Jonathan L. Haines, PhD - US grants

Advancements in recombinant DNA technology have nurtured the growth of linkage analysis into a powerful methodology for human genetic research. Genetic linkage maps of all the chromosomes have been developed using hundreds of cloned genes and anonymous DNA sequences. Such maps further increase the power of linkage analysis to define disease gene location. However, their current utility is limited by rather low resolution and inconsistent spacing of loci. The goal of this proposal is to generate genetic linkage maps of human chromosomes 21 and 22 with a sex-averaged resolution of 1 cM. Data will be generated on 100 sibships containing over 1400 potentially informative meioses. Initial maps with resolutions slightly less than 10 cM already exist and will serve as the backbone for the high resolution maps. Probes will be obtained from all sources, including cosmid libraries. By comparison with physical mapping results (generated under separate proposals), a directed cloning strategy may be used to fill under-represented regions. Efficient methodologies for error checking and analysis of the data will significantly reduce the amount of computer time necessary. The resulting fine-structure maps will be five to ten times as precise as current maps. They will substantially increase the efficiency with which any disease gene residing on these two chromosomes can be localized, and will provide excellent starting points for direct cloning of the disease gene locus. Statistical analysis of the data will help answer questions concerning variation in recombination by sex, age, ethnic background, and familial clustering. It will also aid in the determination of appropriate parameters for interference. Prenatal and presymptomatic diagnosis of disease will be possible with accuracy almost totally dependant on the pedigree structure and clinical diagnosis, not on the markers tested. Finally, these maps will allow informative comparisons between physical and genetic maps, providing new insights into chromosome structure and organization, and facilitating the eventual sequencing of chromosomes 21 and 22.

Von Hippel Lindau Disease (VHL) is a devastating disease associated with various forms of cancer in multiple organ systems frequently leading to serious clinical complications and death. Using DNA linkage analysis, we have recently provided conclusive evidence that the gene causing VHL is located on the short arm of chromosome 3 in the neighborhood of the c- rafI oncogene. Consequently, we propose to bracket, and isolate the disease gene based on the knowledge of its chromosomal location. The currently available DNA markers together with new markers generated from chromosome 3 specific libraries, will be used to define loci that are more tightly linked to, and flank the VHL defect. This should lead to the development of a much needed diagnostic test, and will provide the basis for the isolation of the defective gene itself. In order to gain insights into the mechanism of tumorigenesis in VHL, chromosome 3p markers will be applied to search for chromosomal deletions in VHL tumors. The deleted regions in VHL tumors will be compared with the deletions in the sporadic counterparts of VHL tumors, e.g. in renal cell carcinoma, to address the question of whether sporadic and familial forms of VHL-associated tumor types result from similar pathogenetic mechanisms affecting the same gene locus. Overlapping DNA clones representing the minimum genetically definable region containing the VHL gene will be isolated using one or a combination of cloning strategies. The genes encoded in this region will be analyzed at the DNA, RNA, and protein level. An in depth comparison of the genes will be performed between VHL tumors and corresponding normal tissue, and between tissue from individuals with and without VHL to identify the gene causing VHL. The isolation of the VHL defect might provide the basis for the development of rational therapies in VHL, and could have important impacts not only for VHL patients, but for a much larger number of cancer patients suffering from the sporadic counterparts of VHL tumors, including renal cell carcinoma. Ultimately, the isolation and characterization of the VHL defect should yield new insights into the function of the normal counterpart of the VHL gene which might play a fundamental role in growth and differentiation of endothelial cells in the human central nervous system and other organ systems.

Multiple sclerosis (MS) is a common neurological disorder with a significant genetic component. The long-term goal our research is to identify the underlying susceptibility genes in MS. The initial goal of this proposal is to screen for linkage of MS to markers spanning the entire human genome. We will combine efficient PCR-based marker genotyping with state-of-the-art statistical analysis using a multianalytical approach to achieve this goal. We have identified and sampled 55 families with multiple cases of MS. The families will be analyzed using a multi-analytical approach that includes sibpair (SP), affected pedigree member (APM), and lod score analyses. A set of specific screening criteria have been outlined that will maximize our chances of identifying chromosomal regions carrying susceptibility genes while rapidly eliminating false positive results. The promising chromosomal regions will be followed-up by more detailed statistical analysis, genotyping of additional markers in the region, and genotyping a second, independent dataset. If all these tests confirm that a susceptibility gene lies within the region, we will start more detailed polymorphism studies of this region. In order to further enhance our screening and follow-up process, we will test new statistical analytical techniques currently under development by our collaborators, such as two-trait locus, TDT, and WPC techniques. We will perform detailed studies of the power of these analytical methods by applying them to simulated data that approximates realistic agenetic models of MS, inclusive of multiple genes, and polygenic and environmental components. We are encouraged by our preliminary data, which has excluded several chromosomal region, and identified one promising region on chromosome 19 which we have started to follow-up. The combination of clinical, genetic epidemiological, and molecular expertise represented in this group investigators, and our commitment to MS make this approach a viable method for dissecting the genetic etiology of ms.

