3311 results for "*geneti*"

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• Breast Cancer Family Registry Early-onset Breast Cancer GWAS

  In order to enhance our understanding of the genetic etiology of breast cancer, this study analyzed 1,265,548 Hapmap3 single-nucleotide polymorphisms (SNP) among a discovery set of 3,523 EOBC incident cases and 2,702 age-matched population control women, all of whom were age 50 or younger at enrollment. Subjects were recruited from the eight sites, some of which oversampled cases with a personal or family history of breast cancer.

  Study phs001589

• National Epidemiologic Survey on Alcohol and Related Conditions-III (NESARC-III)

  The National Epidemiologic Survey on Alcohol and Related Conditions-III (NESARC-III) is a nationally representative cross-sectional survey of the U.S. general population, which was sponsored by the National Institute on Alcohol Abuse and Alcoholism (NIAAA) and conducted in 2012-2013. The NESARC-III's target population was the U.S. noninstitutionalized civilian population, 18 years and older, including residents of selected group quarters (e.g., group homes, workers' dormitories). Multistage probability sampling was used to randomly select respondents. Primary sampling units (PSUs) were individual counties or groups of contiguous counties, secondary sampling units (SSU) comprised groups of Census-defined blocks, and tertiary sampling units were households within SSUs. Finally, eligible adults within sampled households were randomly selected. Hispanics, Blacks, and Asians were oversampled and resulted in a total of 36,309 respondents. All respondents provided informed consent for survey participation. Data were adjusted for oversampling and screener - and person-level nonresponse, then weighted through post-stratification to represent the US civilian population based on the 2012 American Community Survey. These weighting adjustments were found to compensate adequately for nonresponse. Interviewer field methods involved initial structured home study, in-person training, ongoing supervision, and random respondent callbacks to verify data. The NESARC-III collected information on alcohol and drug consumption, alcohol use disorder, other substance use disorders (e.g., nicotine, cannabis and opioid), and associated physical and psychiatric adverse consequences. In addition to a full array of sociodemographic characteristics such as race/ethnicity, gender, age, risk and environmental factors including adverse childhood experiences (e.g., sexual, physical abuse and neglect) and family history for alcohol, drug use disorders and other psychiatric disorders (e.g., mood, anxiety, personality disorders and PTSD) were included (phenotypic variables=4,320). As part of the NESARC-III, 22,848 informative samples were genotyped on Affymetrix Axiom Exome Array consisting of 319,283 SNPs and 103,404 custom-selected SNPs Array (refer to the SNP annotation file). The latter array was selected based on the addiction associated genes, the results of 5 GWAS of alcohol and other psychiatric disorders, and animal models with addiction phenotypes. After filtering out poor quality SNPs using the standard Affymetrix pipeline there are 295,218 SNPs in the NESARC-III genetic data. The 22,848 subjects in this study were all deeply and consistently phenotyped via structured diagnostic interview. Controls group can be selected for specific disorders from a pool of all samples. Here are numbers of cases for major DSM-5 mental disorders in NESARC-III genetic data: Alcohol use disorder (7,075); Nicotine use disorder (6,641); Drug use disorder (2,570); Major depressive disorder (5,214); Persistent depression(1,429); Bipolar I (543); Anxiety disorders (4,226); PTSD (1,674); Personality disorders (4,014); Eating Disorders (457).

  Study phs001590

• Center for Oral Health Research in Appalachia (COHRA) Genomic Studies of Oral Health and Disease

  The purpose of this project is to identify the genetic factors contributing to dental caries in children and adults. The datasets come from the Center for Oral Health Research in Appalachia (COHRA), which has the long-term goal of determining the sources of oral health disparities in a high risk, Northern Appalachian population so that effective preventive interventions can be designed and targeted. The Specific Aims of this project are to perform genome-wide association scans of dental caries of the (1) primary dentition in children, and (2) permanent dentition in adults, to identify novel risk variants and to replicate previously nominated risk variants. This project brings together samples from three cohorts: COHRA1 is a cross-sectional cohort comprising members of 862 northern Appalachian families; approximately 80% of the cohort has been previously genotyped by the Center for Inherited Disease Research with support from NIDCR using the Illumina Quad W array (see dbGaP Study Accession: phs000095.v3.p1). Dental SCORE is a cross-sectional cohort comprising approximately 550 unrelated individuals who underwent the same data collection protocol as COHRA1. COHRA2 is an ongoing longitudinal cohort that recruited approximately 1100 northern Appalachian women during pregnancy, and followed them and their children through their children's early childhood; the current project period will continue data collect though age 6 of the child. Phenotypes for this project were derived from intra-oral examinations performed by trained and calibrated research hygienists. In brief, each tooth was recorded as present or absent, and each surface of each present tooth was scored for evidence of decay. From these data, dental caries indices were generated. This project contains two phases of genotyping: (1) collection of exome SNP Chip data for the previously genotyped COHRA1 samples, and (2) collection of whole-genome SNP Chip data for the remaining COHRA1 samples and all Dental SCORE and COHRA2 samples. These data will support efforts to test hypotheses regarding the causal relationships of risk factors contributing to the unusually high rates of caries formation in the Appalachian population. Ultimately, these data may inform the development of an integrated model of caries risk, in which the effects of genetics, oral ecology, diet, and other environmental/psychosocial factors and behaviors are modeled in concert to explain the disparities, including the high rate of caries onset before age 6. The gene-mapping Aims of this project, which seek to identify the genetic factors that contribute to caries risk, are a requisite step in realizing this integrated model.

  Study phs001591

• NHLBI TOPMed - NHGRI CCDG: The Johns Hopkins University School of Medicine Atrial Fibrillation Genetics Study

  Atrial fibrillation (AF), the most common sustained cardiac arrhythmia, is the primary cause of many hospital admissions, and is associated with significant secondary morbidity by increasing the risk of stroke, heart failure, and all-cause mortality. The incidence of AF is on the rise, and it is projected that by the year 2050 more than 10 million patients will be affected by AF in the United States alone. Anti-arrhythmic medications have limited success in maintaining sinus rhythm, are associated with side effects, and appear ineffective at reducing mortality compared to a strategy of rate control and anticoagulation. Given the significant morbidity associated with this common arrhythmia, surgical and catheter ablation techniques have been developed to treat AF. However, despite the incorporation of various strategies for ablation, long-term recurrence rates of AF remain higher than 25 percent after ablation. Current techniques for catheter ablation of AF include pulmonary vein isolation and complex fractionated atrial electrogram (CFAE) ablation. However, the contribution of each strategy to long-term procedural success and the relative importance of each strategy for different patients remain unknown. Recent advances in cardiac imaging have allowed detailed analysis of left atrial myocardial anatomy. Parallel advances in molecular genetics have identified several candidate genes involved in familial and non-familial AF. However, the pathophysiology of AF generation and maintenance, and the potential contribution of such genetic or anatomic substrates for patient selection, and for target identification during catheter ablation have not yet been examined. Advances in molecular genetics and imaging, coupled with techniques for endocardial and epicardial mapping in the electrophysiology laboratory present an opportunity to significantly improve our understanding of (1) The relation of paroxysmal versus persistent AF with (a) structural left atrial changes (left/right atrial scar, wall thinning, pulmonary vein anomalies, and coronary sinus dilation) and with (b) candidate genetic variants. (2) The relation of candidate genetic variants with (a) structural left atrial changes and with (b) electrophysiologic properties (atrial effective refractory period (AERP) inhomogeneity, voltage abnormalities, trigger burden and location, C FAE extent and location), (3) The relation of structural left atrial changes with (a) CFAE location as targets for catheter ablation and with (b) reversible conduction block/myocardial injury after pulmonary vein isolation, and (4) Individualized endocardial targets for AF ablation based on candidate genes and anatomic substrates. The proposed study will improve our understanding of the underlying pathophysiology of AF, and may improve current techniques for treatment of this important arrhythmia.

