Donald W. Bowden - US grants

We propose to identify the genes for autoimmune disease-specific protein antigens by the use of recombinant DNA techniques. The system which we are using lends itself to high level expression of these antigens as hybrid proteins in E. coli. This approach facilitates production of these antigens for the purpose of antigen characterization, generation of antibodies and development of immunodiagnostic tests. A cDNA library will be constructed from human pancreas tissue. Cloning will be into the lambda gt11 system. Clones carrying islet cell antigen sequences will be identified by differential immuno-screening with sera from Type I diabetes patients and sera from normal individuals. With the lambda gt11 system, clones carrying diabetes associated sequences can be induced to express substantial amounts of the pancreas antigen fused to beta-galactosidase (hybrid protein). Because of their large size, these proteins can subsequently be easily purified. The goal of this work is to clone, express and characterize islet cell antigen genes and to develop a simple test for islet cell antibodies using antigens produced by recombinant DNA methods. The use of recombinant DNA techniques gives this methodology the power to identify specific disease associated epitopes. This will facilitate the development of a definitive test for islet cell antibodies.

We propose to develop a methodology by which the genes coding for autoimmune disease-specific protein antigens can be rapidly cloned using recombinant DNA techniques. The system which we are using lends itself to high level expression of these antigens as hybrid proteins in E. coli. This facilitates production of these antigens for generating antibodies or developing immunodiagnostic tests. In Phase I a cDNA library will be constructed from human thyroid tissue. Cloning will be into the lambda gt11 system. Clones carrying Graves' specific sequences will be identified by differential immuno-screening with sera from Graves' patients and sera from normal individuals. Graves' positive clones can be induced with the lambda gt11 system, leading to expression of substantial amounts of the Graves' antigen fused to beta-galactosidase (hybrid protein). Because of their large size, they can subsequently be purified easily. In Phase II the cloned Graves' antigens will be characterized. They will be tested extensively for the ability to bind specifically with autoantibodies present in the sera from Graves' patients. Cloned antigens determined to be Graves' specific will be used to develop diagnostic tests directed for use in clinical diagnostic laboratories.

The risk of developing insulin dependent diabetes mellitus (IDDM) is intimately associated with an individual's immune system as expressed through the class II HLA genes. It is clear however, that inheritance of HLA genes which confer the highest risk of developing IDDM does not mean that an individual will develop the disease. In addition to environmental factors, several lines of evidence suggest that additional, non-HLA, genetic factor(s) may be necessary to acquire IDDM. We have initiated a search for additional genetic factors by systematically searching for linkage between genetic loci and IDDM families having 2 or more affected children. Results to date suggest that we have identified one, and possibly two, locations for IDDM susceptibility genes. Evaluations of these linkages will be the focus of our continued research. This will consist of collecting and testing additional IDDM families to verify the linkage using a variety of genetic approaches. If the evidence for linkage holds, we will evaluate several candidate genes in the region and, if necessary, carry out an intensive molecular genetic analysis to identify the susceptibility gene. This will consist primarily of saturating the region with highly polymorphic genetic markers which should map the susceptibility locus to a small part of the chromosome: a necessary prelude to identify the gene involved by positional cloning techniques. In addition, we will continue to search for other non-HLA loci on other chromosomes which might lead to IDDM susceptibility. This search will be carried out using our collection of over 350 DNA markers which reveal polymorphic loci. This study will continue the collaboration with Dr. Michael Sheehy (AgriCetus Corp., Madison, WI) and Dr. Glenys Thomson (Dept. of Genetics, University of California, Berkeley). Identification and characterization of nonHLA loci associated with IDDM susceptibility would be a significant step toward providing pre-symptomatic diagnosis and risk assessment.

