Gary W. Beecham, Ph.D. - US grants

DESCRIPTION (provided by applicant): Coronary heart disease is the leading cause of death in the United States with atherosclerosis of the coronary arteries being the major underlying etiology. Patients with atherosclerotic coronary artery disease (CAD) are significantly more likely to suffer a myocardial infarction or sudden cardiac death. As such, CAD patients receive the maximum preventive therapies, and their clinicians maintain a low threshold for imaging and invasive vascular procedures. Clearly, knowledge of a patient's CAD burden has a major impact on clinical care, but it is not practical to definitively diagnose CAD on a population scale. We are proposing to use genetic information in conjunction with traditional risk factors, as a means of identifying individuals at increased risk of having CAD who could then receive aggressive risk reduction and/or undergo definitive coronary imaging. To identify genetic risk factors for anatomic CAD, we are engaged in a Genome Wide Association Study (GWAS) of 2000 cardiac catheterization patients using the Affymetrix SNP array 6.0 platform. We are currently accruing a second validation cohort of 2000 patients, in which we will genotype the top association signals from our GWAS. The combined datasets will be used to prioritize genes for sequencing to identify putative functional variants. Any functional or validated risk loci will be analyzed for their utility in risk classification. Furthermore, the diversity of our patient population will allow us to identify CAD gene variants that are common and unique to African American, Caucasian and Hispanic subjects. To our knowledge, this is the first GWAS specifically for anatomic CAD in the context of significant racial and ethnic diversity. PUBLIC HEALTH RELEVANCE: This project will detect genetic risk factors for anatomic coronary artery disease by using genome-wide genotype data and next-generation sequencing. We will use the genetic risk factors in conjunction with traditional cardiovascular risk factors to improve artery disease risk classification in a clinical setting.

Core C: The Statistical Analysis and Bioinformatics Core of the University of Miami (UM) Udall Center builds on our experience in analysis of genes in PD over the previous twelve years. The goal of the Core is to support the needs of the Projects by applying powerful next-generation sequence analysis approaches, bioinformatics techniques, and established statistical analyses. The Core has integrated informatics, bioinformatics and statistical support. It takes advantage of existing resources within UM in the Hussman Institute for Human Genomics (HIHG) and Center for Computational Science (CCS). The core is lead by Dr. Beecham who is the director of informatics at the HIHG, an expert in genetic association analysis. He replaces Dr. Martin as PI, and has been a Project PI in our Udall Center since its inception. She remains on the core as a co-investigator. Members of the data management, computer, statistical, and bioinformatics staff of the HIHG staff will form the nucleus of the Statistical Analysis and Bioinformatics Core, addressing the projects' needs through the following specific aims: ¿ To provide the informatics to support database management, storage, and rapid retrieval of family history, clinical, risk factor, genotypic, DNA sequence and RNA expression data for the projects and clinical core. ¿ To provide analytical support for next-generation sequencing. We will provide support for the entire pipeline of next-generation sequencing data analysis; from data generation to statistical analysis and interpretation. The analyses include quality control, assembly, alignment, variant calling, functional annotation, and phenotype association analyses. ¿ To provide additional statistical analysis support for all projects and cores. We will conduct various analyses, including quality control, association analysis, parametric and non-parametric linkage, gene-gene and gene-environment interaction, biological pathway analysis, and copy-number variant detection and association.

