miRNA Sequencing of olfactory mucosa (OM) cells derived from cognitively healthy and individuals with AD exposed to traffic-related ultrafine particles (UFPs) for 72h in submerged cultures. The UFPs used for exposures were: A0 and A20. Exposures were compared to the corresponding blank samples.
The need for a detailed catalogue of local variability for the study of rare diseases within the context of the Medical Genome Project motivated the whole exome sequencing of 267 unrelated individuals, representative of the healthy Spanish population.
We provide the first detailed insights into the genetic profiles of Thai/Lao ethnolinguistic groups, which should be helpful for reconstructing human genetic history in MSEA and selecting populations for participation in ongoing whole genome sequence and biomedical studies
From 17 patients undergoing knee joint replacement surgery for osteoarthritis, we collected 4 samples each: intact cartilage, degraded cartilage, synovium, and meniscus. We also collected blood for DNA analysis. Multiplexed libraries were sequenced on Illumina HiSeq 2000 (75bp paired-end read length) and a cram file was produced for each sample. This dataset contains all the data available for this study on 2017-06-09.
FASTQ files of the RNA-Seq data for both the normal and tumor samples for the study "Genomic landscape of lung adenocarcinoma in East Asians". For raw read count data as well as other metadata, please download from https://src.gisapps.org/OncoSG_public/study/summary?id=GIS031 by clicking the download icon next to the dataset title.
FASTQ files of the Exome-Seq data for both the normal and tumor samples for the study "Genomic landscape of lung adenocarcinoma in East Asians". For mutations and copy number variants called by this study, please download from https://src.gisapps.org/OncoSG_public/study/summary?id=GIS031 by clicking the download icon next to the dataset title.
January 2016 update of RNA-Seq data (bams, fastqs) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.
ChIP-Seq (H3K4me3, H3K4me1, H3K9me3, H3K27ac, H3K27me3, H3K36me3, Input) data for HL60 cell line generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency.
ChIP-seq data for Lymphoblastoid Cell Lines (LCL) and Fibroblasts (FIB) from the Gencord Cohort: - 160 LCLs assayed for H3K27ac, H3K4me1 and H3K4me3, - 78 FIB assayed for H3K4me3 and 79 FIB assayed for H3K27ac and H3K4me1 This dataset was generated as part of the following study: Delaneau et al (2019). Chromatin 3D interactions mediate genetic effects on gene expression.
The dataset for white blood cell and cell-free DNA analyses for detection of residual disease in gastric cancer includes 169 bam files from targeted deep sequencing on the Illumina HiSeq2500. The samples analyzed include genomic DNA from white blood cells and cell-free DNA from longitudinal blood collections of patients with gastric cancer.
February 2021 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.
We profile 10 high-grade gliomas patient brain tumor samples by single-cell multiome ATAC + gene expression, using the 10X Chromium technology. 3 sets of fastq are provided for each samples: R1 and R2 for gene expression, R1 and R2 for ATAC-seq as well as index1 and index2 for ATAC-seq.
The dataset for Single molecule genome-wide mutation profiles of cell-free DNA for non-invasive detection of cancer includes 57 BAM files from whole genome next-generation sequencing on the Illumina HiSeq2500. The samples analyzed include plasma samples from individuals with and without cancer.
Controlled human infection experiments enable longitudinal profiling of immune responses to a pathogen. 36 healthy volunteers aged 18-29 years, with no evidence of previous infection or vaccination, were inoculated with SARS-CoV-2 virus and quarantined for 14 days. Blood samples (n=374) for RNA sequencing were collected into PAXgene tubes before virus challenge, 6 hours after challenge, daily thereafter for 14 days and on day 28. Mid-turbinate nose swabs (n=96) for RNA sequencing were collected before virus challenge, and on days 1, 3, 5, 7, 10 and 14 after challenge, preserved in RNAprotect. 18 of 36 participants developed a replicative SARS-CoV-2 infection as evidenced by consecutive PCR-positive swabs for the virus. For every participant, blood RNA from selected days were extracted and depleted for genomic DNA and globin mRNA, before cDNA libraries were constructed using KAPA RNA HyperPrep with RiboErase kits. Libraries were sequenced on the Illumina NovaSeq 6000 platform using NovaSeq 6000 S4 Reagent Kits (200 cycles). Nose swab RNA samples were extracted and depleted for genomic DNA before cDNA libraries were constructed using KAPA mRNA HyperPrep Kits. Libraries were sequenced on the Illumina NextSeq platform the using the NextSeq 500/550 High Output Kit (75 cycles).
Recent advances in human blastoids have opened new avenues for modeling early human development and implantation. One limitation of our first protocol for human blastoid generation was relatively low efficiency. We now report an optimized protocol for the efficient generation of large quantities of high-fidelity human blastoids from naive pluripotent stem cells. This enabled proteomics analysis that identified phosphosite-specific signatures potentially involved in the derivation and/or maintenance of the signaling states in human blastoids. Additionally, we uncovered endometrial stromal effects in promoting trophoblast cell survival, proliferation, and syncytialization during co-culture with blastoids and blastocysts. Side-by-side single-cell RNA sequencing revealed similarities and differences in transcriptome profiles between pre-implantation blastoids and blastocysts, as well as post-implantation cultures, and uncovered a population resembling early migratory trophoblasts during co-culture with endometrial stromal cells. Our optimized protocol will facilitate broader use of human blastoids as an accessible, perturbable, scalable, and tractable model for human blastocysts. In addition, this study is the first to use the 10X Genomics platform for human blastocysts, and we anticipate this resource will be widely used by the community as a reference for future studies.
Accurate diagnosis of lung cancer is important for treatment decision-making. Currently, the gold standard for diagnosing histological subtypes of lung cancer relies on tumor biopsies. Recently, liquid biopsy, particularly cell-free DNA (cfDNA), has shown promising results in cancer detection and classification. In this study, we investigated the potential of cfDNA methylome for the noninvasive classification of lung cancer histological subtypes. Specifically, we focused on the two most prevalent lung cancer subtypes, lung adenocarcinoma and lung squamous cell carcinoma. Using a fragment-based marker discovery approach, we identified robust subtype-specific methylation markers from tumor samples. These markers were successfully validated in independent cohorts and associated with subtype-specific transcription activity. Leveraging these markers, we constructed a subtype classification model using cfDNA methylation profiles, achieving an AUC of 0.808 in the cross-validation and an AUC of 0.747 in the independent validation. Additionally, tumor copy number variations inferred from cfDNA methylome analysis revealed potential implications for treatment selection. In summary, our study demonstrates the potential of cfDNA methylome analysis for noninvasively lung cancer subtyping, offering insights for cancer monitoring and early detection.
Fusion genes arising from cancer-associated somatic mutations are a potential rich source for highly immunogenic neo-antigens. However, their exploitation as targets for personalized cancer immunotherapy is currently limited by the lack of computational tools allowing transcriptome-wide identification of unique fusion genes in an accurate and sensitive manner. Here, we present EasyFuse, a computational pipeline, to detect individual and cancer-specific fusion genes in next-generation-sequencing transcriptome data obtained from human cancer samples. Using machine learning, EasyFuse predicts personal fusion genes with high precision and sensitivity and outperforms previously described approaches as qualified by an unprecedented ground-truth dataset of >1500 verification experiments in relevant patient samples. By testing immunogenicity with autologous blood lymphocytes from cancer patients we detected pre-established CD4+ and CD8+ T cell responses for 10 of 21 (48%), and for 1 of 30 (3%) of identified fusion genes, respectively. In conclusion, we demonstrate accurate detection of cancer-specific fusion genes. The high frequency of T cell responses detected in cancer patients support the relevance of private fusion genes as neo-antigens for personalized immunotherapies, especially for tumors with low point mutation burdens.
