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Abstract Background Changes in sleep, physical activity and mental health were observed in older adults during early stages of the COVID-19 pandemic. Here we describe effects of the COVID-19 pandemic on older adult mental health, wellbeing, and lifestyle behaviors and explore predictors of better mid-pandemic mental health and wellbeing. Methods Participants in the Adult Changes in Thought study completed measures of lifestyle behaviors (e.g., sleep, physical activity) and mental health and wellbeing both pre-pandemic during regular study visits and mid-pandemic via a one-time survey. We used paired t-tests to compare differences in these measures pre- vs. mid-pandemic. Using multivariate linear regression, we further explored demographic, health, and lifestyle predictors of pandemic depressive symptoms, social support, and fatigue. We additionally qualitatively coded free text data from the mid-pandemic survey for related comments. Results Participants (N = 896) reported significant changes in mental health and lifestyle behaviors at pre-pandemic vs. mid-pandemic measurements (p

Background: Adult Changes in Thought (ACT), a prospective cohort study, enrolls older adult members of Kaiser Permanente Washington. We describe an ambitious project to abstract medical records facilitating epidemiological investigation. Methods: Abstracted data include medications; laboratory results; women’s health; blood pressure; physical injuries; cardiovascular, neurological, psychiatric and other medical conditions. Results: Of 1419 of 5763 participants with completed abstractions, 1387 (97.7%) were deceased; 602 (42.4%) were diagnosed with Alzheimer’s Disease and Related Dementias; 985 (69.4%) had a brain autopsy. Each participant had an average of 34.3 (SD = 13.4) years of data abstracted. Over 64% had pharmacy data preceding 1977; 87.5% had laboratory data preceding 1988. Stroke, anxiety, depression and confusion during hospitalization were common among participants diagnosed with dementia. Conclusions: Medical records are transformed into data for analyses with outcomes derived from other ACT data. We provide detailed, unparalleled longitudinal clinical data to support a variety of epidemiological research on clinical-pathological correlations.

Abstract Clostridioides difficile (C. diff.) infection (CDI) is a leading cause of hospital acquired diarrhea in North America and Europe and a major cause of morbidity and mortality. Known risk factors do not fully explain CDI susceptibility, and genetic susceptibility is suggested by the fact that some patients with colons that are colonized with C. diff. do not develop any infection while others develop severe or recurrent infections. To identify common genetic variants associated with CDI, we performed a genome-wide association analysis in 19,861 participants (1349 cases; 18,512 controls) from the Electronic Medical Records and Genomics (eMERGE) Network. Using logistic regression, we found strong evidence for genetic variation in the DRB locus of the MHC (HLA) II region that predisposes individuals to CDI (P > 1.0 × 10–14; OR 1.56). Altered transcriptional regulation in the HLA region may play a role in conferring susceptibility to this opportunistic enteric pathogen.

Abstract Background More than 75 common variant loci account for only a portion of the heritability for Alzheimer’s disease (AD). A more complete understanding of the genetic basis of AD can be deduced by exploring associations with AD-related endophenotypes. Methods We conducted genome-wide scans for cognitive domain performance using harmonized and co-calibrated scores derived by confirmatory factor analyses for executive function, language, and memory. We analyzed 103,796 longitudinal observations from 23,066 members of community-based (FHS, ACT, and ROSMAP) and clinic-based (ADRCs and ADNI) cohorts using generalized linear mixed models including terms for SNP, age, SNP × age interaction, sex, education, and five ancestry principal components. Significance was determined based on a joint test of the SNP’s main effect and interaction with age. Results across datasets were combined using inverse-variance meta-analysis. Genome-wide tests of pleiotropy for each domain pair as the outcome were performed using PLACO software. Results Individual domain and pleiotropy analyses revealed genome-wide significant (GWS) associations with five established loci for AD and AD-related disorders (BIN1, CR1, GRN, MS4A6A, and APOE) and eight novel loci. ULK2 was associated with executive function in the community-based cohorts (rs157405, P = 2.19 × 10–9). GWS associations for language were identified with CDK14 in the clinic-based cohorts (rs705353, P = 1.73 × 10–8) and LINC02712 in the total sample (rs145012974, P = 3.66 × 10–8). GRN (rs5848, P = 4.21 × 10–8) and PURG (rs117523305, P = 1.73 × 10–8) were associated with memory in the total and community-based cohorts, respectively. GWS pleiotropy was observed for language and memory with LOC107984373 (rs73005629, P = 3.12 × 10–8) in the clinic-based cohorts, and with NCALD (rs56162098, P = 1.23 × 10–9) and PTPRD (rs145989094, P = 8.34 × 10–9) in the community-based cohorts. GWS pleiotropy was also found for executive function and memory with OSGIN1 (rs12447050, P = 4.09 × 10–8) and PTPRD (rs145989094, P = 3.85 × 10–8) in the community-based cohorts. Functional studies have previously linked AD to ULK2, NCALD, and PTPRD. Conclusion Our results provide some insight into biological pathways underlying processes leading to domain-specific cognitive impairment and AD, as well as a conduit toward a syndrome-specific precision medicine approach to AD. Increasing the number of participants with harmonized cognitive domain scores will enhance the discovery of additional genetic factors of cognitive decline leading to AD and related dementias.

Background: While epidemiologic evidence links higher levels of exposure to fine particulate matter (PM2.5) to decreased cognitive function, fewer studies have investigated links with traffic-related air pollution (TRAP), and none have examined ultrafine particles (UFP, ≤100 nm) and late-life dementia incidence. Objective: To evaluate associations between TRAP exposures (UFP, black carbon [BC], and nitrogen dioxide [NO2]) and late-life dementia incidence. Methods: We ascertained dementia incidence in the Seattle-based Adult Changes in Thought (ACT) prospective cohort study (beginning in 1994) and assessed ten-year average TRAP exposures for each participant based on prediction models derived from an extensive mobile monitoring campaign. We applied Cox proportional hazards models to investigate TRAP exposure and dementia incidence using age as the time axis and further adjusting for sex, self-reported race, calendar year, education, socioeconomic status, PM2.5, and APOE genotype. We ran sensitivity analyses where we did not adjust for PM2.5 and other sensitivity and secondary analyses where we adjusted for multiple pollutants, applied alternative exposure models (including total and size-specific UFP), modified the adjustment covariates, used calendar year as the time axis, assessed different exposure periods, dementia subtypes, and others. Results: We identified 1,041 incident all-cause dementia cases in 4,283 participants over 37,102 person-years of follow-up. We did not find evidence of a greater hazard of late-life dementia incidence with elevated levels of long-term TRAP exposures. The estimated hazard ratio of all-cause dementia was 0.98 (95 % CI: 0.92–1.05) for every 2000 pt/cm3 increment in UFP, 0.95 (0.89–1.01) for every 100 ng/m3 increment in BC, and 0.96 (0.91–1.02) for every 2 ppb increment in NO2. These findings were consistent across sensitivity and secondary analyses. Discussion: We did not find evidence of a greater hazard of late-life dementia risk with elevated long-term TRAP exposures in this population-based prospective cohort study.

