The objective of the proposed research is to provide a series of gender-specific forecasts of the future burden of Alzheimer’s disease and related dementia (AD/ADRD) in connection with the changing trends in other major diseases common in U.S. older adults. This objective will be reached by incorporating relevant information on the demographic, social, economic, health, and genetic structure of the U.S. population into the forecasting models. This information will be obtained from four diverse sources of Medicare data: The Surveillance Epidemiology and End Results (SEER-M), The Medicare 5% Research Identifiable Files (5%-Medicare), The Health and Retirement Study (HRS-M) and the National Long Term Care Survey (NLTCS-M) as well as from other supplementary sources. This work will build on our recent methodological developments in modeling and prediction of health-related traits to account for changes in health-related components and estimate the associated projected changes in utilization of the Medicare system. In these analyses, model parameters and resultant forecasts will be generated using Medicare-5% then validated on SEER-M, HRS-M and NLTCS-M. In analyses requiring individual-level social economic or genetic information, HRS-M will be the primary and NLTCS-M the validation dataset. For each study scenario, short-term (to 2028), medium-term (to 2038) and long-term (to 2050) forecasts will be made. Three specific aims will be addressed: 1. Develop new forecasting models of AD/ADRD burden that incorporate the effects of disease severity, fraction of AD/ADRD under- diagnosis, and mixed (multiple) dementia as well as the time patterns of AD/ADRD using a McKendrick-von Foerster equation-based approach. Apply other approaches including the multistate approach (a popular forecasting method), statistical projections, time series methods, Lee-Carter-based approaches, and microsimulation and compare their performance to that of our primary method. Construct realistic projections under multiple hypothetical scenarios. 2. Develop a McKendrick-von Foerster equation-based approach to incorporate the effects of co- and multi-morbidity including cerebrovascular diseases, type 2 diabetes mellitus, depression, cancer and other health disorders that show strong connections with AD/ADRD. Generate new scenarios based on information on health disorders included in forecasting models. Update and compare previous forecasts of AD/ADRD burden. 3. Create distinct groups of individuals based on their demographic, socioeconomic, behavioral and genetic characteristics. Estimate the group-specific AD/ADRD burden and evaluate the differences in outcomes, disease severity and fraction of under-diagnosis between these groups.. Update and compare previous forecasts of AD/ADRD burden. Integrate findings and compare the results obtained study-wide under all chosen scenarios.

The objective of this project is to further the understanding of Alzheimer’s disease progression in order to develop algorithms to predict the length of time from disease onset to major disease outcomes in individual patients with Alzheimer’s disease (AD).

The three projects of our PPG examine male-female health-survival paradox by comparing numerous life tables, social, behavioral and other environmental factors in various human and nonhuman populations, but none of them deal with the effects of genetic variants and GxE interactions. As reviewer recommended “Down the road, results from genetic demography will likely become important to the study of differential health and mortality by sex (P.10, PPG summary statement), This competing revision project focusing on sex differences in the effects of genetics & GxE interaction on cognition (emphasizing prevention of Alzheimer disease), mental health and survival would make significant contributions to expand our PPG and the research field.

Previous research emphasizes pleiotropic effects of the APOE 19q13.3 region variants supporting protective (notably, the APOE e2 allele) and detrimental (the APOE e4 allele) roles in Alzheimer’s disease (AD) and aging. Despite nearly two-decade progress in the APOE research, however, even pathogenic role of the strongest risk factor for AD, the APOE e4 allele, remains poorly understood. Understanding protective role of the e2 allele is lagged behind the APOE e4 research due to, in part, seemingly smaller effects of this allele on AD. This paradoxical situation of a potentially strong role of the APOE locus in AD and aging, and a hampered progress in the ApoE2-Aging-AD research requires new approaches. Our approach is built on core principles of evolutionary biology in genetics of aging- related traits characteristic for post-reproductive life, insights from genetic epidemiology of such traits, and the results of our large-scale pilot study of five human cohorts proving its significance and feasibility. The core of our approach is the association of AD with complex molecular signatures in the APOE region, rather than with a single allele, which include the e2 allele. These signatures are defined by significant differences in linkage disequilibrium (LD) patterns between affected and unaffected subjects. The principal difference between our approach and previous studies of LD structures in the APOE region, making it highly innovative, is that following the core biological principles in genetics of aging- related traits, the effects in the ApoE2-Aging-AD framework are considered to be associated with AD- specific molecular signatures, rather than with those driven by common evolutionarily forces. This difference justifies the focus on extended signatures comprised of the APOE e2 allele and SNPs spread through the entire genome and interacting with this allele. Analysis of molecular signatures provides invaluable opportunity to dissect heterogeneity in action of the APOE e2 allele by identifying personalized (i.e., more homogeneous, group specific) polygenic profiles with stronger protective effect of this allele. The objective of this proposal is to identify personalized polygenic profiles, comprised of the e2 allele, other SNPs in the APOE region, and SNPs spread through the entire genome, with stronger protection in the ApoE2-Aging-AD framework, and identify the role of AD risk factors in these profiles. Specific aims: Aim 1. Identify molecular signatures of AD and life span as a proxy for aging. Aim 2. Dissect heterogeneity and identify commonalities in the molecular signatures. Aim 3. Identify personalized polygenic profiles of AD and aging traits. Aim 4. Use bioinformatics analysis to characterize functional consequences of SNPs and genes.