Original description of the study: From ELLIPSE (linked to the PRACTICAL consortium), we contributed ~78,000 SNPs to the OncoArray. A large fraction of the content was derived from the GWAS meta-analyses in European ancestry populations (overall and aggressive disease; ~27K SNPs). We also selected just over 10,000 SNPs from the meta-analyses in the non-European populations, with a majority of these SNPs coming from the analysis of overall prostate cancer in African ancestry populations as well as from the multiethnic meta-analysis. A substantial fraction of SNPs (~28,000) were also selected for fine-mapping of 53 loci not included in the common fine-mapping regions (tagging at r2>0.9 across ±500kb regions). We also selected a few thousand SNPs related with PSA levels and/or disease survival as well as SNPs from candidate lists provided by study collaborators, as well as from meta-analyses of exome SNP chip data from the Multiethnic Cohort and UK studies. The Contributing Studies: Aarhus: Hospital-based, Retrospective, Observational. Source of cases: Patients treated for prostate adenocarcinoma at Department of Urology, Aarhus University Hospital, Skejby (Aarhus, Denmark). Source of controls: Age-matched males treated for myocardial infarction or undergoing coronary angioplasty, but with no prostate cancer diagnosis based on information retrieved from the Danish Cancer Register and the Danish Cause of Death Register. AHS: Nested case-control study within prospective cohort. Source of cases: linkage to cancer registries in study states. Source of controls: matched controls from cohort ATBC: Prospective, nested case-control. Source of cases: Finnish male smokers aged 50-69 years at baseline. Source of controls: Finnish male smokers aged 50-69 years at baseline BioVu: Cases identified in a biobank linked to electronic health records. Source of cases: A total of 214 cases were identified in the VUMC de-identified electronic health records database (the Synthetic Derivative) and shipped to USC for genotyping in April 2014. The following criteria were used to identify cases: Age 18 or greater; male; African Americans (Black) only. Note that African ancestry is not self-identified, it is administratively or third-party assigned (which has been shown to be highly correlated with genetic ancestry for African Americans in BioVU; see references). Source of controls: Controls were identified in the de-identified electronic health record. Unfortunately, they were not age matched to the cases, and therefore cannot be used for this study. Canary PASS: Prospective, Multi-site, Observational Active Surveillance Study. Source of cases: clinic based from Beth Israel Deaconness Medical Center, Eastern Virginia Medical School, University of California at San Francisco, University of Texas Health Sciences Center San Antonio, University of Washington, VA Puget Sound. Source of controls: N/A CCI: Case series, Hospital-based. Source of cases: Cases identified through clinics at the Cross Cancer Institute. Source of controls: N/A CerePP French Prostate Cancer Case-Control Study (ProGene): Case-Control, Prospective, Observational, Hospital-based. Source of cases: Patients, treated in French departments of Urology, who had histologically confirmed prostate cancer. Source of controls: Controls were recruited as participating in a systematic health screening program and found unaffected (normal digital rectal examination and total PSA < 4 ng/ml, or negative biopsy if PSA > 4 ng/ml). COH: hospital-based cases and controls from outside. Source of cases: Consented prostate cancer cases at City of Hope. Source of controls: Consented unaffected males that were part of other studies where they consented to have their DNA used for other research studies. COSM: Population-based cohort. Source of cases: General population. Source of controls: General population CPCS1: Case-control - Denmark. Source of cases: Hospital referrals. Source of controls: Copenhagen General Population Study CPCS2: Source of cases: Hospital referrals. Source of controls: Copenhagen General Population Study CPDR: Retrospective cohort. Source of cases: Walter Reed National Military Medical Center. Source of controls: Walter Reed National Military Medical Center ACS_CPS-II: Nested case-control derived from a prospective cohort study. Source of cases: Identified through self-report on follow-up questionnaires and verified through medical records or cancer registries, identified through cancer registries or the National Death Index (with prostate cancer as the primary cause of death). Source of controls: Cohort participants who were cancer-free at the time of diagnosis of the matched case, also matched on age (±6 mo) and date of biospecimen donation (±6 mo). EPIC: Case-control - Germany, Greece, Italy, Netherlands, Spain, Sweden, UK. Source of cases: Identified through record linkage with population-based cancer registries in Italy, the Netherlands, Spain, Sweden and UK. In Germany and Greece, follow-up is active and achieved through checks of insurance records and cancer and pathology registries as well as via self-reported questionnaires; self-reported incident cancers are verified through medical records. Source of controls: Cohort participants without a diagnosis of cancer EPICAP: Case-control, Population-based, ages less than 75 years at diagnosis, Hérault, France. Source of cases: Prostate cancer cases in all public hospitals and private urology clinics of département of Hérault in France. Cases validation by the Hérault Cancer Registry. Source of controls: Population-based controls, frequency age matched (5-year groups). Quotas by socio-economic status (SES) in order to obtain a distribution by SES among controls identical to the SES distribution among general population men, conditionally to age. ERSPC: Population-based randomized trial. Source of cases: Men with PrCa from screening arm ERSPC Rotterdam. Source of controls: Men without PrCa from screening arm ERSPC Rotterdam ESTHER: Case-control, Prospective, Observational, Population-based. Source of cases: Prostate cancer cases in all hospitals in the state of Saarland, from 2001-2003. Source of controls: Random sample of participants from routine health check-up in Saarland, in 2000-2002 FHCRC: Population-based, case-control, ages 35-74 years at diagnosis, King County, WA, USA. Source of cases: Identified through the Seattle-Puget Sound SEER cancer registry. Source of controls: Randomly selected, age-frequency matched residents from the same county as cases Gene-PARE: Hospital-based. Source of cases: Patients that received radiotherapy for treatment of prostate cancer. Source of controls: n/a Hamburg-Zagreb: Hospital-based, Prospective. Source of cases: Prostate cancer cases seen at the Department of Oncology, University Hospital Center Zagreb, Croatia. Source of controls: Population-based (Croatia), healthy men, older than 50, with no medical record of cancer, and no family history of cancer (1st & 2nd degree relatives) HPFS: Nested case-control. Source of cases: Participants of the HPFS cohort. Source of controls: Participants of the HPFS cohort IMPACT: Observational. Source of cases: Carriers and non-carriers (with a known mutation in the family) of the BRCA1 and BRCA2 genes, aged between 40 and 69, who are undergoing prostate screening with annual PSA testing. This cohort has been diagnosed with prostate cancer during the study. Source of controls: Carriers and non-carriers (with a known mutation in the family) of the BRCA1 and BRCA2 genes, aged between 40 and 69, who are undergoing prostate screening with annual PSA testing. This cohort has not been diagnosed with prostate cancer during the study. IPO-Porto: Hospital-based. Source of cases: Early onset and/or familial prostate cancer. Source of controls: Blood donors Karuprostate: Case-control, Retrospective, Population-based. Source of cases: From FWI (Guadeloupe): 237 consecutive incident patients with histologically confirmed prostate cancer attending public and private urology clinics; From Democratic Republic of Congo: 148 consecutive incident patients with histologically confirmed prostate cancer attending the University Clinic of Kinshasa. Source of controls: From FWI (Guadeloupe): 277 controls recruited from men participating in a free systematic health screening program open to the general population; From Democratic Republic of Congo: 134 controls recruited from subjects attending the University Clinic of Kinshasa KULEUVEN: Hospital-based, Prospective, Observational. Source of cases: Prostate cancer cases recruited at the University Hospital Leuven. Source of controls: Healthy males with no history of prostate cancer recruited at the University Hospitals, Leuven. LAAPC: Subjects were participants in a population-based case-control study of aggressive prostate cancer conducted in Los Angeles County. Cases were identified through the Los Angeles County Cancer Surveillance Program rapid case ascertainment system. Eligible cases included African American, Hispanic, and non-Hispanic White men diagnosed with a first primary prostate cancer between January 1, 1999 and December 31, 2003. Eligible cases also had (a) prostatectomy with documented tumor extension outside the prostate, (b) metastatic prostate cancer in sites other than prostate, (c) needle biopsy of the prostate with Gleason grade ≥8, or (d) needle biopsy with Gleason grade 7 and tumor in more than two thirds of the biopsy cores. Eligible controls were men never diagnosed with prostate cancer, living in the same neighborhood