The genetics of non-insulin dependent diabetes (NIDDM; Type 2 diabetes) will be studied in the Pima Indian Tribe. This collaborative study will include the efforts of molecular geneticists, epidemiologists and clinicians focused on finding the inherited factors which lead to NIDDM. A large number of multiplex families and sib pairs have been identified and collected and some DNA typing and analysis has been carried out already. Initially efforts will be focused on 4 regions of human chromosomes which show some evidence for linkage to NIDDM using sib-pair analysis. In addition, numerous candidate genes will also be surveyed and a systematic survey of the genome will be continued using highly polymorphic microsatellite repeat polymorphisms and restriction fragment length polymorphisms. Data will be analyzed using a number of different linkage analysis approaches including sib-pair analysis, conventional linkage analysis, and also quantitative measures of traits such as obesity, glucose tolerance and insulin resistance. Detection of linkage will be followed by detailed molecular genetic analysis to determine the basis of NIDDM susceptibility. Linkages will also be tested in other populations and ethnic groups.

Non-insulin-dependent diabetes mellitus (NIDDM, Type 2 diabetes, maturity onset diabetes) is one of the most common chronic disorders in our population. Despite considerable study, the etiological origins of the disorder remain obscure. A large body of evidence indicates a prominent genetic component in susceptibility to NiDDM, making it an appropriate subject for genetic analysis. The suitability of such an approach has been demonstrated by the discovery of linkage between polymorphic markers on chromosome 20 and a form of NIDDM called maturity onset diabetes of the young (MODY). The goal of this work is to identify the MODY gene on chromosome 20 using molecular biology and genetic techniques and approaches. This goal is being approached in several ways: (l) Genetic techniques will be used to better define the position of the MODY gene on chromosome 20. This will include evaluating the role of several candidate genes in the region. This genetic analysis will be coupled with (2) physical mapping techniques to map the MODY locus to a smaller physical/genetic region (approximately l cM; approximately l megabase) as a prerequisite for identifying candidate gene sequences and the search for potential mutagenic deletions or rearrangements of the genomic DNA. isolation of additional markers on 20q will be the basis of genetic mapping and will be coupled with a search for yeast artificial chromosomes (YACs) containing-these loci. YAC chromosome walking will be carried out to clone the chromosome 20 genomic fragments containing the MODY gene. Coding sequences in these clones will be identified through a variety of approaches and evaluated for the possibility that they are involved in MODY.

The purpose of this study is to identify genes causing non- insulin- dependent diabetes mellitus (NIDDM)-associated nephropathy (NIDDM-NEPH) in high risk African American families. At most, 30 percent of diabetic patients are susceptible to nephropathy with it's invariable progression to end-stage renal disease (ESRD) and high mortality rate. African American and Native American populations are known to be at higher risk for developing NIDDM and it's associated Nephropathy, relative to whites. However, in all populations, select diabetic families demonstrate multi-generational clustering of renal disease. An inherited basis for NIDDM-NEPH is also supported by reports that racial differences in the prevalence and severity of diabetes mellitus and hypertension, socioeconomic status and access to health care fail to fully account for the excess risk of NIDDM-NEPH observed in African Americans, relative to whites. In order to identify genes causing NIDDM- NEPH we will continue to identify, clinically characterize, and collect DNA from NIDDM affected sibling pairs concordant and discordant for NIDDM-NEPH. This phase of the project employs the unique "Family History of ESRD" database, independently compiled by the federally-funded ESRD Network 6 (Southeastern Kidney Council). This registry currently contains family history data from 7,600 incident patients with ESRD and contains data from more than 13,000 patients as of September, 1996 (60 percent of patients are African American; more than 35 percent have NIDDM-associated Nephropathy). Candidate genes will be screened for linkage to NIDDM-NEPH and a systematic genome wide survey for novel loci causing NIDDM-NEPH will be carried out. This effort will be formally linked to, and interact with, a parallel search for chromosome locations with evidence of linkage to insulin dependent diabetes associated nephropathy (IDDM-NEPH) in Caucasians through an interactive IRPG. The goal of this initial phase of the study is to locate chromosome regions with evidence of linkage to NIDDM-NEPH. The identification of NIDDM- NEPH genes would form a genetic basis for detection of high risk individuals and lead to development of intervention and treatment strategies for prevention of diabetic nephropathy, the most common etiology of ESRD in the U.S.