Prior research and the 2018 NIA-Alzheimer’s-Association framework emphasize that novel insights into the complex biology and heterogeneity of Alzheimer’s disease (AD) are needed to develop efficient interventions that can be tailored to persons’ unique risk profiles. These profiles are likely a result of an interplay of many genetic and non-genetic risk and protective factors for AD, including those of vascular origin, which are difficult to disentangle. Emerging evidence suggests also that ADs and vascular diseases tend to cluster together. This project addresses an objective of PAR-17-054 on disentangling heterogeneous interactions of genetic and AD/vascular risk factors in risk and resilience to AD, including age-specific effects, by leveraging existing resources and engaging in activities that will improve statistical power. Our approach, combining thorough methods of genome-wide association studies and the rigor of the candidate-like methods in large samples, is built on: (i) core principles of evolutionary biology in genetics of AD and other age-related traits characteristic of post-reproductive life, which deals with an inherent heterogeneity in genetic predisposition to such traits, (ii) insights from prior studies of such traits (including our own work), and (iii) promising results of our large-scale studies proving its significance, feasibility, and potential to substantially improve power using the existing resources. This research contributed to better understanding of weaknesses in the rigor of prior studies and provided compelling evidence that our approach is a natural and critical strategy to advance the progress in dissecting the inherently heterogeneous mechanisms of AD and vascular traits. The goal is to identify personalized (i.e., more homogeneous, group-specific) mono/polygenic profiles of risks and resilience to AD and vascular diseases in the disease-specific and pleiotropic contexts in prioritized loci leveraging information from the AD-centered pleiotropic meta-analysis planned in this project and previous analyses by our and other research groups, and identify the role of AD risk and other factors in these profiles. We will address the following specific aims: Aim 1. Identify specific and pleiotropic loci for AD and vascular traits from new analyses and the existing studies. Aim 2. Dissect heterogeneity leveraging the analysis of molecular signatures defined as differences in linkage disequilibrium structures in affected and unaffected subjects. Aim 3. Identify personalized genetic profiles of AD-specific and pleiotropic risks and resilience. Aim 4. Characterize the functional roles of SNPs from the identified mono/polygenic variants and biological roles of genes for these SNPs. Characterize transcription pathways for SNPs using individual-level gene expression and epigenetic data and summary statistics from the available expression and methylation quantitative trait loci studies.

NIH/NIA and Alzheimer’s association emphasize that capturing complexity in etiology of Alzheimer’s disease (AD) and AD-related dementias (AD/ADRD) may substantially advance the understanding of the AD/ADRD pathogenesis. Mechanisms of complexity may involve various endogenous (e.g., genetics, epigenetic, cellular, physiology) and exogenous (e.g., environmental exposures, social milieu) factors, including those of vascular origin, and their interactions. It is recognized that novel insights into the complex biology and heterogeneity of AD/ADRD are needed to develop efficient interventions that can be tailored to a person’s unique risk profile. The objective of this project is to identify personalized (i.e., more homogeneous, group-specific) genetic and non-genetic profiles of risk of, protection against, and resilience to AD/ADRD and vascular diseases in the disease-specific and pleiotropic contexts. Our approach leverages an array of comprehensive methods which ensure synergism in dissecting genetic and non-genetic heterogeneity in predisposition to AD/ADRD in pleiotropic context. This approach overcomes core weakness in the rigor of prior studies characterizing effects of different factors “one by one” using analysis-specific methods. High potential of our approach is supported by our recent publications and rich data from the existing studies. We will address the following specific aims: Aim 1. Identify specific and pleiotropic loci for AD/ADRD and vascular traits from the exome-wide association study. Aim 2. Dissect heterogeneity leveraging the analysis of molecular signatures defined as differences in linkage disequilibrium patterns in affected and unaffected subjects. Aim 3. Identify personalized genetic profiles of AD/ADRD-specific and pleiotropic risks, protection, and resilience using rigorous methods. Aim 4. Characterize the functional roles of SNPs from the identified mono/polygenic variants and biological roles of genes for these SNPs. Characterize transcription pathways for SNPs using individual-level gene expression and epigenetic data and summary statistics from the available expression and methylation quantitative trait loci studies.):

