ID
45443
Descripción
Principal Investigator: Susan K. Dutcher, McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA MeSH: https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000756 We propose to undertake, at the McDonnell Genome Institute of Washington University, a collaborative exome sequencing project of ~10,000 samples from a large Finnish population cohort, FINRISK, a participating component of the Sequencing Initiative Suomi (SISu) consortium. Together these sequenced samples will provide a unique resource for identification of infrequent or rare variants with a large impact on cardiovascular and metabolic disorders as well as on a wide range of heritable, disease-related quantitative phenotypes. Our collaborative group has already shown, in exome sequencing studies of smaller Finnish samples, that numerous loss of function variants are dramatically more frequent in Finland compared to other European populations, and that such variants demonstrate strong associations to several disease-related traits. Finland is the largest population isolate in Europe and the enrichment of these variants reflects its rapid growth from a severe population bottleneck about 100 generations ago. Northern and Eastern parts of Finland experienced additional, more recent bottlenecks, and therefore the enrichment of particular high-impact variants in these regions is even more extreme (Stoll et al., 2013, PMID: 23912948). We therefore propose to focus exome sequencing efforts on about 10,000 members of FINRISK who are specifically drawn from these sub-isolate regions. As a very wide range of phenotypes are available from this cohort (including cardiovascular and metabolic disease outcomes obtained from national registries) we hypothesize that the proposed exome sequencing will identify numerous new disease-related associations. Within the National Biobanks of Finland (www.nationalbiobanks.fi) we have DNA and tissue samples from over 200,000 individuals of whom 50,000 have GWAS data; these samples provide an exceptional resource for both imputation from the sequencing studies proposed here, as well as for replication of associations.
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Versiones (1)
- 6/12/22 6/12/22 - Simon Heim
Titular de derechos de autor
Susan K. Dutcher, McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
Subido en
6 de diciembre de 2022
DOI
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Licencia
Creative Commons BY 4.0
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dbGaP phs000756 Exome Sequence of Finnish Sub-Isolate Samples from the FINRISK Cohort
The subject consent data table includes subject IDs and consent information.
- StudyEvent: SEV1
- The subject consent data table includes subject IDs and consent information.
- The subject sample mapping data table includes a mapping of study subject IDs to sample IDs. Samples are the final preps submitted for genotyping, sequencing, and/or expression data. For example, if one patient (subject ID) gave one sample, and that sample was processed differently to generate 2 sequencing runs, there would be two rows, both using the same subject ID, but having 2 unique sample IDs.
- This sample attributes table includes analyte type and tissue type.
- The subject phenotypes data table includes subject's sex, age, anthropometric measurements (n=5 variables; height, weight, waist, hip, and BMI), systolic and diastolic blood pressure, blood measurements (n=6 variables; total cholesterol, LDL, HDL, total triglycerides, plasma adiponectin, and creatine), and medications (n=2 variables; blood pressure and lipids).
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The subject consent data table includes subject IDs and consent information.
- StudyEvent: SEV1
- The subject consent data table includes subject IDs and consent information.
- The subject sample mapping data table includes a mapping of study subject IDs to sample IDs. Samples are the final preps submitted for genotyping, sequencing, and/or expression data. For example, if one patient (subject ID) gave one sample, and that sample was processed differently to generate 2 sequencing runs, there would be two rows, both using the same subject ID, but having 2 unique sample IDs.
- This sample attributes table includes analyte type and tissue type.
- The subject phenotypes data table includes subject's sex, age, anthropometric measurements (n=5 variables; height, weight, waist, hip, and BMI), systolic and diastolic blood pressure, blood measurements (n=6 variables; total cholesterol, LDL, HDL, total triglycerides, plasma adiponectin, and creatine), and medications (n=2 variables; blood pressure and lipids).
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