  Study phs001598

• NHLBI TOPMed - NHGRI CCDG: Early-onset Atrial Fibrillation in the CATHeterization GENetics (CATHGEN) Cohort

  The CATHeterization GENetics (CATHGEN) biorepository collected biospecimens and clinical data on individuals age ≥18 undergoing cardiac catheterization for concern of ischemic heart disease at a single center (Duke University Medical Center) from 2000-2010; a total of N=9334 individuals were collected. Samples were matched at the individual level to clinical data collected at the time of catheterization and stored in the Duke Databank for Cardiovascular Diseases (DDCD). Clinical data included subject demographics, cardiometabolic risk factors, cardiac history including symptoms, age-of-onset of cardiovascular diseases, coronary anatomy and cardiac function at catheterization, laboratory data, and yearly follow-up for hospitalizations, vital status, medication use and lifestyle factors. AF cases were defined as individuals who had ever had AF based on any ECG available at Duke University or ICD-9 code for AF used for inpatient or outpatient billing.

  Study phs001600

• NHLBI TOPMed: Children's Health Study (CHS) Integrative Genetic Approaches to Gene-Air Pollution Interactions in Asthma (GAP)

  The Integrative Genetic Approaches to Gene-Air Pollution Interactions in Asthma (GAP) study was proposed to use an innovative genetics approach in mice and humans to identify novel variants that interact with traffic-related pollutant exposures to affect lung function phenotypes and the risk of childhood asthma. The study participants were enrolled from the original southern California Children's Health Study (CHS). In the TOPMed project, seven Hispanic White participants who did not have asthma history were included in the WGS analysis.

  Study phs001602

• Comprehensive Epigenetic Landscape of Rheumatoid Arthritis Fibroblast-Like Synoviocytes

  We characterized the epigenetic landscape of rheumatoid arthritis fibroblast-like synoviocytes (FLS) compared with osteoarthritis FLS. Multiple technologies were used, including ChIP-seq to assay H3K27ac, H3K4me1, H3K4me3, H3K36me3, H3K27me3, and H3K9me3, ATAC-seq for chromatin accessibility, the transcriptome by RNA-seq and whole genomic bisulfite sequencing for DNA methylation. Integrative analysis was performed using a novel unbiased method to identify regions of the genome that have similar epigenetic marks. The regions that distinguished RA and osteoarthritis cells were primarily located in active enhancers and promoters. The regions and genes identified included immunological pathways. In addition, some unexpected pathways, most notably "Huntington's Disease Signaling", were discovered. The Huntington's Disease pathway was biologically validated for Huntingtin-interacting protein-1, which regulated invasive behavior of FLS. For a complete description, see R. Ai et al., Comprehensive epigenetic landscape of rheumatoid arthritis fibroblast-like synoviocytes. Nat Commun 9, 1921 (2018). Sequencing data of study participants are available through dbGaP's Authorized Access portal, while analyses of the sequencing data may be obtained through NCBI's GEO portal under GSE112658.