as a case, and were frequency matched to cases on age (± 5 y) and race/ethnicity. Controls were identified by a neighborhood walk algorithm, which proceeds through an obligatory sequence of adjacent houses or residential units beginning at a specific residence that has a specific geographic relationship to the residence where the case lived at diagnosis. Malaysia: Case-control. Source of cases: Patients attended the outpatient urology or uro-onco clinic at University Malaya Medical Center. Source of controls: Population-based, age matched (5-year groups), ascertained through electoral register, Subang Jaya, Selangor, Malaysia MCC-Spain: Case-control. Source of cases: Identified through the urology departments of the participating hospitals. Source of controls: Population-based, frequency age and region matched, ascertained through the rosters of the primary health care centers MCCS: Nested case-control, Melbourne, Victoria. Source of cases: Identified by linkage to the Victorian Cancer Registry. Source of controls: Cohort participants without a diagnosis of cancer MD Anderson: Participants in this study were identified from epidemiological prostate cancer studies conducted at the University of Texas MD Anderson Cancer Center in the Houston Metropolitan area. Cases were accrued in the Houston Medical Center and were not restricted with respect to Gleason score, stage or PSA. Controls were identified via random-digit-dialing or among hospital visitors and they were frequency matched to cases on age and race. Lifestyle, demographic, and family history data were collected using a standardized questionnaire. MDACC_AS: A prospective cohort study. Source of cases: Men with clinically organ-confined prostate cancer meeting eligibility criteria for a prospective cohort study of active surveillance at MD Anderson Cancer Center. Source of controls: N/A MEC: The Multiethnic Cohort (MEC) is comprised of over 215,000 men and women recruited from Hawaii and the Los Angeles area between 1993 and 1996. Between 1995 and 2006, over 65,000 blood samples were collected from participants for genetic analyses. To identify incident cancer cases, the MEC was cross-linked with the population-based Surveillance, Epidemiology and End Results (SEER) registries in California and Hawaii, and unaffected cohort participants with blood samples were selected as controls MIAMI (WFPCS): Prostate cancer cases and controls were recruited from the Departments of Urology and Internal Medicine of the Wake Forest University School of Medicine using sequential patient populations as described previously (PMID:15342424). All study subjects received a detailed description of the study protocol and signed their informed consent, as approved by the medical center's Institutional Review Board. The general eligibility criteria were (i) able to comprehend informed consent and (ii) without previously diagnosed cancer. The exclusion criteria were (i) clinical diagnosis of autoimmune diseases; (ii) chronic inflammatory conditions; and (iii) infections within the past 6 weeks. Blood samples were collected from all subjects. MOFFITT: Hospital-based. Source of cases: clinic based from Moffitt Cancer Center. Source of controls: Moffitt Cancer Center affiliated Lifetime cancer screening center NMHS: Case-control, clinic based, Nashville TN. Source of cases: All urology clinics in Nashville, TN. Source of controls: Men without prostate cancer at prostate biopsy. PCaP: The North Carolina-Louisiana Prostate Cancer Project (PCaP) is a multidisciplinary population-based case-only study designed to address racial differences in prostate cancer through a comprehensive evaluation of social, individual and tumor level influences on prostate cancer aggressiveness. PCaP enrolled approximately equal numbers of African Americans and Caucasian Americans with newly-diagnosed prostate cancer from North Carolina (42 counties) and Louisiana (30 parishes) identified through state tumor registries. African American PCaP subjects with DNA, who agreed to future use of specimens for research, participated in OncoArray analysis. PCMUS: Case-control - Sofia, Bulgaria. Source of cases: Patients of Clinic of Urology, Alexandrovska University Hospital, Sofia, Bulgaria, PrCa histopathologically confirmed. Source of controls: 72 patients with verified BPH and PSA<3,5; 78 healthy controls from the MMC Biobank, no history of PrCa PHS: Nested case-control. Source of cases: Participants of the PHS1 trial/cohort. Source of controls: Participants of the PHS1 trial/cohort PLCO: Nested case-control. Source of cases: Men with a confirmed diagnosis of prostate cancer from the PLCO Cancer Screening Trial. Source of controls: Controls were men enrolled in the PLCO Cancer Screening Trial without a diagnosis of cancer at the time of case ascertainment. Poland: Case-control. Source of cases: men with unselected prostate cancer, diagnosed in north-western Poland at the University Hospital in Szczecin. Source of controls: cancer-free men from the same population, taken from the healthy adult patients of family doctors in the Szczecin region PROCAP: Population-based, Retrospective, Observational. Source of cases: Cases were ascertained from the National Prostate Cancer Register of Sweden Follow-Up Study, a retrospective nationwide cohort study of patients with localized prostate cancer. Source of controls: Controls were selected among men referred for PSA testing in laboratories in Stockholm County, Sweden, between 2010 and 2012. PROGReSS: Hospital-based, Prospective, Observational. Source of cases: Prostate cancer cases from the Hospital Clínico Universitario de Santiago de Compostela, Galicia, Spain. Source of controls: Cancer-free men from the same population ProMPT: A study to collect samples and data from subjects with and without prostate cancer. Retrospective, Experimental. Source of cases: Subjects attending outpatient clinics in hospitals. Source of controls: Subjects attending outpatient clinics in hospitals ProtecT: Trial of treatment. Samples taken from subjects invited for PSA testing from the community at nine centers across United Kingdom. Source of cases: Subjects who have a proven diagnosis of prostate cancer following testing. Source of controls: Identified through invitation of subjects in the community. PROtEuS: Case-control, population-based. Source of cases: All new histologically-confirmed cases, aged less or equal to 75 years, diagnosed between 2005 and 2009, actively ascertained across Montreal French hospitals. Source of controls: Randomly selected from the Provincial electoral list of French-speaking men between 2005 and 2009, from the same area of residence as cases and frequency-matched on age. QLD: Case-control. Source of cases: A longitudinal cohort study (Prostate Cancer Supportive Care and Patient Outcomes Project: ProsCan) conducted in Queensland, through which men newly diagnosed with prostate cancer from 26 private practices and 10 public hospitals were directly referred to ProsCan at the time of diagnosis by their treating clinician (age range 43-88 years). All cases had histopathologically confirmed prostate cancer, following presentation with an abnormal serum PSA and/or lower urinary tract symptoms. Source of controls: Controls comprised healthy male blood donors with no personal history of prostate cancer, recruited through (i) the Australian Red Cross Blood Services in Brisbane (age range 19-76 years) and (ii) the Australian Electoral Commission (AEC) (age and post-code/ area matched to ProsCan, age range 54-90 years). RAPPER: Multi-centre, hospital based blood sample collection study in patients enrolled in clinical trials with prospective collection of radiotherapy toxicity data. Source of cases: Prostate cancer patients enrolled in radiotherapy trials: CHHiP, RT01, Dose Escalation, RADICALS, Pelvic IMRT, PIVOTAL. Source of controls: N/A SABOR: Prostate Cancer Screening Cohort. Source of cases: Men >45 yrs of age participating in annual PSA screening. Source of controls: Males participating in annual PSA prostate cancer risk evaluations (funded by NCI biomarkers discovery and validation grant), recruited through University of Texas Health Science Center at San Antonio and affiliated sites or through study advertisements, enrolment open to the community SCCS: Case-control in cohort, Southeastern USA. Prospective, Observational, Population-based. Source of cases: SCCS entry population. Source of controls: SCCS entry population SCPCS: Population-based, Retrospective, Observational. Source of cases: South Carolina Central Cancer Registry. Source of controls: Health Care Financing Administration beneficiary file SEARCH: Case-control - East Anglia, UK. Source of cases: Men < 70 years of age registered with prostate cancer at the population-based cancer registry, Eastern Cancer Registration and Information Centre, East Anglia, UK. Source of controls: Men attending general practice in East Anglia with no known prostate cancer diagnosis, frequency matched to cases by age and geographic region SNP_Prostate_Ghent: Hospital-based, Retrospective, Observational. Source of cases: Men treated with IMRT as primary or postoperative treatment for prostate cancer at the Ghent University Hospital between 2000 and 2010. Source of controls: Employees of the University hospital and members of social activity clubs, without a history of any cancer. SPAG: Hospital-based, Retrospective, Observational. Source of cases: Guernsey. Source of controls: Guernsey STHM2: Population-based, Retrospective, Observational. Source