The 24-h activity cycle (24HAC) is a new paradigm for studying activity behaviors in relation to health outcomes. This approach inherently captures the interrelatedness of the daily time spent in physical activity (PA), sedentary behavior (SB), and sleep. We describe three popular approaches for modeling outcome associations with the 24HAC exposure. We apply these approaches to assess an association with a cognitive outcome in a cohort of older adults, discuss statistical challenges, and provide guidance on interpretation and selecting an appropriate approach. We compare the use of the isotemporal substitution model (ISM), compositional data analysis (CoDA), and latent profile analysis (LPA) to analyze 24HAC. We illustrate each method by exploring cross-sectional associations with cognition in 1,034 older adults (Mean age = 77; Age range = 65–100; 55.8% female; 90% White) who were part of the Adult Changes in Thought (ACT) Activity Monitoring (ACT-AM) sub-study. PA and SB were assessed with thigh-worn activPAL accelerometers for 7-days. For each method, we fit a multivariable regression model to examine the cross-sectional association between the 24HAC and Cognitive Abilities Screening Instrument item response theory (CASI-IRT) score, adjusting for baseline characteristics. We highlight differences in assumptions and the scientific questions addressable by each approach. ISM is easiest to apply and interpret; however, the typical ISM assumes a linear association. CoDA uses an isometric log-ratio transformation to directly model the compositional exposure but can be more challenging to apply and interpret. LPA can serve as an exploratory analysis tool to classify individuals into groups with similar time-use patterns. Inference on associations of latent profiles with health outcomes need to account for the uncertainty of the LPA classifications, which is often ignored. Analyses using the three methods did not suggest that less time spent on SB and more in PA was associated with better cognitive function. The three standard analytical approaches for 24HAC each have advantages and limitations, and selection of the most appropriate method should be guided by the scientific questions of interest and applicability of each model’s assumptions. Further research is needed into the health implications of the distinct 24HAC patterns identified in this cohort.

Abstract Background Research supports that moderate-to-vigorous intensity physical activity (MVPA) is key to prolonged health and function. Among older adults, substantial changes to MVPA may be infeasible, thus a growing literature suggests a shift in focus to whole-day activity patterns. Methods With data from 795 older adults aged 65–100 in the Adult Changes in Thought Activity Monitoring study, we used linear regression to estimate associations between ActiGraph and activPAL measured activity patterns – including light intensity physical activity, steps, standing, and sedentary behaviors – and physical function as measured by a short Performance-based Physical Function (sPPF) score (range 0–12), a composite score based on three standardized physical performance tasks: gait speed, timed chair stands, and grip strength. We examined whether relationships persisted when controlling for MVPA or differed across age, gender, or quartiles of MVPA. Results In models unadjusted for MVPA, a 1-standard deviation (SD) increment of daily sitting (1.9 h more), mean sitting bout duration (8 min longer average), or time spent in sedentary activity (1.6 h more) was associated with ~ 0.3–0.4 points lower mean sPPF score (all p

Abstract Background Advances in antiretroviral therapies have greatly improved the survival of people living with human immunodeficiency virus (HIV) infection (PLWH); yet, PLWH have a higher risk of cardiovascular disease than those without HIV. While numerous genetic loci have been linked to cardiometabolic risk in the general population, genetic predictors of the excessive risk in PLWH are largely unknown. Methods We screened for common and HIV-specific genetic variants associated with variation in lipid levels in 6284 PLWH (3095 European Americans [EA] and 3189 African Americans [AA]), from the Centers for AIDS Research Network of Integrated Clinical Systems cohort. Genetic hits found exclusively in the PLWH cohort were tested for association with other traits. We then assessed the predictive value of a series of polygenic risk scores (PRS) recapitulating the genetic burden for lipid levels, type 2 diabetes (T2D), and myocardial infarction (MI) in EA and AA PLWH. Results We confirmed the impact of previously reported lipid-related susceptibility loci in PLWH. Furthermore, we identified PLWH-specific variants in genes involved in immune cell regulation and previously linked to HIV control, body composition, smoking, and alcohol consumption. Moreover, PLWH at the top of European-based PRS for T2D distribution demonstrated a > 2-fold increased risk of T2D compared to the remaining 95% in EA PLWH but to a much lesser degree in AA. Importantly, while PRS for MI was not predictive of MI risk in AA PLWH, multiethnic PRS significantly improved risk stratification for T2D and MI. Conclusions Our findings suggest that genetic loci involved in the regulation of the immune system and predisposition to risky behaviors contribute to dyslipidemia in the presence of HIV infection. Moreover, we demonstrate the utility of the European-based and multiethnic PRS for stratification of PLWH at a high risk of cardiometabolic diseases who may benefit from preventive therapies.

Abstract Background Few studies characterize older adult physical activity and sitting patterns using accurate accelerometer and concurrent posture measures. In this descriptive paper, we report accelerometer data collection protocols, consent rates, and physical behavior measures from a population-based cohort study (Adult Changes in Thought, ACT). Methods The ACT study holds enrollment steady at approximately 2000 members of Kaiser Permanente Washington aged 65+ without dementia undergoing detailed biennial assessments. In 2016 the ACT-Activity Monitor (ACT-AM) sub-study was initiated to obtain data from wearing activPAL and ActiGraph devices for 7 days following regular biennial visits. We describe the methods protocol of ACT-AM and present characteristics of people who did and did not consent to wear devices. We compute inverse probability of response weights and incorporate these weights in linear regression models to estimate means and 95% confidence intervals (CI) of device-based pattern metrics, adjusted for wear time and demographic factors, and weighted to account for potential selection bias due to device-wear consent. Results Among 1885 eligible ACT participants, 56% agreed to wear both devices (mean age 77 years, 56% female, 89% non-Hispanic white, 91% with post-secondary education). On average, those who agreed to wear devices were younger and healthier. Estimated mean (95% CI) activPAL-derived sitting, standing, and stepping times were 10.2 h/day (603–618 min/day), 3.9 h/day (226–239 min/day), and 1.4 h/day (79–84 min/day), respectively. Estimated mean ActiGraph derived sedentary (Vector Magnitude [VM] 518 counts/15 s) physical activity durations were 9.5 h/day (565–577 min/day), 4.5 h/day (267–276 min/day), and 1.0 h/day (59–64 min/day). Participants who were older, had chronic conditions, and were unable to walk a half-mile had higher sedentary time and less physical activity. Conclusions Our recruitment rate demonstrates the feasibility of cohort participants to wear two devices that measure sedentary time and physical activity. Data indicate high levels of sitting time in older adults but also high levels of physical activity using cut-points developed for older adults. These data will help researchers test hypotheses related to physical behavior and health in older adults in the future.

APOE is the major genetic risk factor for Alzheimer’s disease. In a large number of neuropathologically confirmed cases and controls, the impact of different APOE genotypes on Alzheimer’s dementia risk was greater than previously thought and APOE2 homozygotes had an exceptionally low risk.

