Jose C. Florez, PhD, MD - US grants

DESCRIPTION (provided by applicant): The Principal Investigator in this proposal is an M.D., Ph.D. post-doctoral fellow subspecializing in endocrinology who is interested in becoming an independent translational genomics investigator. He plans to extend the findings of diabetes genetics research into the clinical arena, and thus contribute to understand the heterogeneity of type 2 diabetes (T2DM), the impact of common genetic variation on the development of diabetes and the role of an individual's genetic profile in therapeutic response. In order to do so, he is currently training in Dr. David Altshuler human genetics laboratory at the Massachusetts General Hospital (MGH), which has intellectual and technological ties to the Whitehead Institute/Massachusetts Institute of Technology Center for Genome Research. He is also sponsored by Dr. David Nathan, the head of the MGH Diabetes Center and an international leader in diabetes clinical trials. This proposal aims to study the role of common variation in genes encoding drug targets for T2DM. Type 2 diabetes is a polygenic disease, and recent evidence has implicated single nucleotide polymorphisms (SNPs) in the peroxisome proliferator-activated receptor-gamma (PPARG, a target for thiazolidinediones) and the sulfonylurea receptor complex in the pathogenesis of the disease. A T2DM association of common variants in AMP kinase (a presumed drug target for metformin) has not been reported. During the initial phase of the project, the haplotype structure of the genes for the sulfonylurea receptor, its associated potassium channel and the five known subunits of AMP kinase will be elucidated. Haplotype tag SNPs will be tested for association with T2DM in several family-based and case-control panels totalling 7000 subjects. The role of any associated SNPs and the Pro12Ala variant in PPARG in the development of T2DM and the response to various drugs will be studied in the Diabetes Prevention Program patient sample. In collaboration with Dr. Deirdre Blake, the impact of genetic variation in the above genes on response to short-term therapy will be measured by studying multiple parameters of human beta cell function. Finally, whether variability in long-term response to hypoglycemic therapy can be observed in clinical practice will be determined in a clinical study. This proposal should serve as the foundation for a large pharmacogenomics trial designed to evaluate the feasibility of genetically-tailored therapy in T2DM.

[unreadable] DESCRIPTION (provided by applicant): [unreadable] The E23K polymorphism in KCNJ11 (the gene that encodes the islet ATP-dependent potassium channel Kir6.2, the target for sulfonylurea medications) and common variants in the gene that encodes the transcription factor 7-like 2 (TCF7L2) have been robustly associated with type 2 diabetes. These variants have detectable effects on quantitative glycemic traits. For example, homozygotes for the K allele at KCNJ11 E23K have decreased insulin secretion during the first 30 minutes of an oral glucose tolerance test (OGTT), as measured by the insulin to glucose ratio (IGR). [unreadable] Given these findings, we hypothesize that variants in genes that are reproducibly associated with type 2 diabetes may impact the effect of anti-diabetic medications. In particular, sulfonylureas may have differential effects on individuals depending on the allelic variant they carry at KCNJ11 E23K; conversely, because TCF7L2 is postulated to influence insulin secretion by regulating levels of glucagon-like peptide 1 (GLP-1), and sulfonylureas act at a more distal step in the insulin secretion pathway, the effect of sulfonylureas on insulin secretion should be independent of genetic variation at TCF7L2. Preliminary evidence also suggests a metformin x genotype interaction. [unreadable] We therefore propose to examine 1) the acute response to a sulfonylurea challenge (glipizide 5 mg orally) in 750 subjects at risk of diabetes or with early diabetes (on diet treatment alone), depending on genotype at KCNJ11 E23K and TCF7L2 rs7903146; 2) the acute response to short-term metformin treatment on the insulin sensitivity index in the same group, depending on genotype at KCNJ11 E23K; and 3) acute insulin secretion (by IGR derived from an OGTT) and GLP-1 levels after short-term metformin treatment (500 mg bid x 4 doses) in the same group of subjects, depending on genotype at TCF7L2 rs7903146. [unreadable] In order to maximize statistical power and ensure a timely completion of this project, this proposal intends to perform two simple outpatient measurements in a single major referral center, with the help of a diverse team of established clinical investigators who have an interest and expertise in metabolic traits. If successful, this proposal should help clarify the pathophysiologic mechanisms by which these key genetic variants increase risk of type 2 diabetes, and assess their impact on commonly used antidiabetic treatments. In addition, this pilot study will lay the groundwork for a long-term, outcomes-based pharmacogenetic clinical trial. [unreadable] [unreadable]

