lutz, S. Asthana, R. Green, and M. Sager. “, Vol. 7, no. 4, 2011, pp. 456-65.
Apolipoprotein E (APOE) genotypes are associated with variable risk of developing late-onset Alzheimer’s disease (LOAD), with APOE epsilon 4 (APOE ε4) having higher risk. A variable poly-T length polymorphism at rs10524523, within intron 6 of the translocase of the outer mitochondrial membrane (TOMM40) gene, has been shown to influence age of onset in LOAD, with very long (VL) poly-T length associated with earlier disease onset, and short poly-T length associated with later onset. In this study, we tested the hypothesis that brain and cognitive changes suggestive of presymptomatic LOAD may be associated with this TOMM40 polymorphism.
Jackson, D., W. Irwin, K. Dabbs, J. Lin, J. Jones, D. Hsu, C. Stafstrom, M. Seidenberg, and B. Hermann. “Ventricular Enlargement in New-Onset Pediatric epilepsies.”. Epilepsia, Vol. 52, no. 12, 2011, pp. 2225-32.
To examine baseline and prospective (2-year) changes in third, fourth, and lateral ventricle volumes in children with new-onset idiopathic epilepsies and controls (age 8-18 years).
Arterial spin labeling (ASL) offers MRI measurement of cerebral blood flow (CBF) in vivo, and may offer clinical diagnostic utility in populations such as those with early Alzheimer’s disease (AD). In the current study, we investigated the reliability and precision of a pseudo-continuous ASL (pcASL) sequence that was performed two or three times within one hour on eight young normal control subjects, and 14 elderly subjects including 11 with normal cognition, one with AD and two with Mild Cognitive Impairment (MCI). Six of these elderly subjects including one AD, two MCIs and three controls also received (15)O-water positron emission tomography (PET) scans 2 h before their pcASL MR scan. The instrumental reliability of pcASL was evaluated with the intraclass correlation coefficient (ICC). The ICCs were greater than 0.90 in pcASL global perfusion measurements for both the young and the elderly groups. The cross-modality perfusion imaging comparison yielded very good global and regional agreement in global gray matter and the posterior cingulate cortex. Significant negative correlation was found between age and the gray/white matter perfusion ratio (r = -0.62, p < 0.002). The AD and MCI patients showed the lowest gray/white matter perfusion ratio among all the subjects. The data suggest that pcASL provides a reliable whole brain CBF measurement in young and elderly adults whose results converge with those obtained with the traditional (15)O-water PET perfusion imaging method. pcASL perfusion MRI offers an alternative method for non-invasive in vivo examination of early pathophysiological changes in AD. DOI: 10.1002/nbm.1462
La, R. “Healthy Brain Aging: Role of Cognitive Reserve, Cognitive Stimulation, and Cognitive exercises.”. Clinics in Geriatric Medicine, Vol. 26, no. 1, 2010, pp. 99-111.
Current knowledge about the roles of cognitively stimulating lifestyles and cognitive training interventions in preserving cognitive function in later life is reviewed. Potential mechanisms for beneficial effects of cognitive stimulation and training are discussed, and key gaps in research identified. Suggestions are provided for advising patients about brain-healthy lifestyles, acknowledging that much remains to be learned in this area of research. More randomized controlled trials, using challenging regimes of training and stimulation and long-term follow-up, are needed, measuring cognitive trajectories in normal aging and relative risk of Alzheimer disease as outcomes.
Khachaturian, Z., D. Barnes, R. Einstein, S. Johnson, V. Lee, A. Roses, M. Sager, W. Shankle, P. Snyder, R. Petersen, G. Schellenberg, J. Trojanowski, P. Aisen, M. Albert, J. Breitner, N. Buckholtz, M. Carrillo, S. Ferris, B. Greenberg, M. Grundman, A. Khachaturian, L. Kuller, O. Lopez, P. Maruff, R. Mohs, M. Morrison-Bogorad, C. Phelps, E. Reiman, M. Sabbagh, M. Sano, L. Schneider, E. Siemers, P. Tariot, J. Touchon, B. Vellas, and L. Bain. “, Vol. 6, no. 2, 2010, pp. 89-97.
Among the major impediments to the design of clinical trials for the prevention of Alzheimer’s disease (AD), the most critical is the lack of validated biomarkers, assessment tools, and algorithms that would facilitate identification of asymptomatic individuals with elevated risk who might be recruited as study volunteers. Thus, the Leon Thal Symposium 2009 (LTS’09), on October 27-28, 2009 in Las Vegas, Nevada, was convened to explore strategies to surmount the barriers in designing a multisite, comparative study to evaluate and validate various approaches for detecting and selecting asymptomatic people at risk for cognitive disorders/dementia. The deliberations of LTS’09 included presentations and reviews of different approaches (algorithms, biomarkers, or measures) for identifying asymptomatic individuals at elevated risk for AD who would be candidates for longitudinal or prevention studies. The key nested recommendations of LTS’09 included: (1) establishment of a National Database for Longitudinal Studies as a shared research core resource; (2) launch of a large collaborative study that will compare multiple screening approaches and biomarkers to determine the best method for identifying asymptomatic people at risk for AD; (3) initiation of a Global Database that extends the concept of the National Database for Longitudinal Studies for longitudinal studies beyond the United States; and (4) development of an educational campaign that will address public misconceptions about AD and promote healthy brain aging.
