NIA has established the National Institute on Aging Genetics of Alzheimer's Disease Data Storage Site (NIAGADS) as a national genetics data repository in order to facilitate access by qualified investigators to genotypic data for the study of the genetics of late-onset Alzheimer's Disease (AD). It is the policy of the NIA that all Genetic Data derived from NIA funded studies for the genetics of late-onset Alzheimer's disease be deposited at NIAGADS or another NIA approved site or both whenever possible. NIAGADS is also the Data Coordinating Center for Alzheimer������������������s Disease Sequencing Project (ADSP), an National Institute on Aging initiative to identify new genetic variants by sequencing genomes/exomes of more than 30,000 AD patients and cognitively normal controls. In the third funding period, NIAGADS will continue our primary mission as the national repository for AD genetics and genomics, support ADSP data coordination, and collaborate with NIA-funded and other relevant ADRD research initiatives. The growing data will evolve into a long-lasting resource and a major legacy of ADSP. NIAGADS will: (1) Curate, update, and disseminate a high-quality, lasting data collection with up to 100,000 participants for ADRD genetics/genomics research; (2) Support ADSP data production and analysis activities; (3) Develop informatics infrastructure for cloud-based data analysis, management and dissemination; (4) Expand computational tools for genetic and genomic data annotation, report and visualization; (5) Collaborate with other research resources and initiatives, and expand the outreach program.

Our overarching goal is to learn how to positively influence health trajectories, modify disease risk and reduce health disparities through dietary modification. Emerging data, including our own, suggest that prenatal stressors including prenatal depression, perceived stress, and exposure to environmental contaminants increase oxidative stress to contribute to adverse pregnancy, birth, and postnatal outcomes and a Mediterranean-style diet decreases these health effects. However, data are limited and frequently under-powered to investigate these effects in ethnic minorities. We propose to leverage data and biological samples from our existing cohort resources of the Newborn Epigenetics Study (NEST) and Stress and Health In Pregnancy (SHIP) where more than 1200 women and their children have been followed from 3 months gestation, and now range in age from 2 to 15 years. We will test the overarching hypothesis that Mediterranean style diet prenatal and postnatally mitigates health effects of prenatal stress via epigenetic mechanisms. Specifically, we will determine if a Med-style diet during pregnancy is associated with molecular and epigenetic readouts of oxidative stress, inflammation, gut microbial diversity and DNA methylation. DNA methylation, a specific form of epigenetic modification, in regulatory regions of our genome that impact metabolism and inflammation recently identified by our group. These data will provide the data necessary for clinical trials focused on dietary manipulation, to mitigate the effects of a wide range of prenatal exposures.

The increased prevalence of obesity in the US and elsewhere has led to the hypothesis that epigenetic mechanisms mediate associations between environmental cues and obesity outcomes. However, epigenetic regions that alter obesity risk are still largely unknown, and the current lack of a screening tool for comprehensive measurement of epigenetic modifications hampers the identification of associated regions. Such a screen that could be applied to any disease or exposure of interest would be of great utility for a broad range of human health studies. The interpretation of human epigenetic data generated using genome-scale approaches is hampered by several obstacles. Firstly, the available data are largely based on methylation differences measured in DNA obtained cross-sectionally at different ages throughout the life course, yet DNA methylation marks are known to vary by age. Also, methylation measurements are made in accessible peripheral cell types accessible from otherwise healthy individuals, and variance of epigenetic marks between cell types means that measurements from peripheral cells do not always correlate with those from cell types that contribute to diseases. Additionally, alteration to epigenetic marks can be caused by disease, and this temporal ambiguity between exposure and outcome complicates causal inference. To overcome these obstacles, we have comprehensively identified DNA methylation-controlled regulatory regions for genomically imprinted genes, mapping the first draft of the human ����������������imprint-ome���������������. Epigenetically regulated imprinted genes are estimated to comprise 1-2% (200-400 genes) of the human genome, and are critical in the development of the early embryo; however, only ~30 imprint control regions (ICRs), regulating 70 to 80 genes, presently defined. Monoallelic expression of imprinted genes is regulated by parent-of-origin specific DNA methylation at ICRs that is established prior to germ-layer specification and maintained in somatic tissues throughout life. Our overarching goal is to leverage the newly identified ICRs, develop a custom platform to measure them in human specimens, and statistically identify the subset of the human imprint-ome associated with one of the most common trace metals������������������cadmium, a heavy metal that is sequestered by the placenta, contributing to placental dysfunction. Cadmium related methylation will also be examined in relation to children������������������s metabolic outcomes. Once developed, this ICR custom platform will be invaluable in identifying regions of early epigenetic perturbation associated with other early-acquired diseases or exposures, creating new opportunities for early detection and understanding the fetal origins and consequences of these conditions.