Abstract Alzheimer’s disease neuropathologic change (ADNC) is defined by progressive accumulation of β-amyloid plaques and hyperphosphorylated tau (pTau) neurofibrillary tangles across diverse regions of brain. Non-demented individuals who reach advanced age without significant ADNC are considered to be resistant to AD, while those burdened with ADNC are considered to be resilient. Understanding mechanisms underlying ADNC resistance and resilience may provide important clues to treating and/or preventing AD associated dementia. ADNC criteria for resistance and resilience are not well-defined, so we developed stringent pathologic cutoffs for non-demented subjects to eliminate cases of borderline pathology. We identified 14 resistant (85+ years old, non-demented, Braak stage ≤ III, CERAD absent) and 7 resilient (non-demented, Braak stage VI, CERAD frequent) individuals out of 684 autopsies from the Adult Changes in Thought study, a long-standing community-based cohort. We matched each resistant or resilient subject to a subject with dementia and severe ADNC (Braak stage VI, CERAD frequent) by age, sex, year of death, and post-mortem interval. We expanded the neuropathologic evaluation to include quantitative approaches to assess neuropathology and found that resilient participants had lower neocortical pTau burden despite fulfilling criteria for Braak stage VI. Moreover, limbic-predominant age-related TDP-43 encephalopathy neuropathologic change (LATE-NC) was robustly associated with clinical dementia and was more prevalent in cases with high pTau burden, supporting the notion that resilience to ADNC may depend, in part, on resistance to pTDP-43 pathology. To probe for interactions between tau and TDP-43, we developed a C. elegans model of combined human (h) Tau and TDP-43 proteotoxicity, which exhibited a severe degenerative phenotype most compatible with a synergistic, rather than simply additive, interaction between hTau and hTDP-43 neurodegeneration. Pathways that underlie this synergy may present novel therapeutic targets for the prevention and treatment of AD.

Abstract Background Detecting patients with undiagnosed dementia is an important clinical challenge. Changes in medication adherence might represent an early sign of cognitive impairment. We sought to examine antihypertensive and statin adherence trajectories in community-dwelling older adults, comparing people who went on to develop dementia to those who did not. Methods We analyzed data from Adult Changes in Thought (ACT), a population-based cohort study embedded within an integrated healthcare delivery system. Analyses included 4368 participants aged ≥65 years who had at least one follow-up visit. Research-quality dementia diagnoses were used to identify cases. We selected non-dementia control visits matched on age, sex, and study cohort that occurred at similar ACT follow-up time as the case’s dementia onset; we treated this as the index date. Participants were included if they were prevalent users of either a statin or antihypertensive medication on the first day of follow up – 3 years prior to the index date. Using prescription fill dates and days supply, we calculated daily binary medication availability measures for each participant (‘days covered’) over 3 years leading up to the index date. We used group-based trajectory models to identify patterns of antihypertensive and statin adherence, and used conditional logistic regression to examine associations between adherence trajectories and dementia. Results Four trajectories were identified for antihypertensive users (292 cases, 3890 control visits), including near perfect (n = 1877, 36.6% cases, 45.5% controls), high (n = 1840, 43.2% cases, 44.1% controls), moderate (n = 365, 18.5% cases, 8.0% controls) and early poor adherence (n = 100, 1.7% cases, 2.4% controls). Odds of dementia was 3 times greater for those with moderate antihypertensive adherence compared to those with near perfect adherence (adjusted OR 3.0, 95% CI 2.0, 4.3). Four trajectories were identified for statin users (148 cases, 1131 control visits), including high (n = 1004, 75.0% cases, 79.0% controls), moderate (n = 192, 19.6% cases, 14.4% controls), early poor (n = 43, 2.0% cases, 3.5% controls), and delayed poor adherence (n = 40, 3.4% cases, 3.1% controls). No association was detected between statin adherence trajectories and dementia. Conclusions Patterns of medication adherence may be useful to identify a subset of people at higher likelihood of developing dementia.

The late neuropathological effects of traumatic brain injury have yet to be fully elucidated, particularly with respect to community-based cohorts. To contribute to this critical gap in knowledge, we designed a multimodal neuropathological study, integrating traditional and quantitative approaches to detect pathologic changes in 532 consecutive brain autopsies from participants in the Adult Changes in Thought (ACT) study. Diagnostic evaluation including assessment for chronic traumatic encephalopathy (CTE) and quantitative immunoassay-based methods were deployed to examine levels of pathological (hyperphosphorylated) tau (pTau) and amyloid (A) β in brains from ACT participants with (n = 107) and without (n = 425) history of remote TBI with loss of consciousness (w/LOC). Further neuropathological assessments included immunohistochemistry for α-synuclein and phospho-TDP-43 pathology and astro- (GFAP) and micro- (Iba1) gliosis, mass spectrometry analysis of free radical injury, and gene expression evaluation (RNA sequencing) in a smaller sub-cohort of matched samples (49 cases with TBI and 49 non-exposed matched controls). Out of 532 cases, only 3 (0.6%–none with TBI w/LOC history) showed evidence of the neuropathologic signature of chronic traumatic encephalopathy (CTE). Across the entire cohort, the levels of pTau and Aβ showed expected differences for brain region (higher levels in temporal cortex), neuropathological diagnosis (higher in participants with Alzheimer's disease), and APOE genotype (higher in participants with one or more APOE ε4 allele). However, no differences in PHF-tau or Aβ1−42 were identified by Histelide with respect to the history of TBI w/LOC. In a subset of TBI cases with more carefully matched control samples and more extensive analysis, those with TBI w/LOC history had higher levels of hippocampal pTau but no significant differences in Aβ, α-synuclein, pTDP-43, GFAP, Iba1, or free radical injury. RNA-sequencing also did not reveal significant gene expression associated with any measure of TBI exposure. Combined, these findings suggest long term neuropathological changes associated with TBI w/LOC may be subtle, involve non-traditional pathways of neurotoxicity and neurodegeneration, and/or differ from those in autopsy cohorts specifically selected for neurotrauma exposure.

Disentangling biologically distinct subgroups of Alzheimer’s disease (AD) may facilitate a deeper understanding of the neurobiology underlying clinical heterogeneity. We employed longitudinal [18F]FDG-PET standardized uptake value ratios (SUVRs) to map hypometabolism across cognitively-defined AD subgroups. Participants were 384 amyloid-positive individuals with an AD dementia diagnosis from ADNI who had a total of 1028 FDG-scans (mean time between first and last scan: 1.6 ± 1.8 years). These participants were categorized into subgroups on the basis of substantial impairment at time of dementia diagnosis in a specific cognitive domain relative to the average across domains. This approach resulted in groups of AD-Memory (n = 135), AD-Executive (n = 8), AD-Language (n = 22), AD-Visuospatial (n = 44), AD-Multiple Domains (n = 15) and AD-No Domains (for whom no domain showed substantial relative impairment; n = 160). Voxelwise contrasts against controls revealed that all AD-subgroups showed progressive hypometabolism compared to controls across temporoparietal regions at time of AD diagnosis. Voxelwise and regions-of-interest (ROI)-based linear mixed model analyses revealed there were also subgroup-specific hypometabolism patterns and trajectories. The AD-Memory group had more pronounced hypometabolism compared to all other groups in the medial temporal lobe and posterior cingulate, and faster decline in metabolism in the medial temporal lobe compared to AD-Visuospatial. The AD-Language group had pronounced lateral temporal hypometabolism compared to all other groups, and the pattern of metabolism was also more asymmetrical (left

The clinical presentation of Alzheimer’s disease (AD) varies widely across individuals but the neurobiological mechanisms underlying this heterogeneity are largely unknown. Here, we compared regional gray matter (GM) volumes and associated gene expression profiles between cognitively-defined subgroups of amyloid-β positive individuals clinically diagnosed with AD dementia (age: 66 ± 7, 47% male, MMSE: 21 ± 5). All participants underwent neuropsychological assessment with tests covering memory, executive-functioning, language and visuospatial-functioning domains. Subgroup classification was achieved using a psychometric framework that assesses which cognitive domain shows substantial relative impairment compared to the intra-individual average across domains, which yielded the following subgroups in our sample; AD-Memory (n = 41), AD-Executive (n = 117), AD-Language (n = 33), AD-Visuospatial (n = 171). We performed voxel-wise contrasts of GM volumes derived from 3Tesla structural MRI between subgroups and controls (n = 127, age 58 ± 9, 42% male, MMSE 29 ± 1), and observed that differences in regional GM volumes compared to controls closely matched the respective cognitive profiles. Specifically, we detected lower medial temporal lobe GM volumes in AD-Memory, lower fronto-parietal GM volumes in AD-Executive, asymmetric GM volumes in the temporal lobe (left