tissue /cell culture; cancer information system; biomedical facility; linkage mapping; nervous system neoplasms; molecular pathology; biopsy; congenital nervous system disorder;

DESCRIPTION (provided by applicant): Dementia of the Alzheimer's type (DAT) is the most common form of dementia in the elderly. The etiology of DAT is a combination of genetic and environmental factors. Forty-five to fifty-five per cent of the total genetic risk. in DAT has been pegged to four genes (APP, PS1, PS2, APOE) with by far the greatest proportion explained by the APOE-4 allele. However, additional novel genes remain to be identified and would be most easily identified in large families having a low frequency of the APOE-4 allele. Large families are extremely valuable because they can provide identity-by-descent data across many affected individuals. Unfortunately the late-onset nature of DAT makes family histories difficult to trace and the geographic dispersion of families in the United States often results in lost contact between distant familial branches. While pervasive these problems are not universal, with certain cultural and religious isolates, such as the Amish, having large and stable families. The Amish present numerous advantages for study, including recent derivation from a small number of founder couples, large family size, extensive genealogical records, few marriages outside the Amish communities, and stable social and environmental influences. Over the past six years, we have successfully approached and studied several Amish families with DAT in Indiana/Michigan and Ohio. Our initial studies of the Indiana/Michigan Amish have shown a lower frequency of the APOE-4 allele yet strong clustering of DAT cases in families, suggesting that genetic factors other than APOE are at work. At the same time, progress in completing the human genome sequence and in developing molecular and statistical tools has opened many new avenues for gene identification. We wish to avail ourselves of these strengths to map the DAT genes in the Amish families. Our specific aims are to: 1). Ascertain every Amish DAT family in Adams and surrounding counties of Indiana/Michigan and Holmes and surrounding counties of Ohio with the goal of identifying all DAT cases; 2). Screen the Amish pedigrees for genetic linkage to known loci and perform a genomic screen; 3). Perform fine mapping to identify the minimal candidate region and use SNPs to identify the underlying genes; and 4). Develop new methods to examine gene-gene interactions in large and complex pedigrees such as those found in the Amish.

"Neurogenetics of candidate systems in autism" takes a functional candidate approach toward autism gene identification. In the past, most functional candidates have been studied in isolation, one gene at a time, and often one polymorphism at a time. This is an inefficient approach since it ignores the possibility that autism susceptibility results from gene-gene interactions within or across pathways. Additionally, examining a single polymorphism can be very misleading since it ignores the known variation in linkage disequilibrium even across small distances, and does not comprehensively test the gene. Research focuses on two candidate systems, serotonin and GABA, which are known to be involved in some of the behaviors exhibited by autistic children. It resolves the previous problems with functional candidate searches by testing a comprehensive set of SNPs in each gene, and specifically testing for gene-gene interactions. This approach has been made possible by significant advances in both molecular genotyping and statistical genetic analysis. Coupled with the large dataset and detailed clinical characterization provided by the other projects and cores described in this application, this research will discern the roles of serotonergic and GABAergic genes in autism.

Multiple sclerosis (MS) is a debilitating neuroimmunological and neurodegenerative disorder affecting more than 400,000 individuals in the United States. Epidemiological and genetic studies have produced overwhelming evidence for a genetic influence on the risk of MS. While the first confirmed MS genetic association (with the HLA-DRB1*1501 allele) was identified in the early 1970's, additional success was not forthcoming using the then available molecular and statistical tools. In 2007, and as a direct result of the current funding, we identified the first new genetic association in MS in over 30 years;we demonstrated that a common non-synonymous functional SNP in the IL7RA gene was associated with an increased risk of MS. Since making this discovery, we and others have identified and confirmed associations to several other genes, including IL2RA, CLEC16A, CD58, TYK2, TNFRSF1A, IRF8, CD6, and CD226. However, there are very significant genetic questions that remain unanswered in MS. First, these genes explain only a small fraction of the overall genetic influence on MS. Numerous additional genes of modest yet important effect remain to be found. Second, all this work has assumed the common-disease/common-variant hypothesis, which we contend is only part of the story. Detailed examination for rarer variants of stronger effect in both the nuclear and mitochondrial genomes has yet to be performed and may well explain a measurable proportion of the genetic influence on MS. We are in an excellent position to further examine the genetic role in both severity and type of progression of MS. Our specific aims are to: 1). Confirm additional important genes in the IL7RA pathway;2). Confirm additional important genes identified in the top 5% of SNPs from the original MS GWAS analysis;3). Identify all variants in the confirmed non-MHC genes (currently IL7RA, IL2RA, CLEC16A, CD58, CD226) using high-throughput sequencing techniques. We will take advantage of our unique large multiplex family dataset to sequence MS cases most likely to carry rare variants of strong effect.