Alzheimer������������������s disorder (AD) is a devastating neurodegenerative disease and the most common cause of dementia. In the United States, there are ~6 million Americans with AD and ~29.8 million worldwide. The genetic predisposition of AD is considerable even for late-onset AD patients (60������������������80%); yet SNPs identified from genome-wide association studies only explain <50% of AD heritability. Multiple studies highlighted the roles of copy number variants (CNVs) in AD, including involving in the pathogenesis of AD and being associated with late-onset AD risk genes. We hypothesize that a systematic investigation of genome-wide CNVs at the full spectrum (small and large in size, common and rare in frequency, and coding and no-coding in genomic regions) from whole-genome sequencing (WGS) can further enhance the knowledge of AD etiology and risk. Leveraging the rich resources from the Alzheimer������������������s Disease Sequencing Project (ADSP), in this application, we propose to focus on a large multi-ethnic WGS sample (n>17,000) composed of AD cases and normal healthy elderly controls, and to (1) identify and genotype CNVs from WGS for ADSP case-control samples; (2) perform CNV-WGS association analysis of AD for each ethnic group using tools tailored toward CNV WGS data; and (3) conduct cross-ethnic CNV-WGS association studies and replicate findings. Successful completion of our aims will provide (i) a reference library of CNVs for AD patients, which permit biological inferences for AD mechanism; (ii) a list of AD-associated CNVs that are unique and shared across ethnic groups; and (iii) an optimized computational pipeline with open-source code for CNV discovery and CNV WGS analysis applicable to other large-scale WGS projects.

Primary liver cancer, the vast majority of which is hepatocellular carcinoma (HCC) is one of the few cancers with increasing incidence in the US. Incidence of HCC has tripled since 1980, which is particularly worrisome given that HCC confers a median survival of less than two years. The steepest increases in incidence are in Southern rural states and among ethnic minorities. While the prevalence of HCC had paralleled high rates of viral hepatitis in the last several decades, recent increases in the prevalence of nonalcoholic fatty liver disease (NAFLD) and its progression to nonalcoholic steatohepatitis (NASH) with fibrosis and cirrhosis, has fueled HCC in recent years. Yet, these factors alone do not explain the substantial regional and ethnic variation in HCC progression. One understudied but potentially potent HCC risk factor with increasing prevalence that disproportionately affects ethnic minorities, is exposure to environmental contaminants. These contaminants degrade slowly and therefore persist in the environment, providing a stable exogenous source for human exposure. Toxic metal(oid)s such as cadmium and arsenic are classified as probable carcinogens, and emerging data from murine models suggest that exposure is associated with hepatic steatosis, cirrhosis and liver cancer. Per- and poly-fluoroalkyl substances (PFAS) exposure in humans is associated with obesity and NASH. Further, emerging evidence indicates that these environmental exposures can induce epigenetic alterations that may promote adverse effects on the liver, but we lack longitudinal human data. These data underscore the need for longitudinal human data to assess whether and how these contaminants impact HCC risk. To address these knowledge gaps, and in response to RFA-CA-20-049, we propose the Southeastern Liver Health Study, a longitudinal cohort study of two sub-cohorts comprising 16,000 males and females aged 40 years and older in two Southeastern states, North Carolina and Georgia. We will test the overarching hypothesis that cadmium alone or in a mixture with other toxic metals and PFAS increases the risk of progression from NAFLD to liver fibrosis and HCC. The cohort will be recruited from community clinics including Federally Qualified Health Centers and University Health Systems������������������ Primary Care Centers and Hepatology programs at Duke, UNC Chapel Hill and Emory. Sub-cohort I will comprise 10,000 otherwise healthy adults who will be followed for 1������������������5 years, anticipating that ~1,100 fibrosis cases, including cirrhosis, will develop, and sub-cohort II will comprise 6,000 advanced fibrosis cases, anticipating ~750 HCC cases will develop. We will nest case-control studies within the cohorts, evaluate associations between environmental exposures and HCC incidence, and identify epigenetic marks responsive to contaminants that predict progression to HCC. Impact: This will be the first large-scale effort to longitudinally determine the link between environmental contaminants, liver disease and cancer in a residentially and ethnically diverse population. Additionally, we will create a data and specimen repository that will provide the research community with an invaluable resource to study HCC and other cancers.