of cases: Cases were selected among men referred for PSA testing in laboratories in Stockholm County, Sweden, between 2010 and 2012. Source of controls: Controls were selected among men referred for PSA testing in laboratories in Stockholm County, Sweden, between 2010 and 2012. PCPT: Case-control from a randomized clinical trial. Source of cases: Randomized clinical trial. Source of controls: Randomized clinical trial SELECT: Case-cohort from a randomized clinical trial. Source of cases: Randomized clinical trial. Source of controls: Randomized clinical trial TAMPERE: Case-control - Finland, Retrospective, Observational, Population-based. Source of cases: Identified through linkage to the Finnish Cancer Registry and patient records; and the Finnish arm of the ERSPC study. Source of controls: Cohort participants without a diagnosis of cancer UGANDA: Uganda Prostate Cancer Study: Uganda is a case-control study of prostate cancer in Kampala Uganda that was initiated in 2011. Men with prostate cancer were enrolled from the Urology unit at Mulago Hospital and men without prostate cancer (i.e. controls) were enrolled from other clinics (i.e. surgery) at the hospital. UKGPCS: ICR, UK. Source of cases: Cases identified through clinics at the Royal Marsden hospital and nationwide NCRN hospitals. Source of controls: Ken Muir's control- 2000 ULM: Case-control - Germany. Source of cases: familial cases (n=162): identified through questionnaires for family history by collaborating urologists all over Germany; sporadic cases (n=308): prostatectomy series performed in the Clinic of Urology Ulm between 2012 and 2014. Source of controls: age-matched controls (n=188): age-matched men without prostate cancer and negative family history collected in hospitals of Ulm WUGS/WUPCS: Cases Series, USA. Source of cases: Identified through clinics at Washington University in St. Louis. Source of controls: Men diagnosed and managed with prostate cancer in University based clinic. Acknowledgement Statements: Aarhus: This study was supported by the Danish Strategic Research Council (now Innovation Fund Denmark) and the Danish Cancer Society. The Danish Cancer Biobank (DCB) is acknowledged for biological material. AHS: This work was supported by the Intramural Research Program of the NIH, National Cancer Institute, Division of Cancer Epidemiology and Genetics (Z01CP010119). ATBC: This research was supported in part by the Intramural Research Program of the NIH and the National Cancer Institute. Additionally, this research was supported by U.S. Public Health Service contracts N01-CN-45165, N01-RC-45035, N01-RC-37004, HHSN261201000006C, and HHSN261201500005C from the National Cancer Institute, Department of Health and Human Services. BioVu: The dataset(s) used for the analyses described were obtained from Vanderbilt University Medical Center's BioVU which is supported by institutional funding and by the National Center for Research Resources, Grant UL1 RR024975-01 (which is now at the National Center for Advancing Translational Sciences, Grant 2 UL1 TR000445-06). Canary PASS: PASS was supported by Canary Foundation and the National Cancer Institute's Early Detection Research Network (U01 CA086402) CCI: This work was awarded by Prostate Cancer Canada and is proudly funded by the Movember Foundation - Grant # D2013-36.The CCI group would like to thank David Murray, Razmik Mirzayans, and April Scott for their contribution to this work. CerePP French Prostate Cancer Case-Control Study (ProGene): None reported COH: SLN is partially supported by the Morris and Horowitz Families Endowed Professorship COSM: The Swedish Research Council, the Swedish Cancer Foundation CPCS1 & CPCS2: Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev Ringvej 75, DK-2730 Herlev, DenmarkCPCS1 would like to thank the participants and staff of the Copenhagen General Population Study for their important contributions. CPDR: Uniformed Services University for the Health Sciences HU0001-10-2-0002 (PI: David G. McLeod, MD) CPS-II: The American Cancer Society funds the creation, maintenance, and updating of the Cancer Prevention Study II cohort. CPS-II thanks the participants and Study Management Group for their invaluable contributions to this research. We would also like to acknowledge the contribution to this study from central cancer registries supported through the Centers for Disease Control and Prevention National Program of Cancer Registries, and cancer registries supported by the National Cancer Institute Surveillance Epidemiology and End Results program. EPIC: The coordination of EPIC is financially supported by the European Commission (DG-SANCO) and the International Agency for Research on Cancer. The national cohorts are supported by the Danish Cancer Society (Denmark); the Deutsche Krebshilfe, Deutsches Krebsforschungszentrum and Federal Ministry of Education and Research (Germany); the Hellenic Health Foundation, Greek Ministry of Health; Greek Ministry of Education (Greece); the Italian Association for Research on Cancer (AIRC) and National Research Council (Italy); the Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF); the Statistics Netherlands (The Netherlands); the Health Research Fund (FIS), Regional Governments of Andalucía, Asturias, Basque Country, Murcia and Navarra, Spanish Ministry of Health ISCIII RETIC (RD06/0020), Red de Centros RCESP, C03/09 (Spain); the Swedish Cancer Society, Swedish Scientific Council and Regional Government of Skåne and Västerbotten, Fundacion Federico SA (Sweden); the Cancer Research UK, Medical Research Council (United Kingdom). EPICAP: The EPICAP study was supported by grants from Ligue Nationale Contre le Cancer, Ligue départementale du Val de Marne; Fondation de France; Agence Nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail (ANSES). The EPICAP study group would like to thank all urologists, Antoinette Anger and Hasina Randrianasolo (study monitors), Anne-Laure Astolfi, Coline Bernard, Oriane Noyer, Marie-Hélène De Campo, Sandrine Margaroline, Louise N'Diaye, and Sabine Perrier-Bonnet (Clinical Research nurses). ERSPC: This study was supported by the DutchCancerSociety (KWF94-869,98-1657,2002-277,2006-3518, 2010-4800), The Netherlands Organisation for Health Research and Development (ZonMW-002822820, 22000106, 50-50110-98-311, 62300035), The Dutch Cancer Research Foundation (SWOP), and an unconditional grant from Beckman-Coulter-HybritechInc. ESTHER: The ESTHER study was supported by a grant from the Baden Württemberg Ministry of Science, Research and Arts. The ESTHER group would like to thank Hartwig Ziegler, Sonja Wolf, Volker Hermann, Heiko Müller, Karina Dieffenbach, Katja Butterbach for valuable contributions to the study. FHCRC: The FHCRC studies were supported by grants R01-CA056678, R01-CA082664, and R01-CA092579 from the US National Cancer Institute, National Institutes of Health, with additional support from the Fred Hutchinson Cancer Research Center. FHCRC would like to thank all the men who participated in these studies. Gene-PARE: The Gene-PARE study was supported by grants 1R01CA134444 from the U.S. National Institutes of Health, PC074201 and W81XWH-15-1-0680 from the Prostate Cancer Research Program of the Department of Defense and RSGT-05-200-01-CCE from the American Cancer Society. Hamburg-Zagreb: None reported HPFS: The Health Professionals Follow-up Study was supported by grants UM1CA167552, CA133891, CA141298, and P01CA055075. HPFS are grateful to the participants and staff of the Physicians' Health Study and Health Professionals Follow-Up Study for their valuable contributions, as well as the following state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, and WY. IMPACT: The IMPACT study was funded by The Ronald and Rita McAulay Foundation, CR-UK Project grant (C5047/A1232), Cancer Australia, AICR Netherlands A10-0227, Cancer Australia and Cancer Council Tasmania, NIHR, EU Framework 6, Cancer Councils of Victoria and South Australia, and Philanthropic donation to Northshore University Health System. We acknowledge support from the National Institute for Health Research (NIHR) to the Biomedical Research Centre at The Institute of Cancer Research and Royal Marsden Foundation NHS Trust. IMPACT acknowledges the IMPACT study steering committee, collaborating centres, and participants. IPO-Porto: The IPO-Porto study was funded by Fundaçäo para a Ciência e a Tecnologia (FCT; UID/DTP/00776/2013 and PTDC/DTP-PIC/1308/2014) and by IPO-Porto Research Center (CI-IPOP-16-2012 and CI-IPOP-24-2015). MC and MPS are research fellows from Liga Portuguesa Contra o Cancro, Núcleo Regional do Norte. SM is a research fellow from FCT (SFRH/BD/71397/2010). IPO-Porto would like to express our gratitude to all patients and families who have participated in this study. Karuprostate: The Karuprostate study was supported by the the Frech National Health Directorate and by the Association pour la Recherche sur les Tumeurs de la ProstateKarusprostate thanks Séverine Ferdinand. KULEUVEN: F.C. and S.J. are holders of grants from FWO Vlaanderen (G.0684.12N and G.0830.13N), the Belgian federal government (National Cancer Plan KPC_29_023), and a Concerted Research Action of the KU Leuven (GOA/15/017). TVDB is holder of a doctoral fellowship of the FWO. LAAPC: This study was funded by grant R01CA84979 (to S.A. Ingles) from the National Cancer Institute, National Institutes of Health. Malaysia: The study was funded by the University Malaya High Impact Research Grant (HIR/MOHE/MED/35). Malaysia thanks all associates in the Urology