DESCRIPTION (provided by applicant): A growing number of common genetic variants have been robustly and reproducibly associated with type 2 diabetes (T2D). Despite these advances, the precise identity of the genes involved in increasing T2D risk has not yet been established. We propose to use pharmacogenetic and metabolomic approaches to inform the searches for causal variants and better define the molecular pathways involved. By challenging human subjects with a sulfonylurea or with glucose in the presence of metformin we hope to 1) distinguish responses depending on genotype at loci associated with T2D or related glycemic traits, or which impact metabolism of either drug;2) confirm and expand an emerging metabolomic signature of insulin resistance by examining the human response to a glucose load with a larger panel of 380 metabolites (including lipid metabolites), 3) distinguish between the insulin and the glucose components of such response by discriminating the metabolomic profile in response to glucose versus the response to an insulin secretagogue;and 4) evaluate to what extent the refined metabolomic signature is correlated with genetic loci that predict insulin resistance. If successful, this proposal should help clarify the mechanisms by which genetic variants increase risk of T2D, and assess their impact on commonly used therapies. Whether the genetic defect is sufficient to prevent the expected action of either drug, or whether it can be overcome pharmacologically, would both be of clinical interest. In addition, this study should lay the groundwork for a longer outcomes-based pharmacogenetic trial. PUBLIC HEALTH RELEVANCE: Recent studies have identified a growing number of common genetic variants that are reproducibly associated with type 2 diabetes. Despite these advances, the precise identity of the genes involved in increasing diabetes risk has not yet been established, because in most cases the association signals detected merely signal genomic regions that are overrepresented in cases versus controls. We propose to use pharmacogenetic (describing the human response to a pharmacologic perturbation based on the genetic background of the individual) and metabolomic (describing the various metabolites that appear in serum in response to a perturbation) approaches to inform the searches for causal variants and better define the molecular pathways involved.

DESCRIPTION (provided by applicant): A growing number of common genetic variants have been robustly and reproducibly associated with type 2 diabetes (T2D). Despite these advances, the precise identity of the genes involved in increasing T2D risk has not yet been established. The newly developed Metabochip supports genotyping of ~200,000 single nucleotide polymorphisms (SNPs) that display robust evidence for association with diseases and traits relevant to metabolic endpoints, as well as detailed fine-mapping of loci already validated at genome-wide statistical significance. We propose to deploy this array in the Diabetes Prevention Program (DPP), a clinical trial whose strengths include the enrollment of high-risk participants from multiple ethnic groups, exquisite longitudinal phenotyping, the presence of behavioral and pharmacologic interventions, and ongoing monitoring with additional accrual of hard endpoints. We will leverage the exquisitely phenotyped DPP samples to 1) test the association of select Metabochip SNPs with baseline T2D-related quantitative traits in 3,548 DPP participants at high risk of diabetes from five ethnic groups; 2) assess the effect of select Metabochip SNPs on the incidence of metabolic outcomes in the DPP, and establish whether a lifestyle intervention modifies this risk; and 3) examine the impact of metformin and troglitazone on relevant SNPs, as a way to place them on metabolic pathways and describe potentially useful pharmacogenetic interactions. If successful, this proposal should help clarify the pathophysiologic mechanisms by which genetic variants increase risk of T2D, assess their impact on interventions to prevent T2D, generate a unique resource, and help lay the groundwork for pharmacogenetic and genetically-guided lifestyle intervention trials. PUBLIC HEALTH RELEVANCE: Recent studies have identified a growing number of common genetic variants that are reproducibly associated with type 2 diabetes and related traits. A newly developed genotyping array (the Metabochip) supports genotyping of ~200,000 single nucleotide polymorphisms that display robust evidence for association with diseases and traits relevant to metabolic endpoints, as well as detailed fine-mapping of validated genetic loci. We propose to deploy this array in the Diabetes Prevention Program (DPP), a clinical trial which enrolled 3,819 high-risk participants from multiple ethnic groups and randomized them to placebo, metformin, troglitazone or a lifestyle intervention to prevent diabetes. In the DPP, we will test the association of select variants with baseline diabetes-related quantitative traits, incidence of metabolic outcomes, response to the lifestyle intervention, and the effects of metformin and troglitazone.