  Study phs001615

• eMERGE Network Phase III Clinical Sequencing: eMERGEseq Panel

  The Electronic Medical Records and Genomics (eMERGE) Network is a National Institutes of Health (NIH)-organized and funded consortium of U.S. medical research institutions. The primary goal of the eMERGE Network is to develop, disseminate, and apply approaches to research that combine biorepositories with electronic medical record (EMR) systems for genomic discovery and genomic medicine implementation research. eMERGE was announced in September 2007 and began its third phase in September 2015. eMERGE III consists of nine study sites, two central sequencing and genotyping facilities, and a coordinating center. eMERGE Phase III aims to: 1) sequence and assess the phenotypic implication of rare variants in a custom designed eMERGEseq panel consisting of 109 genes (including 56 ACMG actionable finding list genes and the top 6 genes from each site relevant to their specific aims), as well as approximately 1400 SNPs; 2) assess the phenotypic implications of these variants by developing, validating and implementing new phenotype algorithms, 3) integrate genetic variants into EMRs to inform clinical care; and 4) create community resources. Included in this study are: ~24,000 eMERGE participants from 10 eMERGE III study sites. Corresponding demographics, body mass index measurements. Top PheWAS codes generated from a collated list of ICD codes from all study sites. Study sites and participants include: Cincinnati Children's Hospital Medical Center (CCHMC): Cincinnati Children's Hospital Medical Center (CCHMC) is a not-for-profit hospital and research center pioneering breakthrough treatments, providing outstanding family-centered patient care and training healthcare professionals for the future, and dedicated to improving health and welfare of children and to the shared purpose of discovery and practical application of new genomic information to the ordinary care of children. We bring a comprehensive electronic health record (EPIC), a deidentified i2b2 data warehouse of 680K patient records, a biobank with >261,000 consents that allow return of results to >84,000 patients and guardians who have provided DNA samples, and hundreds of faculty and senior staff who make genomics or informatics an active focus of their research. CCHMC will help the eMERGE III Steering Committee identify genes for the eMERGE III targeted sequencing panel, provide 3,000 DNA samples from CCHMC patients to be sequenced, review targeted gene panels from clinical care at CCHMC for somatic mosaicism and reinterpretation, and further develop and disseminate a software workflow suite for sequence analysis. We will also extend our work generating phenotype algorithms using heuristic and machine learning methods to many new childhood diseases. We will develop tools to evaluate adolescent return of results preferences, examine the ethical and legal obligations and potential to reanalyze results, and develop clinical decision support for phenotyping, test ordering, and returning sequencing results. Children's Hospital of Philadelphia (CHOP): The Center for Applied Genomics (CAG) is a specialized Center of Emphasis at the Children's Hospital of Philadelphia (CHOP), and one of the world's largest genetics research programs, with to state-of-the-art high-throughput sequencing and genotyping technology. Our primary goal is to translate basic research findings to medical innovations. We aim to develop new and better ways to diagnose and treat children affected by rare and complex medical disorders, including asthma, autism, epilepsy, pediatric cancer, learning disabilities, and a range of rare diseases. Ultimately, our objective is to generate new diagnostic tests and to guide physicians to the most appropriate therapies. Participants were recruited from the CAG biorepository (n>450,000), specifically from >100,000 CHOP pediatric patients and family members, which is enriched for rare-diseases (n>12,000). Center for Applied Genomics, The Children's Hospital of Philadelphia We gratefully thank all the children and their families who enrolled in this study, and all individuals who donated blood samples for research purposes. Genotyping for this project was performed at the Center for Applied Genomics and supported by an Institutional Development Award from The Children's Hospital of Philadelphia. Sequencing was supported by the National Institutes of Health through an award from the National Human Genome Research Institute's Electronic Medical Records and Genomics (eMERGE) program (U01HG008684). Columbia University: The goal of the Columbia eMERGE III project is to develop methods for integrating genomic data in EHRs and to study the impact of such genomic informatics interventions on the health of a diverse, underserved urban adult English- and Spanish-speaking patient population in Northern Manhattan served by Columbia University Medical Center/New York-Presbyterian Hospital system. The study group is 2500 patients recruited from diverse clinics and community outreach centers of self-reported White (~61%), Asian (~11%), African-American (~11%), American Indian/Alaska Native (<1%) racial and Hispanic (~33%) ethnic backgrounds. There are two subgroups in the study cohort - a retrospective group (N=1052) that includes patients from oncology and nephrology clinics, and a prospective one (N=1448) that includes healthy individuals as well as participants with diverse medical conditions. Confirmed pathogenic variants in 70 selected genes will be returned to participants and their healthcare providers through the EHR integration. Participants are able to choose the results they receive and will have the freedom to meet with a genetic counselor and a geneticist to review results. The impact of genetic testing on clinical care is determined by periodic monitoring of EHRs. Geisinger: Samples and phenotype data in this study were provided by the Geisinger MyCode® Community Health Initiative. Participants are recruited across the Geisinger System via online consents or in-person consents at a hospital or clinic visit. Enrollment is ongoing with over 100,000 individuals currently consented. Partners Healthcare (Harvard University): The Partners HealthCare Biobank is a large research program designed to help researchers understand how people's health is affected by their genes, lifestyle, and environment. This large research data and sample repository provides access to high-quality, consented blood samples to help foster research, advance our understanding of the causes of common diseases, and advance the practice of medicine. For the Partners research community (Massachusetts General Hospital and Brigham and Women's Hospital), the Biobank provides: Banked samples (plasma, serum, and DNA) collected from consented patients Blood samples that were discarded after clinical testing in the Crimson Cores maintained in the Brigham and Women's Hospital and Massachusetts General Hospital Pathology Departments Sample handling and preparation services Link to the biobank data to the Partners Research Patient Data Registry (RPDR) a research instance of our electronic clinical chart Data access through our research portal. To date, over 70,000 Partners patients have given their consent to enroll, give a blood sample, receive research results and agreed to be re-contacted for additional research studies. The Biobank has enabled Partners investigators to compete for nationally recognized grants in personalized medicine such as a clinical electronic Medical Records and Genomics network (eMERGE) site and the national All of US program. The Biobank currently supports over 120 Partners investigators and over 130 million dollars in NIH research. Kaiser Permanente Washington/ (KPWA) / University of Washington (UW): KPWA participants were enrolled in the eMERGE Network through the Northwest Institute of Genetic Medicine (NWIGM) biorepository, and provided the appropriate consent to receive clinically relevant genetic results (N=2,500.) NWIGM is based at the University of Washington and co-managed by the University of Washington and KPWA. The purpose of the NWIGM biorepository is to build infrastructure and resources to carry out a broad range of future genetic research. KPWA members enrolled in the biorepository are asked to provide informed consent to providing a DNA sample for storage in the NWIGM biorepository. The consent is purposefully broad to serve the dual purpose of reducing the burden on researchers who wish to use this biorepository and the IRB committees who will be responsible for reviewing these requests in the future. Participants were eligible if aged 50 - 65 years old at the time of their enrollment into the NWIGM repository, living, enrolled in KPWA's integrated group practice, and had completed an online Health Risk Appraisal. The selection algorithm was based on several data sources from the EHR at KPWA. 1) Demographics - participants with self-reported race as Asian ancestry were prioritized and selected to enrich for non-European ancestry. The KPWA eMERGE cohort includes N=1,245 members of Asian ancestry. 2) Participants were also selected for a history of colorectal cancer (N=1,255), in order to allow us to enrich germline pathogenic variants. Mayo Clinic: The Return of Actionable Variants Empirical (RAVE) Study was approved by the Mayo Clinic IRB. We recruited 2537 participants from Mayo Clinic biobanks in Rochester, MN, who had hypercholesterolemia or colon polyps, thereby enriching for Familial hypercholesterolemia (FH) and monogenic causes of colorectal cancer (CRC). Additional eligibility criteria were: 1) residents of Southeast MN who were alive and aged 18-70 years; 2) LDL-C level >155 or >120 mg/dl while on lipid-lowering therapy; 3) no known cause of secondary hyperlipidemia; and 4) no cognitive impairment or dementia that would compromise their ability to give written informed consent. Based on these criteria, we identified 5270 eligible patients and obtained informed consent from 3030 participants. Recruitment was conducted in waves and utilized mailed recruitment packets consisting of a study brochure, a written informed consent form, a baseline psychosocial questionnaire, and a return postage-paid envelope. DNA of 2537 participants was sent for CLIA-certified targeted sequencing of 109 genes including genes associated with FH and CRC. Targeted sequencing and genotyping was performed in a Central Laboratory Improvement Amendment (CLIA)-certified laboratory. Northwestern University: Samples and data used in this study were obtained from patients from Northwestern Medicine, an integrated healthcare system, formed through a partnership of Northwestern Memorial HealthCare and Northwestern University Feinberg School of Medicine. Participants include a retrospective cohort from the Northwestern Pharmacogenomics Study, funded through the eMERGE II project, NHGRI (3U01HG006388-02S1) and a prospective cohort from the Genetic Testing and Your Health Study, funded through the eMERGE III project, NHGRI (U01HG008673). Patients were eligible to participate if they were18 years or older and see a physician at Northwestern Medicine. Patients consented to genetic testing and to allow their results to be placed in their electronic medical record. Vanderbilt University Medical Center: Vanderbilt University Medical Center (VUMC) participants were enrolled in the eMERGE Network through the Vanderbilt Genome-Electronic Records (VGER) project. Patients were provided the appropriate consent to receive clinically relevant genetic results (N=2,700). Participants were eligible if aged 21 or over, had a healthcare provider at VUMC, and visited the provider at least 3 times in the past 3 years. Meharry Medical College: Inclusion of ethnic groups in genomic research is critical to identify possible reasons for health disparities. African-Americans are being enrolled in various outpatient clinics of Nashville General Hospital at Meharry, an inner city hospital primary serving a poorer patient group. A total of 500 African Americans with four cancer types demonstrating health disparities in this population - prostate, colon, breast, lung are identified and approached by clinical research coordinators. The purpose of the study is to determine if any genetic information can be identified from these patients who have or are at high risk of one of these disparate cancers. All participants provide written informed consent and HIPAA authorization to provide blood samples for broad research use and permission to access data in their hospital electronic medical record for research now and in the future. An extensive demographic profile is obtained and entered into a REDCap database. Blood samples are obtained for a panel of alleles from extracted DNA at Baylor. In addition, de-identified coded samples are processed and stored in a central biorepository for further DNA, RNA and proteomic analyses. The survey and phlebotomy are performed at the time of the initial contact and agreement to participate. Nearly all patients approached willingly agree to participate for potential benefit to themselves, family members, or humankind. Little concern is voiced of providing samples for genetic analysis. Study investigators will share results with the participants and providers if testing does not indicate high risk. Results indicating increased risk or actionable alleles for the patient and/or family will be returned by a genetic counselor. Monitoring of the patients' health in this cohort will continue to be followed in the EMR to identify any future associations that might explain health disparities in African Americans. Proposals will be reviewed from investigators to study the genetic or proteomic samples as well as the clinical and demographic information in the repository. Please note that this version of the dataset has a handful of mismatches between genotyped and provided sex. Data with the following IDs should be removed prior to analysis: 420252874213744142412243424569384245694642672223