Bendlin, B., M. Ries, E. Canu, A. Sodhi, M. Lazar, A. Alexander, C. Carlsson, M. Sager, S. Asthana, and S. Johnson. “, Vol. 6, no. 5, 2010, pp. 394-03.
Brain alterations in structure and function have been identified in people with risk factors for sporadic type Alzheimer’s disease (AD), suggesting that alterations can be detected decades before AD diagnosis. Although the effect of apolipoprotein E (APOE) varepsilon4 on the brain is well-studied, less is known about the effect of family history of AD. We examined the main effects of family history and APOE varepsilon4 on brain integrity, in addition to assessing possible additive effects of these two risk factors.
Ward, M., B. Bendlin, D. McLaren, T. Hess, C. Gallagher, E. Kastman, H. Rowley, S. Asthana, C. Carlsson, M. Sager, and S. Johnson. “Low HDL Cholesterol Is Associated With Lower Gray Matter Volume in Cognitively Healthy Adults.”. Frontiers in Aging Neuroscience, Vol. 2, 2010.
Dyslipidemia is common in adults and contributes to high rates of cardiovascular disease and may be linked to subsequent neurodegenerative and neurovascular diseases. This study examined whether lower brain volumes and cognition associated with dyslipidemia could be observed in cognitively healthy adults, and whether apolipoprotein E (APOE) genotype or family history of Alzheimer’s disease (FHAD) alters this effect. T1-weighted magnetic resonance imaging was used to examine regional brain gray matter (GM) and white matter (WM) in 183 individuals (58.4 +/- 8.0 years) using voxel-based morphometry. A non-parametric multiple linear regression model was used to assess the effect of high-density lipoprotein (HDL) and non-HDL cholesterol, APOE, and FHAD on regional GM and WM volume. A post hoc analysis was used to assess whether any significant correlations found within the volumetric analysis had an effect on cognition. HDL was positively correlated with GM volume in the bilateral temporal poles, middle temporal gyri, temporo-occipital gyri, and left superior temporal gyrus and parahippocampal region. This effect was independent of APOE and FHAD. A significant association between HDL and the Brief Visuospatial Memory Test was found. Additionally, GM volume within the right middle temporal gyrus, the region most affected by HDL, was significantly associated with the Controlled Oral Word Association Test and the Center for Epidemiological Studies Depression Scale. These findings suggest that adults with decreased levels of HDL cholesterol may be experiencing cognitive changes and GM reductions in regions associated with neurodegenerative disease and therefore, may be at greater risk for future cognitive decline.
Bendlin, B., L. Newman, M. Ries, L. Puglielli, C. Carlsson, M. Sager, H. Rowley, C. Gallagher, A. Willette, A. Alexander, S. Asthana, and S. Johnson. “NSAIDs May Protect Against Age-Related Brain atrophy.”. Frontiers in Aging Neuroscience, Vol. 2, 2010.
The use of non-steroidal anti-inflammatory drugs (NSAIDs) in humans is associated with brain differences including decreased number of activated microglia. In animals, NSAIDs are associated with reduced microglia, decreased amyloid burden, and neuronal preservation. Several studies suggest NSAIDs protect brain regions affected in the earliest stages of AD, including hippocampal and parahippocampal regions. In this cross-sectional study, we examined the protective effect of NSAID use on gray matter volume in a group of middle-aged and older NSAID users (n = 25) compared to non-user controls (n = 50). All participants underwent neuropsychological testing and T1-weighted magnetic resonance imaging. Non-user controls showed smaller volume in portions of the left hippocampus compared to NSAID users. Age-related loss of volume differed between groups, with controls showing greater medial temporal lobe volume loss with age compared to NSAID users. These results should be considered preliminary, but support previous reports that NSAIDs may modulate age-related loss of brain volume.
To examine the latent structure of a test battery currently being used in a longitudinal study of asymptomatic middle-aged adults with a parental history of Alzheimer’s disease (AD) and test the invariance of the factor solution across subgroups defined by selected demographic variables and known genetic risk factors for AD.
Hermann, B., and J. Langfitt. “Forgetting to Remember in Epilepsy: A Family affair?”. Neurology, Vol. 75, no. 24, 2010, pp. 2144-55.
Johnson, S., T. Schmitz, M. Trivedi, M. Ries, B. Torgerson, C. Carlsson, S. Asthana, B. Hermann, and M. Sager. “The Influence of Alzheimer Disease Family History and Apolipoprotein E Epsilon4 on Mesial Temporal Lobe activation.”. The Journal of Neuroscience : The Official Journal of the Society for Neuroscience, Vol. 26, no. 22, 2006, pp. 6069-76.