DESCRIPTION (provided by applicant): A growing number of common genetic variants have been robustly and reproducibly associated with type 2 diabetes (T2D). Despite these advances, the precise identity of the genes involved in increasing T2D risk has not yet been established. We propose to use pharmacogenetic and metabolomic approaches to inform the searches for causal variants and better define the molecular pathways involved. By challenging human subjects with a sulfonylurea or with glucose in the presence of metformin we hope to 1) distinguish responses depending on genotype at loci associated with T2D or related glycemic traits, or which impact metabolism of either drug; 2) confirm and expand an emerging metabolomic signature of insulin resistance by examining the human response to a glucose load with a larger panel of 380 metabolites (including lipid metabolites), 3) distinguish between the insulin and the glucose components of such response by discriminating the metabolomic profile in response to glucose versus the response to an insulin secretagogue; and 4) evaluate to what extent the refined metabolomic signature is correlated with genetic loci that predict insulin resistance. If successful, this proposal should help clarify the mechanisms by which genetic variants increase risk of T2D, and assess their impact on commonly used therapies. Whether the genetic defect is sufficient to prevent the expected action of either drug, or whether it can be overcome pharmacologically, would both be of clinical interest. In addition, this study should lay the groundwork for a longer outcomes-based pharmacogenetic trial. PUBLIC HEALTH RELEVANCE: Recent studies have identified a growing number of common genetic variants that are reproducibly associated with type 2 diabetes. Despite these advances, the precise identity of the genes involved in increasing diabetes risk has not yet been established, because in most cases the association signals detected merely signal genomic regions that are overrepresented in cases versus controls. We propose to use pharmacogenetic (describing the human response to a pharmacologic perturbation based on the genetic background of the individual) and metabolomic (describing the various metabolites that appear in serum in response to a perturbation) approaches to inform the searches for causal variants and better define the molecular pathways involved.

DESCRIPTION (provided by applicant): Metformin is the first-line agent in the treatment of type 2 diabetes, yet little is known about the molecular mechanisms of metformin action. The genetic parsing of metformin responders versus non-responders remains similarly underexplored. The Diabetes Prevention Program (DPP) includes 988 participants randomized to metformin. We propose to complete a genome-wide association study (including exome content) for metformin response in the DPP. In parallel, we will explore genetic determinants of metformin response for diabetes prevention and for lowering glycated hemoglobin: the latter will be meta-analyzed with data from 3,500 participants in the GoDARTS cohort. To prioritize human findings we will leverage information from an siRNA genomic screen for metformin response in the roundworm nematode C. elegans, integrating genes and pathways identified in the course of this screen with the human findings. Results that emerge from this integration will undergo further replication in three independent human cohorts. Top signals will be carried forward for functional validation in an established human hepatocyte model, where knockout and point mutation approaches using CRISPR technology will be used to confirm the causal gene and variant. If successful, this project will accomplish the twin goals of elucidating the mechanism of action of metformin and identifying genetic predictors of clinical response, while illustrating the arc of progress from genetic association to identifying the causal gene/variant in order to illuminate function.