The project objective is to significantly improve our understanding of heterogeneous and shared mechanisms in normal aging and Alzheimer’s disease (AD); identify genetic factors that may protect against the age-associated declines in brain resilience and resistance to AD, and validate new candidate genetic targets for AD prevention/treatment using preclinical biomarkers of AD pathology. This objective will be addressed using data collected in twelve large longitudinal and cross-sectional human studies with genetic and phenotypic information on more than half a million individuals in total. Specific Aims: 1. Identify new pleiotropic variants that influence both aging and AD traits, and evaluate their joint impacts on AD risk and survival. Our hypothesis is that pleiotropic SNPs that are associated with multiple phenotypes of aging and AD may have a broad systemic influence on these traits and jointly affect AD risk and longevity. We will select such pleiotropic SNPs, using PheWas approach; evaluate their joint impacts (additive and epistatic) on AD and survival traits; select top results and specify pathways enriched in respective genes; and suggest potential mechanisms connecting these pathways with AD. Pre-clinical validation of the results will be done in Aim 3. Aim 2. Explore shared biological mechanisms between aging and AD, and their genetic heterogeneity, and identify new candidate genetic targets for AD prevention. Our hypothesis is that genes connected in the same pathway relevant to aging and AD will more likely jointly influence relevant phenotypes than genes from different pathways. We will first select sets of candidate genes representing major pathways and processes involved in physiological aging, brain resilience to damage and resistance to AD, based on current evidence from human and experimental studies. Then we will evaluate the collective effects (additive and epistatic) of genes from these pathways on aging and AD traits. Top results will be further validated in Aim 3. Aim 3. Preclinical validation of candidate genetic targets selected in Aims 1, 2, using biomarkers of AD pathology, and further exploration of mechanisms of genetic associations. To further validate sets of genetic variants that together influenced AD risk and/or survival in Aims 1 and 2, we will estimate their joint effects on preclinical biomarkers of AD pathology, such as hippocampal volume, CSF and metabolic (FDG) biomarkers, and metabolomics profiles, considering other covariates. We will also explore causal relationships between the genetic factors found in Aims 1 and 2, and phenotypes of aging and AD, using Mendelian Randomization and related approaches. Results of this project will significantly improve our understanding of the shared and heterogeneous mechanisms of aging and AD, and will help identify protective genetic factors against the age-declines in brain resilience and resistance to AD, and suggest new genetic targets for AD personalized prevention and treatment.

The objective of this project is to significantly improve our understanding of the heterogeneity of Alzheimer’s disease (AD) and common genetic mechanisms in aging and AD, and find new genetic targets for AD prevention, with emphasis on regulatory and rare functional variants involved in both aging and AD. This objective will be addressed using data collected in several longitudinal and cross-sectional human studies with genetic and phenotypic information on more than half a million individuals in total. Specific Aims: Aim 1. Identify new pleiotropic variants that influence both aging and AD traits, and evaluate their joint impacts on AD risk and survival. We will select such pleiotropic SNPs, using PheWas approach, and evaluate their collective impacts on AD and survival, using new methods of estimating joint effects of genetic interactions (Interaction Polygenic Risk Scores, IPRS). We will also specify pathways enriched in respective genes, and suggest mechanisms connecting them to AD. Aim 2. Investigate shared genetic mechanisms between physiological aging and AD, using candidate genes from relevant biological pathways, and suggest new targets for AD prevention. Our hypothesis is that genes, which products are connected in the same biological pathway/process relevant to both aging and AD, will work in concert and jointly significantly influence AD traits, especially in people with signs of accelerated physical aging. Based on current literature, we will select sets of candidate genes representing pathways that were linked to aging, and also relevant to AD (e.g., mitochondrial biogenesis declines with aging, and also (exacerbated) in AD), and regulatory elements such as miRNAs that influence translation of respective genes and protein levels. Then we will evaluate joint effects (additive, GxG, IPRS) of these genes on aging and AD traits, including in subsamples of individuals with signs of accelerated aging, and select candidate genetic targets that will be further validated in Aim 3. Aim 3. Preclinical validation of candidate genetic targets selected in Aims 1, 2, using biomarkers of AD pathology, and further exploration of mechanisms of observed associations. We will estimate effects of the selected variants on hippocampal volume, CSF and metabolic (FDG) biomarkers, and on cognitive scores, considering other covariates. We will also further explore causal relationships between genetic factors selected in Aims 1 and 2, and phenotypes of aging and AD, using Mendelian Randomization and related approaches. Results of this project will significantly.

