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• Starr County Health Studies' Genetics of Diabetes Study

  An initial observation in the 1970s that Starr County, Texas, had the highest diabetes-specific mortality of any of the 254 Texas counties led to the establishment of a field office in Rio Grande City, Texas (the county seat of Starr County) and the initiation of a series of studies to understand the epidemiology and genetics of type 2 diabetes, its complications and related conditions in this predominantly (97%) Mexican American population. The field office opened in February 1981 and has operated continuously since then. During this time, three systematic surveys of the population have been conducted as well as family and longitudinal studies. Culturally sensitive diabetes education programs have been developed and implemented and also a weight loss intervention. In total, more than 23,000 Mexican American individuals have been examined with more than 200,000 aliquots of biological specimens stored. Collectively, these studies are known as the Starr County Health Studies. The present Genetics of Diabetes Study has the goal of identifying loci/alleles that underlie susceptibility to type 2 diabetes in this high risk population using genome wide markers and association testing. The study makes use of two primary resources that have been developed in order to identify 1,000 type 2 diabetes cases and 1,000 disease free controls. In the first instance we have identified a subset of unrelated cases from the total cases that we have identified. Where multiply affected sibships were available, the youngest onset case with detailed phenotyping (including assessment of diabetic retinopathy) was selected. Controls came from a recent survey to establish a representative sample of the Starr County population. Blocks were randomly selected, households on selected blocks enumerated and one individual randomly selected from each household for a detailed examination. The examination included an oral glucose tolerance test. Those included as controls are those with no prior diagnosis of diabetes and a negative oral glucose tolerance test. This collection of cases and controls provides the opportunity to identify susceptibility loci for type 2 diabetes and its complications, specifically diabetic retinopathy and albuminuria. The data set also allows the examination of impaired fasting glucose and impaired glucose tolerance. The samples are split between those born in the United States and those born in Mexico and this gives a natural contrast for examining genotype and environmental interactions. It is anticipated that the understanding that will come will lead to strategies for delaying and preventing the onset of diabetes and its complications.

  Study phs000143

• Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) - OncoArray Genotypes

  Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) was one of five projects funded in 2010 as part of the NCI's Genetic Associations and Mechanisms in Oncology (GAME-ON) initiative (http://epi.grants.cancer.gov/gameon/). GAME-ON's overall goal was to foster an intra-disciplinary and collaborative approach to the translation of promising research leads deriving from the initial wave of cancer GWAS. Specific goals included replication of previous GWAS findings and identification of new susceptibility loci through meta analyses of existing GWAS data and fine mapping of identified loci to better pinpoint causal variants; and identify germline variants that are associated with risk of multiple cancers. The other four funded GAME-ON projects were: the ColoRectal TransdisciplinaryStudy (CORECT), Elucidating Loci Involved in Prostate Cancer Susceptibility (ELLIPSE), Follow-up of Ovarian Cancer Genetic Association and Interaction Study (FOCI), and Transdisciplinary Research in Cancer of the Lung (TRICL). To identify additional cancer risk loci, improve the precision of fine-mapping, and facilitate cross-cancer analyses, the GAME-ON projects and other consortia formed the OncoArray network (http://epi.grants.cancer.gov/oncoarray/), which developed and genotyped a new custom genotyping array (the "OncoArray") in large numbers of cancer cases and controls (over 400,000 samples). The OncoArray is a custom array manufactured by Illumina. The array includes a backbone of approximately 260,000 SNPs that provide genome-wide coverage of most common variants, together with markers of interest for each of the five GAME-ON cancers identified through genome-wide association studies (GWAS), fine-mapping of known susceptibility regions, sequencing studies, and other approaches. The array also includes loci of interest identified through studies of other cancer types, and other loci of interest to multiple cancer types (including loci associated with cancer related phenotypes, drug metabolism and radiation response). Additionally, SNPs relating to quantitative phenotypes such as body mass index (BMI), height, and breast density that correlate with common cancer risks are also included. The DRIVE data included under this dbGAP submission include OncoArray data from 60,015 breast cancer cases and controls genotyped at the Center for Inherited Disease Research (CIDR), University of Cambridge, National Cancer Institute, University of Copenhagen, University of Southern California and Mayo Clinic. Details on an additional approx. 80,000 breast cancer cases and controls genotyped at other centers can be found at http://bcac.ccge.medschl.cam.ac.uk/bcacdata/oncoarray/.