Insulin resistance is an important risk factor for atherosclerosis. Insulin resistance varies widely within populations, and substantial evidence indicates that much of this variation can be attributed to genetic sources. Visceral adiposity, another important atherosclerosis risk factor, is strongly correlated with insulin resistance, and this trait also appears to be under substantial genetic control. The overall goals of the proposed research project are to: 1) identify the genetic determinants of insulin resistance and visceral adiposity; and 2) determine the extent to which insulin resistance, visceral adiposity, and metabolic cardiovascular disease risk factors share common genetic influences. To address these goals, we will enroll 160 families of African-American and Hispanic background who are participating in the Insulin Resistance Atherosclerosis Study (IRAS). Approximately 1280 additional family members will be recruited. Insulin resistance will be measured using the frequently sampled intravenous glucose tolerance test, and visceral adiposity will be measured using computed tomography. A panel of other metabolic cardiovascular disease risk factors will also be assessed. A panel of 370 microsatellite markers will be genotyped from DNA, and a genome-wide scan will be performed at the Mammalian Genotyping Service to detect chromosomal regions containing loci that influence phenotypic variation. We will then saturate the regions of linkage identified in these analyses with additional markers and will then perform linkage disequilibrium analyses in effort to localize further the putative loci. The organization of this study will be similar to that of IRAS, with three clinical centers, a coordinating center, a central laboratory and a genetics laboratory. This Molecular Genetics component of the study will (1) carry out genomic DNA isolation and quality control, (2) fill significant gaps and correct errors in data from the whole genome screen, and (3) carry out detailed analysis of chromosome regions which show evidence for linkage. This project will contribute substantially to our understanding of the genetic determinants of insulin sensitivity, and consequently to risk of atherosclerosis.

High blood sugar (glucose) levels for a long period of time in people with diabetes can cause significant complications including heart disease, stroke, blindness and kidney disease. It is thought that these complications result from glucose that binds to sensitive tissues and other substances such as proteins in a process called glycation. This study is aimed at understanding inheritance of factors which lead to diabetes and complications of diabetesm specifically cardiovascular disease. Genetic material (DNA) will be extracted from blood cells and used in laboratory analysis of genes which may contribute to diabetes in families in which diabetes is common.

The goal of this study is to map, clone, sequence, and determine the function of genes, which cause type 2 diabetes. Multiple studies now suggest that one or more genes in the region of chromosome 20q12-13.1 contribute to type 2 diabetes susceptibility in Caucasians. In order to determine the number of genes and contribution which they make to type 2 diabetes susceptibility, the mutant forms of these genes will be identified. The putative type 2 susceptibility genes within 20q12-q13.1 will be precisely defined through disequilibrium analysis using high density SNP maps in a variety of study groups including case-control and sibling pairs discordant for type 2 diabetes. An accurate correlation, expressed sequence physical map of chromosome 20q12-q13.1 will provide the framework for focused analysis of specific regions for linkage disequilibrium. Identification of candidate type 2 diabetes loci in the genetically defined region will be carried out by a detailed sequence survey of genes and non-gene sequences with the initial focus on sequences which are under disequilibrium peaks. SSCP and DNA sequence analysis of aberrantly migrating peaks will be used for this purpose. This effort will be complemented by analysis of increasing volume of sequence from the HGP. Polymorphic sequences which are candidate diabetogenic loci will be surveyed for differences in distribution between normal and type 2 diabetes-affected individuals to identify the diabetogenic gene. Based on SNP disequilibrium studies, coding and non-coding polymorphisms strongly associated with diabetes will be functionally evaluated.