? DESCRIPTION (provided by applicant) Metformin, a biguanide, is used as first-line therapy to treat type 2 diabetes (T2D), yet over 35% of patients on metformin monotherapy fail to achieve acceptable glycemic control. In addition, studies indicate that there are profound inter-ethnic differences in the pharmacokinetics and pharmacodynamics of metformin, and that genetic factors contribute to metformin response. To date, there has been only a single published genomewide association study (GWAS) of metformin response in Europeans, and no GWAS in other ethnic The major goal of our study is to identify the genetic loci and pathways that confer nonresponse to metformin in a large multi-ethnic cohort of T2D patients on metformin. Our second goal is to identify rare causal variants that underlie variation in response to metformin through detailed cellular and clinical studies. To this end, we have assembled rich and diverse clinical cohorts including two groups. large multi-ethnic cohorts of patients with T2D on metformin who have provided DNA samples and clinical information (N = 15,000) made available largely through partnerships with the Kaiser Permanente Northern California (KPNC) Research Program on Genes, Environment and Health (RPGEH) and MetGen, an international consortium, which includes multiple cohorts from Europe and the U.S. of patients on metformin (N ~ 10,000). Our overall aims are to: Aim 1. Identify genetic variants that impact response to metformin in 28,000 participants from multiple ethnic groups in the U.S. and Europe; and Aim 2. Identify the causal variants of genes discovered in Aim 1, using a multi-tier approach. In particular, we will first use genomewide approaches with meta analyses to discover variants that underlie variation in response to metformin. Next targeted resequencing will be used to associate rare variants in genes that are identified in our GWAS with metformin response. Functional genomic studies in cells will be performed to identify functional variants, which will then be associated with metformin response in our clinical cohorts. Finally, in Aim 3, we will conduct endophenotypic clinical studies to determine clinical measurements of insulin sensitivity and glucose tolerance to understand the mechanisms through which the variants modulate metformin response. Collectively, this research proposal provides a robust multi-tier approach beginning with the largest cohort of patients with T2D on metformin to identify rare and common genetic variants that underlie variation in response to metformin and importantly, to understand their mechanisms. Data generated in this project will contribute enormously to predictive models that ultimately will be used for data-driven prescribing and precision medicine for anti- diabetic drug therapy.

? DESCRIPTION (provided by applicant) Metformin, a biguanide, is used as first-line therapy to treat type 2 diabetes (T2D), yet over 35% of patients on metformin monotherapy fail to achieve acceptable glycemic control. In addition, studies indicate that there are profound inter-ethnic differences in the pharmacokinetics and pharmacodynamics of metformin, and that genetic factors contribute to metformin response. To date, there has been only a single published genomewide association study (GWAS) of metformin response in Europeans, and no GWAS in other ethnic The major goal of our study is to identify the genetic loci and pathways that confer nonresponse to metformin in a large multi-ethnic cohort of T2D patients on metformin. Our second goal is to identify rare causal variants that underlie variation in response to metformin through detailed cellular and clinical studies. To this end, we have assembled rich and diverse clinical cohorts including two groups. large multi-ethnic cohorts of patients with T2D on metformin who have provided DNA samples and clinical information (N = 15,000) made available largely through partnerships with the Kaiser Permanente Northern California (KPNC) Research Program on Genes, Environment and Health (RPGEH) and MetGen, an international consortium, which includes multiple cohorts from Europe and the U.S. of patients on metformin (N ~ 10,000). Our overall aims are to: Aim 1. Identify genetic variants that impact response to metformin in 28,000 participants from multiple ethnic groups in the U.S. and Europe; and Aim 2. Identify the causal variants of genes discovered in Aim 1, using a multi-tier approach. In particular, we will first use genomewide approaches with meta analyses to discover variants that underlie variation in response to metformin. Next targeted resequencing will be used to associate rare variants in genes that are identified in our GWAS with metformin response. Functional genomic studies in cells will be performed to identify functional variants, which will then be associated with metformin response in our clinical cohorts. Finally, in Aim 3, we will conduct endophenotypic clinical studies to determine clinical measurements of insulin sensitivity and glucose tolerance to understand the mechanisms through which the variants modulate metformin response. Collectively, this research proposal provides a robust multi-tier approach beginning with the largest cohort of patients with T2D on metformin to identify rare and common genetic variants that underlie variation in response to metformin and importantly, to understand their mechanisms. Data generated in this project will contribute enormously to predictive models that ultimately will be used for data-driven prescribing and precision medicine for anti- diabetic drug therapy.