DESCRIPTION (provided by applicant): Multiple Sclerosis (MS) is a debilitating neuroimmunological and neurodegenerative disorder affecting over 400,000 individuals in the United States. Myelin loss, gliosis, and varying degrees of axonal pathology culminate in progressive neurological dysfunction including sensory loss, weakness, visual loss, vertigo, incoordination, sphincter disturbances, and altered cognition. The evidence for a genetic influence in MS is overwhelming but the etiology springs not from a single major gene, but from multiple genes acting either independently or interactively. This complexity has made the search for the responsible genetic variations difficult. A candidate gene approach identified allelic association with the HLA-DR2 allele but no other allelic associations have been confirmed. In the current funding cycle we completed a second-generation genomic screen and initial follow-up has identified one strong chromosomal linkage signal congruent with other studies. We also generated exciting data suggesting that the expression of clinical symptoms of MS is influenced by genomic variation(s) in or near APOE on chromosome 19q13. With the explosion of data from the human genome project, new methods of laboratory and statistical genetic analysis, and substantial expansion of our MS dataset, we can now take new approaches toward dissecting the complex genetics of MS. To achieve these goals, we propose five specific aims (1): To examine in detail chromosome 1q42 to identify the underlying MS risk gone; (2): To analyze SNPs in and near APOE for allelic associations to MS disease expression; (3): To test for association between MS and genes involved in oxidative stress; (4): To examine genes identified through expression analysis in MS tissues and acting in critical pathways; and (5): To test for gene-gene interactions. All analyses will take into account the known association with the HLA-DR2 allele seen in both our Caucasian and African-American datasets. We will genotype over 200 multiplex families, 1,500 Caucasian US singleton families, 1,000 Caucasian UK singleton families, 1,000 controls, and 1,000 African-American singleton families.

DESCRIPTION (provided by applicant): Human genetics has emerged over the past 50 years as a dominant force in biology and medicine. This critical position stems not only from its central importance in explaining the most basic biological processes, but also from its growing repertoire of critical technologies and methods that can elucidate molecular, cellular, organismal, and population biology. A remarkable change is now underway with the Human Genome Project revolutionizing the paradigms for using human genetics to understand and treat human disease. We are entering the "Genomic Era" where the information generated from once disparate subfields (e.g. molecular genetics, model organisms, genetic epidemiology) is being integrated and is spawning new understanding of the underlying mechanisms of disease. Indeed, genetic subfield identities are quickly blurring as investigators take advantage of multiple approaches toward human genetic discovery. Thus it is incumbent upon us to train the next generation of human geneticists to take advantage of this developing synergy. This proposed Training Program in Human Genetics requests eight training slots. It builds upon the substantial increase in resources, faculty, facilities, and expertise in human genetics at Vanderbilt. It also builds upon Vanderbilt's existing Interdisciplinary Graduate Program (IGP) and its excellent and large pool of student applicants. Our goal is to train future investigators to characterize genetic variation and understand its phenotypic implications in humans. Vanderbilt has particular strengths statistical and computational genetics, genetic epidemiology, clinical, and molecular genetics, and growing strengths in model organisms of human disease. All students will undergo a rigorous didactic program and intensive research training. We have enhanced this program with regular seminars, journal clubs, the annual genetics symposium, informal "mini-retreats", and an annual retreat. In addition students will gain formal exposure to the clinical application and ethical implications of their work through an applied genetics rotation, as we believe it is critical that students in human genetics understand the implications of their work.

DESCRIPTION (provided by applicant): Human genetic research has made remarkable progress in understanding the underlying genetic architecture of numerous human genetic traits. The underlying genetic lesions for thousands of Mendelian traits have now been identified and hundreds of associations with common polymorphisms have now been described using genome-wide association studies (GWAS). Among these successes are numerous traits of aging, including dementia, Parkinson disease, macular degeneration, and successful aging, to name just a few. However, these studies have just begun the job of describing in detail the genetic architecture of traits of aging, as even for the intensively studied dementias, only a minority of the risk architecture has been described. The goal of this P30 Core application is to support the recruitment and start-up activities of a new tenure track faculty member in the Vanderbilt University School of Medicine. The focus of this individual's research will be the neurogenetics of aging, with a further focus on human genetics. They will have an appointment within the Division of Human Genomics (DHG), Department of Molecular Physiology and Biophysics in the School of Medicine, Vanderbilt University. They will also be appointed as an Investigator within the Center for Human Genetics Research (CHGR), the primary location for their research activities. They will have access to superlative core resources, collaborations and mentoring. Our goal is to identify and recruit an outstanding candidate who will complement the current expertise within the DHG and the CHGR and perform ground-breaking research in the neurogenetics of aging. To achieve this goal, we specifically propose to recruit internationally to identify a large pool of qualified applicants, select the best possible candidate, provide start-up resources and a collaborative atmosphere, and provide exemplary mentoring to guide this individual through their first years as a faculty member.