NIA Genetics of Alzheimer's Disease Data Storage Site (NIAGADS) is an access portal for Alzheimer's disease genetics and serves as the data coordinating center for the Alzheimer's Disease Sequencing Project (ADSP), a NIH initiative to identify new genetic variants by sequencing genomes/exomes of AD patients and cognitively normal controls. The major mission of NIAGADS is to advance AD genetics via activities including coordinating data production, supporting analysis activities for ADSP, developing tools for cloud-based ADSP data analysis, expanding NIAGADS resource by interfacing with other research initiatives, and promoting community involvement with active outreach programs.

Since 1980, the incidence of HCC has tripled, becoming one of the fastest rising cancers globally and in the United States (US). HCC is now the second leading cause of cancer-related death worldwide. This increase in HCC-related incidence and mortality disproportionally affects racial/ethnic minority populations: African Americans and Hispanics have a two-fold higher incidence of liver cancer than Whites in the US. Because HCC mortality occurs on average 10 years earlier than other solid cancers, the potential years of life lost to HCC is substantial. While racial disparities have been reported for multiple cancers, less is understood about disparities in HCC. First, established risk factors for HCC are exposure to aflatoxins, alcohol, cirrhosis, and infection with hepatitis B virus (HBV) and hepatits C virus (HCV). However, the variation in the prevalence of these factors by race/ethnicity cannot fully explain the steep increase in the incidence and the widening of race/ethnic disparities. Second, exposure to heavy metals, including cadmium, has been associated with HCC in animal models; however, the cadmium doses examined were much higher than non-occupational exposures observed in the general population. Recent data indicate that adverse health effects, including cancer, may occur at lower exposures than previously thought but this has not be adequately investigated for HCC. Third, data from genome-scale DNA methylation studies suggest that widespread epigenetic ���������������signatures������������������ or changes accompany both hepatic fibrosis progression and tumor development. However, these promising data derive from resected or transplanted liver which comprises only ~20% of HCC, and minority populations are less likely to undergo either surgery. These knowledge gaps have hindered our understanding of the key underlying mechanism for disparities in HCC and have contributed to poorer outcomes in these populations. Hence, our goal is to determine if cadmium exposure alone or as a part of a mixture that includes lead and nickel, essential elements including zinc, copper, selenium, manganese, magnesium and/or calcium associate with increased risk of HCC, and determine if associations vary by ethnicity/race. To do this we will conduct a population-based case control study comprising 200 African Americans and 200 whites using the North Carolina Cancer registry to identify primary HCC cases. Urinary cadmium will be measured to estimate chronic exposure. We will also determine if regulatory sequences of cadmium assopciated genes mediate the relationship between cadmium exposure and HCC risk. Our vision is to identify epigenetic marks in accessible tissues that can be used to identify people at increased risk for HCC and for early detection when still treatable. We anticipate that with improved understanding of the integrated exposure, sociodemographic and molecular data that we will be better poised to combat and prevent the rise in HCC, particularly in underserved and minority populations.