  Study phs001265

• Genetics of Human Inherited Retinal Diseases (GHIRD)

  The goal of this project is to identify novel mutations and genes involved in human retinal disorders, a stated priority of the National Eye Institute. To accomplish this, additional genes whose mutations cause inherited retinal diseases (IRD) will be identified by combining targeted gene panel sequencing, whole exome sequencing, and whole genome sequencing. We have collected about 1050 patient families around the world. In this proposal, we will identify the underlying mutations in these patients using a combination of targeted gene panel sequencing, whole exome sequencing, whole genome sequencing, bioinformatics, statistics, and functional studies. Genes targeted for gene panel sequencing are: ABCA4; ASIC2; JAG1; ABCC6; ARL3; ATP1B2; BBS1; BBS2; BBS4; OPN1SW; CAPN5; C21orf2; CA4; CACNA1F; CDH3; CHM; ERCC8; CLCN2; CLCN3; CLCN7; TPP1; CLN3; CLN5; CNGB1; CNGA1; CNGA3; COL2A1; COL9A1; COL11A1; CRX; VCAN; CTSD; TIMM8A; DMD; CLN8; ERCC6; EFEMP1; OPN1MW; GNAT1; GNAT2; GNGT1; GRM6; GUCA1A; GUCA1B; GUCY2F; GUCY2D; HARS; CFH; HK1; IDH3B; IMPDH1; IMPG1; KCNJ13; KIF11; LRP5; MAK; MITF; TRPM1; MTTP; MVK; MYO7A; NDP; NEK2; NEUROD1; NPHP1; NRL; OAT; OPA1; OTX2; PAX2; PAX6; PDCL; PCYT1A; PDE6A; PDE6C; PDE6G; PDE6H; PDE6B; PEX1; PEX6; PEX7; PEX10; PEX12; PEX13; PEX14; PFDN5; PGK1; PHYH; PIN1; PLA2G5; PPT1; PRKCZ; PEX19; PEX2; PEX5; RB1; RBP3; RBP4; OPN1LW; RDH5; PRPH2; RGR; RHO; GRK1; RLBP1; ROM1; RP9; RP1; RP2; RPGR; RPE65; RS1; SAG; ATXN7; CCL2; SLC6A6; ELOVL4; TEAD1; NR2F1; TIMP3; NR2E1; TTPA; TUB; TULP1; UCHL3; USH2A; CLRN1; VLDLR; BEST1; WFS1; ALMS1; MKKS; FZD4; OFD1; PEX3; CTSF; GBF1; ADAM9; RGS9; PEX11B; PROM1; UNC119; PRPF4; PRPF3; AIFM1; SLC24A1; LRAT; ASIC3; RAB28; PEX16; ITM2B; SLC4A7; IQCB1; CROCC; IFT140; DHX38; MFN2; NR2E3; USH1C; TOPORS; MERTK; FBLN5; CIB2; PRPF8; SDCCAG8; IFT27; TREX1; RRAS2; CEP164; ATF6; TRIM32; RIMS1; SNRNP200; CLUAP1; EMC1; ZNF423; TTLL5; AGTPBP1; RPGRIP1L; CRB1; TSPAN12; ARL2BP; AIPL1; PRPF6; FSCN2; ABHD12; PRPF31; TCTN3; IFT172; CNNM4; NPHP3; INVS; BBS9; FLVCR1; RDH8; IMPG2; WDPCP; RDH11; TMEM216; TMEM138; LZTFL1; CNGB3; AHI1; MKS1; CLN6; BBS7; POMGNT1; PEX26; SPATA7; KIZ; KLHL7; INPP5E; MDM1; CABP4; RPGRIP1; MCOLN1; CC2D2A; KIAA1549; SLC7A14; WDR19; NYX; CDH23; SEMA4A; MPP5; NMNAT1; TMEM237; PCDH15; C5orf42; GNPTAB; TMEM231; TCTN1; SRD5A3; BBS10; ZNF408; TTC21B; CSPP1; LPCAT1; DHDDS; PDZD7; PANK2; CEP290; OPA3; DNAJC5; PITPNM3; MFRP; HMCN1; ADGRV1; ARL6; FAM161A; TMEM126A; GNPTG; GJA10; RAX2; TUBGCP6; TMEM67; ACBD5; C12orf65; CDHR1; BBIP1; REEP6; CACNA2D4; RP1L1; CEP41; C1QTNF5; NXNL1; TTC8; USH1G; BBS5; ZNF513; RDH12; SLC38A8; C8orf37; VPS13B; NXNL2; BBS12; ADGRA3; LCA5; KCNV2; ADAMTS18; ARL13B; ATOH7; MFSD8; NPHP4; CCDC66; CYP4V2; CRB2; RD3; LRIT3; EYS; KIF7; CERKL; RGS9BP; C2orf71; GDF6; DTHD1; GPR179; CISD2; CCR2; PRCD; WHRN; ADGRA3. The current dbGaP study release makes available all sequencing-derived vcf data of study participants.