DESCRIPTION (provided by applicant): Determining the genetic architecture of human traits has been a successful and rapidly advancing aspect of Human Genetics. Our ability to characterize individual genetic variation is rapidly approaching the whole genome sequence level. However, equally important is rapid and detailed characterization of the phenotypic variation in the traits themselves, such that meaningful correlations can be identified between genotype and phenotype. The initial phase of the eMERGE network explored the use of electronic medical records for rapid and large-scale characterization of phenotypes and the ability to use linked DNA repositories to generate and analyze genetic variation. The eMERGE network has already demonstrated the viability and utility of this approach in a number of proof-of-principle studies. It is now important to determine the portability and expandability of these approaches in a second and expanded phase of the network. Vanderbiit provided the underlying support for the initial eMERGE network through a supplement to its current eMERGE grant (VGER). We propose to continue our support for an expanded network through a coordinating center (eMERGE-CC) that will provide a combination of scientific and logistical efforts through four specific aims: 1). Accelerate phenotype algorithm development and sharing across the eMERGE-ll network; 2). Expand methods to integrate high quality genomic information within EMRs across the eMERGE-ll network and analyze the resulting data; 3). Expand and accelerate methods to determine the reidentification risk and levels of privacy afforded by performing research on combined clinical and genetic data from the eMERGE-ll network; and 4). Continue to provide logistical support to the entire eMERGE-ll network. RELEVANCE (See instructions): The goal of the eMERGE project is to develop methods for using data from electronic medical records and data from genetic studies to better understand the genetic underpinnings of clinical disease. A further goal is to integrate this information into clinical care. The role of the Coordinating Center is to support these activities.

DESCRIPTION (provided by applicant): Age-related macular degeneration (AMD) is a significant health problem that affects millions of individuals and is the most common cause of severe vision loss among individuals over age 50 in the U.S. (Rein et al. 2006). The influence of genetic variation on AMD is strong and through the application of recent technological advances the genetic etiology of risk for AMD is being deconstructed. Independent studies, including our own, have identified and confirmed variations in multiple genes that affect risk to AMD, including CFH, HTRA1/ARMS2, C2/CFB, and C3 (DeAngelis et al. 2007; Edwards et al. 2005; Haines et al. 2005; Jakobsdottir et al. 2005; Klein et al. 2005; Maller et al. 2006; Rivera et al. 2005; Schaumberg et al. 2007; Schmidt et al. 2006; Hageman et al. 2005; Yates et al. 2007; Maller et al. 2007). Variation in these genes explain a significant portion of the genetic risk for AMD and ongoing studies are continuing to identify additional such genes. Also important are environmental risk factors such as smoking, hormone therapy and diet that contribute to AMD risk both independently and through their interactions with genes (Schmidt et al. 2006; Schaumberg et al. 2007; Wang et al. 2009). Again, ongoing studies are teasing apart these contributions. However, risk is just one of the many facets of the overall genetic architecture of AMD. Disease progression and treatment response are two critical elements also influenced by genetic variation (Shuler, Jr. et al. 2007; Seddon et al. 2007; Francis et al. 2009). The goal of this proposal is to increase our understanding of the genetic etiology of progression and treatment response in AMD, both of which have been understudied. Identifying the genes underlying clinical outcomes is directly relevant to better directing current treatments and developing new and better treatments and regimens for those suffering this disabling disorder.

Vanderbilt University and Meharry Medical College are uniquely positioned to contribute new knowledge in the field of AIDS research. Vanderbilt has a strong core of basic and clinical scientists working in the HIV field, and has top-notch clinical trials in the areas of therapy and vaccines. Meharry has an independent basic HIV research program and considerable expertise in healthcare research relevant to minority populations. The Vanderbilt-Meharry CFAR Virology Core will provide laboratory capabilities that will greatly enhance AIDS research at both institutions. The overall objective of the Virology Core is to foster new discoveries by providing common resources and infrastructure that will link basic scientists to clinical scientists at both institutions. This objective will be achieved through carrying out four specific aims. Efforts outlined in Aim I will provide centralized facilities and expert staff to assist in laboratory-based experimentation with HIV. A new state-ofthe- art Biosafety Level 3 facility has been constructed and is available to CFAR members, along with expert instruction and training in BSL3 practices. The second specific aim of the Core is to promote and enhance discovery in HIV research at Vanderbilt and Meharry through common access to unique reagents and clinical specimens. A Reagent and Specimen Repository has been created that will enhance the number and quality of HIV reagents available to HIV researchers on both campuses;this repository will be expanded to meet current and future demands during the requested funding period. In Aim III, the Core will provide stateof- the-art virologic and genetic assays relevant to basic and clinical research in HIV biology. Standard virologic assays, such as p24 antigen ELISA, as well innovative new technologies will be offered to the research communities at Vanderbilt and Meharry. Aim IV is focused on HIV imaging. Efforts described in this Aim will link HIV researchers with existing imaging strengths at Vanderbilt. In addition, two state-of-the-art imaging stations have been set up within BSL3 space. Experts in confocal and deconvolution microscopy will assist CFAR researchers in applying the latest imaging modalities to their research questions. The CFAR Virology Core will thus provide significant added value to new researchers entering the HIV field and to established investigators on both campuses. The laboratory services offered through the Virology Core will synergize with the strong clinical research base at both institutions, will integrate seamlessly with the other core services outlined in this CFAR application, and will stimulate important new discoveries in HIV pathogenesis, therapeutics, and prevention.