Unit, University of Malaya, Cancer Research Initiatives Foundation (CARIF) and the Malaysian Men's Health Initiative (MMHI). MCCS: MCCS cohort recruitment was funded by VicHealth and Cancer Council Victoria. The MCCS was further supported by Australian NHMRC grants 209057, 251553, and 504711, and by infrastructure provided by Cancer Council Victoria. Cases and their vital status were ascertained through the Victorian Cancer Registry (VCR) and the Australian Institute of Health and Welfare (AIHW), including the National Death Index and the Australian Cancer Database. MCC-Spain: The study was partially funded by the Accion Transversal del Cancer, approved on the Spanish Ministry Council on the 11th October 2007, by the Instituto de Salud Carlos III-FEDER (PI08/1770, PI09/00773-Cantabria, PI11/01889-FEDER, PI12/00265, PI12/01270, and PI12/00715), by the Fundación Marqués de Valdecilla (API 10/09), by the Spanish Association Against Cancer (AECC) Scientific Foundation and by the Catalan Government DURSI grant 2009SGR1489. Samples: Biological samples were stored at the Parc de Salut MAR Biobank (MARBiobanc; Barcelona) which is supported by Instituto de Salud Carlos III FEDER (RD09/0076/00036). Also sample collection was supported by the Xarxa de Bancs de Tumors de Catalunya sponsored by Pla Director d'Oncologia de Catalunya (XBTC). MCC-Spain acknowledges the contribution from Esther Gracia-Lavedan in preparing the data. We thank all the subjects who participated in the study and all MCC-Spain collaborators. MD Anderson: Prostate Cancer Case-Control Studies at MD Anderson (MDA) supported by grants CA68578, ES007784, DAMD W81XWH-07-1-0645, and CA140388. MDACC_AS: None reported MEC: Funding provided by NIH grant U19CA148537 and grant U01CA164973. MIAMI (WFPCS): ACS MOFFITT: The Moffitt group was supported by the US National Cancer Institute (R01CA128813, PI: J.Y. Park). NMHS: Funding for the Nashville Men's Health Study (NMHS) was provided by the National Institutes of Health Grant numbers: RO1CA121060. PCaP only data: The North Carolina - Louisiana Prostate Cancer Project (PCaP) is carried out as a collaborative study supported by the Department of Defense contract DAMD 17-03-2-0052. For HCaP-NC follow-up data: The Health Care Access and Prostate Cancer Treatment in North Carolina (HCaP-NC) study is carried out as a collaborative study supported by the American Cancer Society award RSGT-08-008-01-CPHPS. For studies using both PCaP and HCaP-NC follow-up data please use: The North Carolina - Louisiana Prostate Cancer Project (PCaP) and the Health Care Access and Prostate Cancer Treatment in North Carolina (HCaP-NC) study are carried out as collaborative studies supported by the Department of Defense contract DAMD 17-03-2-0052 and the American Cancer Society award RSGT-08-008-01-CPHPS, respectively. For any PCaP data, please include: The authors thank the staff, advisory committees and research subjects participating in the PCaP study for their important contributions. For studies using PCaP DNA/genotyping data, please include: We would like to acknowledge the UNC BioSpecimen Facility and LSUHSC Pathology Lab for our DNA extractions, blood processing, storage and sample disbursement (https://genome.unc.edu/bsp). For studies using PCaP tissue, please include: We would like to acknowledge the RPCI Department of Urology Tissue Microarray and Immunoanalysis Core for our tissue processing, storage and sample disbursement. For studies using HCaP-NC follow-up data, please use: The Health Care Access and Prostate Cancer Treatment in North Carolina (HCaP-NC) study is carried out as a collaborative study supported by the American Cancer Society award RSGT-08-008-01-CPHPS. The authors thank the staff, advisory committees and research subjects participating in the HCaP-NC study for their important contributions. For studies that use both PCaP and HCaP-NC, please use: The authors thank the staff, advisory committees and research subjects participating in the PCaP and HCaP-NC studies for their important contributions. PCMUS: The PCMUS study was supported by the Bulgarian National Science Fund, Ministry of Education and Science (contract DOO-119/2009; DUNK01/2-2009; DFNI-B01/28/2012) with additional support from the Science Fund of Medical University - Sofia (contract 51/2009; 8I/2009; 28/2010). PHS: The Physicians' Health Study was supported by grants CA34944, CA40360, CA097193, HL26490, and HL34595. PHS members are grateful to the participants and staff of the Physicians' Health Study and Health Professionals Follow-Up Study for their valuable contributions, as well as the following state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, and WY. PLCO: This PLCO study was supported by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIHPLCO thanks Drs. Christine Berg and Philip Prorok, Division of Cancer Prevention at the National Cancer Institute, the screening center investigators and staff of the PLCO Cancer Screening Trial for their contributions to the PLCO Cancer Screening Trial. We thank Mr. Thomas Riley, Mr. Craig Williams, Mr. Matthew Moore, and Ms. Shannon Merkle at Information Management Services, Inc., for their management of the data and Ms. Barbara O'Brien and staff at Westat, Inc. for their contributions to the PLCO Cancer Screening Trial. We also thank the PLCO study participants for their contributions to making this study possible. Poland: None reported PROCAP: PROCAP was supported by the Swedish Cancer Foundation (08-708, 09-0677). PROCAP thanks and acknowledges all of the participants in the PROCAP study. We thank Carin Cavalli-Björkman and Ami Rönnberg Karlsson for their dedicated work in the collection of data. Michael Broms is acknowledged for his skilful work with the databases. KI Biobank is acknowledged for handling the samples and for DNA extraction. We acknowledge The NPCR steering group: Pär Stattin (chair), Anders Widmark, Stefan Karlsson, Magnus Törnblom, Jan Adolfsson, Anna Bill-Axelson, Ove Andrén, David Robinson, Bill Pettersson, Jonas Hugosson, Jan-Erik Damber, Ola Bratt, Göran Ahlgren, Lars Egevad, and Roy Ehrnström. PROGReSS: The PROGReSS study is founded by grants from the Spanish Ministry of Health (INT15/00070; INT16/00154; FIS PI10/00164, FIS PI13/02030; FIS PI16/00046); the Spanish Ministry of Economy and Competitiveness (PTA2014-10228-I), and Fondo Europeo de Desarrollo Regional (FEDER 2007-2013). ProMPT: Founded by CRUK, NIHR, MRC, Cambride Biomedical Research Centre ProtecT: Founded by NIHR. ProtecT and ProMPT would like to acknowledge the support of The University of Cambridge, Cancer Research UK. Cancer Research UK grants (C8197/A10123) and (C8197/A10865) supported the genotyping team. We would also like to acknowledge the support of the National Institute for Health Research which funds the Cambridge Bio-medical Research Centre, Cambridge, UK. We would also like to acknowledge the support of the National Cancer Research Prostate Cancer: Mechanisms of Progression and Treatment (PROMPT) collaborative (grant code G0500966/75466) which has funded tissue and urine collections in Cambridge. We are grateful to staff at the Welcome Trust Clinical Research Facility, Addenbrooke's Clinical Research Centre, Cambridge, UK for their help in conducting the ProtecT study. We also acknowledge the support of the NIHR Cambridge Biomedical Research Centre, the DOH HTA (ProtecT grant), and the NCRI/MRC (ProMPT grant) for help with the bio-repository. The UK Department of Health funded the ProtecT study through the NIHR Health Technology Assessment Programme (projects 96/20/06, 96/20/99). The ProtecT trial and its linked ProMPT and CAP (Comparison Arm for ProtecT) studies are supported by Department of Health, England; Cancer Research UK grant number C522/A8649, Medical Research Council of England grant number G0500966, ID 75466, and The NCRI, UK. The epidemiological data for ProtecT were generated though funding from the Southwest National Health Service Research and Development. DNA extraction in ProtecT was supported by USA Dept of Defense award W81XWH-04-1-0280, Yorkshire Cancer Research and Cancer Research UK. The authors would like to acknowledge the contribution of all members of the ProtecT study research group. The views and opinions expressed therein are those of the authors and do not necessarily reflect those of the Department of Health of England. The bio-repository from ProtecT is supported by the NCRI (ProMPT) Prostate Cancer Collaborative and the Cambridge BMRC grant from NIHR. We thank the National Institute for Health Research, Hutchison Whampoa Limited, the Human Research Tissue Bank (Addenbrooke's Hospital), and Cancer Research UK. PROtEuS: PROtEuS was supported financially through grants from the Canadian Cancer Society (13149, 19500, 19864, 19865) and the Cancer Research Society, in partnership with the Ministère de l'enseignement supérieur, de la recherche, de la science et de la technologie du Québec, and the Fonds de la recherche du Québec - Santé.PROtEuS would like to thank its collaborators and research personnel, and the urologists involved in subjects recruitment. We also wish to acknowledge the special contribution made by Ann Hsing and Anand Chokkalingam to the conception of the genetic component of PROtEuS. QLD: The QLD research is supported by The National Health and Medical Research Council (NHMRC) Australia Project Grants (390130, 1009458) and NHMRC Career Development Fellowship and Cancer Australia PdCCRS funding to J Batra. The QLD team would like to acknowledge and sincerely thank the