  Study phs001616

• Genetic Causes of Growth Disorders

  Description of the disorder: A very common disorder presenting to pediatricians/pediatric endocrinologists is childhood growth failure. Sometimes the cause is evident, for example, growth hormone deficiency. In other children, the etiology remains unknown despite extensive evaluation, resulting in the unhelpful diagnosis of severe idiopathic short stature (SISS). These conditions are quite heterogeneous, including children with isolated growth failure and others who also have other abnormalities such as developmental delay or a constellation of congenital anomalies (syndromic short stature). Sometimes, the disorder appears to primarily affect the growth plate, which drives skeletal growth and thereby determines overall body proportions, whereas in other children, the disorder affects skeletal and non-skeletal tissues equally. Some cases of SISS have a polygenic inheritance while others appear to follow a Mendelian inheritance model, recessive, dominant or X-linked. Very recently, genome-wide analysis for copy number variants (CNVs) and whole-exome sequencing have begun to identify some of the molecular etiologies of these disorders.1 Identifying the molecular etiology of growth disorders has clinical and scientific value. Clinically, identifying a molecular cause prevents extensive further testing and may direct anticipatory care for associated medical problems. For example, we recently studied aggrecan (ACAN) gene mutations in families with autosomal dominant short stature and accelerated skeletal maturation. These mutations affect both growth plate cartilage, causing linear growth failure, and also articular cartilage, causing osteochondritis dissecans and early-onset osteoarthritis.1 Etiological classification of idiopathic growth failure allows more precise characterization of prognosis and response to treatment, which are currently highly imprecise because of the locus heterogeneity. In some cases, finding the genetic etiology points to a novel treatment approach that targets the specific molecular pathway involved. The proposed project is central to the main focus of our group, the Section on Growth and Development, NICHD. Our primary goal is to investigate cellular and molecular mechanisms governing childhood growth and to gain insight into the many human genetic disorders causing childhood growth failure. The proposed project is well suited for the intramural program because it takes advantage of Clinical Center expertise to phenotype subjects with SISS. Study subjects: We will study subjects with SISS and nuclear family members. SISS will be defined by height SDS < -2.5 for age without evident cause after routine evaluation including: growth hormone axis evaluation; thyroid function testing; celiac disease screening; urinalysis; CBC; chemistry; karyotype (girls, for Turner syndrome); and testing for single gene defects based on the clinical evaluation (for example, SHOX or Noonan-associated genes). Candidate families will include isolated growth disorders and growth disorders that are accompanied by congenital anomalies, developmental delay, or other syndromic short stature. Strong preference will be given to subjects with a severe phenotype and a pedigree that indicates a Mendelian inheritance. Multiple independent families with the same phenotype will have priority. The pool of applicants for recruitment is large, and we receive many inquiries by emails and phone consultations from pediatric endocrinologists for advice regarding diagnosis and management of unusual growth disorders, including familial disease. Often these families are seeking further evaluation and are willing to participate in a research study. From this pool, we will be selecting pedigrees with very favorable Mendelian characteristics, for example de novo dominant occurrences where two normal parents have a child with SISS, and the child grows up to be an adult who passes this phenotype on to multiple grandchildren in the next generation. Subjects and family members will be brought to the NIH Clinical Center (NIHCC) for outpatient evaluation. Participants will be evaluated by pediatric endocrinology fellows (as part of our training program) and by senior staff to establish the clinical findings and construct a pedigree. Subjects will receive additional biochemical and imaging studies at the Clinical Center to complete the phenotyping and assign affected status. The growth abnormality will be evaluated by assessing body proportions, relative organ size, and skeletal imaging as indicated. Associated clinical abnormalities beyond altered growth will be characterized with the help of other Clinical Center subspecialists. Subjects and family members will be evaluated by SNP microarray and whole-exome sequencing. We anticipate 4-5 persons for each of 16-20 families, for a total of 72-90 whole-exome sequences. Half of the families will be recruited and studied within the first year and half in the second year. We will use freshly collected peripheral blood as the DNA source for SNP array and NextGen Sequencing. Analytic approach: The candidate genes will be chosen based on 1) inheritance state consistency, 2) population frequency in the ESP and UDP databases, and 3) predictions of deleteriousness. We will use VarSifter and the B road Institute Integrated Genome Viewer to filter and visualize these data. The genetic model will be dependent on the family's pedigree. For a simple trio, we will explore variants using genetic models including autosomal recessive, de novo (dominant), compound heterozygous, deletion/point mutation recessive, and X-linked (male only). The candidate variants will be identified using Boolean logic sets in VarSifter following intramural NHGRI/UDP methods. We will also use SNP microarray data to identify copy number variations, complete/single copy deletions, duplications, non-paternity, consanguinity for homozygosity mapping, uniparental isodisomy, mosaicism, and segregation patterns (bed file generation for use in VarSifter filter work). After a list of candidate sequence variants has been generated, annotation will include using the Exome Variant Server, Polyphen-2, MutationTaster, Sift, and CADD predictions of deleteriousness. Biological laboratory data will be included to prioritize candidate variants. Our group has expertise in the molecular mechanisms regulating both skeletal growth2,3 and growth of other tissues4,5, which may be helpful in this phase of the analysis. The most promising candidate mutations will be confirmed by Sanger sequencing and studied functionally, in vitro and/or in vivo. For mutations that affect skeletal growth, we will use experimental systems related to growth plate cartilage. For in vitro studies, we have experience transfecting chondrocyte cell lines, such as ATDC5, and primary chondrocytes. We will determine whether the mutation alters protein and/or cell function. In vivo studies can be used to explore pathophysiology. We have recently successfully used a new approach, the CAS9/CRISPR system to knockout multiple loci in mice (unpublished), which can be used again in the future to create mouse models efficiently. 1J Clin Endocrinol Metab, 2014 (PMID: 24762113) 2J Mol Endocrinol, 2014 (PMID: 24740736) 3Hum Mol Genet, 2012 (PMID: 22914739) 4Proc Natl Acad Sci U S A, 2013 (PMID: 23530192) 5Endocr Rev, 2011 (PMID: 21441345)