DESCRIPTION (provided by applicant): Human genetics has emerged over the past 50 years as a dominant force in biology and medicine. This critical position stems not only from its central importance in explaining the most basic biological processes, but also from its growing repertoire of critical technologies and methods that can elucidate molecular, cellular, organismal, and population biology. However, the application of these technologies and methods to different diseases and phenotypes has varied greatly. Despite the medical, social, and cultural importance of eyesight, genetic studies of ocular phenotypes have lagged behind other disease entities. This is due in part to the lack of cross-disciplinary training opportunities. The primary goal of this Training Program in Quantitative Ocular Genomics is to fill this gap by training a new generation of ocular researchers who have specific expertise in genomic analysis. The proposed Training Program in Quantitative Ocular Genomics requests two pre-doctoral and four post-doctoral training slots. It builds upon the substantial increase in resources, faculty, facilities, and expertise in both ophthalmology (through the Vanderbilt Eye Institute) and human genetics (through the Center for Human Genetics Research) at Vanderbilt. For pre-doctoral training it also builds upon Vanderbilt's existing pre-doctoral Interdisciplinary Graduate Program (IGP) and its excellent and large pool of student applicants. Our goal is to train future investigators to characterize genetic variation and understand its phenotypic implications on ocular phenotypes in humans. Vanderbilt has particular strengths in statistical genetics, computational genomics, genetic epidemiology, bioinformatics, and clinical and basic ophthalmological research. All pre-doctoral trainees will undergo a rigorous didactic program and intensive research training. Post-doctoral trainees will be integrated into our extensive and rich research environment. We have enhanced this training program with regular seminars, journal clubs, an informal works-in-progress seminar, and an annual retreat. To ensure a balanced and complete training experience, each trainee will be co-mentored by a preceptor with extensive experience in genomics and another in ocular function. PUBLIC HEALTH RELEVANCE: This training program will provide training into statistical genetics and genome bioinformatics for both pre-doctoral and post-doctoral fellows. They will have an integrated training environment providing specific training in both the clinical and genomic aspects of quantitative ocular phenotypes.

ABSTRACT Age-related macular degeneration (AMD) is the most common cause of severe vision loss among individuals over age 50 in the U.S. with millions of individuals around the world suffering severe vision loss. The influence of genetic variation on AMD is strong and through recent technological advances the genetic etiology of risk for AMD is being deconstructed. Independent studies have identified and confirmed variations in multiple genes that strongly affect risk to AMD, including CFH, HTRA1/ARMS2, C2/CFB, and C3 explaining a significant portion of the genetic risk for AMD. Initial efforts at genome-wide association studies have identified and/or confirmed several additional loci of more modest individual effect (CFI, LIPC, TIMP3), with many more loci providing suggestive associations. However, a substantial portion of the genetic architecture remains unexplained and detailed examination of effects specific to subtypes of AMD have been lacking. To address these deficiencies very large sample sizes of well characterized cases and controls and families are needed. Over the past year we have formed the AMDgene consortium to combine both samples and expertise. The initial goal of the consortium was a meta-analysis of existing GWAS data in a combined dataset of over 9,000 cases and 49,000 controls. Preliminary findings have identified new genome-wide significant loci. We have chosen an approach that maintains the primary data at each site, which promotes continued engagement by all participating sites, is cost and time efficient, and avoids potential consent, ethics, and privacy issues of sharing data collected under a wide variety of informed consent. The primary goal of this proposal is to support the AMDgene consortium effort through the following specific aims (1) Coordinate the activities of the AMDgene Consortium; (2) Add new datasets and augment current datasets; (3) Perform detailed meta-analyses on existing and new datasets:; and (4) Perform detailed secondary analyses on these data.