urologists, pathologists, data managers and patient participants who have generously and altruistically supported the QLD cohort. RAPPER: RAPPER is funded by Cancer Research UK (C1094/A11728; C1094/A18504) and Experimental Cancer Medicine Centre funding (C1467/A7286). The RAPPER group thank Rebecca Elliott for project management. SABOR: The SABOR research is supported by NIH/NCI Early Detection Research Network, grant U01 CA0866402-12. Also supported by the Cancer Center Support Grant to the Cancer Therapy and Research Center from the National Cancer Institute (US) P30 CA054174. SCCS: SCCS is funded by NIH grant R01 CA092447, and SCCS sample preparation was conducted at the Epidemiology Biospecimen Core Lab that is supported in part by the Vanderbilt-Ingram Cancer Center (P30 CA68485). Data on SCCS cancer cases used in this publication were provided by the Alabama Statewide Cancer Registry; Kentucky Cancer Registry, Lexington, KY; Tennessee Department of Health, Office of Cancer Surveillance; Florida Cancer Data System; North Carolina Central Cancer Registry, North Carolina Division of Public Health; Georgia Comprehensive Cancer Registry; Louisiana Tumor Registry; Mississippi Cancer Registry; South Carolina Central Cancer Registry; Virginia Department of Health, Virginia Cancer Registry; Arkansas Department of Health, Cancer Registry, 4815 W. Markham, Little Rock, AR 72205. The Arkansas Central Cancer Registry is fully funded by a grant from National Program of Cancer Registries, Centers for Disease Control and Prevention (CDC). Data on SCCS cancer cases from Mississippi were collected by the Mississippi Cancer Registry which participates in the National Program of Cancer Registries (NPCR) of the Centers for Disease Control and Prevention (CDC). The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the CDC or the Mississippi Cancer Registry. SCPCS: SCPCS is funded by CDC grant S1135-19/19, and SCPCS sample preparation was conducted at the Epidemiology Biospecimen Core Lab that is supported in part by the Vanderbilt-Ingram Cancer Center (P30 CA68485). SEARCH: SEARCH is funded by a program grant from Cancer Research UK (C490/A10124) and supported by the UK National Institute for Health Research Biomedical Research Centre at the University of Cambridge. SNP_Prostate_Ghent: The study was supported by the National Cancer Plan, financed by the Federal Office of Health and Social Affairs, Belgium. SPAG: Wessex Medical ResearchHope for Guernsey, MUG, HSSD, MSG, Roger Allsopp STHM2: STHM2 was supported by grants from The Strategic Research Programme on Cancer (StratCan), Karolinska Institutet; the Linné Centre for Breast and Prostate Cancer (CRISP, number 70867901), Karolinska Institutet; The Swedish Research Council (number K2010-70X-20430-04-3) and The Swedish Cancer Society (numbers 11-0287 and 11-0624); Stiftelsen Johanna Hagstrand och Sigfrid Linnérs minne; Swedish Council for Working Life and Social Research (FAS), number 2012-0073STHM2 acknowledges the Karolinska University Laboratory, Aleris Medilab, Unilabs and the Regional Prostate Cancer Registry for performing analyses and help to retrieve data. Carin Cavalli-Björkman and Britt-Marie Hune for their enthusiastic work as research nurses. Astrid Björklund for skilful data management. We wish to thank the BBMRI.se biobank facility at Karolinska Institutet for biobank services. PCPT & SELECT are funded by Public Health Service grants U10CA37429 and 5UM1CA182883 from the National Cancer Institute. SWOG and SELECT thank the site investigators and staff and, most importantly, the participants who donated their time to this trial. TAMPERE: The Tampere (Finland) study was supported by the Academy of Finland (251074), The Finnish Cancer Organisations, Sigrid Juselius Foundation, and the Competitive Research Funding of the Tampere University Hospital (X51003). The PSA screening samples were collected by the Finnish part of ERSPC (European Study of Screening for Prostate Cancer). TAMPERE would like to thank Riina Liikanen, Liisa Maeaettaenen and Kirsi Talala for their work on samples and databases. UGANDA: None reported UKGPCS: UKGPCS would also like to thank the following for funding support: The Institute of Cancer Research and The Everyman Campaign, The Prostate Cancer Research Foundation, Prostate Research Campaign UK (now Prostate Action), The Orchid Cancer Appeal, The National Cancer Research Network UK, The National Cancer Research Institute (NCRI) UK. We are grateful for support of NIHR funding to the NIHR Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust. UKGPCS should also like to acknowledge the NCRN nurses, data managers, and consultants for their work in the UKGPCS study. UKGPCS would like to thank all urologists and other persons involved in the planning, coordination, and data collection of the study. ULM: The Ulm group received funds from the German Cancer Aid (Deutsche Krebshilfe). WUGS/WUPCS: WUGS would like to thank the following for funding support: The Anthony DeNovi Fund, the Donald C. McGraw Foundation, and the St. Louis Men's Group Against Cancer.
ATACseq data for this study.
SNP array study for UTUC
Objectives The Heart and Vascular Health Study (HVH) is a case-control study of risk factors for the development of myocardial infarction (MI), stroke, venous thrombosis (VT), and atrial fibrillation (AF). The study setting is Group Health, an integrated health care delivery system in Washington State. Only VT cases and early-onset AF cases are included as part of TOPMed. Background The HVH study originated in 1988 with the examination of risk factors for MI. Over the ensuing years, the study has been funded by a series of grants which have added case subjects with stroke, VT, and AF. Study aims focused on the associations of medication use with cardiovascular events, and starting in 1997, the study aims expanded to include genetic associations with cardiovascular disease. Participants recruited in 2009 or later who provided blood samples for genetic analysis were asked for consent to deposit genetic and phenotypic data in dbGaP. Design As part of the HVH study, case subjects were identified by searching for ICD-9 codes consistent with MI, stroke, VT, or AF, and medical records were reviewed to confirm the diagnosis. Control subjects were identified at random from the Group Health enrollment and were matched to MI cases. All subjects have an index date. For cases, the index date was assigned as the date that the cardiovascular event (MI, stroke, VT, or AF) came to clinical attention. For controls, the index date was a random date within the range of the case index dates. For both cases and controls, information was collected from the inpatient and outpatient medical record, by telephone interview with consenting survivors, and from the Group Health pharmacy and laboratory databases. Consenting participants provided a blood specimen. Subjects Only VT and early-onset AF cases from HVH are included in TOPMed. Within the HVH study, VT and AF cases were diagnosed in both inpatient and outpatient settings, and only incident cases are eligible for inclusion in TOPMed. Genetic Research Genetic factors underlying cardiovascular disease are studied using DNA isolated from the blood samples. Phenotype data for HVH study participants are available through dbGaP phs001013.
In acute myeloid leukemia (AML) with inv(3)(q21;q26) or t(3;3)(q21;q26), a translocated GATA2 enhancer drives oncogenic expression of EVI1. We generated an EVI1-GFP AML model and applied an unbiased CRISPR/Cas9 enhancer scan to uncover sequence motifs essential for EVI1 transcription. Using this approach, we pinpoint a single regulatory element in the translocated GATA2 enhancer that is critically required for aberrant EVI1 expression while being dispensable for GATA2 expression from its endogenous locus. This element contains a DNA binding motif for the transcription factor MYB that heavily occupies this site specifically at the translocated allele. MYB knockout as well as peptidomimetic blockade of p300-dependent MYB function resulted in downregulation of EVI1 but not of GATA2. Targeting MYB or mutating its DNA-binding motif within the GATA2 enhancer resulted in myeloid differentiation and cell death, suggesting that interference with MYB-driven EVI1 transcription provides a potential entry point for therapy of inv(3)/t(3;3) AMLs.
Systemic pan-tumor analyses may reveal the significance of common features implicated in cancer immunogenicity and patient survival. Here, we provide a comprehensive multi-omics data set for 32 patients across 25 tumor types for proteogenomic-based discovery of neoantigens. By using an optimized computational approach, we discover a large number of tumor-specific and tumor-associated antigens. To create a pipeline for the identification of neoantigens in our cohort, we combine DNA and RNA sequencing with MS-based immunopeptidomics of tumor specimens, followed by the assessment of their immunogenicity and an in-depth validation process. We detect a broad variety of non-canonical HLA-binding peptides in the majority of patients demonstrating partially immunogenicity. Our validation process allows for the selection of 32 potential neoantigen candidates. The majority of neoantigen candidates originates from variants identified in the RNA data set, illustrating the relevance of RNA as a still understudied source of cancer antigens. This study underlines the importance of RNA-centered variant detection for the identification of shared biomarkers and potentially relevant neoantigen candidates.