DESCRIPTION: The goal of this study is to locate and identify genes contributing to the genetic component of subclinical cardiovascular disease (CVD) in Type 2 diabetes and to evaluate the impact of lifestyle and environment on the expression of these genetic components of subclinical CVD. These goals will be achieved by the concerted efforts of clinicians, epidemiologists, and geneticists. The hypotheses are: 1) The risk of developing Type 2 diabetes-associated cardiovascular disease (CVD) has a significant heritable component that can be measured, and 2) The chromosomal locations of genes contributing to CVD in Type 2 diabetes can be determined and the genes identified using modern molecular genetic approaches. The investigators predict that these genetic factors can be detected in studies of sibling pairs with Type 2 diabetes through genetic epidemiology methods and linkage analysis. Type 2 diabetes-affected sibling pairs, unaffected siblings, and parents, if available, will be recruited and multiple clinical and subclinical measures of subclinical CVD risk will be assessed, including coronary artery calcification (CAC), carotid arterial wall thickness (IMT), ECG variables, and prevalent CVD. Data on the patients is collected in one visit to the General Clinical Research Center (GCRC) which includes an interview and physical examination, a resting 12-lead electrocardiogram (ECG), B-mode ultrasound of the carotid arteries, retrospectively gated helical CT (RGHCT), and a spectrum of clinical laboratory measures. Genetic and epidemiological methods will be used to evaluate the familial aggregation of subclinical CVD taking into consideration the effects of shared environmental exposures (e.g. smoking, diet, alcohol intake and physical activity) and clinical measures (e.g., BMI, blood pressure, lipids, age, sex, etc.). Initial estimates of heritability suggest a significant heritable component to subclinical CVD. Clinical evaluation will be followed by a comprehensive molecular genetic analysis of the sib pairs/families including a genome wide screen, which will be followed by a focused effort to create a high quality dataset by regenotyping or replacing problem markers. Evidence for linkage to QTLs influencing CAC and IMT will be pursued in those chromosomal regions showing suggestive evidence for linkage and then performing further analyses to detect associations with these "saturation" markers.

genetics

DESCRIPTION (provided by applicant): We have carried out a detailed genetic evaluation of the 20q12-q13.1 diabetes susceptibility region of chromosome 20. Results of this study are: 1. evidence for association of one gene, PTPN1, with type 2 diabetes susceptibility and metabolic measures of insulin resistance, and 2. evidence for association with type 2 diabetes of at least 2 other genomic segments in this region. In this renewal application we propose to determine the molecular genetic basis for PTPN1 gene association with T2DM through comprehensive DMA sequencing of the 100 kb PTPN1 haplotype block associated with type 2 diabetes and insulin resistance. This data will supplement SNP data available in existing databases. The resulting comprehensive database of genetic variation in this region, i.e. an "ultra high density" SNP map, will be the basis for identifying new PTPN1 haplotypes and will determine whether association to diabetes phenotypes is due to a single SNP, a small number of SNPs, or an extended haplotype encompassing most or the entire haplotype block. Expanded genetic analyses in multiple additional populations will establish the extent to which PTPN1 contributes to diabetes phenotypes in the general population and explore the effect of phenotypic traits (e.g. BMI) on the genetic association. In addition, several other 20q12-13 regions with evidence of association to T2DM will be subjected to detailed molecular genetic analysis to determine if they are true T2DM susceptibility loci. At least two other haplotype blocks within the 20q12-q13.1 genomic region show evidence of association with type 2 diabetes. Additional genotyping and genetic analysis will be carried out in an effort to confirm that these haplotype blocks contain type 2 diabetes susceptibility genes. These studies will consist of high density SNP genotyping to clearly define the associated haplotype blocks and expansion of the analysis to other populations to try to confirm association to type 2 diabetes and assess association with metabolic phenotypes (e.g. insulin resistance, (3-cell function, etc.). Confirmation of association in multiple populations will justify a more detailed molecular genetic analysis similar to that being proposed for PTPN1.