Accumulating evidence suggests that infections may play a major role in Alzheimer’s disease (AD), however, exact mechanism is unclear. Recent studies linked diverse microorganisms (viruses, bacteria, fungi) to AD- related traits. This indicates a possibility that the culprit may be not a specific microbe (or not only it) but a compromised host immunity that may increase brain vulnerability to various infections and related toxins. Recent data (including our own) suggested that some vaccines may have broader than expected beneficial off-target effects on the immunity that span beyond the protection against specific disease and may reduce risks of seemingly unrelated disorders, including AD, as well as all-cause-mortality. The broad objective of this project is to significantly improve our understanding of the connections between AD and infectious diseases and suggest new candidates for AD prevention based on repurposing of existing vaccines in older adults. To address this objective, we will assess the impact of infectious diseases and vaccinations occurring at ages 65+ on AD-related traits in population-based human data, taking into account genetic and other factors. This study will employ advanced pseudo-randomization techniques (“proxy for clinical trials”) that take into account multiple variables and bring the interpretation of study results closer to that seen in randomized clinical trials. Specific Aims: Aim 1. Evaluate relationships between AD and common infectious diseases and vaccines in older adults. We will estimate and compare risks of AD and other dementias among older individuals diagnosed with herpes simplex, herpes zoster (shingles), bacterial pneumonia, flu, recurrent mycoses, and some other infections. We will also evaluate off-target effects of vaccinations against pneumonia, flu, and shingles on AD onset and survival to select promising candidate vaccines for repurposing for AD prevention. Aim 2. Evaluate the impact of genes involved in AD and brain vulnerability to infections on associations of AD with infections and vaccines. We will select candidate genes from the literature that are involved in AD, and BBB permeability, brain response to infection, and myelin repair, and test if such genes can influence associations between infections/vaccines and AD, or AD biomarkers, and may be used in personalized AD prevention, with repurposed vaccines matching particular genotypes. Aim 3. Compare effects of infections, and vaccines, on AD vs. other major diseases and all-cause mortality. We will evaluate and compare associations of infectious diseases/vaccines with risks of AD and other diseases (cancer, CHD, stroke, diabetes), as well as all-cause mortality, to check for potential trade-offs. Such trade-offs are important to identify for optimizing AD prevention and avoiding the situation in which a protective factor for AD may have undesirable effect on other major diseases, and/or survival. Results of this project will significantly improve our understanding of infectious etiology of AD, and connections between AD and common infectious diseases, and will facilitate repurposing of existing vaccines for AD prevention in older adults.