WTCCC genome-wide case-control association study for Multiple Sclerosis (MS) using the 1958 British Birth Cohort collection as controls.
WTCCC genome-wide case-control association study for Breast cancer (BC) using the 1958 British Birth Cohort collection as controls.
WTCCC genome-wide case-control association study for Ankylosing Spondylitis (AS) using the 1958 British Birth Cohort collection as controls.
Targeted capture sequencing for cases with MDS who were subjected to unrelated bone marrow transplantation via Japan marrow donor program
The dataset included Dynatag data for the occupancy of transcription factors and single nuclei RNA-seq data. Corresponding metadata is provided for both experiments.
Cell free DNA sequencing data for 233 samples across multiple cancer types for cfDNA cohort
Ionizing radiation is an effective therapeutic agent for cancer treatment as well as a potent carcinogen. Sensitivity to the cell-killing effects of radiation can vary across human population with a subset of individuals displaying extreme hypersensitivity. It is usually attributable to inherited defects in DNA damage response pathways. The present study was designed to elucidate the genetic basis of variation in hypersensitivity to radiation exposure through exome sequencing of radiosensitive individuals, with the ultimate goal of identifying genes with the most significant effects on cellular DNA damage responses. The study participants included subjects referred for clinical testing for Ataxia-telangiectasia (A-T), Nijmegen Breakage Syndrome (NBS) or Ligase IV Syndrome. These are rare, recessive genetic disorders and hypersensitivity to radiation exposure is a common phenotype among individuals affected by all the three disorders. The study participants exhibited phenotypic characteristics similar to individuals with A-T, NBS or Ligase IV Syndrome, but lacked the causative mutations in ATM (GeneID:472) or NBN (GeneID:4683) genes. For further validation of the radiation sensitivity phenotype among the enrolled subjects, B-lymphoblastoid cells lines were established for each subject from peripheral blood lymphocytes. Each cell line was evaluated for displaying impaired survival rates relative to normal controls after exposure to ionizing radiation. 53 subjects with validated phenotype were finally included in the study and DNA extracted from their B-lymphoblastoid cell lines was used for exome sequencing. This sequencing data for radiation sensitive subjects is being made available in the dbGaP. It is hoped that this resource will be beneficial for researchers who wish to further investigate components of human cellular DNA damage response pathways and/or genetic architecture underlying radiation hypersensitivity. This data may also aid in the rational design of new radiosensitizing or radioprotective agents.
The STOP II trial evaluated whether prophylactic transfusion in patients with sickle cell disease and high risk of stroke can be safely halted after 30 months of treatment during which patients became low risk for stroke.Stroke causes substantial morbidity in children with sickle cell disease. To prevent first strokes, the Stroke Prevention Trial in Sickle Cell Anemia (STOP) used prophylactic transfusions in children who were identified by transcranial Doppler (TCD) ultrasonography as being at high risk for stroke. This strategy reduced the incidence of stroke among such children from 10% per year to less than 1% per year, leading to recommendations for TCD screening and prophylactic transfusion for children with abnormal velocities on ultrasonography. Despite the reduced risk of stroke, long-term use of transfusions can cause adverse side effects, such as iron overload or alloimmunization. However, cessation of transfusions is associated with recurrence of stroke, and at the time of the STOP II trial, there were no clinical or laboratory indicators to guide the duration of prophylaxis. Therefore the STOP II trial was initiated to determine whether transfusions could be limited by monitoring patients with TCD examinations after transfusions were halted and resuming transfusions if the examination indicated a high risk of stroke.The trial was halted for safety concerns after 79 of a planned 100 children were randomized. Discontinuation of transfusion for the prevention of stroke in children with sickle cell disease resulted in a high rate of reversion to abnormal blood-flow velocities on Doppler studies and stroke incidence.Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact.
monozygotic twin discordant for schizophrenia
This project aims to investigate gene expression biomarkers for noise-induced sleep disruption and cognitive changes. The project is a sub-study, part of the larger ASCENT COE project 86 designed to test the ability of broadband pink noise to serve as a countermeasure for sleep loss from simulated aircraft noise. Gene expression research was sponsored by the Federal Aviation Administration.
Glioblastoma multiforme (GBM) remains a highly aggressive brain tumor with limited treatment options and poor prognosis. Temozolomide (TMZ) is the only approved first-line therapy, but frequent resistance limits its efficacy, highlighting the urgent need for alternative treatments. Patient-derived glioblastoma organoids (GBOs) offer a promising preclinical model for personalized drug testing and therapy development.
This dataset contains RNA004 DRS data for a single patient sample with heterozygous inactivating SNPs for the methyltransferase METTL5. We provide 1) all reads in a GRCh38 aligned bam file + unaligned reads and 2) filtered reads just for the relevant part of chrR. Both bam files have been called with dorado 0.7.2 to contain the neccessary m6A methylation information. Companion datasets are 1) EGAS50000001201 for DRS of a healthy control with intact METTL5 and 2) PRJEB74238 for IVT 18S rRNA vector data as unmodified control. Please note, that both the companion datasets contain pod5 data, to faciliate re-basecalling.
This dataset includes all FASTQ files for 11 samples where different capture-based methods for transcriptome profiling have been tested. Specifically, we have the 'traditional' RNA-seq experiment with fresh frozen (FF) material, and 3 different capture methods for the matching formalin-fixed paraffin-embedded samples: Agilent (AGI), IDT, and Twist Biosciences (TBS). In total, there are 43 samples with paired-end FASTQ files (1 sample did not have sufficient material to test all methods). Samples are identified by the R01-R11 IDs with a suffix that indicates the capture method used (or FF for fresh frozen).
RNAseq of baseline tumor tissue obtained during TUR to identify biomarkers for ICB response in MIBC. Constitutes the entire NABUCCO phase 1B clinical trial cohort. The NABUCCO 1 trial contains 18 single-end RNA sequenced samples and 6 paired end RNA sequenced samples. The NABUCCO 2 trial contains 25 paired end RNA sequenced samples. The file type for all of the samples is FASTQ. For single end RNA sequencing, Illumina HiSeq 2500 was used as the sequencing platform. For paired end RNA sequencing, the Illumina NovaSeq 6000 was used as the sequencing platform.
ORCHID was a multicenter, blinded, placebo-controlled randomized trial conducted at 34 hospitals in the US between April 2 and June 19, 2020. Adults hospitalized with respiratory symptoms from severe acute respiratory syndrome coronavirus 2 infection were enrolled, with the last outcome assessment on July 17, 2020. The planned sample size was 510 patients with five interim analyses; however, the trial was stopped at the fourth interim analysis for futility with a sample size of 479 patients.The distribution of the day 14 clinical status score (measured using a 7-category ordinal scale) was not significantly different for patients randomized to receive hydroxychloroquine compared with placebo.Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact.
The NeuroGAP-Psychosis study was conducted in South Africa, Kenya, Uganda and Ethiopia as a response to the lack of genetic diversity in large genomic studies of psychiatric disorders. The study aims to expand knowledge of the genetic and environmental risk factors for neuropsychiatric disorders in Africa through large-scale sample collection and analysis. The initial design is a case-control study in which cases are individuals with schizophrenia or bipolar disorder and controls are age, sex and ancestry matched with individuals from the same geographic location. Cases are patients who are recruited from clinical facilities, both inpatient and outpatient. Controls are people who present for treatment for general medical conditions at health facilities. Data on phenotype, mental disorders, history of physical health problems, substance use and history of past traumatic events was collected from all participants. Additionally, a sample of saliva is collected for DNA extraction. DNA samples were sent to the Broad Institute for genotyping using Illumina Infinium Global Screening Array.
This is a genome-wide association study (GWAS) of global brain tissue volumes in human infants. The published study for this project includes 561 infants, and 239 parents gave consent for data sharing through dbGaP. An intronic single-nucleotide polymorphism (SNP) in IGFBP7 (rs114518130; GeneID: 3490) met genome-wide significance for gray matter volume (P=4.15x10-10). An intronic SNP in WWOX (rs10514437; GeneID: 51741) neared genome-wide significance for white matter volume (P=1.56x10-8). Additional loci with small P-values include psychiatric GWAS associations and transcription factors expressed in the developing brain. Genetic risk scores for schizophrenia and ASD, and the number of genes affected by rare copy number variants (CNV burden) did not predict global brain tissue volumes. Integrating these results with large-scale GWAS in adolescents [Philadelphia Neurodevelopmental Cohort (PNC)] and adults [Enhancing Neuro Imaging Genetics through Meta-Analysis version 2 (ENIGMA2)] suggested minimal overlap between common variants impacting brain volumes at different ages.