Project Summary To further disentangle the molecular mechanisms underlying Alzheimer's disease (AD) and to foster the mapping of therapeutic targets, we propose an extreme phenotype design: a whole-genome sequencing (WGS) study of early-onset AD (EOAD) in a large set of multiply affected, well-phenotyped Caribbean Hispanic (CH) and non-Hispanic White (NHW) families. Extreme phenotype designs (e.g., early age-at-onset--AAO, fast vs. slow progressors, very high vs. very low biomarker levels, etc) increase statistical power by creating more homogeneous and genetically loaded populations, and have the potential to reveal genetic risk factors and mechanisms that are difficult to identify in more heterogeneous datasets. This is critical for clarifying AD etiology and developing more effective therapeutic targets. Early studies in AD focused on EOAD and identified a limited number of highly penetrant risk variants: APP, PSEN1, and PSEN2. These genes increase the generation and/or aggregation of the amyloid ß peptide, an observation that underlies current therapeutic strategies. However, these known mutations account for less than half of the genetic basis of EOAD. Many of the EOAD families do not carry known mutations, and among known mutation carriers AAO is often highly variable. This unexplained genetic component to EOAD represents a critical gap in our understanding of AD etiology?a gap not filled by the ongoing AD sequencing studies, which largely focus on the more heterogeneous late-onset form of AD (LOAD). Additionally, this proposal includes both Hispanic and non-Hispanic white samples. The inclusion of minority populations allows us to examine EOAD risk in an understudied but fast-growing population and to map AD risk loci that are unique to this ethnic group, giving further insight into the etiologic mechanisms underlying the disease. To accomplish these goals, we propose the following Aims: (SA1) Identification of novel genetic risk factors for EOAD by whole genome and targeted sequencing. We will perform WGS in 87 multiplex EOAD families, followed by bioinformatics annotation and prioritization based on segregation and function. Highest priority genes/regions will be validated in the family and then will become targets for custom sequencing in a set of EOAD singletons to maximize variant identification. (SA2) Putative functional loci resulting from SA1 will be validated in independent EOAD samples using custom genotyping arrays and (SA3) evaluated for generalizability to late-onset AD using existing LOAD resources such as the ADSP, ADGC, and WHICAP datasets. Finally (4), the most interesting variants will be subject to rapid, biological screening procedures to determine their molecular effects.

PROJECT SUMMARY To identify new treatment targets, we and others have examined the genomics of Alzheimer's disease (AD). However, genomic successes so far have arisen from studying primarily non-Hispanic White (NHW) participants, and the study of minority populations has been minimal. What few studies have been done in minority populations have suggested that the genetic architectures overlap, but only partially. Thus, studying minority populations not only serves to test generalization of the NHW findings but also provides a unique opportunity for discovery of novel targets and pathways. To begin addressing these issues, we propose here the Puerto Rico Alzheimer Disease and Related Disorders Initiative (PRADI). We will whole-genome sequencing (WGS) Caribbean Hispanic Puerto Rican (CHPR) AD multiplex families to identify novel AD variation in CHPRs, and to generalize existing AD genetic discoveries to this underrepresented population. This initiative will increase our knowledge about genetic variation, particularly for the Caribbean Hispanic population of Puerto Rico (CHPR). The Puerto Rican (PR) population is the 2nd largest Hispanic/Latino population in the continental US. The prevalence of AD in the Caribbean Hispanic population of the island of PR is estimated in 65,000. The PR population is a highly mixed population with average ancestry values of ~64% European, ~21% African, and ~15% Native American. The unique genetic make-up of the PR AD population will be critical in new discovery as well in replication of findings from the Alzheimer Disease Sequencing Consortium (ADSP) CHDR data and the Alzheimer's Disease Genetics Consortium (ADGC) African American (AA) data. Thus, discovery of genetic contributions to AD risk and protective variants in CHPR would have a substantial influence on our understanding of AD and towards our goal of identifying new treatment targets. Through this proposal in response to PAR-15-356 we will address this important issue by conducting genomic studies of AD in PR. Specifically we propose a family-based study in PR that parallels the family-based efforts in the ADSP Discovery phase and that will enhance and extend both current ADSP and ADGC efforts to a broader AD community. We aim to 1) Characterize the genetic epidemiology of AD in PR 2.) Generalize and refine known risk and protective loci in familial PR AD. 3.) Perform variant discovery in our PR AD families and case control data 4.) Leverage multi-ethnic populations (PR, DR and AA) to discover novel AD risk/protective effects by calculation of local ancestry, admixture mapping and bioinformatics analysis and 4.) Perform multi-locus analyses providing insight into functional implications of the risk and protective loci. Our overall goal is to identify targets for therapeutic development that will either prevent or significantly delay the onset of AD.