Statement of Work There is a fundamental gap in understanding the nature of interregional differences in health outcomes and longevity in the U.S.: people in certain U.S. states and counties live up to 3.5 years (males) and 4.6 years (females) less than in states with better health outcomes. The persistence, and even widening, of this gap over time represents an important problem for the U.S. health system. These geographic disparities are associated with increased burden of disease, increased health expenditures in the health-care system, and showcase an observed lag in health and longevity compared to other industrialized nations. The objective of this application is to identify the mechanisms underlying the observed geographic disparities and clarify the role clinic- and non-clinic-related factors play in them. We expect that these geographic differences can be observed in individual Medicare trajectories and that the size and scope of the 5% Medicare dataset supplemented by Medicare records linked to the Health and Retirement Study will allow us to discover the causes of such disparities. In this project, we will test four scenarios on how these disparities could be reflected in health measures extracted from Medicare data: the regions with lower life expectancy exhibit higher disease incidence (scenario #1), worse patient survival (scenario #2), higher multimorbidity (scenario #3), and/or worse health state of individuals aged 65 (i.e., at time of entry into the Medicare system) (scenario #4). In Aim 1 we will test in what extent each scenario (or their combinations) can explain observed geographic disparities in mortality. We will identify specific diseases that contribute most to health disparities through each of the scenarios to be studied. In Aim 2, we will identify how clinic-related characteristics such as use of specific treatments, treatment choice and adherence to treatment, utilization of screening and diagnostic procedures (especially for early-stage diagnostics) impact the health outcomes and contribute to geographic disparities. Finally, in Aim 3 we will identify how non-clinic-related factors such as socioeconomic, behavioral, environmental characteristics, and access to and quality of care measures (constructed from 5%-Medicare data) impact the clinical measures identified in Aim 2 as determinants of geographic disparities. The results will provide new knowledge about clinic- and non-clinic-related barriers to improvement of health and increase of life expectancy in underperforming U.S. regions, identify the most affected population groups, and explain the role of the clinic and non-clinic-related factors in morbidity and mortality trends. The results of the proposed study will make possible the next step in approaching our long-term goal: to improve strategies of disease prevention, optimize allocations of medical resources with the focus on underprivileged communities and to improve health care standards to slow down or stop the growing gap in health disparities in the U.S.

Abstract There exists a limited number of studies that assess health disparities in Alzheimer’s Disease (AD) and even fewer for non-AD dementias. Insight from existing literature and our preliminary studies suggest that the most essential health disparities in Alzheimer’s disease (AD) and related dementias (ADRD) are related to race/ethnicity effects in AD risk and strong geographic gradient in mortality from AD. Our preliminary studies showed significant gaps between incidence rates for different race groups and mortality rates between East and West coast populations. In addition less significant disparities related to effects in rural/urban subpopulations and differences in survival from AD/ADRD were also identified. Detailed epidemiologic descriptions of these disparities, especially incorporating subgroups of AD-related dementias (ADRD), are lacking and the role of behavioral factors, comorbidity, time-dependent cognitive trajectories, and genetic effects in the developments of AD/ADRD are not sufficiently evaluated. Thus, there is a critical need to quantitatively describe the persistent disparities in the AD/ADRD outcomes and clarify the role of the multiple contributing factors. Our preliminary studies proved the ability to extract high-quality measures of the factors to be studied from the three datasets to be used in this study: 5%-Medicare, HRS-Medicare, and SEER-Medicare as well as Multiple Cause of Death database. Research in the project will be focused on i) re-evaluation of the disparities by calculating them with better accuracy and addressing limitations of our preliminary analyses, ii) multiple analyses designed to explain these disparities by analyzing the effects of potential mediators, iii) incorporating recent advanced methodological approaches such as a new partitioning approach for the decomposition of an overall trend into its causal components for analyses of these disparities in high volume data, and iv) incorporating new concepts for the explanation of these disparities, such as the contribution of over/underdiagnoses, heterogeneity in disease severity at time of diagnosis, analyses of patterns of conditions related to AD and ADRD, and the contribution of AD resilience to these disparities. Four Specific Aims planned in this study will deal with i) epidemiology of AD/ADRD, ii) behavior factors and comorbidity, iii) cognitive status and the effects of diagnosis severity and over/under diagnosis, and iv) genetic effects and cognitive resilience. The completion of these Aims will results not only in robust estimates of the disparities in AD/ADRD outcomes in diverse populations, but also, ultimately results in improvements in public health that can be achieved through reducing the identified disparities in AD/ADRD using targeted information based on the in-depth analyses conducted in this project. The expected outcome will be detailed disease-specific information presented in a quantitative form that provides the contribution of each studied factor to race/income-related health disparities in U.S. older adults. We will uncover the barriers in health-care provision that can be further used for improving primary, secondary, and tertiary prevention in the U.S. resulting, in their turn, in improved survival and higher life span.