Abstract Introduction Alzheimer's disease (AD) neuropathological subtypes (limbic predominant [lpAD], hippocampal sparing [HpSpAD], and typical [tAD]), defined by relative neurofibrillary tangle (NFT) burden in limbic and cortical regions, have not been studied in prospectively characterized epidemiological cohorts with robust cognitive assessments. Methods Two hundred ninety‐two participants with neuropathologically confirmed AD from the Religious Orders Study and Memory and Aging Project were categorized by neuropathological subtype based on previously specified diagnostic criteria using quantitative regional NFT counts. Rates of cognitive decline were compared across subtypes using linear mixed‐effects models that included subtype, time, and a subtype–time interaction as predictors and four cognitive domain factor scores (memory, executive function, language, visuospatial) and a global score as outcomes. To assess if memory was relatively preserved in HpSpAD, non‐memory factor scores were included as covariates in the mixed‐effects model with memory as the outcome. Results There were 57 (20%) with lpAD, 22 (8%) with HpSpAD and 213 (73%) with tAD. LpAD died significantly later than the participants with tAD (2.4 years, P = .01) and with HpSpAD (3.8 years, P = .03). Compared to tAD, HpSpAD, but not lpAD, performed significantly worse in all cognitive domains at the time of initial impairment and declined significantly faster in memory, language, and globally. HpSpAD did not have relatively preserved memory performance at any time point. Conclusion The relative frequencies of AD neuropathological subtypes in an epidemiological sample were consistent with a previous report in a convenience sample. People with HpSpAD decline rapidly, but may not have a memory‐sparing clinical syndrome. Cohort‐specific differences in regional tau burden and comorbid neuropathology may explain the lack of clinicopathological correlation.

Objectives: Sociodemographic trends in the United States may influence future dementia-associated mortality, yet there is little evidence about their potential impact. Our study objective was to estimate the effect of dementia on survival in adults stratified by sex, education, and marital status. Methods: Using survey data from the Health and Retirement Study (HRS) linked to Medicare claims from 1991 to 2012, we identified a retrospective cohort of adults with at least one International Classification of Diseases—ninth revision—Clinical Modification (ICD-9-CM) dementia diagnosis code ( n = 3,714). For each case, we randomly selected up to five comparators, matching on sex, birth year, education, and HRS entry year ( n = 9,531), and assigned comparators the diagnosis date of their matched case. Participants were followed for up to 60 months following diagnosis. We estimated a survival function for the entire study population and then within successive strata defined by sex, education, and marital status. Results: On average, dementia cases were 80.5 years old at diagnosis. Most were female, had less than college-level education, and approximately 40% were married at diagnosis. In multivariate analyses, dementia diagnosis was associated with earlier mortality for women (predicted median survival of 54.5 months vs. 62.5 months; dementia coefficient = −0.13; 95% confidence interval [CI] = [−0.22, −0.04]; p = .003), but even more so among men (predicted median survival of 35.5 months vs. 54.5 months; dementia coefficient = −0.42; 95% CI = [−0.52, −0.31]; p < .001). We found substantial heterogeneity in the relationship between dementia and survival, associated with both education and marital status. Conclusion: Both sex and level of education moderate the relationship between dementia diagnosis and length of survival.

Abstract Background Mechanisms linking cognitive and physical functioning in older adults are unclear. We sought to determine whether brain pathological changes relate to the level or rate of physical performance decline. Methods This study analyzed data from 305 participants in the autopsy subcohort of the prospective Adult Changes in Thought (ACT) study. Participants were aged 65+ and free of dementia at enrollment. Physical performance was measured at baseline and every two years using the Short Physical Performance Battery (SPPB). Data from 3174 ACT participants with ≥2 SPPB measurements were used to estimate two physical function measures: 1) rate of SPPB decline defined by intercept and slope; and 2) estimated SPPB 5 years prior to death. Neuropathology findings at autopsy included neurofibrillary tangles (Braak stage), neuritic plaques (CERAD level), presence of amyloid angiopathy, microinfarcts, cystic infarcts, and Lewy bodies. Associations (adjusted for sex, age, body mass index and education) between dichotomized neuropathologic outcomes and SPPB measures were estimated using modified Poisson regression with inverse probability weights (IPW) estimated via Generalized Estimating Equations (GEE). Relative risks for the 20th, 40th, and 60th percentiles (lowest levels and highest rates of decline) relative to the 80th percentile (highest level and lowest rate of decline) were calculated. Results Decedents with the least vs. most SPPB decline (slope > 75th vs.

Abstract Introduction Composite scores may be useful to summarize overall language or visuospatial functioning in studies of older adults. Methods We used item response theory to derive composite measures for language (ADNI‐Lan) and visuospatial functioning (ADNI‐VS) from the cognitive battery administered in the Alzheimer's Disease Neuroimaging Initiative (ADNI). We evaluated the scores among groups of people with normal cognition, mild cognitive impairment (MCI), and Alzheimer's disease (AD) in terms of responsiveness to change, association with imaging findings, and ability to differentiate between MCI participants who progressed to AD dementia and those who did not progress. Results ADNI‐Lan and ADNI‐VS were able to detect change over time and predict conversion from MCI to AD. They were associated with most of the pre‐specified magnetic resonance imaging measures. ADNI‐Lan had strong associations with a cerebrospinal fluid biomarker pattern. Discussion ADNI‐Lan and ADNI‐VS may be useful composites for language and visuospatial functioning in ADNI.

Abstract Introduction We modeled associations between glycated hemoglobin (HbA1c) levels (8%) and cognitive and physical function among adults 80+ years of age with diabetes and determined whether associations differ by frailty, multimorbidity, and disability. Methods A total of 316, adults with diabetes, 80+ years of age, were from the Adult Changes in Thought Study. The Cognitive Abilities Screening Instrument Item Response Theory (CASI‐IRT) measured cognition. Short performance‐based physical function (sPPF) and gait speed measured physical function. Glycosylated hemoglobin (HbA1c) levels were from clinical measurements. Analyses estimated associations between average HbA1c levels (8%) and functional outcomes using linear regressions estimated with generalized estimating equations. Results sPPF scores did not differ significantly by HbA1c levels. Gait speed did, but only for non‐frail individuals; those with HbA1c >8% were slower (‐0.10 m/s [95% CI, −0.16 to −0.04]) compared to those with HbA1c 7% to 8%. The association between HbA1c and CASI‐IRT varied with age (interaction P = 0.04). At age 80, for example, relative to people with HbA1c levels of 7% to 8%, CASI‐IRT scores were, on average, 0.18 points lower (95% CI, −0.35 to −0.02) for people with HbA1c 8%. At older ages, these estimated differences were attenuated. Estimated associations were not modified by multimorbidity or disability. Discussion Moderate HbA1c levels of 7% to 8% were associated with better cognition in early but not late octogenarians with diabetes. Furthermore, HbA1c >8% was associated with slower gait speed among those without frailty. These results add to an evidence base for determining glucose targets for very old adults with diabetes.