  Study phs001517

• Heart Failure Network: Functional Impact of GLP-1 for Heart Failure Treatment (HFN FIGHT-BioLINCC)

  Objectives To test whether therapy with a GLP-1 agonist improves clinical stability following hospitalization for acute heart failure. Background Heart failure was the leading cause of hospitalization in the United States with more than 4 million admissions per year from 2003–2009. Abnormal cardiac metabolism contributes to the pathophysiology of advanced heart failure with reduced left ventricular ejection fraction (LVEF). As heart failure progresses, these abnormalities become more pronounced and are observed in both patients with and without type 2 diabetes. At this time of this study, there was no heart failure therapy that targeted these metabolic abnormalities; however, in earlier clinical studies, glucagon-like peptide 1 (GLP-1) agonists showed cardioprotective effects in patients with advanced heart failure, irrespective of type 2 diabetes status. Glucagon-like peptide 1 is an endogenous incretin hormone that improves insulin sensitivity with minimal risk of hypoglycemia. This study was created to determine if use of GLP-1 agonists improved clinical stability in recently hospitalized patients with acute heart failure and reduced LVEF. Participants There were 300 participants. Design Participants were identified by hospital admission records and were enrolled during either the last 24 hours of his or her hospitalization for heart failure or the 2-week interval after the hospitalization. Baseline evaluations were conducted, which included echocardiographic measures, the 6-minute walk test, the Kansas City Cardiomyopathy Questionnaire (KCCQ), and blood tests. After the baseline evaluation, patients were randomized in a 1:1 ratio to receive either the GLP-1 agonist liraglutide or placebo as a daily subcutaneous injection. The protocol involved titration of study drug dosage as tolerated every 14 days from 0.6 mg/d to 1.2 mg/d to 1.8 mg/d during the first 30 days of the trial (as tolerated). Follow-up testing was performed at 30-, 90-, and 180-day study visits. The primary end point was a global rank score in which all participants, regardless of treatment assignment, were ranked across 3 hierarchical tiers: time to death, time to rehospitalization for heart failure, and time-averaged proportional change in N-terminal pro-B-type natriuretic peptide (NT-proBNP) level from baseline to 180 days. Conclusions The GLP-1 agonist liraglutide did not improve post-hospitalization clinical stability in patients with advanced heart failure and reduced LVEF. There was no significant between-group difference in the global rank scores and furthermore, there were no significant differences detected in any of the secondary endpoints.

  Study phs003542

• Rapid Acceleration of Diagnostics - Underserved Populations (RADx-UP): CO-CREATE-Ex: Community-engaged Optimization of COVID-19 Rapid Evaluation And TEsting Experiences

  Cases of COVID-19 infection in San Diego have persistently remained high in the county's central and southern communities near the US/Mexico border, home to primarily Latino residents who have been one of the ethnic minority communities most impacted by COVID-19. To address this, our Phase I RADx-UP project partnered with San Ysidro Health (SYH), a federally qualified health center, and the Global Action Research Center (Global ARC), a social change organization, to co-create and demonstrate the impact of a PCR-based COVID-19 testing program in San Ysidro. To date, we have administered approximately 15,000 PCR tests for >10,000 community members (92% Latino) and received requests from SYH to scale-out the testing program to additional primary care clinic sites. Responsive to RFA-OD-22-006, we will continue working with our community (Global ARC) and clinical (SYH) partners to refine, specify, implement, and evaluate an implementation strategy bundle that optimizes COVID-19 testing, expanding beyond current PCR testing to focus on FDA-authorized COVID-19 rapid antigen testing. Use of self-administered rapid antigen tests will allow participants to build capacity to self-test and use health information technology to access additional clinic services. Based on initial implementation mapping with the project's established Community and Scientific Advisory Board, three implementation strategies were prioritized to accelerate sustained uptake of rapid COVID-19 testing. These three strategies include: (1) current, walk-up onsite free testing; (2) promotores-led COVID-19 test counseling and preventive care reminders; (3) vending machines that dispense FDA-authorized self-testing kits. Our primary objectives are to: 1) refine and operationalize our multi-component implementation strategy bundle and a related set of measures of success for rapid FDA- authorized COVID-19 testing and 2) implement and evaluate impact of our innovative, multilevel, and multicomponent implementation strategy bundle to optimize COVID-19 rapid testing among underserved, Latino communities using a roll-out implementation optimization study design across four clinics over 18 months. The COVID-19 pandemic has underscored the urgent and essential need to engage invested community parties continuously and meaningfully in public health research to reduce health disparities. This proposal is well-positioned to provide a set of strategies and measures of success that can be used in settings serving underserved communities while maintaining flexibility to adjust to the changing COVID-19 landscape.