  Study phs001617

• NHLBI TOPMed: Outcome Modifying Genes in Sickle Cell Disease (OMG)

  Sickle cell disease (SCD) is caused by homozygosity for a single mutation of the beta hemoglobin gene. Despite the constancy of this genetic abnormality, the clinical course of patients with SCD is remarkably variable. SCD can affect the function and cause the failure of multiple organ systems through the pathophysiologic processes of vaso-occlusion and hemolysis. These pathophysiological processes are complex and expected to impact multiple organ systems in a variety of ways. This study, therefore, was designed to identify genetic factors that predispose SCD patients to develop specific end-organ complications and to experience more or less severe clinical courses. We enrolled > 700 patients with Hb SS, Hb S-beta0 thalassemia and HbSC being followed primarily at three southeastern U.S. regional institutions (Duke University Medical Center, University of North Carolina Medical Center, and Emory University Medical Center). Medical information obtained included the presence or absence of specific targeted outcomes (overall disease severity as well as specific types of end organ damage). Clinical data include medical status (history, physical, examination, and laboratory results) and information regarding potentially confounding environmental factors. Limited plasma samples are available for correlative studies (e.g. of cytokine levels, coagulation activation). Targeted SNP for candidate gene analysis as well as GWAS has been performed on most samples. Whole genome sequencing has been conducted through the TOPMed Consortium. The subjects in this analysis were collected as part of a larger study, "Outcome Modifying Genes in Sickle Cell Disease" (OMG-SCD) aimed at identifying genetic modifiers for sickle cell disease. More information about the study can be found in Elmariah et al. (2014), PMID: 24478166. Clinical and genetic data have been used to identify genetic characteristics predisposing patients with SCD to a more or less severe overall clinical course as well as to individual organ-specific complications. It is anticipated that identification of such genetic factors will reveal new therapeutic targets individualized to specific complications of SCD, leading to improved outcomes and increased life expectancy for patients with SCD.

  Study phs001608

• Genetic contributions of lupus nephritis in a multi-ethnic cohort of systemic lupus erythematosus (SLE)

  Lupus nephritis (LN) is a severe manifestation of systemic lupus erythematosus (SLE) and it occurs at a much higher rate in patients that are not of European descent. The purpose of this study is to identify genetic variants contributing to the risk of LN in a multi-ethnic cohort of SLE patients. We used a comprehensive genome-wide screen and 1244 SLE patients from 5 different ethnic groups. In genome-wide gene-based and candidate SNP analyses, we found distinct genes and pathways, and established risk SNPs associated with lupus nephritis for each ethnic group. This study represents progress in elucidating the genetic underpinnings driving LN among SLE patients of different ethnic groups.

  Study phs001609

• Genetic analysis of patients with Inherited Retinal Dystrophies (IRDs) using next generation sequencing to identify the causative variants

  Genetic analysis of patients with Inherited Retinal Dystrophies (IRDs) was carried out by performing Whole Genome Sequencing (WGS). The main purpose of this study is to identify simple and complex mutations responsible for IRD in patients. WGS was performed on selected affected and unaffected individuals using the Illumina HiSeqX10. The reads were aligned to human genome 19 (hg19) and variant calling was performed using Genome Analysis Toolkit (GATK). The genotyping quality of single nucleotide variants (SNVs) and indels was assessed using the variant quality score recalibration approach implemented in GATK. Copy number variations (CNVs) were called using Genome STRiP and SpeedSeq. This large set of whole genome sequencing data from different ethnicity can be stored and shared through dbGaP. This data could serve as a source for checking frequencies of variants or the pathogenicity of selected variants in different ethnicities.

  Study phs001619

• Genetic Testing to Understand and Address Renal Disease Disparities

  People of African ancestry (Blacks) have increased risk of kidney failure due to numerous socioeconomic, environmental, and clinical factors. Two variants in the APOL1 gene (GeneID: 8542) are now thought to account for much of the racial disparity associated with hypertensive kidney failure in Blacks. One in 7 AAs carry this risk allele, but it is nearly absent in other populations; the variants protect against infection with African trypanosomiasis which is endemic to Africa. However, this knowledge has not been translated into clinical care to help improve patient outcomes and address disparities. It is unknown whether patient or clinician knowledge of genetic risk impacts patient care (i.e., renal surveillance, BP medication use/intensification) or outcomes such as BP control and CKD. GUARDD is a randomized trial to evaluate the effects and challenges of incorporating genetic risk information into primary care. Hypertensive, nondiabetic, adults with self-reported African ancestry, without kidney dysfunction, are recruited from diverse clinical settings and randomized to undergo APOL1 genetic testing at baseline (intervention) or at one year (waitlist control). Prior to enrolling their patients, providers are educated about genomics and APOL1. Guided by a genetic counselor, trained staff return APOL1 results to patients and provide low-literacy educational materials. Real-time clinical decision support tools alert clinicians of their patients' APOL1 results and associated risk status at the point of care. Our academic - community clinical partnership designed a study to generate information about the impact of genetic risk information on our primary outcome - patient care (renal surveillance by clinicians, of serum creatinine and/or urine albumin tests. with a sub-aim of reduction of systolic blood pressure). Secondary outcomes include impact on primary outcomes at 12 months, psycho-behavioral differences of patients between groups and over time, clinician knowledge, attitudes and beliefs at baseline and 12 months, and differences in outcomes between those tested and not tested. GUARDD will help establish the effective implementation of APOL1 risk informed management of hypertensive patients at high risk of CKD, and will provide a robust framework for future endeavors to implement genomic medicine in diverse clinical practices. It will also add to the important dialog about factors that contribute to and may help eliminate racial disparities in kidney disease.

  Study phs001620

• Genetic Susceptibility and Biomarkers of Platinum-Related Toxicities

  The Platinum Study is an R01-funded, multicenter study of testicular cancer survivors that characterizes both long-term cisplatin-induced peripheral neuropathy (CisIPN) and cisplatin-associated ototoxicity, i.e., permanent, bilateral hearing loss. We collected data abstracted from medical records (e.g., cumulative cisplatin dose), conducted audiometric examinations, and administered self-report questionnaires, which included CisIPN symptoms.