Abstract Background Practice effects (PEs) are improvements in performance after repeated exposure to test materials, and typically viewed as a source of bias in repeated cognitive assessments. We aimed to determine whether characterizing PEs could also provide a useful marker of early cognitive decline. Methods We conducted a systematic review of the literature, searching PsycInfo (Ebsco) and PubMed databases for articles studying PEs in aging and dementia populations. Articles published between 1920 and 2019 were included. Result We identified 259 articles, of which 27 studied PEs as markers of cognitive performance. These studies consistently showed that smaller, less‐robust PEs were associated with current diagnostic status and/or future cognitive decline. In addition, lower PEs were associated with Alzheimer's disease risk factors and neurodegeneration biomarkers. Conclusion PEs provide a potentially useful marker of cognitive decline, and could prove valuable as part of a cost‐effective strategy to select individuals who are at‐risk for dementia for future interventions.

An amendment to this paper has been published and can be accessed via the original article.

Abstract Introduction We hypothesized that, like apolipoprotein E (APOE), other late‐onset Alzheimer's disease (LOAD) genetic susceptibility loci predict mortality. Methods We used a weighted genetic risk score (GRS) from 21 non‐APOE LOAD risk variants to predict survival in the Adult Changes in Thought and the Health and Retirement Studies. We meta‐analyzed hazard ratios and examined models adjusted for cognitive performance or limited to participants with dementia. For replication, we assessed the GRS‐longevity association in the Cohorts for Heart and Aging Research in Genomic Epidemiology, comparing cases surviving to age ≥90 years with controls who died between ages 55 and 80 years. Results Higher GRS predicted mortality (hazard ratio = 1.05; 95% confidence interval: 1.00–1.10, P = .04). After adjusting for cognitive performance or restricting to participants with dementia, the relationship was attenuated and no longer significant. In case‐control analysis, the GRS was associated with reduced longevity (odds ratio = 0.64; 95% confidence interval: 0.41–1.00, P = .05). Discussion Non‐APOE LOAD susceptibility loci confer risk for mortality, likely through effects on dementia incidence.

Fructosamine is an alternative method to hemoglobin A1c (HbA1c) for determining average glycemia. However, its use has not been extensively evaluated in persons living with HIV (PLWH). We examined the relationship between HbA1c and fructosamine values, specifically focusing on anemia (which can affect HbA1c) and albumin as a marker of liver disease. We included 345 PLWH from two sites. We examined Spearman rank correlations between fructosamine and HbA1c and performed linear test for trends to compare fructosamine and HbA1c correlations by hemoglobin and albumin quartiles. We examined discrepant individuals with values elevated only on one test. We found a correlation of 0.70 between fructosamine and HbA1c levels. Trend tests for correlations between fructosamine and HbA1c were significant for both albumin (p=0.05) and hemoglobin (p=0.01) with the lowest correlations in the lowest hemoglobin quartile. We identified participants with unremarkable HbA1c values but elevated fructosamine values. These discrepant individuals had lower mean hemoglobin levels than those elevated by both tests. We demonstrated a large correlation between HbA1c and fructosamine across a range of hemoglobin and albumin levels. There were discrepant cases particularly among those with lower hemoglobin levels. Future studies are needed to clarify the use of fructosamine for diabetes management in PWLH.

Logistic regression provides a flexible framework for detecting various types of differential item functioning (DIF). Previous efforts extended the framework by using item response theory (IRT) based trait scores, and by employing an iterative process using group--specific item parameters to account for DIF in the trait scores, analogous to purification approaches used in other DIF detection frameworks. The current investigation advances the technique by developing a computational platform integrating both statistical and IRT procedures into a single program. Furthermore, a Monte Carlo simulation approach was incorporated to derive empirical criteria for various DIF statistics and effect size measures. For purposes of illustration, the procedure was applied to data from a questionnaire of anxiety symptoms for detecting DIF associated with age from the Patient--Reported Outcomes Measurement Information System.

Rich data from large biobanks, coupled with increasingly accessible association statistics from genome-wide association studies (GWAS), provide great opportunities to dissect the complex relationships among human traits and diseases. We introduce BADGERS, a powerful method to perform polygenic score-based biobank-wide association scans. Compared to traditional approaches, BADGERS uses GWAS summary statistics as input and does not require multiple traits to be measured in the same cohort. We applied BADGERS to two independent datasets for late-onset Alzheimer’s disease (AD; n=61,212). Among 1738 traits in the UK biobank, we identified 48 significant associations for AD. Family history, high cholesterol, and numerous traits related to intelligence and education showed strong and independent associations with AD. Furthermore, we identified 41 significant associations for a variety of AD endophenotypes. While family history and high cholesterol were strongly associated with AD subgroups and pathologies, only intelligence and education-related traits predicted pre-clinical cognitive phenotypes. These results provide novel insights into the distinct biological processes underlying various risk factors for AD.

BackgroundThe prevalence of substance use in people with HIV (PWH) in the United States is higher than in the general population and is an important driver of HIV-related outcomes. We sought to assess if previously identified genetic associations that contribute to substance use are also observed in a population of PWH.MethodsWe performed genome-wide association studies (GWAS) of alcohol, smoking, and cannabis use phenotypes in a multi-ancestry population of 7,542 PWH from the Center for AIDS Research Network of Integrated Clinical Systems (CNICS). We conducted multi-ancestry GWAS for individuals of African (n = 3,748), Admixed American (n = 1,334), and European (n = 2,460) ancestry. Phenotype data were self-reported and collected using patient reported outcomes (PROs) and three questions from AUDIT-C, an alcohol screening tool. We analyzed nine phenotypes: 1) frequency of alcohol consumption, 2) typical number of drinks on a day when drinking alcohol, 3) frequency of five or more alcoholic drinks in a 30-day period, 4) smoking initiation, 5) smoking cessation, 6) cigarettes per day, 7) cannabis use initiation, 8) cannabis use cessation, 9) frequency of cannabis use during the previous 30 days. For each phenotype we considered a) variants previously identified as associated with a substance use trait and b) novel associations.ResultsWe observed evidence for effects of previously reported single nucleotide polymorphisms (SNPs) related to alcohol (rs1229984, p = 0.001), tobacco (rs11783093, p = 2.22E-4), and cannabis use (rs2875907, p = 0.005). We also report two novel loci (19p13.2, p = 1.3E-8; and 20p11.21, p = 2.1E-8) associated with cannabis use cessation.ConclusionsOur analyses contribute to understanding the genetic bases of substance use in a population with relatively higher rates of use compared to the general population.