ABSTRACT We are entering a new era in which the explosion of genomic and biological information across multiple developmental and metabolic states is poised to transform the practice of medicine. The clinician's ability to absorb, assimilate and translate this information will determine the extent of its impact on public health. There is an urgent need to train clinical and non-clinical scientists who are competent on big biological data, and who can curate, disseminate and implement the clinically actionable findings that emerge from ongoing efforts. The PI on this application has dedicated himself to advance genomic and metabolomic discoveries in type 2 diabetes, and now seeks to mentor a cadre of highly trained investigators who will be enabled and empowered to lead the application of genomic and systems-wide approaches to the clinical setting. To achieve this goal, he will 1) establish an infrastructure of pertinent genomic and physiologic datasets available for mining, 2) develop a rigorous yet nurturing training pipeline of carefully selected mentees, and 3) guide the investigation of clinically relevant hypotheses that can be tested in the appropriate environment. Dr. Florez is embedded in a successful and productive milieu that embraces a culture of collaboration. As the Chief of the Diabetes Unit and member of the Center for Human Genetic Research at the Massachusetts General Hospital, an Associate Professor at Harvard Medical School, and an Institute Member at the Broad Institute, he is placed in a unique position that will enable him and his trainees to benefit from direct access to an unparalleled suite of training resources and datasets germane to the proposed patient-oriented research in type 2 diabetes and its complications.

ABSTRACT Over the past decade we have witnessed transformative technological and analytical advances which can query biological systems in a global manner, typically across a select axis in the molecular spectrum. The comprehensive study of genes, gene marks, transcripts, proteins, small molecules, and their interactions have generated enormous data sets that reflect a specific metabolic, developmental or tissue state. Increasingly this activity has been feasible in the organism most relevant to disease, the human: when coupled with the rich clinical and phenotyping information available in observational cohorts, clinical trials or the electronic medical record, tremendous inferences can be made to derive pathophysiological insight. This type of activity has produced a trove of information relevant to type 2 diabetes, obesity and related metabolic traits. There is an urgent need to attract investigators experienced in mathematics, statistics, computational biology and bioinformatics to the analysis and interpretations of such data, and to equip investigators who have an interest in these phenotypes with the tools and skills required to extract valuable knowledge. In this proposal, we have assembled a team of three dozen accomplished investigators across the Harvard system who have cutting-edge capabilities in each of the pertinent skill sets, and whose track record supports a declared interest in metabolic disease. This training grant will leverage their complementary expertise by funding eight selected trainees, providing them with dedicated instruction, and pairing them with faculty mentors who can provide rigorous training in a multidisciplinary setting pertinent to diseases of interest to the NIDDK.

PROJECT SUMMARY ? DISCOVERY AND ANALYSIS PROGRAM ABSTRACT Here we describe the Discovery and Analysis Program for the National Center for the Identification and Study of Individuals with Atypical Diabetes Mellitus. The purpose of the project is to bring together internationally recognized diabetes investigators with expertise in the pathophysiology and genetics of diabetes to: A) Foster the study of individuals with rare/atypical forms of diabetes mellitus and B) Identify and analyze rare phenotypes and genotypic variants of diabetes that may ultimately provide insights into more prevalent, heterogeneous forms of type 2 diabetes mellitus (T2DM) in the general population. The central hypothesis of the entire center is that the identification and study of new cases of rare/atypical forms of diabetes will yield greater insights into the etiology and genetic heterogeneity of T2DM. To reach the goals of this project, building on the track records of the participating groups over the last three decades, we will seek to accomplish the following Specific Aims: (1) Identify and enroll individuals/families (children and adults) with rare/atypical forms of diabetes utilizing a unified ascertainment protocol supported by the resources and expertise from participating diabetes centers; (2) Characterize novel diabetes genes/variants in the cohort associated with new rare/atypical forms of diabetes and identify pre-symptomatic at-risk members of the family; and (3) Characterize the cardinal features and phenotypic spectrum associated with the identified novel genes/variants and evaluate age-related disease penetrance. The general approach is to promulgate a strategy for identification of rare/atypical forms, filter out primary autoimmune and known monogenic forms, and further characterize the remainder. Deeper phenotyping and genomic characterization of these individuals and their families in subsequent studies should help to characterize milder or otherwise atypical subtypes present in the spectrum of T2DM in the general population and reveal novel mechanistic pathways involved in the pathogenesis of diabetes. Identification of these novel genes and pathways may ultimately point to novel strategies for the diagnosis, treatment, and prevention of T2DM.