  Study phs001621

• Clinical Resistance to Crenolanib in Acute Myeloid Leukemia Due to Diverse Molecular Mechanisms

  FLT3 mutations are commonly detected in Acute Myeloid Leukemia (AML) patients and are associated with poor prognosis. Crenolanib, a potent type I pan-FLT3 (GeneID:2322) inhibitor, is effective against both internal tandem duplications (ITD) and resistance-conferring tyrosine kinase domain (TKD) mutations. While crenolanib monotherapy has demonstrated significant clinical benefit in heavily pretreated relapsed/refractory AML patients, responses are transient and relapse eventually occurs. To investigate the mechanisms of crenolanib resistance, we performed whole exome sequencing of AML patient samples before and after crenolanib treatment (122 samples from 59 patients). Unlike other FLT3 inhibitors, crenolanib did not induce FLT3 activation loop mutations, and mutations of the FLT3 "gatekeeper" residue were infrequent. Instead, mutations of NRAS (GeneID:4893) and IDH2 (GeneID:3418) arose, mostly as FLT3-independent subclones, while TET2 (GeneID:54790) and IDH1 (GeneID:3417) predominantly co-occurred with the FLT3-mutant clone and were enriched in crenolanib poor-responders. The remaining patients exhibited post-crenolanib expansion of mutations associated with epigenetic regulators, transcription factors, and cohesion factors, suggesting diverse non-FLT3 genetic/epigenetic mechanisms of crenolanib resistance. Drug combinations in experimental models restored crenolanib sensitivity.

  Study phs001628

• The Immunogenetics of Measles Immunity - Measles (MMR) vaccination (NIAID/NIH)

  To examine the role of gene polymorphisms (including functional studies of SNPs) on variations in vaccine-induced immune responses, in approximately 3,000 healthy school-age children, adolescents and young adults/adults, who were vaccinated with measles-containing vaccine (MMR). To achieve greatest power to detect SNPs associated with measles-specific immune response phenotypes, we pooled our data across three genotyping platforms and three cohorts (US cohort, San Diego cohort and Rochester cohort).

  Study phs001630

• Genetics of Mood Disorders: Aging and Emotion Regulation Brain Circuitry in Bipolar

  This single-site study is designed to investigate age-related changes in structure and function of a ventral prefrontal cortex (VPFC) neural system, that subserves emotion processing and regulation, during mid to later adulthood in individuals with bipolar disorder (BD), compared to healthy controls (HC). It is a 5-year study of age-related changes in mood, emotion regulation and related symptoms and behaviors using multimodality imaging measures [structural magnetic resonance imaging (MRI) of gray matter, diffusion tensor imaging (DTI) of white matter, and functional MRI measures of functional connectivity and of brain responses during implicit and explicit emotion regulation] comparing BD and HC groups ages 40-79 years, 50% female; a subgroup will be reassessed and rescanned after 2 years to study brain and associated behavioral changes over time. We will explore relationships between brain aging with risk factors implicated in progression. This will include genes, as well as adverse outcomes of progression such as suicide ideation and behavior. As there has been little study of effects of aging of the VPFC emotional circuitry in healthy individuals, findings could provide new insights into brain circuitry and emotional regulation in older adults. In addition to the importance of contributing to understanding BD, as BD is unique in having both elevated and depressive episodes, its study can provide a model for understanding progressive emotion dysregulation to both intervention and prevention that can be better targeted specifically for older individuals with BD. A de-identified blood sample will be sent to the Repository and Genomics Resource.

  Study phs001631

• Prospective Analysis of Genotypes in Adults Undergoing Therapy for Lung Cancer (Paclitaxel Cohort)

  Lung cancer is frequently treated with paclitaxel in combination with several other agents; however, paclitaxel treatment is often ineffective or limited by treatment-related toxicities. Heritable variants in genes associated with absorption, distribution, metabolism, and elimination may predict paclitaxel clinical outcome and toxicity. We designed a prospective multi-institutional study that recruited 546 patients receiving therapy with a 5-year follow up. All patients were genotyped using the Drug Metabolizing Enzymes and Transporters (DMET) platform, which ascertains 1931 genotypes in 235 genes. Genotypes were compared to the progression-free survival of paclitaxel therapy and clinically-significant paclitaxel toxicities. Seven genetic variants were associated with paclitaxel PFS (in ABCB11, ABCC3, ABCG1, CYP8B1, NR3C1, FMO6P, and GSTM3), whereas four genetic variants (in VKORC1, SLC22A14, GSTA2, and DCK) were associated with paclitaxel toxicities. The present SNPs have limited clinical utility but suggest that certain genes are related to important paclitaxel pathways in lung cancer.

  Study phs001660

• Center for Craniofacial and Dental Genetics: Exome Sequencing of Orofacial Cleft Families

  Orofacial Clefts (OFCs) are genetically complex structural birth defects caused by genetic factors, environmental exposures, and their interactions. OFCs are the most common craniofacial anomalies in humans. Affect about 1 in 800 newborns, OFCs are also one of the most common structural birth defects worldwide. OFCs can impose a substantial personal cost resulting from the associated emotional and financial burden. On average a child undergoes 6 surgeries, spends 30 days in hospital, receives 5 years of orthodontic treatment, and participates in ongoing speech therapy, leading to an estimated total lifetime treatment cost of about $200,000. Individuals born with an OFC have higher infant mortality (especially in developing countries with limited access to care), higher mortality rates at all other stages of life, increased incidence of mental health problems, and higher risk for other disorders (notably including breast, brain, and colon cancers). Prior genetic studies have focused on the contribution of common genetic variants through genome-wide linkage and association studies. These studies have revealed a significant etiologic heterogeneity. One promising approach to dissect the etiology of OFCs into focus on subclinical phenotypic features present in the non-cleft family members of affected individuals. These subclinical features are subtle phenotypic features that may represent mild manifestations of the same risk genes; thus, their inclusion in family-based studies may clarify the inheritance patterns in OFC families. In this project, we conducted whole exome sequencing in multiplex families with both overt OFCs and subclinical phenotypes to identify high-impact genes causing OFCs.

  Study phs001675

• African American Multiple Myeloma GWAS

  The case set is from a case-control study designed to identify common genetic risk factors for multiple myeloma in African Americans, the population with the highest risk for this cancer. We conducted two GWAS and combined each of these with convenience controls consisting of unaffected African American participants in cohorts with existing GWAS data. We then conducted a meta-analysis of the two sets. Cases were persons of African ancestry with smoldering or active multiple myeloma identified at participating oncology clinics or through SEER registries, as part of the African American Multiple Myeloma Study (AAMMS) diagnosed from Jan 1, 1988 through July 31, 2016. The majority of the samples were collected from incident and prevalent cases diagnosed since Jan 1, 2008 (80.9%), with a minority obtained from biobanks from cases diagnosed prior to 2008 (19.1%). Additional samples were obtained from the Multiethnic Cohort (USC and University of Hawaii) (n=40), the University of California at San Francisco Multiple Myeloma Study (n=27), and from the Multiple Myeloma Research Consortium for secondary analysis (samples originally provided to MMRC by 8 additional sites (n=84)). We have identified the phenotype (smoldering myeloma, plasma cell multiple myeloma, or myeloma not otherwise specified (myeloma NOS) when myeloma phenotype was not known), sex and age at diagnosis in this data set. The initial GWAS set consisted of 1308 (1,305 passed QC) cases with DNA samples, with a GWAS performed on the Illumina Human Core. Controls consisted of 7,078 unaffected African American subjects who were participants in the African American Prostate and Breast Consortium, with existing GWAS data from the Illumina1M Duo BeadChip. The second GWAS set consisted of 529 African American multiple myeloma patients with samples (406 from University of Arkansas, results not contained in this dataset because NCI funds were not used for the collection and genotyping) with GWAS data resulting from the Illumina Mega-BeadChip v1.1. Controls were 2,390 unaffected African American participants in the Multiethnic Cohort with existing GWAS data from the same array. After QC and removal of duplicates within sets, sex mismatches, and removal of plasmacytoma cases (ICD-0 code 9731), this deposited data set contains the typed GWAS data for the Illumina Human Core (set 1) (n=1298), and for the MegaBead Chip v1.1 (set 2) (n=123), with the University of Arkansas samples removed, for a total of 1,421 case genotypes. Note that 13 samples that overlap set 1 and set 2 were included.