Late-Onset Alzheimer's disease (LOAD) is a common, complex genetic disorder well-known for its heterogeneous pathology. The genetic heterogeneity underlying common, complex diseases poses a major challenge for targeted therapies and the identification of novel disease-associated variants. Case-control approaches are often limited to examining a specific outcome in a group of heterogenous patients with different clinical characteristics. Here, we developed a novel approach to define relevant transcriptomic endophenotypes and stratify decedents based on molecular profiles in three independent human LOAD cohorts. By integrating post-mortem brain gene co-expression data from 2114 human samples with LOAD, we developed a novel quantitative, composite phenotype that can better account for the heterogeneity in genetic architecture underlying the disease. We used iterative weighted gene co-expression network analysis (WGCNA) to reduce data dimensionality and to isolate gene sets that are highly co-expressed within disease subtypes and represent specific molecular pathways. We then performed single variant association testing using whole genome-sequencing data for the novel composite phenotype in order to identify genetic loci that contribute to disease heterogeneity. Distinct LOAD subtypes were identified for all three study cohorts (two in ROSMAP, three in Mayo Clinic, and two in Mount Sinai Brain Bank). Single variant association analysis identified a genome-wide significant variant in TMEM106B (p-value < 5×10-8, rs1990620G) in the ROSMAP cohort that confers protection from the inflammatory LOAD subtype. Taken together, our novel approach can be used to stratify LOAD into distinct molecular subtypes based on affected disease pathways.

As more people live longer, age-related neurodegenerative diseases are an increasingly important societal health issue. Treatments targeting specific pathologies such as amyloid beta in Alzheimer’s disease (AD) have not led to effective treatments, and there is increasing evidence of a disconnect between traditional pathology and cognitive abilities with advancing age, indicative of individual variation in resilience to pathology. Here, we generated a comprehensive neuropathological, molecular, and transcriptomic characterization of hippocampus and two regions cortex in 107 aged donors (median = 90) from the Adult Changes in Thought (ACT) study as a freely-available resource (http://aging.brain-map.org/). We confirm established associations between AD pathology and dementia, albeit with increased, presumably aging-related variability, and identify sets of co-expressed genes correlated with pathological tau and inflammation markers. Finally, we demonstrate a relationship between dementia and RNA quality, and find common gene signatures, highlighting the importance of properly controlling for RNA quality when studying dementia.

Continuing efforts from large international consortia have made genome-wide epigenomic and transcriptomic annotation data publicly available for a variety of cell and tissue types. However, synthesis of these datasets into effective summary metrics to characterize the functional non-coding genome remains a challenge. Here, we present GenoSkyline-Plus, an extension of our previous work through integration of an expanded set of epigenomic and transcriptomic annotations to produce high-resolution, single tissue annotations. After validating our annotations with a catalog of tissue-specific non-coding elements previously identified in the literature, we apply our method using data from 127 different cell and tissue types to present an atlas of heritability enrichment across 45 different GWAS traits. We show that broader organ system categories (e.g. immune system) increase statistical power in identifying biologically relevant tissue types for complex diseases while annotations of individual cell types (e.g. monocytes or B-cells) provide deeper insights into disease etiology. Additionally, we use our GenoSkyline-Plus annotations in an in-depth case study of late-onset Alzheimer's disease (LOAD). Our analyses suggest a strong connection between LOAD heritability and genetic variants contained in regions of the genome functional in monocytes. Furthermore, we show that LOAD shares a similar localization of SNPs to monocyte-functional regions with Parkinson's disease. Overall, we demonstrate that integrated genome annotations at the single tissue level provide a valuable tool for understanding the etiology of complex human diseases. Our GenoSkyline-Plus annotations are freely available at http://genocanyon.med.yale.edu/GenoSkyline.

BackgroundAlzheimer disease (AD) is a progressive disorder that affects cognitive function. There is increasing support for the role of neuroinflammation and aberrant immune regulation in the pathophysiology of AD. The immunoregulatory human leukocyte antigen (HLA) complex has been linked to susceptibility for a number of neurodegenerative diseases, including AD; however, studies to date have failed to consistently identify a risk HLA haplotype for AD. Contributing to this difficulty are the complex genetic organization of the HLA region, differences in sequencing and allelic imputation methods, and diversity across ethnic populations.Methods and findingsBuilding on prior work linking the HLA to AD, we used a robust imputation method on two separate case-control cohorts to examine the relationship between HLA haplotypes and AD risk in 309 individuals (191 AD, 118 cognitively normal [CN] controls) from the San Francisco-based University of California, San Francisco (UCSF) Memory and Aging Center (collected between 1999-2015) and 11,381 individuals (5,728 AD, 5,653 CN controls) from the Alzheimer's Disease Genetics Consortium (ADGC), a National Institute on Aging (NIA)-funded national data repository (reflecting samples collected between 1984-2012). We also examined cerebrospinal fluid (CSF) biomarker measures for patients seen between 2005-2007 and longitudinal cognitive data from the Alzheimer's Disease Neuroimaging Initiative (n = 346, mean follow-up 3.15 ± 2.04 y in AD individuals) to assess the clinical relevance of identified risk haplotypes. The strongest association with AD risk occurred with major histocompatibility complex (MHC) haplotype A*03:01~B*07:02~DRB1*15:01~DQA1*01:02~DQB1*06:02 (p = 9.6 x 10-4, odds ratio [OR] [95% confidence interval] = 1.21 [1.08-1.37]) in the combined UCSF + ADGC cohort. Secondary analysis suggested that this effect may be driven primarily by individuals who are negative for the established AD genetic risk factor, apolipoprotein E (APOE) ɛ4. Separate analyses of class I and II haplotypes further supported the role of class I haplotype A*03:01~B*07:02 (p = 0.03, OR = 1.11 [1.01-1.23]) and class II haplotype DRB1*15:01- DQA1*01:02- DQB1*06:02 (DR15) (p = 0.03, OR = 1.08 [1.01-1.15]) as risk factors for AD. We followed up these findings in the clinical dataset representing the spectrum of cognitively normal controls, individuals with mild cognitive impairment, and individuals with AD to assess their relevance to disease. Carrying A*03:01~B*07:02 was associated with higher CSF amyloid levels (p = 0.03, β ± standard error = 47.19 ± 21.78). We also found a dose-dependent association between the DR15 haplotype and greater rates of cognitive decline (greater impairment on the 11-item Alzheimer's Disease Assessment Scale cognitive subscale [ADAS11] over time [p = 0.03, β ± standard error = 0.7 ± 0.3]; worse forgetting score on the Rey Auditory Verbal Learning Test (RAVLT) over time [p = 0.02, β ± standard error = -0.2 ± 0.06]). In a subset of the same cohort, dose of DR15 was also associated with higher baseline levels of chemokine CC-4, a biomarker of inflammation (p = 0.005, β ± standard error = 0.08 ± 0.03). The main study limitations are that the results represent only individuals of European-ancestry and clinically diagnosed individuals, and that our study used imputed genotypes for a subset of HLA genes.ConclusionsWe provide evidence that variation in the HLA locus-including risk haplotype DR15-contributes to AD risk. DR15 has also been associated with multiple sclerosis, and its component alleles have been implicated in Parkinson disease and narcolepsy. Our findings thus raise the possibility that DR15-associated mechanisms may contribute to pan-neuronal disease vulnerability.

Analyses of imperfectly assessed time to event outcomes give rise to biased hazard ratio estimates. This bias is a common challenge for studies of Alzheimer's Disease (AD) because AD neuropathology can only be identified through brain autopsy and is therefore not available for most study participants. Clinical AD diagnosis, although more widely available, has imperfect sensitivity and specificity relative to AD neuropathology. In this study we present a sensitivity analysis approach using a bias-adjusted discrete proportional hazards model to quantify robustness of results to misclassification of a time to event outcome and apply this method to data from a longitudinal panel study of AD. Using data on 1,955 participants from the Adult Changes in Thought study we analyzed the association between average glucose level and AD neuropathology and conducted sensitivity analyses to explore how estimated hazard ratios varied according to AD classification accuracy. Unadjusted hazard ratios were closer to the null than estimates obtained under most scenarios for misclassification investigated. Confidence interval estimates from the unadjusted model were substantially underestimated compared to adjusted estimates. This study demonstrates the importance of exploring outcome misclassification in time to event analyses and provides an approach that can be undertaken without requiring validation data.