DESCRIPTION (provided by applicant): Determining the genetic architecture of human traits has been a successful and rapidly advancing aspect of Human Genetics. Our ability to characterize individual genetic variation is rapidly approaching the whole genome sequence level. However, equally important is rapid and detailed characterization of the phenotypic variation in the traits themselves, such that meaningful correlations can be identified between genotype and phenotype. The initial phase of the eMERGE network explored the use of electronic medical records for rapid and large-scale characterization of phenotypes and the ability to use linked DNA repositories to generate and analyze genetic variation. The eMERGE network has already demonstrated the viability and utility of this approach in a number of proof-of-principle studies. It is now important to determine the portability and expandability of these approaches in a second and expanded phase of the network. Vanderbiit provided the underlying support for the initial eMERGE network through a supplement to its current eMERGE grant (VGER). We propose to continue our support for an expanded network through a coordinating center (eMERGE-CC) that will provide a combination of scientific and logistical efforts through four specific aims: 1). Accelerate phenotype algorithm development and sharing across the eMERGE-ll network; 2). Expand methods to integrate high quality genomic information within EMRs across the eMERGE-ll network and analyze the resulting data; 3). Expand and accelerate methods to determine the reidentification risk and levels of privacy afforded by performing research on combined clinical and genetic data from the eMERGE-ll network; and 4). Continue to provide logistical support to the entire eMERGE-ll network. RELEVANCE (See instructions): The goal of the eMERGE project is to develop methods for using data from electronic medical records and data from genetic studies to better understand the genetic underpinnings of clinical disease. A further goal is to integrate this information into clinical care. The role of the Coordinating Center is to support these activities.

DESCRIPTION (provided by applicant): This proposal, entitled the Consortium for Alzheimer's Sequence Analysis (CASA) describes plans to analyze whole exome and whole genome sequence data generated from subjects with Alzheimer's disease (AD) and elderly normal controls. These data will be generated by the National Human Genome Institute Large-Scale Sequence Program. The goal of the planned analyses is to identify genes that have alleles that protect against or increase susceptibility to AD. This is a multiple PI proposal, a collaboration between five senior AD genetics investigators (Farrer, Haines, Mayeux, Pericak-Vance, Schellenberg). CASA has 4 cores and 3 projects. Core A is the Administrative core that will coordinate all aspects of CASA. Core B is the Analysis Statistics and Innovation core that will design and assist analysis by other cores/projects and devise novel methods of statistical analysis. Core C is that Data Management and Information Transfer Core that will implement analyses designed by Core B and the projects. Core C will provide high-performance computing for CASA. These three cores are mandated by FOA PAR-12-183. Core D is the In Silico Functional Genomics Core that will annotate AD-associated variants and perform pathway and interaction analyses. Project 1 will evaluate variants detected in the sequence data for association with AD to identify protective and susceptibility alleles. Project 2 will evaluate sequence data from multiplex AD families to identify variants associated with AD risk and protection, and evaluate variant co-segregation with AD. Project 3 will focus on structural variants (insertion-deletions, copy number variants, and chromosomal rearrangements). The project will use existing methods and develop and implement novel approaches for detecting structural variants. The projects and cores are highly interdependent. For example, structural variants identified by Project 3 will be integrated with single nucleotide AD-associated variants identified by Projects 1 and 2. Likewise variants identified by Project 1 will be tested in the family-based data sets. Core B will assist all projects in designing analyses and Core C will implement Project analyses. Core D will annotate and help interpret results from all projects.

ABSTRACT The most frequent neurodegenerative disease is late-onset Alzheimer's disease (AD). We have recently reported a novel subgroup of patients who have a particularly malignant form of rapidly progressive late-onset Alzheimer's disease (rpAD) with atypical clinical symptoms, a low frequency of the e4 allele of APOE gene, unique structural characteristics of beta amyloid and an amyloid proteome that is distinct from typical slowly progressive Alzheimer's disease (spAD). Based on our preliminary data, we hypothesize that the rapid rates of cognitive decline and variable spectrum of symptoms in rpAD arise from the interplay between differently structured amyloid beta and tau proteins, triggering divergent pathogenetic cascades on a distinct genetic background. Accordingly, this proposal will focus on the integrated investigation of (i) conformational structural characteristics of beta amyloid and tau proteins with novel biophysical tools, (ii) proteomic profiling of amyloid plaques, neurofibrillary tangles, astrocytes and neurons of rpAD versus spAD, and (iii) genetic determinants linked to rpAD. The ultimate goal of these studies is to advance our understanding of the molecular mechanims governing the propagation of toxic beta amyloid and tau protein aggregates in the brain and the impact of their conformations upon the AD phenotype in the context of specific risk genes. This insight is critical for efforts to characterize key factors responsible for the very rapid rate of cognitive decline in this subtype of AD and ultimately to novel therapeutic strategies to slow AD progression.

