ID
45055
Beschreibung
Principal Investigator: Michele M. Sale, PhD, University of Virginia, Charlottesville, VA, USA MeSH: Type 2 Diabetes Mellitus,Dyslipidemia https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000433 Recent genome-wide association studies (GWAS) have successfully identified genetic variants that influence diabetes risk in European populations, however most do not have a major impact on diabetes risk in populations of African descent. The African American (AA) population from the Sea Islands of coastal South Carolina and Georgia has high rates of type 2 diabetes, low levels of admixture, and in general, consume a diet rich in saturated fats. We postulate that this unique combination of ancestral and environmental factors results in a more consistent penetrance of diabetes risk alleles, as well as enrichment of risk alleles of African origin. The existing DNA samples and rich phenotypic data from the Sea Island Families Project comprise a unique resource for genetic studies of type 2 diabetes and related metabolic traits such as dyslipidemia. Our central hypothesis is that the increased risk for T2DM in AA compared with European American (EA) is due, in part, to susceptibility alleles of African origin, and that these alleles can be identified using a GWAS. The Specific Aims are to: 1) Identify genetic risk factors for type 2 diabetes utilizing DNA samples and data from the Sea Island Families Project, Reasons for Geographic and Racial Differences in Stroke (REGARDS) Study recruited from SC, GA, NC, and AL; and a GWAS approach; 2) Identify genetic contributors to lipoprotein subclasses in African Americans using the lipoprotein subclass profile (particle size and concentration for multiple subclasses of VLDL, LDL, and HDL) assessed by NMR at LipoScience, Inc., and the GWAS data from Aim 1. The rationale for this project is that identification and validation of novel pathophysiological pathways and informed selection of candidate genes for diabetes risk will inform development of new, targeted prevention and treatment strategies in this underserved, high risk population.
Link
https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000433
Stichworte
Versionen (2)
- 04.08.22 04.08.22 - Chiara Middel
- 12.10.22 12.10.22 - Adrian Schulz
Rechteinhaber
Michele M. Sale, PhD, University of Virginia, Charlottesville, VA, USA
Hochgeladen am
4. August 2022
DOI
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Lizenz
Creative Commons BY 4.0
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dbGaP phs000433 The Sea Islands Genetic Network (SIGNET)
This data table contains subject IDs, consent group information, affection status and subject aliases. In this study, there are 4 different subject study sources (COBRE, SUGAR, REGARDS and SLEIGH) and 1 cell repository (Coriell).
- StudyEvent: SEV1
- Eligibility Criteria
- This data table contains subject IDs, consent group information, affection status and subject aliases. In this study, there are 4 different subject study sources (COBRE, SUGAR, REGARDS and SLEIGH) and 1 cell repository (Coriell).
- The data table contains pedigree, gender and twin information of study participants.
- The data table contains 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. The data table also includes a mapping of sample IDs to other sample ID aliases and sample use.
- The subject phenotype data table includes , race (n=1 variable), age and year of enrollment (n=2 variables), anthropometric measures (n=3 variables), blood pressure and pulse measures (n=3 variables), diagnosis of diabetes, hypertension and hyperlipidemia (n=3 variables), blood glucose test (n=3 variables), cholesterol and lipid levels (n=24 variables), diabetic diet (n=2 variables), and medication use (n=6 variables).
- The sample attributes data table includes sample type, body site where sample was extracted, sample analyte type and additional comments to indicate rela duplicate samples genotyped for QC.
Ähnliche Modelle
This data table contains subject IDs, consent group information, affection status and subject aliases. In this study, there are 4 different subject study sources (COBRE, SUGAR, REGARDS and SLEIGH) and 1 cell repository (Coriell).
- StudyEvent: SEV1
- Eligibility Criteria
- This data table contains subject IDs, consent group information, affection status and subject aliases. In this study, there are 4 different subject study sources (COBRE, SUGAR, REGARDS and SLEIGH) and 1 cell repository (Coriell).
- The data table contains pedigree, gender and twin information of study participants.
- The data table contains 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. The data table also includes a mapping of sample IDs to other sample ID aliases and sample use.
- The subject phenotype data table includes , race (n=1 variable), age and year of enrollment (n=2 variables), anthropometric measures (n=3 variables), blood pressure and pulse measures (n=3 variables), diagnosis of diabetes, hypertension and hyperlipidemia (n=3 variables), blood glucose test (n=3 variables), cholesterol and lipid levels (n=24 variables), diabetic diet (n=2 variables), and medication use (n=6 variables).
- The sample attributes data table includes sample type, body site where sample was extracted, sample analyte type and additional comments to indicate rela duplicate samples genotyped for QC.
C3847505 (UMLS CUI [1,2])
C0449416 (UMLS CUI [1,2])
C3847505 (UMLS CUI [1,3])
C1997370 (UMLS CUI [1,2])
C4684638 (UMLS CUI [1,2])
C0011860 (UMLS CUI [1,2])
C0011854 (UMLS CUI [1,2])
C0011849 (UMLS CUI [1,2])
C0332307 (UMLS CUI [1,3])
C0439673 (UMLS CUI [1,4])
C0449438 (UMLS CUI [1,2])
C0439673 (UMLS CUI [1,3])