  Study phs003686

• Framingham Heart Study-Cohort (FHS-Cohort) - Imaging

  The Framingham Heart Study (FHS) is a population-based, observational cohort study initiated in 1948 to prospectively investigate the determinants of cardiovascular disease to guide public health prevention. The FHS began by recruiting an Original Cohort of 5,209 men and women between the ages of 30 and 62 from the town of Framingham, Massachusetts, who had not yet developed overt symptoms of cardiovascular disease or suffered a heart attack or stroke. The Original cohort Exam 1 took place between 1948 and 1953. Since that time the cohort has had a total of 32 biennial exams (ending in 2014) and event follow-up through 2022. In 1971, the FHS added the Offspring cohort, comprising 5124 children whose parents were enrolled in the Original cohort and the spouses of the children. This cohort on average has been examined every three to four years. However, there was an eight year gap between Exam 1 and Exam 2 and a seven year gap between Exam 7 and Exam 8. The latest exam (10) was completed in 2022. In 2002, the transgenerational FHS design was facilitated with the recruitment of 4095 children of the Offspring cohort (Third Generation), and 103 spouses of the Offspring who were not previously enrolled in the study (New Offspring Spouses, NOS). These cohorts have completed 3 exams through 2019. To reflect the changing demographic characteristics of the greater Framingham community, the FHS additionally recruited and enrolled 2 cohorts comprising racial and ethnic minority groups, termed Omni-1 and Omni-2, (n = 506 and 410, respectively) in 1995 and 2002, respectively. These cohorts included individuals of African American, Hispanic, Asian, Indian, Native American, and Pacific Islander descent. The OMNI-1 cohort have completed 5 exams through 2022. The OMNI-2 cohort have completed 3 exams through 2019. Data available for request include Echocardiogram images, available from the following exams in each cohort. Original Cohort: exams 18-32; Offspring cohort: exams 3-10; Third Generation, NOS and OMNI-2 cohorts: exams 1-3; OMNI-1 cohort: exams 1-5.CT image data at one or two timepoints were added for 4427 participants in the offspring, third generation, and OMNI1 and OMNI2 cohorts.Summary level phenotypes for the Framingham Cohort study participants can be viewed at the top-level study page phs000007 Framingham Cohort. Individual level phenotype data and molecular data for all Framingham top-level study and substudies are available by requesting Authorized Access to the Framingham Cohort study phs000007.

  Study phs003593

• TNBC ctDNA Targeted Panel

  Circulating tumour DNA (ctDNA) detection in liquid biopsy is an emerging alternative to tissue biopsy, but its utility in treatment response monitoring and prognosis in triple negative breast cancer (TNBC) remains to be well understood. In this study, we determined the presence of early stage TNBC ctDNA detectable actionable mutations with a clinically validated hotspot treatment indication panel. Sequencing of plasma DNA from 130 TNBC patients collected within 7 months of primary treatment completion revealed that 7.7% had detectable residual disease with a hotspot panel. Among neoadjuvant treated patients, we observed a trend where patients with incomplete pathologic response and positive ctDNA within 7 months of treatment completion were at risk of reduced progression free survival. We propose that a high risk subset of early TNBC patients treated in NAT protocols may be identifiable by combining tissue response and sensitive ctDNA detection.

  Study EGAS00001006937

• Response to tumor-infiltrating lymphocyte adoptive therapy is associated with preexisting CD8+ T-myeloid cell networks in melanoma

  Adoptive cell therapy (ACT) using ex vivo–expanded tumor-infiltrating lymphocytes (TILs) can eliminate or shrink metastatic melanoma, but its long-term efficacy remains limited to a fraction of patients. Using longitudinal samples from 13 patients with metastatic melanoma treated with TIL-ACT in a phase 1 clinical study, we interrogated cellular states within the tumor microenvironment (TME) and their interactions. We performed bulk and single-cell RNA sequencing, whole-exome sequencing, and spatial proteomic analyses in pre- and post-ACT tumor tissues, finding that ACT responders exhibited higher basal tumor cell–intrinsic immunogenicity and mutational burden. Compared with nonresponders, CD8+ TILs exhibited increased cytotoxicity, exhaustion, and costimulation, whereas myeloid cells had increased type I interferon signaling in responders. Cell-cell interaction prediction analyses corroborated by spatial neighborhood analyses revealed that responders had rich baseline intratumoral and stromal tumor–reactive T cell networks with activated myeloid populations. Successful TIL-ACT therapy further reprogrammed the myeloid compartment and increased TIL-myeloid networks. Our systematic target discovery study identifies potential T-myeloid cell network–based biomarkers that could improve patient selection and guide the design of ACT clinical trials.