ABSTRACT: Alzheimer disease (AD) is the most common form of dementia in older individuals. Both genetic and environmental factors contribute to AD risk, yet despite huge research efforts, a significant portion of the genetic etiology of AD remains unexplained. Population-wide studies of unrelated AD cases and controls have identified several common genetic risk factors and through the Alzheimer?s Disease Sequencing Project (ADSP) whole exome (WES) and whole genome sequencing (WGS) data are being analyzed to identify AD risk modulators. However, the primary focus of almost all of these studies has been on identifying variants that increase risk; studies designed to identify variants that may protect from AD are few and usually underpowered. Thus, additional strategies are required to identify functional variants that protect against or delay the development of AD. The Amish provide a powerful and unique opportunity to identify variants protecting against AD whilst controlling for some confounding factors such as level of education, lifestyle and diet. In addition, the large Amish pedigrees offer an enrichment strategy for identifying rare variants since Mendelian transmissions from parents to offspring, coupled to inbreeding loops, maximize the chance that multiple copies of rare variants exist. The primary goal of this project is to identify genetic variations offering protection against AD. The project will achieve this goal by pursuing three specific aims: (1): Generation of a family-based Amish AD Protective Variant dataset. We will collect DNA and phenotype data from Amish families in Ohio and Indiana by examining and following 800 known and newly identified cognitively normal individuals age 80+ and their 1st and 2nd degree relatives. We will perform SNP genotyping on all samples and WGS on a subset of 200 cognitively normal individuals; (2): Identification of AD protective variants. Sibships with multiple individuals who are age 80+ and cognitively normal will be analyzed for genetic linkage, IBD segment sharing, and association. Single-marker analyses will be supplemented by gene-wise analysis and pathway (gene set-based) analysis; (3): Perform functional validation of candidate protective variants. These experiments will include screening for effects on gene expression, impact on A? or tau processing, and effects on cellular function.

Age-related macular degeneration (AMD) is one of the leading causes of blindness in the elderly. It has a significant impact on the independence, quality of life, and healthcare costs for those afflicted and the additional social cost on caregivers and family members is incalculable. There is substantial variability in the AMD phenotype and the primary treatment, to repeatedly inject anti-VEGF antibodies into the eye of those severely affected, is effective in only a subset of individuals. Thus a better understanding of the underlying causes of AMD is needed to help guide development of more universal and effective treatments and potential preventive measures for AMD. AMD is strongly influenced by genomic variation. Through the initial funding period of this proposal, we supported the development of the International AMD Genomics Consortium (IAMDGC), which brought together 26 research groups from around the world. The IAMDGC has increased the known genomic loci from 12 to 52 and successfully performed a new and larger genotyping study focused on rarer variation using a high-density genome-wide SNP chip with exome content. This collaborative effort has also spawned numerous additional interesting avenues of research that we now need to explore in more detail through the renewal of this highly successful project. While the current genotypic dataset of over 50,000 samples has much left to be mined, expansion of the available samples, with a particular focus on families and minority samples, is necessary if we are to achieve our stated goal of completely defining the genetic architecture of AMD. To address these unresolved issues we propose four specific aims: 1) Expand the IAMDGC resource with additional datasets and expansion of current datasets, with a focus on family data and diverse genetic ancestry; 2) Expand the range of clinical diagnostic measures (e.g. fundus photos, OCT measures), biomarker, comorbidity, and covariate data associated with the samples; 3) Use an analytical hub infrastructure to perform detailed analyses of these data; and 4) Support the logistics and administration of the IAMDGC.

The Alzheimer's Disease Sequencing Project (ADSP) is a national sequencing initiative focused on identifying genetic variants that either protect from or increase the risk for late onset Alzheimer Disease (LOAD), with the goal of accelerating development of effective therapeutics. The ADSP Discovery phase includes whole exome sequencing (WES) of 10,571 unrelated non-Hispanic White (NHW) cases (N=5,606) and controls (N=4,965), and whole genome sequencing (WGS) of 578 NHW and Hispanic (HI) familial samples. The Discovery Extension Phase of the project added WGS on 434 new familial samples and 3,343 NHW, AA, and HI cases and controls (collectively the ADSP-DEP). Preliminary analyses of these data confirm known LOAD genes and point toward several new LOAD-related genes and their functional relationships to APP processing, neuroinflammation, endocytosis, and cholesterol metabolism. The current Follow-Up Study phase (ADSP-FUS) will generate >15,000 additional WGS focused on samples that `encompass the richest possible ethnic diversity', which will include primarily HI and African-American (AA) datasets. This combination of diverse datasets derived from case-control, cohort, and family study designs requires an intensive and comprehensive analytical effort to uncover the wealth of information sequestered in the WGS. We (the Collaboration on Alzheimer Disease REsearch [CADRE]) hypothesize that protective and risk genomic variants will provide potential therapeutic targets for Alzheimer disease. Thus, the primary goal of this proposal is to integrate comprehensive genomic analysis of the combined ADSP data (WGS, WES, SNP array) with extant biological data to identify the highest priority variants and loci as candidates for downstream functional analysis. By leveraging the data derived from the AA and HI admixed populations, we use their increased diversity to accelerate and define likely targets. This goal will be met by: 1) Characterizing genomic variation in LOAD using ethnically diverse datasets. We will supplement the ADSP-DEP and ADSP-FUS with additional, separately funded WES and WGS data; 2) enhancing discovery and fine-mapping using admixture analyses in ethnically diverse datasets; and 3) Prioritizing variants and genes by integrating statistical and biological information. For the variants we identify, we will generate additional information from structural and gene expression data and integrate all data into a genomically driven comprehensive biological network that will be used to prioritize loci for functional testing as therapeutic targets.