? DESCRIPTION (provided by applicant): Alzheimer disease (AD) is the leading cause of dementia in the elderly and occurs in all ethnic and racial groups. A multitude of genetic studies in AD have identified multiple AD associated genes and loci, but a large portion of the genetic influence on AD remain unknown. The Alzheimer Disease Sequencing Project (ADSP) will use large-scale sequencing efforts to increase our knowledge about the genetic variation that influences AD, particularly rare genetic variants that enhance AD risk or protect against AD. Substantially underrepresented in these efforts, however, is the generalization of current and future findings in African Americans (AA). AA have a higher prevalence of dementia than non-Hispanic Whites (NHW). Despite steady improvement in the overall health of the U.S. population, individuals within these underserved groups continue to be vulnerable to lapses in care and are at increased risk for health problems. Health disparities have had an especially profound negative effect on the overall health of AA. AA have disproportionally higher health-risk factors, limited access to health services, and ultimately poorer health outcomes and life expectancies than NHW. The determinants of the health disparities seen in AA are many, including public health policy, clinical practices, and social, economic, cultural and/or language factors. One promising avenue for reducing health disparities is the use of precision medicine to improve disease prediction, prevention, diagnosis, and treatment. However, genomic medicine relies on participation from diverse populations in both research and clinical applications. Through this application, we will address this important issue by conducting genomic studies of AD in AA. In response to RFA AG-16-002, we are proposing a set of experiments that will complement and extend the activities and results of the ADSP Discovery and Replication phases, thereby addressing the issue of health disparities in AD research. Specifically we propose a family-based study in AA that parallels the family-based efforts in the ADSP Discovery phase and that will enhance and extend current ADSP efforts to a broader AD community. Specifically, we will 1) Expand our existing AA family dataset; 2.) Generalize and refine ADSP risk and protective loci in familial AA AD. 3.) Prioritize variants by admixture mapping and bioinformatics analysis and 4.) Perform multi-locus analyses providing insight into functional implications of the known risk and protective loci and identifying possible additional genic targets. Our overall goal is to identify targets for therapeutic development that will either prevent or significantly delay the onset of AD.

PROJECT SUMMARY Genomic studies of Alzheimer's disease (AD) have primarily focused on non-Hispanic White (NHW) participants affected by the late-onset form of the disease (LOAD; onset age: >65), or the study of early onset AD (EOAD; onset age <=65) cases from families showing Mendelian inheritance patterns associated with mutations in the APP, PSEN1 and PSEN2 genes. However, mutations in these three genes explain ~10% of EOAD cases. There are no large-scale efforts to collect and study EOAD cases not explained by these genes, despite the fact that this unexplained EOAD category accounts for ~90% of cases. The few smaller studies that have been conducted suggest that the genetic architecture of EOAD overlaps with the late-onset form only partially. Thus, studying EOAD in subjects without APP, PSEN1 and PSEN2 mutations is a critical gap that provides a unique opportunity for discovering novel therapeutic targets and molecular pathways. To address this issue we aim to identify additional EOAD-associated variants through a large-scale whole- genome sequencing (WGS) study of unexplained EOAD. We will include cases from several well-established AD cohorts including the Resource for Early-onset Alzheimer Disease Research (READR), the Knight-ADRC at Washington University, the Alzheimer's Disease Genetics Consortium (ADGC), and others. Generating and harmonizing a dataset of 200 non-Hispanic White (NHW) and Caribbean Hispanic (CH) multiplex EOAD families, over 4,000 EOAD singletons and over 13,000 unrelated, cognitive controls, all with WGS, this project will yield the largest EOAD genomics dataset to-date, improving statistical power for variant identification and allowing us to assess the impact of specific factors such as APOE genotype, vascular risk factors, and neuropsychiatric comorbidities. The inclusion of a large set of CH families and singletons will allow the examination of EOAD risk in a significantly understudied but fast-growing minority population. Analyses will comprise both linkage and association-based approaches, analyses of polygenic and ancestry effects, and a thorough examination of neurocognitive, neuropsychiatric and cardiovascular endophenotypes. We expect that when successfully completed, this study will point to novel genetic contributors to EOAD, shed light on the mechanisms of AD and facilitate the development of novel therapeutics. Sampling, phenotyping and sequencing analysis protocols will be complementary to and compatible with the existing LOAD genomics resources, such as the Alzheimer Disease Sequencing Project (ADSP) and related studies. This phenotypic and genomic consistency, together with the use of existing AD infrastructure (NIAGADS), allows for immediate integration with the leading efforts on LOAD, enabling rapid large-scale investigation of a variety of additional critical AD genomics hypotheses.