In this study we will locate and identify genes contributing to glucose homeostasis and adiposity in the IRAS Family Study. The molecular genetics will be carried out by two collaborating laboratories at the Center for Human Genomics at Wake Forest University and the Cedars-Sinai Molecular Genetics Core Facility incorporating the molecular genetic, bioinformatics, and analytical skills of these laboratories to identify genes contributing to glucose homeostasis and adiposity. Initially targeted linkage studies will be carried out for the most likely locations for linkage consisting of fine mapping previously identified linkage locations. Analysis of this data will provide confirmation and some narrowing of linkage peaks and elimination of other locations due to inability to confirm evidence of linkage. Two high quality linkage peaks will be chosen for high intensity analysis. Haplotype maps will be constructed for the chromosomal region with a target SNP density of 1 SNP/10 kb or greater. This construction effort will be based upon genotyping large numbers of SNPs on DNAs from the Hispanic and African American families in the IRASFS and result in a high density SNP map with the SNPs in defined haplotype LD blocks. The SNP map will be used as the framework for intensive SNP genotyping of the IRASFS DNA collection for comprehensive association analysis of regions under the linkage peaks. This association analysis should lead to the identification of specific SNPs and haplotype blocks associated with the appropriate phenotype. The phenotype associated haplotype blocks will be the subject of intensive molecular analysis to identify the alleles contributing to the phenotype. Initially this will take the form of sequencing the block in multiple individual DNAs to comprehensively identify sequence variants in the region, e.g. create an "ultra high density" SNP map of the associated chromosomal region. These new SNPs will be genotyped on the IRASFS DNAs to identify the trait defining alleles.

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. A large proportion of dementia cases in the aged population are not due to Alzheimers disease (AD), but rather to cerebrovascular disease. Dementia due to cerebrovascular disease, broadly described as stroke, is referred to as vascular dementia or vascular cognitive impairment (VCI). Despite the enormous prevalence of VCI, the biological basis of this disease has been much less well studied than AD. A striking feature of VCI is that it is difficult to predict based on medical diagnosis alone. This suggests that unknown genetic factors may play a role in a person's susceptibily to develop VCI. This study is designed to accurately measure cerebrovascular disease through magnetic resonance imaging (MRI) and cognitive ability(through a battery of tests for intellectual functioning) in a population of families highly enriched for the presence of type 2 diabetes, the Diabetes Heart Study (DHS). The DHS has recruited over 1200 subjects from 450 families and has extensive sophisticated measures of atherosclerosis, body composition, bone density, and other clinical measures. In addition, as part of the DHS, a genome-wide scan is being performed which will create a database of inheritance markers for each part of each chromosome in each individual. Family members will be given MRI scans and cognitive tests. Initially we will estimate the extent that genetics contributes to cerebrovascular disease and cognitive impairment (i.e. estimates of heritability) in the DHS families. Second, results from the MRI scans and cognitive tests will be used to map genes that influence these traits.

DESCRIPTION (provided by applicant): We propose the integration of two powerful technologies: molecular genetics and functional analysis, to facilitate identification genes which contribute to important biological problems. The focus of this study is genes that dysregulate glucose homeostasis by impairing insulin sensitivity and beta cell function. This dysregulation results in diabetes and other common disorders. Molecular genetics and functional biology individually have great strengths, but also countervailing limitations. Importantly, these strengths and weaknesses are cross-compensating. We propose to combine the strengths to develop an integrated system for gene discovery. This will be achieved by testing this integration strategy in two different scenarios faced by investigators searching for genes that contribute to human disorders. In Aim 1 there is extensive molecular genetic evidence for genes contributing to acute insulin response and disposition index on chromosome 11q in the IRAS Family Study, but to date we have no complementary functional biology studies. We will use RNAi technology to systematically knock down genes prioritized from prior molecular genetic analysis to identify candidates for involvement in acute insulin response and disposition index. In Aim 2 we will use the knock down technology to assess genes identified by Genome Wide Association analysis in the IRASFS. In this Aim we will knock down H150 genes which have identified in GWAS analysis of acute insulin response, insulin resistance, and disposition index using various knockdown models. Aim 3 will expand the molecular genetic and functional analysis on the subset of genes identified in Aims 1 to 3. This will include intense resequencing of genes and functionally assessing specific alleles, or combinations of alleles. The goals of this study are both the scientific identification of genes important in glucose homeostasis and diabetes and, second, the technical demonstration that integrated molecular genetic and functional analysis can be translated into substantial savings in time, labor, and materials. PUBLIC HEALTH RELEVANCE: We propose to integrate the use of two technologies, molecular genetics and functional analysis, to accelerate the identification of genes contributing to insulin sensitivity and pancreatic beta cell function.