First-degree family history of sporadic Alzheimer disease (AD) and the apolipoprotein E epsilon4 (APOE4) are risk factors for developing AD. Although the role of APOE4 in AD pathogenesis has been well studied, family history remains a rarely studied and poorly understood risk factor. Both putatively cause early brain changes before symptomatic disease, but the relative contribution of each to brain function is unknown. We examined 68 middle-aged participants with a parent diagnosed with AD [family history (+FH)] and 64 age- and education-matched controls without a first-degree family history of any dementia [no family history (-FH)]. All underwent cognitive testing, APOE genotyping, and a functional magnetic resonance imaging encoding task that required discrimination of novel items from previously learned items. A 2 x 2 factorial ANOVA (presence/absence of parental family history and presence/absence of the APOE4) was used to detect group effects. A greater response to novel items was detected in the mesial temporal lobe and fusiform gyrus bilaterally among persons without a first-degree family history of AD. In hippocampal areas, the -FH +epsilon4 group exhibited the greatest signal change, and the +FH +epsilon4 group exhibited the least. These findings indicate that FH of AD is an important predictor of hippocampal activation during encoding and that FH may modulate the effect of APOE4 in these middle-aged adults, suggesting that an as yet unspecified factor embodied in first-degree family history of AD is influencing the expression of APOE4 on brain function.
Gleason, C., T. Schmitz, T. Hess, R. Koscik, M. Trivedi, M. Ries, C. Carlsson, M. Sager, S. Asthana, and S. Johnson. “Hormone Effects on FMRI and Cognitive Measures of Encoding: Importance of Hormone preparation.”. Neurology, Vol. 67, no. 11, 2006, pp. 2039-41.
We compared fMRI and cognitive data from nine hormone therapy (HT)-naive women with data from women exposed to either opposed conjugated equine estrogens (CEE) (n = 10) or opposed estradiol (n = 4). Exposure to either form of HT was associated with healthier fMRI response; however, CEE-exposed women exhibited poorer memory performance than either HT-naive or estradiol-exposed subjects. These preliminary findings emphasize the need to characterize differential neural effects of various HTs.
This study examined the functionality of the medial temporal lobe (MTL) and posterior cingulate (PC) in mild cognitive impairment amnestic type (MCI), a syndrome that puts patients at greater risk for developing Alzheimer disease (AD). Functional MRI (fMRI) was used to identify regions normally active during encoding of novel items and recognition of previously learned items in a reference group of 77 healthy young and middle-aged adults. The pattern of activation in this group guided further comparisons between 14 MCI subjects and 14 age-matched controls. The MCI patients exhibited less activity in the PC during recognition of previously learned items, and in the right hippocampus during encoding of novel items, despite comparable task performance to the controls. Reduced fMRI signal change in the MTL supports prior studies implicating the hippocampus for encoding new information. Reduced signal change in the PC converges with recent research on its role in recognition in normal adults as well as metabolic decline in people with genetic or cognitive risk for AD. Our results suggest that a change in function in the PC may account, in part, for memory recollection failure in AD.
The presence of the apolipoprotein E (APOE) epsilon4 allele is a major risk factor for the development of Alzheimer’s disease (AD), and has been associated with metabolic brain changes several years before the onset of typical AD symptoms. Functional MRI (fMRI) is a brain imaging technique that has been used to demonstrate hippocampal activation during measurement of episodic encoding, but the effect of the epsilon4 allele on hippocampal activation has not been firmly established.
La, R., B. Hermann, J. Jones, S. Johnson, S. Asthana, and M. Sager. “, Vol. 4, no. 4, 2008, pp. 285-90.
An exaggerated recency effect (ie, disproportionate recall of last-presented items) has been consistently observed in the word list learning of patients with Alzheimer’s disease (AD). Our study sought to determine whether there were similar alterations in serial position learning among asymptomatic persons at risk for AD as a result of parental family history.
First-degree family history (FH) of sporadic Alzheimer’s disease and the apolipoprotein E epsilon4 allele (APOE4) are risk factors for Alzheimer’s disease that may affect brain function prior to onset of clinical symptoms. In this functional MRI (fMRI) study, we used an episodic recognition task that required discrimination of previously viewed (PV) and novel (NV) faces to examine differences in blood oxygen level dependent (BOLD) signal due to risk factors in 74 middle-aged cognitively normal individuals. The group effects on this recognition task were tested with a 2 x 2 ANCOVA factorial design (+FH/-FH and +APOE4/-APOE4). There were significant APOE4 and FH effects in the left dorsal posterior cingulate cortex and precuneus, where decreased risk resulted in greater activity during recollection. Recognition performance was positively correlated with BOLD signal in the left posterior hippocampus, parahippocampal-retrosplenial gyrus and left superior frontal cortex regardless of risk factors. To examine condition-specific group effects, both the PV and NV faces were tested further in separate 2 x 2 ANCOVAs. Both models revealed an APOE effect, with the -APOE4 group showing stronger signal than the +APOE4 group in anterior cingulate cortices, while a FH effect was found in the dorsal cuneus and medial frontal cortices with the -FH group showing stronger signal than the +FH group. Finally, interactions between APOE4 and FH effects were found bilaterally in the fusiform gyrus. These results suggest that risk factors and cognitive performance each influence brain activity during recognition. The findings lend further support to the idea that functional brain changes may begin far in advance of symptomatic Alzheimer’s disease.