Project Abstract There are currently no effective treatments for atrophic age-related macular degeneration (AMD), in part because we may be intervening too late in the disease course after geographic atrophy (GA) has developed. A far preferable strategy would be to intervene at an earlier phase of the disease, but there is uncertainty with regards to disease biomarkers to select the most appropriate patients as well as endpoints which could be used to conduct an interventional trial in a clinically-practical time-frame. This is in large part because of the lack of a sufficiently granular staging system describing the progression from early to late stage AMD. The best currently available data comes from studies such as the Age-Related Eye Diseases Study and the Beaver Dam Eye Study, but these studies were largely based on color fundus photographs with AMD disease features assessed using historical protocols developed in the film-based imaging era. The AMD disease severity scales and staging systems built from these studies are insufficiently granular and fail to take advantage of modern, pervasive digital imaging technologies such as optical coherence tomography (OCT) and OCT angiography (OCT-A) which readily lend themselves to quantification. Extensive research over the past decade has identified a number of structural OCT features of AMD, such as intraretinal hyper-reflective foci and subretinal drusenoid deposits, which appear to increase the risk for developing late AMD (atrophy and/or neovascularization). More recently, choriocapillaris (CC) flow deficits have been shown to increase with age and in AMD. The relationship between CC flow deficits and the onset and stage of AMD still remains to be defined. In addition, although a number of genetic risk factors for AMD have been identified, the genetics of AMD progression are not yet elucidated. This research application proposes to address these critical knowledge gaps by evaluating elderly subjects with AMD who have previously been recruited as part of the NEI-funded Amish Eye Study. The Amish represent a homogenous population with regards to environmental and social exposures which reduces variability and makes this group ideally suited for epidemiologic studies of AMD progression. Through that previous study, baseline (and some 2-year follow up) clinical, multimodal imaging (including OCT), and genetic data have already been collected. However, long-term (7 year) data, which will be a focus of our proposed research, is critical to actually establish which individuals go on to progress to late AMD, which is vital in order to determine which baseline features are associated with a higher risk of progression, and to develop a granular and quantitative staging system for AMD. The development of this novel AMD staging system will provide points of intervention and outcome assessment to enable early intervention clinical trials and provide new insights into the genetics and pathophysiology of AMD.

Age-related macular degeneration (AMD) is a leading cause of vision loss in older Americans and severely impacts the independence, quality of life, and healthcare costs for those afflicted and their families. Genetic variation has a major influence on AMD, but only about half of the heritability is currently understood. Understanding the genetic architecture of AMD is critical for developing better treatments for AMD. The International AMD Genomics Consortium (IAMDGC) has assembled 33 research groups and over the past four years of this grant has enabled significant progress by extending the number of known risk loci and implicating new biological pathways. This renewal extends these efforts to multiple genetic ancestries, study designs, and more detailed phenotypic data. We propose the following aims: 1) Continue to expand the IAMDGC resource with new datasets. We have added seven new collaborators and now have access to data from >100,000 participants. 2) Use universal hubs to process and share genomic, phenotypic, and biomarker data. Regeneron Pharmaceuticals has agreed to conduct whole exome sequencing on approximately 40,000 participants at no cost to the grant. By statistical imputation on the remaining GWASed samples, we will create an extremely large dataset. We will continue to house the data in two analytic hubs (US and Europe) to simplify access and provide computational and analytic support. 3) Perform detailed analyses on the extensive resulting dataset. The dataset (87,542 cases/controls and 13,766 related individuals in nearly 6,000 families) enables testing of numerous genetic hypotheses underlying clinical subtypes, biomarkers, effects of rare variants, and variability in the genetic architecture across ancestries. The initial processing and analysis of the combined genomic data will be overseen through this application and results will be available to all members. We have an efficient process allowing members to propose additional studies and the broader research community to access these data and computational and analytical support through the appropriate analytic hub. 4) Support the logistics and administration of the IAMDGC. Successful collaboration requires constant communication and support. We will continue our yearly IAMDGC-specific face-to-face meeting, a second half- day meeting for those attending the ARVO annual meeting, and regular teleconference calls. Our goal is to greatly advance the understanding of AMD pathophysiology (using genomics as our foundational guide) and thus speed the development of better treatments and/or preventions of AMD.