This program project, entitled "Statistical Methods for Cancer Clinical Trials," is a joint venture of Duke University, North Carolina State University (NCSU), and the University of North Carolina at Chapel Hill (UNC). Biostatistician and clinician researchers from these three top research institutions collaborate on project research and share project-related resources. The scientific goal of this ambitious program project is to develop innovative statistical methods for cancer clinical trials that can hasten successful introduction of effective new therapies into practice, with focus on personalized cancer treatment. The method of approach is to leverage recent advances in statistical and computational science to create new clinical trial designs and data analysis tools that resolve many of the key scientific limitations of current clinical trial methodology. The program project involves five interrelated research projects focusing on developing these tools for personalized medicine. The proposed methods have the potential to alter the prevailing clinical trial paradigm and increase the discovery and translation of new treatments into clinical practice. The multi-institutional approach, which exploits the complementary strengths of each the three universities, includes an effective and energetic process for coordinated implementation, communication, and dissemination of the results, including development of new software for public dissemination to practitioners. The project will lead to significant improvements in cancer clinical trial practice that will result in improved health and outcomes for cancer patients The NCSU investigators will collaborate with each other and investigators from Duke and UNC to address the research problems jointly through synergistic interactions that exploit the complementary expertise from all three institutions.

This joint proposal from RTI and NCSU seeks to create a multi-faceted three-year Program in Genetic Discovery and Prediction (PGDP), initially organized around a demonstration and feasibility pilot for a highly ambitious effort the team calls the ����������������1000 GWAS Project.��������������� The Project will compile an unprecedented number of publicly available genome-wide association studies (GWAS, representing hundreds of thousands of patients). These studies have been used to identify genetic variants that predispose humans to disease and can be used to predict patient outcomes. The Project will re-analyze the combined data using the latest methods for genetic analysis and quality control, combined with new linkages to standard measures for phenotypes, as well as data on clinical covariates and exposures. In addition, the team will make progress on a GWAS Connector tool to support exploration and prioritization of dbGaP phenotypes for enriched secondary analysis. Finally, the Project will feed back into public repositories, providing an open-source analysis pipeline and community resource for ongoing research. The unprecedented data compilation and comprehensive analysis will reveal subtle and more complex interactions between genes, environmental exposures and resulting disease and treatment outcomes.

In addition to high blood sugar (hyperglycemia), diabetic patients frequently have high blood pressure (hypertension) and high levels of LDL-cholesterol and triglycerides, often coupled with low HDL-cholesterol (dyslipidemia).The majority of diabetes related mortality is due to cardiovascular events, and epidemiological studies have shown that cardiovascular risk increases with increasing levels of blood sugar, blood pressure, and blood lipids. A variety of drugs are available to treat each of these conditions, and some have been shown to have an effect on cardiovascular risk. For example, controlling LDL-cholesterol with statin therapy reduces the rate of cardiovascular events in diabetic patients, but not to the level characteristic of non-diabetic individuals. The ACCORD trial investigated whether intensive pharmacological therapy in diabetic patients, with the goal of normalizing glycemia, blood pressure, and blood lipids, would further reduce cardiovascular events. However, no additional effect was seen with intensive blood pressure or lipid therapy, and intensive glycemia management actually increased mortality. These failures of seemingly rational treatment approaches could be the result of differential response of individuals to particular therapeutic regimens due to genetic polymorphism in genes relating to the metabolism or mechanism of action of the medicines used. Many candidate genes could be advanced as possible sources of this genetic variation, but our knowledge of all genes contributing to metabolic and cardiovascular phenotypes is incomplete, and therefore a candidate gene approach cannot be assured of identifying the relevant genes. We therefore propose a genetic study of the ACCORD trial that looks at functionally significant genetic variation in all genes in the human genome to investigate the following questions: 1) Does genetic variation between individuals explain differences in response to fenofibrate, a drug that lowers triglycerides and raises HDL? 2) Does genetic variation between individuals explain differences in response to statins, drugs that lower LDL? 3) Does genetic variation between individuals explain differences in response to individual anti-hyperglycemia drugs in the short term, and to the intensive therapy approach to glycemia management in the longer term? Identification of genetic variants affecting outcomes of glycemia and lipid modifying therapies would enable the targeting of particular interventions to patients most likely to benefit and least likely to be harmed, improving cardiovascular outcomes and reducing the burden of morbidity and mortality attributable to diabetes. The genes containing these variants may prove to be novel targets for drug development, leading to new medicines for improving outcomes for diabetic patients in the future.