We evaluated dementia and Alzheimer's disease (AD) risks after a cancer diagnosis in a population-based prospective cohort, the Adult Changes in Thought (ACT) study.We followed community-dwelling people aged ≥65 years without dementia at study entry for incident dementia and AD from 1994-2015. We linked study data with cancer registry data and categorized cancer diagnoses as prevalent (diagnosed before ACT study enrollment) or incident (diagnosed during follow-up). We used Cox regression to estimate cause-specific hazard ratios (HRs) with 95% confidence intervals (CIs) for dementia or AD risk comparing people with a cancer diagnosis to people without cancer. We conducted sensitivity analyses restricted to people surviving beyond age 80, and stratified by cancer stage, type, and whether the cancer was smoking-related.Among 4,357 people, 756 (17.4%) had prevalent cancer; 583 (13.4%) developed incident cancer, 1,091 (25.0%) developed dementia, and 877 (20.1%) developed AD over a median 6.4 years (34,482 total person-years) of follow-up. Among complete cases (no missing covariates) with at least one follow-up assessment, adjusted HRs for dementia following prevalent and incident cancer diagnoses were 0.92 (95%CI: 0.76, 1.11) and 0.87 (95%CI: 0.64, 1.04), compared to no cancer history. HRs for AD were 0.95 (95%CI: 0.77, 1.17) for prevalent cancer and 0.73 (95%CI: 0.55, 0.96) for incident cancer. In sensitivity analyses, prevalent late-stage cancers were associated with reduced risks of dementia (HR = 0.51, 95%CI: 0.30, 0.89) and AD (HR = 0.50, 95%CI: 0.27, 0.94). When limited to people who survived beyond age 80, incident cancers were still associated with reduced AD risk (HR = 0.69, 95%CI: 0.51, 0.92).Our results do not support an inverse association between prevalent cancer diagnoses, which were primarily early-stage, less aggressive cancers, and risk of dementia or AD. A reduced risk of AD following an incident cancer diagnosis is biologically plausible but may reflect selective mortality.

BackgroundPotentially modifiable risk factors including obesity, diabetes, hypertension, and smoking are associated with Alzheimer disease (AD) and represent promising targets for intervention. However, the causality of these associations is unclear. We sought to assess the causal nature of these associations using Mendelian randomization (MR).Methods and findingsWe used SNPs associated with each risk factor as instrumental variables in MR analyses. We considered type 2 diabetes (T2D, NSNPs = 49), fasting glucose (NSNPs = 36), insulin resistance (NSNPs = 10), body mass index (BMI, NSNPs = 32), total cholesterol (NSNPs = 73), HDL-cholesterol (NSNPs = 71), LDL-cholesterol (NSNPs = 57), triglycerides (NSNPs = 39), systolic blood pressure (SBP, NSNPs = 24), smoking initiation (NSNPs = 1), smoking quantity (NSNPs = 3), university completion (NSNPs = 2), and years of education (NSNPs = 1). We calculated MR estimates of associations between each exposure and AD risk using an inverse-variance weighted approach, with summary statistics of SNP-AD associations from the International Genomics of Alzheimer's Project, comprising a total of 17,008 individuals with AD and 37,154 cognitively normal elderly controls. We found that genetically predicted higher SBP was associated with lower AD risk (odds ratio [OR] per standard deviation [15.4 mm Hg] of SBP [95% CI]: 0.75 [0.62-0.91]; p = 3.4 × 10(-3)). Genetically predicted higher SBP was also associated with a higher probability of taking antihypertensive medication (p = 6.7 × 10(-8)). Genetically predicted smoking quantity was associated with lower AD risk (OR per ten cigarettes per day [95% CI]: 0.67 [0.51-0.89]; p = 6.5 × 10(-3)), although we were unable to stratify by smoking history; genetically predicted smoking initiation was not associated with AD risk (OR = 0.70 [0.37, 1.33]; p = 0.28). We saw no evidence of causal associations between glycemic traits, T2D, BMI, or educational attainment and risk of AD (all p > 0.1). Potential limitations of this study include the small proportion of intermediate trait variance explained by genetic variants and other implicit limitations of MR analyses.ConclusionsInherited lifetime exposure to higher SBP is associated with lower AD risk. These findings suggest that higher blood pressure--or some environmental exposure associated with higher blood pressure, such as use of antihypertensive medications--may reduce AD risk.

Alzheimer's disease (AD) and related dementias are a major public health challenge and present a therapeutic imperative for which we need additional insight into molecular pathogenesis. We performed a genome-wide association study and analysis of known genetic risk loci for AD dementia using neuropathologic data from 4,914 brain autopsies. Neuropathologic data were used to define clinico-pathologic AD dementia or controls, assess core neuropathologic features of AD (neuritic plaques, NPs; neurofibrillary tangles, NFTs), and evaluate commonly co-morbid neuropathologic changes: cerebral amyloid angiopathy (CAA), Lewy body disease (LBD), hippocampal sclerosis of the elderly (HS), and vascular brain injury (VBI). Genome-wide significance was observed for clinico-pathologic AD dementia, NPs, NFTs, CAA, and LBD with a number of variants in and around the apolipoprotein E gene (APOE). GalNAc transferase 7 (GALNT7), ATP-Binding Cassette, Sub-Family G (WHITE), Member 1 (ABCG1), and an intergenic region on chromosome 9 were associated with NP score; and Potassium Large Conductance Calcium-Activated Channel, Subfamily M, Beta Member 2 (KCNMB2) was strongly associated with HS. Twelve of the 21 non-APOE genetic risk loci for clinically-defined AD dementia were confirmed in our clinico-pathologic sample: CR1, BIN1, CLU, MS4A6A, PICALM, ABCA7, CD33, PTK2B, SORL1, MEF2C, ZCWPW1, and CASS4 with 9 of these 12 loci showing larger odds ratio in the clinico-pathologic sample. Correlation of effect sizes for risk of AD dementia with effect size for NFTs or NPs showed positive correlation, while those for risk of VBI showed a moderate negative correlation. The other co-morbid neuropathologic features showed only nominal association with the known AD loci. Our results discovered new genetic associations with specific neuropathologic features and aligned known genetic risk for AD dementia with specific neuropathologic changes in the largest brain autopsy study of AD and related dementias.