  Study phs001632

• Implementation, Adoption, and Utility of Family History in Diverse Care Settings

  The purpose of this study is to address the key question of whether and how family health history (FHH) is adopted as a tool to more efficiently manage patients at risk for breast, colon, ovarian, and hereditary cancer syndromes as well as thrombophilia and coronary heart disease (CHD) and to provide evidence supporting clinical utility -- improved health behaviors in patients and physician screening recommendations. Five health care delivery organizations will participate in this demonstration project: Duke University, the Medical College of Wisconsin, the Air Force, Essentia Health, University of North Texas. Duke will serve as a coordinating center for this project (Pro00043372) as well as a site. Healthcare Effectiveness Data and Information Set (HEDIS) measures as intermediate clinical effectiveness measures for Coronary Heart Disease (CHD) and selected cancers as well as survey/formative data and electronic medical record (EMR) data will be used as outcomes measures. The research model is purposely designed to mimic clinical delivery as an important step toward widespread implementation and sustainability. In addition, a cost-effectiveness analysis comparing usual care to the FHH guided preventive health model will be used. The completion of this project will result in an optimal strategy for integration of FHH data collection and clinical decision support (CDS) tools into an EMR and demonstrate the utility of the FHH intervention among diverse primary care patients, their settings, their providers, and the health systems that deliver their care. Specific Aim 1: To optimize the collection of patient entered FHH in diverse clinical environments for coronary heart disease, thrombosis, and selected cancers Specific Aim 2: To export FHH data to an open clinical decision support (open CDS) platform and return CDS results to providers and patients (and to EMRs where relevant). To explore the integration of genetic risk and FHH data at selected sites. Specific Aim 3: To assess the clinical and personal utility of FHH using a pragmatic observational study design to assess reach, adoption, integrity, exposure, and sustainability, and to capture, analyze, and report effectiveness outcomes at each stakeholder level: patient, provider, and clinic/system. Specific Aim 4: To take a leadership role in the dissemination of guidelines for a FHH intervention across in diverse practice settings. AAA Hypertension Lupus Multiple sclerosis Obesity Osteoporosis Thyroid disease Rheumatoid arthritis Blood clotting (6): Blood Clot (high risk features) Factor V PT mutation AT III deficiency Protein S deficiency Protein C deficiency Brain Disorders (5): Dementia Hemorrhagic stroke Ischemic stroke Macrocephaly Seizure Cancer/Adenomas (32): Bone cancer Brain cancer Breast cancer Colon cancer Adrenal cortex tumor Neuroendocrine tumor Paraganglioma Pheochromoctyoma Pituitary adenoma Medullary thyroid cancer Non-medullary (follicular or papillary) thyroid cancer Don't know type of thyroid cancer Thyroid nodule Other type of endocrine cancer Esophageal cancer Kidney cancer Leukemia Lipoma Liver cancer Muscle cancer Ovarian cancer Pancreatic cancer Prostate cancer Rectal cancer Retinoblastoma Melanoma Non-melanoma skin cancer Do not know type of skin cancer Small bowel cancer Stomach cancer Uterine cancer Other type of cancer Cardiovascular/heart/artery disease (5): Atrial fibrillation Carotid stenosis Heart attack/coronary artery disease Peripheral arterial disease Other heart disease Diabetes (3): Gestational diabetes Diabetes type I Diabetes type 2 Digestive Disorders (5): Colon polyp Crohn's disease Irritable bowel syndrome Ulcerative colitis Other digestive disorder Eye Disorder (3): Blindness Glaucoma Macular degeneration Hereditary Cancer Syndromes (22): Birt-Hogg-Dube syndrome Cowden syndrome Familial adenomatous polyposis Hereditary breast and ovarian cancer syndrome Hereditary diffuse gastric cancer Hereditary leiomyomatosis and renal cell carcinoma syndrome Hereditary melenoma Hereditary papillary renal cancer syndrome Hereditary paraganglioma-pheochromocytoma syndrome Hereditary retinoblastoma Juvenile polyposis Li-Fraumeni syndrome Lynch syndrome Mutyh-associated polyposis Malignant hyperthermia susceptibility Multiple endocrine neoplasia type 1 Multiple endocrine neoplasia type 2 Nevoid basal cell carcinoma syndrome Peutz-Jeghers syndrome Tuberous Sclerosis complex Von-Hippel Lindau syndrome Other hereditary cancer Hereditary Cardiovascular syndromes (10): Long qt Brugada Catecholaminergic polymorphic ventricular tachycardia Hypertrophic cardiomyopathy Dilated cardiomyopathy Left ventricular non-compaction syndrome Arrhythmogenic right ventricular dysplasia Ehlers-Danlos syndrome Marfan syndrome Other hereditary cardiovascular syndrome High cholesterol (2): Hyperlipidemia Familial hypercholesterolemia Kidney Disease (6): Cystic kidney disease Diabetic kidney disease Kidney nephrosis Nephritis Nephrotic syndrome Other kidney disease Liver Disease (6): Alpha 1 antitrypsinase deficiency Auto-immune hepatitis Hereditary hemochromatosis Primary biliary cirrhosis Sclerosing cholangitis Wilson's disease Lung Disease (3): Asthma COPD/chronic bronchitis/emphysema Other lung disease Psychological disorder (14): Addiction ADHD Autism Bipolar Depression Eating disorder Intellectual disability Obsessive compulsive disorder Panic disorder Personality disorder PTSD Schizophrenia Social phobia Sickle cell/thalassemia (3): Sickle cell disease Sickle cell trait Thalassemia