DESCRIPTION (provided by applicant): Diabetes is a risk factor for cerebrovascular disease, cognitive impairment, and related dementia. Data derived from populations suggest that several comorbidities of diabetes increase the risk for cognitive impairment, structural brain changes associated with dementia as measured with magnetic resonance imaging (MRI), and dementia. The relationship between cerebrovascular disease and cognition, especially in diabetes remains understudied and poorly understood. Dementia due to cerebrovascular disease is often referred to as vascular dementia" or vascular cognitive impairment (VCI). Despite the high prevalence of VCI, the biological basis of this disease and its relationship with structural brain changes measured with MRI has been far less studied than Alzheimer's disease. A striking feature of VCI is that risk to date has been difficult to predict based on medical diagnosis alone. We hypothesize genetic factors are significant contributors to cerebrovascular disease and associated cognitive impairment in families enriched for type 2 diabetes. Further, the magnitude of these genetic factors can be measured, their interaction with environmental influences can be quantitated, and the chromosomal location of genes contributing to these traits can be mapped. These hypotheses will be tested in the Diabetes Heart Study (DHS) sample, an extensively characterized collection of families, by recruiting 1200 subjects from 500 families that previously participated in the DHS who will undergo cognitive testing and MRI brain scans. The relationships between MRI measures (white matter lesion score, diffusion anisotropy index, mean white matter perfusion, total brain volume, total white matter volume, total gray matter volume), cognitive ability, and extensive clinical measures available from the DHS will be evaluated to identify correlates of cerebrovascular disease and cognitive ability. The heritable component of cognition and MRI measures will be estimated and a comprehensive genetic analysis will be performed using preexisting genome scan data from the DHS to map regions that contain genes contributing to cognition and cerebrovascular disease. These studies will create unique data collection for genetic and other studies of cerebrovascular disease and cognition. This is a study of the genetics of MRI-derived measures of cerebrovascular disease and cognitive impairment in diabetes families. Successful completion of the study will create a unique database of information and provide insights into the genetic and lifestyle contributors to these disorders.

DESCRIPTION (provided by applicant): The goal of this proposal is to identify genes that contribute to cardiovascular disease (CVD) in people with diabetes. Diabetes is a profound influence on CVD development. The focus of this study is subclinical measures of CVD: vascular calcified plaque and carotid atherosclerosis. In the first phase of the Diabetes Heart Study we successfully recruited and extensively phenotyped 1443 subjects in 564 families with multiple type 2 diabetes (T2DM) affected subjects. This created a unique data resource for the study of CVD and other related traits in a diabetes-enriched (85%) population. Extensive genetic and epidemiological analyses were performed. These results provide a strong foundation for the proposed identification of important genes using a Genome Wide Association Study (GWAS) approach. Specific Aims are: 1). GWAS genotyping and analysis of subjects from the Diabetes Heart Study. The entire European American sample will be genotyped on the Affymetrix SNP Array 6.0 platform. A comprehensive analysis of the genotypic data will be carried out to identify loci/genes associated with the primary measures of subclinical CVD of vascular calcified plaque and carotid wall thickness. 2). Replication and meta analyses of coronary calcified plaque and carotid wall thickness. A meta analysis of European American samples with GWAS data for coronary calcified plaque and, where possible, carotid wall thickness, will be performed in the Framingham Heart Study, Genetic Epidemiology Network of Arteriopathy (GENOA), Amish Family Calcification Study (AFCS), and the Diabetes Heart Study. 3). High scoring polymorphisms from Aims 2 will be evaluated for replication in other study samples to further test for association with: a) prevalent CVD in European Americans, b) subclinical CVD in other ethnicities/races, and c) prevalent CVD in other ethnicities/races. 4). Intensive molecular genetic analysis, novel analytic, and bioinformatic approaches will be used to identify trait influencing variants. The best replicated loci from the Aims 2 &3 will be subjected to additional genotyping (if appropriate) and resequencing to clearly define risk loci. Innovative analysis approaches will be used to define trait associated variants. We have assembled an experienced, highly productive, interdisciplinary team to perform this promising study. PUBLIC HEALTH RELEVANCE: In this research study, genes which contribute to heart disease in people with diabetes will be identified.