PROJECT SUMMARY Multiple population and community based studies conducted across the US, Europe, Japan, and Australia all have repeatedly observed complex neuropathologic changes in individuals with a clinical diagnosis of Alzheimer's disease (AD) dementia. Although usually including neuritic plaques (NP) and neurofibrillary tangles (NFT), the regional levels and extent of distribution of these hallmark lesions are variable. Additionally, more than half of individuals with AD dementia have other comorbid lesions in brain that when present in isolation can be diagnostic of dementia?the AD-Related Dementias (ADRDs). These include cerebral amyloid angiopathy (CAA), vascular brain injury (VBI), Lewy body disease (LBD), and hippocampal sclerosis of the elderly (HS), among others. Indeed, individuals with a clinical diagnosis of AD dementia frequently show a complex mix of AD lesions and comorbid lesions, making it unclear the extent to which each contributed to cognitive decline and dementia in that person. We hypothesize that the mechanisms of injury and response to injury that produce these different disease-specific brain lesions are influenced by differing genetic factors. With few exceptions, genetic studies for AD have associated genetic variants with a clinical diagnosis of AD dementia. The comorbid complexity described above is a serious limitation to interpreting these data. Are the associations with AD dementia related to the hallmark lesions of AD (common assumption), the variably present comorbid lesions, or both? Only two studies have attempted to address this limitation. As a core analysis of the Alzheimer Disease Genetics Consortium (U01AG032984), our study of AD neuropathologic changes was the larger of these studies with approximately 4900 brain autopsies. However, even this initial study was limited by sample size, platform, and less sophisticated analysis tools. To address these limitations and to advance our knowledge of the full spectrum of dementia neuropathology, we propose a genomics study of hallmark AD lesions together with comorbid lesions associated with ADRDs. This study will expand the sample size of neuropathology subjects, will expand efforts to include next-generation sequence data, and will implement more advanced statistical techniques to better understand the relationships between traits. When successfully completed, our results will point to novel, relevant molecular contributors for each of the pathologic lesions of AD or ADRDs, either alone or in combination. To accomplish these goals we propose four Specific Aims. SA1: Identify genetic variants associated with hallmark AD lesions by whole genome sequencing and genome-wide genotyping; SA2: Identify genetic variants associated with comorbid lesions commonly present in brains of older individuals; SA3: Determine the inter-trait genetic landscape by assessing confounding and genetic correlations across traits; and, SA4: Determine regional, cellular, and lesion distribution of protein products of selected genes identified in SA1-2.

ABSTRACT Alzheimer disease (AD) is the leading cause of dementia in older adults and occurs in all ethnic and racial groups. Genetic studies of AD have mostly been performed in non-Hispanic Whites (NHW) of Northern European (NE) ancestry. Only recently have efforts in AD started to expand into other populations, such as African-Americans (AA) and Hispanics (HI), and have a ready demonstrated differences in both risk effect size (e.g., APOE in AA and HI) and risk loci (e.g., ABCA7 in AA). Further evaluation demonstrates that genetic ancestry (as opposed to environmental/cultural factors) likely underlie at least part of this heterogeneity. Individuals with the Amerindian (AI) ancestry remain one of the most underrepresented groups in AD. Importantly, the NHW datasets did not differentiate among the Europeans (EU), whereas recent investigations showed that these pan-European results only partially overlap with the findings from populations from the Iberian Peninsula (IP) with Southern European (SE) ancestry. Caribbean and South American Hispanic populations are admixed with both AI and SE, thus making their study a critical scientific objective. Our proposed study enables testing the generalization of findings from NHW to these other ancestries, as well as identify AD risk/protective factors correlated specifically with AI and SE ancestry. Our results will allow for a better and more complete understanding of the genetic architecture of AD which will help improve disease prediction, prevention, diagnosis, and treatment in AI, admixed Hispanic populations, and beyond. To accomplish these goals, we propose three aims. In Aim 1 we will characterize known AD loci in admixed populations with AI and SE ancestry. This includes expanding collections, generalizing known AD loci to AI/SE populations, and variant discovery through admixture mapping and fine-mapping. In Aim 2 we will extend our Puerto Rican dataset by expanding PR multiplex families. This will allow more powerful linkage analyses, longitudinal neurocognitive and biomarker data, and the initiation of a brain donation program. Finally, in Aim 3 we will perform functional follow-up of variants using bioinformatics approaches, assessment of AD biomarkers, and assessment of cellular function using IPSc.