Phenome-wide association studies (PheWAS) have demonstrated utility in validating genetic associations derived from traditional genetic studies as well as identifying novel genetic associations. Here we used an electronic health record (EHR)-based PheWAS to explore pleiotropy of genetic variants in the fat mass and obesity associated gene (FTO), some of which have been previously associated with obesity and type 2 diabetes (T2D). We used a population of 10,487 individuals of European ancestry with genome-wide genotyping from the Electronic Medical Records and Genomics (eMERGE) Network and another population of 13,711 individuals of European ancestry from the BioVU DNA biobank at Vanderbilt genotyped using Illumina HumanExome BeadChip. A meta-analysis of the two study populations replicated the well-described associations between FTO variants and obesity (odds ratio [OR]=1.25, 95% Confidence Interval=1.11-1.24, p=2.10 x 10 9) and FTO variants and T2D (OR=1.14, 95% CI=1.08-1.21, p=2.34 x 10 6). The meta-analysis also demonstrated that FTO variant rs8050136 was significantly associated with sleep apnea (OR=1.14, 95% CI=1.07-1.22, p=3.33 x 10 5); however, the association was attenuated after adjustment for body mass index (BMI). Novel phenotype associations with obesity-associated FTO variants included fibrocystic breast disease (rs9941349, OR=0.81, 95% CI=0.74-0.91, p=5.41x10 5) and trends toward associations with nonalcoholic liver disease and gram-positive bacterial infections. FTO variants not associated with obesity demonstrated other potential disease associations including noninflammatory disorders of the cervix and chronic periodontitis. These results suggest that genetic variants in FTO may have pleiotropic associations, some of which are not mediated by obesity.

Translation of results from genetic findings to inform medical practice is a highly anticipated goal of human genetics. The aim of this paper is to review and discuss the role of genetics in medically-relevant prediction. Germline genetics presages disease onset and therefore can contribute prognostic signals that augment laboratory tests and clinical features. As such, the impact of genetic-based predictive models on clinical decisions and therapy choice could be profound. However, given that (i) medical traits result from a complex interplay between genetic and environmental factors, (ii) the underlying genetic architectures for susceptibility to common diseases are not well-understood, and (iii) replicable susceptibility alleles, in combination, account for only a moderate amount of disease heritability, there are substantial challenges to constructing and implementing genetic risk prediction models with high utility. In spite of these challenges, concerted progress has continued in this area with an ongoing accumulation of studies that identify disease predisposing genotypes. Several statistical approaches with the aim of predicting disease have been published. Here we summarize the current state of disease susceptibility mapping and pharmacogenetics efforts for risk prediction, describe methods used to construct and evaluate genetic-based predictive models, and discuss applications.

BACKGROUND:Alzheimer's disease is a common debilitating dementia with known heritability, for which 20 late onset susceptibility loci have been identified, but more remain to be discovered. This study sought to identify new susceptibility genes, using an alternative gene-wide analytical approach which tests for patterns of association within genes, in the powerful genome-wide association dataset of the International Genomics of Alzheimer's Project Consortium, comprising over 7 m genotypes from 25,580 Alzheimer's cases and 48,466 controls. PRINCIPAL FINDINGS:In addition to earlier reported genes, we detected genome-wide significant loci on chromosomes 8 (TP53INP1, p = 1.4×10-6) and 14 (IGHV1-67 p = 7.9×10-8) which indexed novel susceptibility loci. SIGNIFICANCE:The additional genes identified in this study, have an array of functions previously implicated in Alzheimer's disease, including aspects of energy metabolism, protein degradation and the immune system and add further weight to these pathways as potential therapeutic targets in Alzheimer's disease.

BACKGROUND:Although self-rated health (SRH) and performance-based physical function (PPF) are both strong predictors of mortality, little research has investigated the relationships between them. The objective of this study was to evaluate longitudinal, bi-directional associations between SRH and PPF. METHODS:We evaluated longitudinal associations between SRH and PPF in 3,610 adults aged 65-89 followed for an average of 4.8 (standard deviation [SD]: 4.4) years between 1994 and July 2011 in the Adult Changes in Thought study, a population-based cohort in the Seattle area. SRH was assessed with a single-item question in the ACT study. Participants were asked at each evaluation to rate their health as "excellent", "very good", "good", "fair", or "poor" in response to the question "In general, how would you rate your health at this time". PPF scores (ranging from 0-16, with higher indicating better performance) included walking speed, chair rises, grip strength, and balance. RESULTS:At the baseline visit, participants averaged 74.5 (SD: 5.8) years of age and 2,115 (58.6%) were female. In multivariable linear mixed models, PPF declined with age, with more rapid decreases associated with very good, good, and fair (vs. excellent) baseline SRH. Adjusted annual change in PPF was -0.17 points (95% confidence interval [CI]: -0.19, -0.15) for individuals with excellent baseline SRH and -0.21 points (95% CI: -0.22, -0.19) for participants with fair SRH. In multivariable generalized linear mixed models, lower baseline PPF quartiles were associated with lower odds of excellent/very good/good SRH at age 75, however, differences between baseline PPF quartiles diminished with age. CONCLUSIONS:These results suggest that less than excellent SRH predicts decline in physical functioning, however, poor physical functioning may not predict change in SRH in a reciprocal fashion. SRH provides a simple assessment tool for identifying individuals at increased risk for decline in physical function.

The feasibility of using imperfectly phenotyped "silver standard" samples identified from electronic medical record diagnoses is considered in genetic association studies when these samples might be combined with an existing set of samples phenotyped with a gold standard technique. An analytic expression is derived for the power of a chi-square test of independence using either research-quality case/control samples alone, or augmented with silver standard data. The subset of the parameter space where inclusion of silver standard samples increases statistical power is identified. A case study of dementia subjects identified from electronic medical records from the Electronic Medical Records and Genomics (eMERGE) network, combined with subjects from two studies specifically targeting dementia, verifies these results.

Chromosomal abnormalities provide clinical utility in the diagnosis and treatment of hematologic malignancies, and may be predictive of malignant transformation in individuals without apparent clinical presentation of a hematologic cancer. In an effort to confirm previous reports of an association between clonal mosaicism and incident hematologic cancer, we applied the anomDetectBAF algorithm to call chromosomal anomalies in genotype data from previously conducted Genome Wide Association Studies (GWAS). The genotypes were initially collected from DNA derived from peripheral blood of 12,176 participants in the Group Health electronic Medical Records and Genomics study (eMERGE) and the Women's Health Initiative (WHI). We detected clonal mosaicism in 169 individuals (1.4%) and large clonal mosaic events (>2 mb) in 117 (1.0%) individuals. Though only 9.5% of clonal mosaic carriers had an incident diagnosis of hematologic cancer (multiple myeloma, myelodysplastic syndrome, lymphoma, or leukemia), the carriers had a 5.5-fold increased risk (95% CI: 3.3-9.3; p-value = 7.5×10(-11)) of developing these cancers subsequently. Carriers of large mosaic anomalies showed particularly pronounced risk of subsequent leukemia (HR = 19.2, 95% CI: 8.9-41.6; p-value = 7.3×10(-14)). Thus we independently confirm the association between detectable clonal mosaicism and hematologic cancer found previously in two recent publications.

Alzheimer's disease (AD) is a complex disorder influenced by environmental and genetic factors. Recent work has identified 11 AD markers in 10 loci. We used Genome-wide Complex Trait Analysis to analyze >2 million SNPs for 10,922 individuals from the Alzheimer's Disease Genetics Consortium to assess the phenotypic variance explained first by known late-onset AD loci, and then by all SNPs in the Alzheimer's Disease Genetics Consortium dataset. In all, 33% of total phenotypic variance is explained by all common SNPs. APOE alone explained 6% and other known markers 2%, meaning more than 25% of phenotypic variance remains unexplained by known markers, but is tagged by common SNPs included on genotyping arrays or imputed with HapMap genotypes. Novel AD markers that explain large amounts of phenotypic variance are likely to be rare and unidentifiable using genome-wide association studies. Based on our findings and the current direction of human genetics research, we suggest specific study designs for future studies to identify the remaining heritability of Alzheimer's disease.