  Study EGAS50000001217

• Genome Diversity in Africa Project: Benin (2021-02-16)

  Globally, human populations show structured genetic diversity as a result of geographical dispersion, selection and drift. Understanding this genetic variation can provide insights into the evolutionary processes that shape both human adaptation and variation in disease. Populations from SSA have the highest levels of genetic diversity. This characteristic, in addition to historical genetic admixture, can lead to complexities in the design of studies assessing the genetic determinants of disease and human variation. However, such studies of African populations are also likely to provide new opportunities to discover novel disease susceptibility loci and variants and refine gene-disease association signals. A systematic assessment of genetic diversity within SSA would facilitate genomic epidemiological studies in the region. The Genome Diversity in Africa Project (GDAP) aims to produce a comprehensive catalogue of human genetic variation in SSA, including single nucleotide polymorphisms (SNPs), structural variants, and haplotypes. This resource will make a substantial contribution to understanding patterns of genetic diversity within and among populations in SSA, as well as providing a global resource to help design, implement and interpret genomic studies in SSA populations and studies comprising globally diverse populations, complementing existing genomic resources. Specifically, we plan to carry out high depth whole genome sequencing of up to 2000 individuals across Africa (25 individuals from each ethnolinguistic group). Our scientific objectives are to: 1) develop a resource that provides a comprehensive catalogue of genetic variation in populations from SSA accessible to the global scientific community; 2) characterise population genetic diversity, structure, gene flow and admixture across SSA; 3) develop a cost-efficient, next-generation genotype array for diverse populations across SSA; and 4) facilitate whole genome-sequencing association studies of complex traits and diseases by developing a reference panel for imputation and resource for enhancing fine-mapping disease susceptibility loci. These scientific objectives will be supported by cross-cutting operational activities, including network and management of the consortium, research ethics, and research capacity building in statistical genetics and bioinformatics This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2021-02-16.

  Dataset EGAD00001006970

• Whole genome sequencing of retinoblastoma reveals the diversity of rearrangements disrupting RB1 and uncovers a treatment related mutational signature

  Background: The development of retinoblastoma is thought to require pathological genetic changes in both alleles of the RB1 gene. However, cases exist where RB1 mutations are undetectable suggesting alternative pathways to malignancy. Methods: We applied comprehensive whole genome sequencing (WGS) and transcriptomics to sporadic retinoblastomas derived from twenty patients attending our clinic, contrasting these results to that obtained through customary clinical testing. We sought RB1 and other driver mutations, investigated mutation burden, mutational signatures and phylogenetic relatedness in one case of bilateral retinoblastoma. Results: At least one RB1 mutation was identified in all retinoblastomas. We confirmed RB1 mutations previously identified by clinical screening, identified three new RB1 mutations and provided clarity to the mechanism behind a further six mutations. Eight tumours carried structural rearrangements involving RB1 ranging from relatively simple to extremely complex rearrangement patterns, including a chromothripsis-like pattern in one tumour. Potential driver mutations included mutations in BCOR (5/20) and amplification of MYCN (2/20) and MDM4 (1/20). We show that RB1 mutations are not mutually exclusive of MYCN amplifications, and further reveal that all tumours demonstrate increased MYCN expression suggesting a universal role in retinoblastoma tumorigenesis.  Bilateral tumours obtained from one patient harboured conserved germline but divergent somatic RB1 mutations, indicating independent evolution. In-keeping with previous WGS of paediatric cancers, the mutation burden in retinoblastomas was extremely low. Mutational signature analysis showed a predominance of signatures associated with cell division and an absence of ultraviolet-related DNA damage. In a tumour exposed to chemotherapy prior to enucleation, a profound platinum-related mutational signature was observed. Conclusions: WGS provides a complete picture of the genomic landscape of retinoblastomas, allowing the discovery of mutations otherwise undetected by conventional clinical screening approaches. The presence of at least one RB1 mutation in all retinoblastomas and the relative paucity of driver mutations in other genes suggests mutations beyond RB1, MYCN and BCOR are rare. Whilst most RB1 mutations are identifiable by clinical screening, the increased resolution and ability to detect otherwise elusive rearrangements of RB1 by WGS, confirming whether they are somatic or germline, has important repercussions on clinical management and advice on recurrence risks.

  Dataset EGAD00001006431