GABAergic interneurons are essential for neural circuit function and their loss or dysfunction is implicated in human neuropsychiatric disease. In vitro methods for interneuron generation hold promise for studying human cellular and functional properties and ultimately therapeutic cell replacement. We used a protocol for generating cortical interneurons from hESCs and analyzed the properties and maturation timecourse of cell types using single-cell RNAseq (data available at GEO under: GSE93802 on March 10 2017). Transcriptomic profiles of the hESC-derived interneurons were compared to several different populations of cells from mid-gestation human neocortex that showed differing levels of PAX6 and SOX2 expression. For this study, 104 samples of 100 human neocortical cells each, have been sorted based on SOX2 and PAX6 expression, mRNA recovered from the fixed cells by FRISCR, and transcriptomic profiles generated by SmartSeq2. The RNA-seq data from the 104 100-cell samples is included in this dbGaP study.
Genome engineering using CRISPR/Cas9 technology enables simple, efficient and precise genomic modifications in human cells. Conventional immortalized cell lines can be easily edited or screened using genome-wide libraries with lentiviral transduction. However, cell types derived from the differentiation of induced Pluripotent Stem Cells (iPSC), which often represent more relevant, patient-derived models for human pathology, are much more difficult to engineer as CRISPR/Cas9 delivery to these differentiated cells can be inefficient and toxic. Here, we present an efficient, lentiviral transduction protocol for delivery of CRISPR/Cas9 to macrophages derived from human iPSC with efficiencies close to 100%. We demonstrate CRISPR/Cas9 knockouts for three non-essential proof-of-concept genes - HPRT1, PPIB and CDK4. We then scale the protocol and validate for a genome-wide pooled CRISPR/Cas9 loss-of-function screen. This methodology enables, for the first time, systematic exploration of macrophage involvement in immune responses, chronic inflammation, neurodegenerative diseases and cancer progression, using efficient genome editing techniques.
The EVE Asthma Genetics Consortium comprises U.S. investigators who have conducted genome-wide association studies (GWAS) of asthma; the main objective is to combine results of individual studies to increase the overall power to identify loci for asthma and asthma-associated traits. The consortium includes investigators at 9 U.S. institutions with GWAS results for >10,000 individuals representing European American, African American, African Caribbean, U.S. Hispanic, and Mexican populations and includes the following studies: The Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-Ethnicity (SAPPHIRE) The Genetic Research on Asthma in the African Diaspora (GRAAD) Study The Genetics of Asthma in Latino Americans (GALA 1) Study The Childhood Asthma Management Program (CAMP) The Childhood Asthma Research and Education (CARE) Network The Children's Health Study (CHS) Mexico City Childhood Asthma Study (MCCAS) The Chicago Asthma Genetics Study (CAG)* The National Heart, Lung, and Blood Institute Collaborative Studies of the Genetics of Asthma (CSGA)* The Severe Asthma Research Program (SARP)* (*CAG, CSGA, and SARP are part of the NHLBI-supported SNP Typing for Association with Multiple Phenotypes from Existing Epidemiologic Data (STAMPEED) consortium.) For the GWAS, we developed a common set of >1 million genotyped and imputed SNPs from the EVE Asthma Genetics Consortium to be tested for association with asthma and associated phenotypes in all samples and combined p-values for a grand meta-analysis for asthma gene discovery. A subset of 296 individuals representing African American, European American, and Latino ancestry were selected for whole genome sequencing. The broad goals of this project were to characterize the genetic architecture of asthma and associated quantitative phenotypes (e.g., lung function, total serum IgE) in ethnically diverse populations from the U.S., Mexico, Puerto Rico, and Barbados.
Objectives The Heart and Vascular Health Study (HVH) is a case-control study of risk factors for the development of myocardial infarction (MI), stroke, venous thrombosis (VT), and atrial fibrillation (AF). The study setting is Group Health, an integrated health care delivery system in Washington State. Background The HVH originated in 1988 with the examination of risk factors for MI. Over the ensuing years, the study has been funded by a series of grants, which have added case subjects with stroke, VT, and AF, and used a common control group. Study aims have focused on the associations of medication use with cardiovascular events. Starting in 1997, the study aims expanded to include genetic associations with cardiovascular disease. Participants recruited in 2009 or later and who provided blood samples for genetic analysis were asked for consent to deposit genetic and phenotype data in dbGaP. Design As part of the HVH study, case subjects were identified by searching for ICD-9 codes consistent with MI, stroke, VT, or AF, and medical records were reviewed to confirm the diagnosis. Control subjects were identified at random from the Group Health enrollment and were matched to MI cases. All subjects have an index date. For cases, the index date was assigned as the date that the cardiovascular event (MI, stroke, VT, or AF) came to clinical attention. For controls, the index date was a random date within the range of the case index dates. For both cases and controls, information was collected from the inpatient and outpatient medical record, by telephone interview with consenting survivors, and from the Group Health pharmacy and laboratory databases. Consenting participants provided a blood specimen. Genetic Research Genetic factors underlying cardiovascular disease are studied using DNA isolated from the blood samples.
We established lymphoblastoid cell lines from 10 adult individuals of Tibetan ancestry living in the Chicago area. These lines were reprogrammed to induced pluripotent stem cells (iPSC). We validated genetic ancestry by genome-wide SNP array genotyping and population genetic analyses. After being subjected to standard quality control testing iPSCs were differentiated into endothelial cells. Following differentiation, endothelial cells were isolated via a pull down protocol using beads coated with an antibody for a canonical surface cell marker of the vascular endothelium (CD144). Purified vascular endothelial cells were cultured in parallel in normoxia (20% O2) and hypoxia (1% O2) for 48 hours prior to harvesting and processing for bulk RNA-sequencing. We provide imputed genotype data and bulk RNA-sequencing data in normoxia and in hypoxia for each of the 10 individuals. We also provide multiplexed scRNA-sequencing data for the 10 Tibetan individuals pooled with 10 CHB individuals from the 1000 Genome Project. Additionally, we provide scRNAseq data for the cardiomyocytes derived from the same iPSC lines from the Tibetan individuals pooled together with cardiomyocytes derived from iPSC lines of 10 CHB individuals from the 1000 Genome Project. Lymphoblastoid cell lines from the CHB were reprogrammed to iPSCs and differentiated to cardiomyocytes using the same protocols as used for the Tibetans. The batches of 4 lines were balanced by sex and population. These iPSC-derived cardiomyocytes were cultured in hypoxia (1% O2) for 48 hours and subjected to scRNAseq in pooled batches of 3 or 4 lines. The CHB individuals included in this analysis were: NA18528, NA18531, NA18557, NA18596, NA18606, NA18608, NA18614, NA18619, NA18633, and NA18748.
Sequencing of cell-free DNA in the blood of cancer patients (“liquid biopsy”) provides attractive opportunities not only for early diagnosis, but also for minimally invasive monitoring of treatment response and disease courses. To unlock liquid biopsy analysis for pediatric tumors with few genetic aberrations, we developed an integrated genetic/epigenetic analysis method and applied it to 241 deep whole-genome sequencing profiles of 95 patients with Ewing sarcoma and 31 patients with other pediatric sarcomas. We achieved sensitive detection and classification of circulating tumor DNA in peripheral blood independent of any genetic alterations. We evaluated different metrics for cell-free DNA fragmentation analysis and developed LIQUORICE, a bioinformatic tool for detecting circulating tumor DNA based on tumor-specific chromatin structure. Using machine learning methods, we combined several fragmentation-based metrics into an integrated approach for liquid biopsy analysis tailored to cancers with low mutation rates but widespread epigenetic deregulation. Clinical associations highlighted the potential value of cfDNA fragmentation patterns as prognostic biomarkers in Ewing sarcoma. Additionally, we performed low coverage whole-genome-sequencing on 43 tumor biopsy samples from patients with Ewing sarcoma, in order to compare copy number aberrations detected in cell-free DNA and biopsy samples of the same patients. For validation of the epigenetic signatures inferred from cell-free DNA, we further performed reduced representation bisulfite sequencing (RRBS) on 38 matched biopsy samples from patients with Ewing sarcoma. In summary, our study provides a comprehensive analysis of circulating tumor DNA beyond recurrent somatic mutations, and it renders the benefits of liquid biopsy more readily accessible for childhood cancers.