PROJECT SUMMARY ? OVERVIEW ABSTRACT Here we describe our vision for the National Center for the Identification and Study of Individuals with Atypical Diabetes Mellitus in response to RFA-DK-17-006. The Center?s purpose is to convene key diabetes centers with expertise in the clinical assessment, genetics, and physiological study of diabetes as institutional foci of a nation-wide call for subjects with atypical forms of diabetes designed to: a) Foster the study of individuals with rare/atypical forms of diabetes mellitus of unknown cause; b) Identify and analyze phenotypic and genotypic defects that may provide insights into more common, heterogeneous forms of type 2 diabetes mellitus (T2DM) in the general population; and c) Develop a community resource to advance research in this area through a database to facilitate the collection and dissemination of phenotypic and genetic data with biorepository samples and a living biobank for access by the diabetes research community. Our central hypothesis is that the identification and study of new cases of rare/atypical forms of diabetes will yield greater insights into the etiology and genetic heterogeneity of T2DM. The Center, building on the track records of the participating groups over the last three decades, will support primary research endeavors to: i. Build on our existing monogenic diabetes resources, genetics expertise, and deep knowledge of the biology of diabetes to develop and implement processes (based on pedigree analysis and strategic whole exome sequencing) for identifying and studying individuals/families with rare and uncharacterized forms of diabetes; ii. Create a national network of collaborators to help ascertain and initially phenotype the individuals in pedigrees identified; iii. Adapt our existing REDCap-based monogenic diabetes database to create and manage a study database for rare/atypical forms of diabetes, a living biobank and biospecimen repository, and a public portal for use by the diabetes research community in future studies; and iv. Facilitate future investigation of the impact of genetic variation by providing access to biobanked materials and the living biobank. Detailed phenotyping, genotyping, and gene sequencing of these individuals and their families will help to characterize rare atypical subtypes present in the spectrum of T2DM in the general population, and reveal novel mechanistic pathways involved in the pathogenesis of diabetes. Knowledge of the pathways and their constituent molecules should point to novel strategies for the treatment and/or prevention of T2DM.

? DESCRIPTION (provided by applicant): The Boston Area Diabetes Endocrinology Research Center (BADERC) is a dynamic consortium of 63 laboratory-based and clinical investigators whose efforts are directed toward addressing many of the major research questions bearing on the etiology, pathogenesis, treatment and cure of type 1 and type 2 diabetes, and their associated microvascular and atherosclerotic complications. The center Director (Joseph Avruch and Associates Directors (Joel F. Habener, Jose Florez and Brian Seed) are highly productive investigators of international stature in signal transduction, gene expression, human genetics, molecular biology and immunology, topics central to advances in diabetes research. The participating scientists are based at a large number of Boston-area research institutions, including the major Harvard Medical School-affiliated teaching hospitals (the Massachusetts General Hospital, the Brigham and Women's Hospital, the Beth Israel-Deaconess Medical Center) and Harvard-affiliated research institutions (the School of Arts and Sciences, School of Public Health, the Schepens Eye Research Institute, Dana-Farber Cancer Institute), the Boston University Medical Center, the New England Medical Center and the Massachusetts Institute of Technology. These investigators are working at the cutting edge of fields most relevant to defining the pathogenesis and optimal treatment of type 1 and type 2 diabetes: The molecular arid genetic basis of Diabetes, molecular regulation of energy balance and insulin resistance; the biology of the vascular system and pancreatic beta cell; the immunologic basis and optimal therapies for autoimmunity and transplant rejection; the development of new methods for glycemic monitoring and control. The BADERC offers these scientists an array of core support services (Cell Biology/Morphology, Transgenics, Immunology/Flow Cytometry and Metaboljc Physiology, Human Islet preparation and Mouse Enerergetics) that incorporate the latest technical advances in molecular genetics, cell biology, and metabolic physiology provided by acknowledged experts. A program that enables facilitated access for BADERC investigators to several platforms of the Broad institute is ongoing (Genomics, Proteomics, Metabolomics, lentiviral encoded shRNA design and production, Imaging and Chemical screening platforms). Most BADERC cores are heavily oriented towards hands-on training. The BADERC also supports a highly subscribed pilot and feasibility grant program. The easy access to cost effective support services of outstanding quality together with the educational and pilot grants program has promoted many collaborations, and attracted to diabetes research new talent from this outstanding scientific community. Finally, it is a goal of the center to foster the closest interactions between the laboratory based and clinical scientists, so as to ensure the translation of research discoveries into advances in the care of diabetic patients. Total direct costs of the investigator's research base is $93,852,058.