Abstract Two of a series of in-person workshops in 2020-2022 will be hosted at Duke to provide new knowledge on how existing and recently developed analytic methods can be used for detailed population and clinical data analysis in order to make progress in understanding the causes and mechanisms of health-related disparities in Alzheimer’s disease (AD), related dementias (ADRD), and other prominent age-related diseases. The long- term goal of the series is to provide a resource focused on diffusing methodological know-how in terms of demonstrating the capabilities of newly developed methodologies, expanding on the rigor and range of application of well-established and familiar methods, promoting correct use of big health data both from a methodological and ethical prospective as well as providing a forum for experts and newcomers interested in health disparities and age-related diseases to discuss their ideas and promote their research. The pilot Duke- NIA workshop of the series held in February 2019 at Duke University was successful in drawing broad scientific interest to the topic and generated the background for the current proposal. The focus of the first workshop (planned in Winter 2020/2021) will be on demonstrating how studies using established administrative health data resources such as the Medicare claims database combined with innovative analytic approaches such as partitioning analyses, time-series based methods of projection/forecasting, and stochastic process models can be used to uncover previously overlooked and/or understudied aspects in this area of research. Specific topics to be discussed will include: i) disparities in risks and survival of AD/ADRD and other age- related diseases; ii) forecasting approaches for prevalence and mortality of AD/ADRD and other age-related diseases; iii) analysis of Medicare and other administrative claim-based data. The focus of the second workshop (planned in Winter 2021/2022) will extend this to include the health records data routinely collected in hospitals or University medical centers (e.g., the Duke Clinical Data Warehouse) and demonstrate how well- established and new analytic methods can be rigorously applied to such data to contribute to identifying the causes of persistent health disparities between specific groups of the U.S. population and narrowly defined patient strata. Specific topics will be expanded to include: i) analytic approaches to identify and quantify the contribution of treatment-related and medical care access-related factors to disparities in outcomes of AD/ADRD and other age-related diseases; ii) comorbidity, multimorbidity, treatment-related, social and genetic factors as sources of disparities in health outcomes of AD/ADRD and other age-related diseases; iii) forecasting of health outcomes and approaches for analyses of potential health interventions. The proceedings will be streamed live on the workshop website and presentations will be freely available in text and video form after the fact.

Life expectancy at age 65 increased steadily in the United States over the past half-century. There is great uncertainty, however, regarding the extent to which this increase was accompanied by the compression of morbidity/disability due to Alzheimer’s disease (AD), AD-related dementias (ADRD), and stroke—the leading causes of cognitive impairment (CI) among the elderly—or to heart disease, cancer, diabetes, obesity, arthritis, and fractures—the leading causes of non-cognitive disablement in basic activities of daily living (ADL) among the elderly. Given the aging of the U.S. population and the increasing costs of health care and long-term care above age 65, addressing this uncertainty is of profound public health importance. The 1982–1994 National Long Term Care Survey (NLTCS) produced the first reports of major improvements in ADL and instrumental ADL (IADL) disability rates above age 65. While ADL/IADL improvements continued through 2004 in the NLTCS, dramatically larger improvements occurred for severe cognitive impairment—including AD/ADRD—during 1984– 2004. Moreover, multiple reports from the Health and Retirement Study (HRS) indicated that the favorable trends in severe cognitive impairment continued, but at a slower pace, through 2012; similar reports from the National Health and Aging Trends Study (NHATS) provided additional independent evidence of continuing improvement during 2011–2015. We propose to conduct comprehensive analyses of genetic and non-genetic modulators of the compression of morbidity/disability in the NLTCS, HRS, NHATS, and Long Life Family Study (LLFS), using morbidity/disability criteria consistent with the HIPAA ADL and CI triggers, to test two major hypotheses: (1) that modifiable non-genetic risk factors account for the recent temporal changes in the incidence, prevalence, and continuance of cognitive and physical impairments; and (2) that constitutional genetic and epigenetic factors modulate individual differences in lifetime morbidity/disability incidence, prevalence, and continuance of cognitive and physical impairments. We will analyze the roles of modifiable non-genetic risk factors in longevity, co-morbidity, functional health (ADL/IADL), and severe cognitive impairment (Aim 1). We will complete the SNP array analysis of 2,680 biospecimen samples (918 currently done) and conduct DNA methylation analysis of 639 blood samples in the NLTCS. De-identified NLTCS genetic and epigenetic data will be released using NIAGADS protocols. We will use SNP and DNA methylation data to conduct genetic and epigenetic association analyses with phenotypes of aging, health, longevity, physical disability, and severe cognitive impairment (Aim 2). We will analyze associations of phenotypes of long healthy life with candidate polymorphisms within two highly relevant coupled gene networks—Insulin/IGF1 signaling (incl. FOXO3A and IGFR) and mTOR pathways—linked to aging and longevity across different species and associations of global and pathway-specific indices of heterozygosity with exceptionally high/low morbidity/disability risks; we will determine the roles of AD/ADRD, heart disease, cancer, stroke, and diabetes in these associations (Aim 3).