  Study phs001641

• NHLBI TOPMed - NHGRI CCDG: The BioMe Biobank at Mount Sinai

  The IPM BioMe Biobank, founded in September 2007, is an ongoing, broadly-consented electronic health record (EHR)-linked clinical care biobank that enrolls participants non-selectively from the Mount Sinai Medical Center patient population. BioMe currently comprises >42,000 participants from diverse ancestries, characterized by a broad spectrum of longitudinal biomedical traits. Participants are enrolled through an opt-in process and consent to be followed throughout their clinical care (past, present, and future) in real-time, allowing us to integrate their genomic information with their EHRs for discovery research and clinical care implementation. BioMe participants consent for recall, based on their genotype and/or phenotype, permitting in-depth follow-up and functional studies for selected participants at any time. Phenotypic and genomic data are stored in a secure database and made available to investigators, contingent on approval by the BioMe Governing Board. BioMe uses a "data-broker" system to protect confidentiality. Ancestral diversity - BioMe participants represent a broad racial, ethnic and socioeconomic diversity with a distinct and population-specific disease burden. Specifically, BioMe participants are of African (AA), Hispanic/Latino (HL), European (EA) and other/mixed ancestry. BioMe participants are predominantly of African (AA, 24%), Hispanic/Latino (HL, 35%), European (EA, 32%), and other ancestry (OA, 10%). Participants who self-identify as Hispanic/Latino further report to be of Puerto Rican (39%), Dominican (23%), Central/South American (17%), Mexican (5%) or other Hispanic (16%) ancestry. More than 40% of European ancestry participants are genetically determined to be of Ashkenazi Jewish ancestry. With this broad ancestral diversity, BioMe is uniquely positioned to examine the impact of demographic and evolutionary forces that have shaped common disease risk. Phenotypes available in BioMe - BioMe has a high-quality and validated set of fully implemented clinical phenotype data that has been culled by a multi-disciplinary team of experienced investigators, clinicians, information technologists, data-managers, and programmers who apply advanced medical informatics and data mining tools to extract and harmonize EHRs. BioMe, as a cohort, offers a great versatility for designing nested case-control sample-sets, particularly for studying longitudinal traits and co-morbidity in disease burden. Biomedical and clinical outcomes: The BioMe Biobank is linked to Mount Sinai's system-wide Epic EHR, which captures a full spectrum of biomedical phenotypes, including clinical outcomes, covariate and exposure data from past, present and future health care encounters. As such, the BioMe Biobank has a longitudinal design as participants consent to make all of their EHR data from past (dating back as far as 2003), present and future inpatient or outpatient encounters available for research, without restriction. The median number of outpatient encounters is 21 per participant, reflecting predominant enrollment of participants with common chronic conditions from primary care facilities. Environmental data: The clinical and EHR information is complemented by detailed demographic and lifestyle information, including ancestry, residence history, country of origin, personal and familial medical history, education, socio-economic status, physical activity, smoking, dietary habits, alcohol intake, and body weight history, which is collected in a systematic manner by interview-based questionnaire at time of enrollment. The IPM BioMe Biobank contributed ~10,600 DNA samples for whole genome sequencing to the TOPMed program. Samples were selected for the Coronary Artery Disease (CAD) and the Chronic Obstructive Pulmonary Disease (COPD) working groups. Using a Case-Definition-Algorithm (CDA), we identified ~4,100 individuals with CAD (~50% women) and ~3,000 individuals as controls (65% women). In addition, we identified ~800 individuals with COPD (62% women) and 1800 individuals as controls (72% women). Another 600 BioMe participants with Atrial Fibrillation, all of African ancestry, were included.

  Study phs001644

• Genomic Landscape of Cutaneous Diffuse Large B Cell Lymphoma

  Cutaneous diffuse large B cell lymphomas (DLBCL) are aggressive lymphomas with a poor prognosis. To elucidate their genetic bases, we performed whole exome capture and massively parallel sequencing on 19 tumor samples of diffuse large B cell lymphoma, leg type (DLBCL-LT) and 6 samples of secondary cutaneous diffuse large B cell lymphoma, not otherwise specified (DLBCL-NOS). Tumor specimens and their associated sequencing data were from multiple institutions, including Northwestern University (Chicago, IL), Massachusetts General Hospital (Boston, MA), and Medical University of Graz (Graz, Austria).

  Study phs001645

• NHLBI TOPMed: Genetic Causes of Complex Pediatric Disorders - Asthma (GCPD-A)

  The Center for Applied Genomics (CAG) at the Children's Hospital of Philadelphia (CHOP) is focused on addressing the roles of both single nucleotide variants and structural copy number variants, and their functional impact, together with gene-environment interactions and their influence on asthma drug response.

  Study phs001661

• Varieties of Impulsivity in Opiate and Stimulant Users

  The study was conducted in Bulgaria as a collaboration between Virginia Commonwealth University (Richmond, VA, USA), the Bulgarian Addictions Institute (Sofia, Bulgaria), the Molecular Medicine Center/Medical University (Sofia, Bulgaria), and Indiana University (Bloomington, IN, USA). The overall aim of this study is to investigate the role of impulsivity as an endophenotype for drug addiction. Although impulsivity is considered one of the strongest candidate endophenotypes for addiction, progress in the field is hampered by the heterogeneity of impulsivity, characterized by multiple personality, psychiatric, and neurocognitive dimensions, rarely examined concurrently in the same population; and the heterogeneity of addiction phenotypes, due in part to the high rates of polysubstance dependence among substance users. To address these challenges, we have developed a program of addiction research in Bulgaria, a key transit country for heroin trafficking due to its strategic geographical location on the "Balkan Drug Route" and a major European center for production of synthetic amphetamine-type stimulants. This has allowed us to access rare populations of predominantly mono-substance dependent heroin and amphetamine users, many in protracted abstinence. Our preliminary results reveal a complex relationship between trait and neurocognitive (state) dimensions of impulsivity, often manifested in opposite directions in heroin and amphetamine dependent individuals. Pilot computational modeling analyses of decision-making, a central neurocognitive aspect of impulsivity, have proved particularly informative by indicating that different mechanisms may underlie the impaired decision-making of opiate and stimulant users. A different modeling approach, i.e. phenotypic modeling, holds significant promise to address the pervasive "missing heritability" problem in genetic studies. While genetic heterogeneity is often invoked as an explanation, the manner in which complex phenotypic traits are measured and modeled is equally important contributor to the missing heritability problem but has received much less attention in the literature. Despite the multidimensionality of traits measured by psychometric, diagnostic, and neurocognitive instruments, most GWAS studies typically use aggregate sum scores that do not reflect the underlying phenotypic multidimensionality. Therefore, at least part of the missing heritability problem may originate in misspecification of the phenotypic models. Consequently, sample sizes requirements may increase from ~800 subjects in correctly specified models to 6,000-16,000 subjects in incorrectly specified models. The current study aims to increase our understanding of the complex relationship between multiple putative impulsivity endophenotypes to help redefine endophenotypes as multi-level combination of measures that could inform multivariate multilevel models of complex phenotypes. The specific aims of the study are to: (1) Assess the utility of various personality, psychiatric, and neurocognitive indices of impulsivity (either individually or in combination) as candidate endophenotype(s) for drug addiction in general and for opiate and stimulant addictions in particular; (2) Evaluate the viability of computational model parameters modeling various neurocognitive dimensions of impulsivity as novel endophenotype(s) for addiction; and (3) Test the external validity of the optimal endophenotype(s) by evaluating their associations with HIV and other risk behaviors in opiate and stimulant users in protracted abstinence, a question of critical importance for prevention and intervention efforts in this much less-well understood stage of the addiction cycle.

  Study phs001647