Administrative Core-Summary The Administrative core of the Boston Area Diabetes Endocrinology Research Center (BADERC) is responsible for the proper operation of the center. It is overseen by the Center director J. Avruch, in collaboration with the Associate directors, J. Habener, J. Florez and B. Seed, and the center Research Coordinator J. Prendable. Senior fiscal oversight is provided by J. Maclaughlin. The Administrative core sets the policies of the center, coordinates and supervises the activities of the BADERC technical cores, and awards pilot and feasibility grants. BADERC policies and goals are set by an Executive committee composed of BADERC investigators (Avruch, chair; Seed, Habener, Florez, B. Kahn, N. Ruderman, G. Williams, D. Nathan). Access to institutional resources and facilities is assured by consultation with a Senior Inter-institutional Advisory committee, chaired by Katrina Armstrong, Chair Medicine, MGH and composed of senior Faculty from the major participating institutions (R. Xavier, MGH; M. Zeidel, BIDMC; J. Loscalzo BWH; B. Corkey BMC; H. Orf, MGH ex officio). The Administrative core monitors the operation of the Technical cores, assuring their proper fiscal management, continuous quality assurance and delivery of services most needed and appropriate to the science pursued by BADERC investigators. This function is coordinated by a committee of BADERC core directors (Avruch, Seed, Brown, Faustman, B. Kahn and Lowell) chaired by Dr. Seed. A collaborative program between BADERC investigators and the Broad Institute is overseen by Associate Director J. Florez and is managed through the Administrative core. The pilot and feasibility grant program is overseen by Associate center director Dr. Habener, with the assistance of Associate Director J. Florez and Resaearch Copordinator J. Prendable. After receipt of outside reviews, the center Executive committee makes final recommendations regarding funding. Advice concerning opportunities for collaborations, new technologies and advances in science relevant to diabetes is provided by a committee composed of the regional Senior diabetes investigators . R. Sherwin, G. Weir and M. Czech. Up-to-date information about the science of BADERC investigators and the P&F grant program is available on the BADERC web site www.baderc.org.

Discovery of Pharmacogenomic Biomarkers for OATP1B1 and OATP1B3 In marked contrast to the plethora of genome-wide association studies (GWAS) focused on human disease, there has been a dearth of GWAS focused on pharmacogenomic traits such as variation in drug response and toxicity. Further, many of the pharmacogenomic GWAS have been underpowered and therefore few genetic variants at genomewide levels of significance have been discovered. Among the world's most widely prescribed drugs, sulfonylureas are associated with great inter-individual variation in response, with ~35% of patients with type 2 diabetes failing therapy after 5 years and frequently needing insulin therapy to achieve acceptable glycemic control. In exciting preliminary GWAS focused on response to sulfonylureas, we discovered a strong association between change in glycated hemoglobin levels (HbA1c) on sulfonylureas and a SNP in the SLCO1B1/1B3 locus encoding the transporters OATP1B1 and OATP1B3 at genome-wide levels of significance (p=4.8×10-8, N = 5,479). The major goals of this competing renewal application are to determine the pharmacologic mechanisms by which OATP1B1 and OATP1B3 associate with response to sulfonylureas, discover and validate selective biomarkers for the transporters and discover other genes that associate with response to sulfonylureas. To achieve our goals, we will use two large clinical resources: MetGen PLUS, a large multi-ethnic international consortium, established during this granting period and SUGAR-MGH, a rich deeply phenotyped consortium of healthy volunteers, which can be used to probe clinical pharmacokinetic and pharmacodynamic mechanisms. Three specific aims are proposed. In aim 1, we will employ a genome-wide approach in MetGen PLUS to identify common genetic variants in SLCO1B1/1B3 and other genes that impact response to sulfonylureas. In aim 2, we will identify the causal variants in the SLCO1B1/1B3 locus associated with drug response, using a multi-tiered approach, beginning with targeted resequencing of the SLCO1B3/1B1 locus and extending through detailed functional genomic studies in cells and in samples obtained from healthy volunteers in SUGAR-MGH. Finally, in aim 3, we will discover and validate metabolomic biomarkers of SLCO1B3 that can be used as tools to predict OATP1B3 activity including OATP1B3-mediated drug-drug interactions for a wide range of prescription drugs that are substrates, inhibitors or inducers of the transporter. Our proposed methods range from genomewide association and NextGen sequencing studies and analyses in large cohorts of patients to high throughput functional genomic and metabolomic studies in cellular assays to clinical pharmacokinetic studies in healthy volunteers. We postulate that this comprehensive genomic, metabolomic and functional approach including deep clinical phenotyping will serve as a blueprint for systematic evaluations of other drugs, paving the way for precision therapeutics.