DESCRIPTION (provided by applicant): The goal of this study is to identify low frequency and rare coding variants that have significant biomedical impact in Hispanic Americans and African Americans. Family-based linkage analysis has been a powerful tool for identification of genes contributing to monogenic disorders. Until recently family-based approaches have been of limited utility in complex trait genetics. Searches for common genetic variants associated with complex traits have been highly successful in Genome Wide Association Studies (GWAS). It is now widely recognized, however, that common variations frequently explain only a small part of the inter-individual variation in populations. For example, numerous cardiovascular disease (CVD), type 2 diabetes, and body mass genes have been identified, but these genes collectively only explain 10% or less of the heritability. There are several possible sources for the missing heritability. We have developed a powerful and highly efficient family-based method for identification of low frequency (LF) or rare variants which contribute significantly to phenotypic variation of complex traits in the Insulin Resistance Atherosclerosis Family Study (IRASFS). This method has been demonstrated with the identification of an LF (1.1% MAF) coding variant in the ADIPOQ (adiponectin) gene that reduces circulating adiponectin to <20% of normal in Hispanic Americans. This mutations accounts for 17% of the variance in plasma adiponectin in the entire population and accounts for the LOD score of 8.2 in linkage analysis. Based on these efforts, we hypothesize that LF and rare variants contribute substantially to the variance in CVD risk factors. We propose a combination of family-based linkage analyses, whole exome sequencing, and association analysis to identify LF/rare variants of large effect in novel genes that significantly influence a wide range of CVD risk factors. Comprehensive analysis of IRASFS Hispanic and African American families will be used to target chromosomal regions for detailed evaluation of exome sequence data. Families contributing to evidence of linkage at selected chromosomal locations will be assessed for significant coding variations. Importantly this approach enables the rapid interrogation of a wide range of CVD risk phenotypes including novel measures. Variants identified from the family-based approaches will be tested for association in the entire IRASFS sample and replicated in meta analysis of multiple Hispanic (n=6880) and African American (n=15,180) DNA samples to test the primary trait association and assess the influence of high effect variants on subclinical and clinical CVD.

Project Summary Currently there are 153 consensus coronary artery disease (CAD) associated common genetic variants identified through meta-analysis of genome-wide association studies (GWAS).1 For some, the molecular mechanisms explaining their association with CAD are well-defined (e.g. PCSK9, LDL-R). However, for the vast majority, the molecular mechanisms are less well understood or completely unknown. A more comprehensive characterization of the mechanisms for these CAD GWAS variants could lead to new insights concerning the pathogenesis of coronary disease or suggest novel therapeutic or preventive strategies. Recent advances in high-throughput nuclear magnetic resonance (NMR) spectroscopy and mass-spectrometry (MS) make it possible to perform highly accurate, precise, and sensitive metabolomic profiling on thousands of biologic samples 2-6. Unlike conventional targeted metabolomics, un-targeted metabolomics uses a combination of NMR and MS assays to access a broader range of metabolites (both known and unknown) than possible from any single metabolomic assay or target list. The overall goal of this proposal is to use un-targeted metabolomics to characterize the metabolomic signatures associated with each consensus CAD GWAS hit. We aim to generate new knowledge about the mechanisms and biological pathways involved in the pathogenesis of CAD. We propose to use previously obtained GWAS and metabolomic data from subsets of MESA (N=4,000), RHS (N=2,000), Airwave (N=4,000), 1. To perform univariate and multivariate metabolome-wide association analyses with each of the consensus CAD GWAS hits. The metabolomic data will include two NMR assays (NOESY and CPMG) and four MS assays (lipid+/-, HILIC+/-) representing >100,000 distinct metabolomic features. 2. To use statistical, bioinformatic and analytic chemistry methods to identify the specific metabolites represented by the NMR and MS features identified in Specific Aim 1. 3. To use unsupervised and supervised network and systems biology analyses to characterize the groups of metabolites and pathways associated with each GWAS hit. 4. To create a data repository of all the metabolomic data and the generated association and network analyses for the benefit of the wider scientific community. This project will be carried out by a collaborating group of international scientists with expertise in cardiovascular disease, metabolomics, biochemistry, statistical genetics, computational and systems biology, and project management. The resulting data may provide novel insights concerning the metabolic and physiologic mechanisms through which CAD GWAS hits influence cardiovascular risk factors and risk for clinical cardiovascular events.

The NIH APOL1 Long-term Transplantation Outcomes Network (APOLLO) Collaborative U01 will perform a national prospective evaluation of donor and recipient APOL1 renal-risk variants in all US kidney transplants from African American kidney donors to determine their effect on transplant outcomes. In addition, the post- donation health and kidney function of African American living kidney donors will be assessed. We are applying to be the APOLLO Scientific and Data Research Center (SDRC) for this NIH Funding Announcement. Shorter renal allograft survival is observed for transplantations from deceased African American kidney donors, relative to deceased European American kidney donors. Reasons for this are unknown, but retrospective reports suggest that presence of two apolipoprotein L1 gene (APOL1) renal-risk variants in kidney donors may contribute to the disparity. These variants are common in populations with recent African ancestry (such as African Americans), where they are strongly associated with non-diabetic end-stage kidney disease, but rare in other racial/ethnic groups. APOL1 genotype data may provide more accurate assessment of the likelihood for long-term renal allograft function in donor kidneys, thereby improving the matching of donor kidneys with potential recipients in order to optimize renal allograft and patient survival. This information may better inform physicians about organ quality prior to decisions on allocation are made and regarding the safety of living kidney donation. Before this genotypic data can be used clinically, a prospective national study is required to evaluate all kidney transplantation outcomes from African American donors and recipients of their kidneys based on APOL1 genotypes. Information lacking from retrospective studies needs to be collected, including recipient APOL1 genotypes, renal histologic data in failed allografts and presence or development of BK viral infections, donor specific antibodies, and acute rejections after kidney transplantation. We will perform the following activities for the APOLLO Network: overall study coordination, assist with preparation of the final protocol and Manual of Procedures, develop data tracking tools and the study website, collect and archive clinical and outcomes data, perform genotyping, statistical analyses, assessment of the primary outcome ?time to allograft failure in transplanted kidneys from African American donors, based on donor APOL1 genotypes? and create a bio-repository. We will longitudinally assess vital status, kidney function and proteinuria in living African American kidney donors based on APOL1 genotypes. Prospective assessment of the effects of kidney donor APOL1 genotypes on serum creatinine concentration, estimated glomerular filtration rate, and proteinuria in transplant recipients with functioning allografts will also be performed. Results have the potential to transform the organ allocation and informed consent processes in kidney transplantation, optimize renal allograft survival, reduce the discard of good-quality kidneys, and protect the health of living kidney donors.