Type 2 diabetes (T2D) is a heterogeneous disorder characterized by resistance of hepatic, skeletal muscle and adipose tissues to insulin and a relative deficiency of insulin secretion by pancreatic ? cells. T2D has a substantial genetic component, and over the past decade human genetic studies have identified over 400 association signals across diverse populations. However, in most cases the specific variants and genes responsible for these association signals are not known. T2D signals include loci for which functions of the protein products encoded by nearby genes are poorly characterized, the closest known gene is distant, or more than one gene appears to be a plausible biological candidate. Identifying the causal variants, the regulatory gene networks affected by the change in DNA sequence, and the mechanisms by which such variation leads to disease are critical steps toward understanding the genetic architecture of T2D, validating potential drug targets, and developing novel therapeutic strategies. Here, we propose large-scale multi-disciplinary functional genomics projects in islet, liver, adipose and muscle cells to determine the contributions and mechanisms underlying T2D risk-associated variants and their downstream effector transcripts. Throughout the project, we leverage our prior and ongoing generation of genomic data sets and genome-wide and targeted screens for function of variants and genes. To complement these efforts, we will first collect genome-wide array and sequencing-based association study results, identify conditionally distinct association signals and construct credible sets of variants. We propose to link variants to effector transcripts through analyses of genome-wide transcriptomic and epigenomic data, perturbation assays that alter thousands of variant-containing regulatory elements and effector transcripts, perturbations of tens of specific variants, and integrative computational analyses. Next, we propose systematic evaluation of hundreds of potential effector transcripts through use of genome-wide and targeted screens of insulin secretion, lipid accumulation, mitochondrial function, glucose uptake, and differentiation state, with assay selection depending on cell type. Based on these results, we propose focused studies on tens to hundreds of potential effector transcripts to evaluate electrophysiology, gluconeogenesis, lipid metabolism and signaling pathways, and we propose thorough investigation the context-specific mechanism of action of individual genes. Finally, we propose to analyze, integrate, and visualize all data by placing effector transcripts into cell-type and environmental context-specific networks, selecting network nodes as candidate biomarkers and modulation points for drugs, and building a framework to understand the tissue-specific contribution of variants and transcripts to individual disease heterogeneity. Successful completion of these aims will translate T2D association signals into biological insights and therapeutic targets.

ABSTRACT We have entered a new era in which the explosion of genomic and biological information across multiple developmental and metabolic states is poised to transform the practice of medicine. The clinician?s ability to absorb, assimilate and translate this information will determine the extent of its impact on public health. There is an urgent need to train clinical and non-clinical scientists who are competent on big biological data, and who can curate, disseminate and implement the clinically actionable findings that emerge from ongoing efforts. The PI on this application has dedicated himself to advance genomic and metabolomic discoveries in type 2 diabetes and related metabolic traits, and during the first funding cycle of this award generated resources and established a training pipeline at the Massachusetts General Hospital (MGH) and Broad Institute. He now seeks to continue attracting and mentoring a cadre of highly trained investigators who will be enabled and empowered to lead the application of genomic and systems-wide approaches to the clinical setting. To achieve this goal, he will 1) expand the infrastructure of pertinent genomic and physiologic datasets available for mining, 2) maintain a rigorous yet nurturing training pipeline of carefully selected mentees, and 3) guide the investigation of clinically relevant hypotheses that can be tested in the ideal environment. Dr. Florez is embedded in a successful and productive milieu that embraces a culture of collaboration. As the Chief of the Endocrine Division and member of the Center for Genomic Medicine at the MGH and an Institute Member at the Broad Institute, he is placed in a unique position that will enable him and his trainees to benefit from direct access to an unparalleled suite of training resources and datasets germane to the proposed patient-oriented research in cardiometabolic disease.