ID

45055

Description

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

Keywords

  1. 8/4/22 8/4/22 - Chiara Middel
  2. 10/12/22 10/12/22 - Adrian Schulz
Copyright Holder

Michele M. Sale, PhD, University of Virginia, Charlottesville, VA, USA

Uploaded on

August 4, 2022

DOI

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License

Creative Commons BY 4.0

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dbGaP phs000433 The Sea Islands Genetic Network (SIGNET)

The data table contains pedigree, gender and twin information of study participants.

pht002434
Description

pht002434

Family ID
Description

FAMID

Data type

text

Alias
UMLS CUI [1,1]
C0015576
UMLS CUI [1,2]
C2348585
Unique subject ID
Description

SUBJID

Data type

text

Alias
UMLS CUI [1,1]
C2348585
Father's subject ID
Description

FATHER

Data type

text

Alias
UMLS CUI [1,1]
C2348585
UMLS CUI [1,2]
C0015671
Mother's subject ID
Description

MOTHER

Data type

text

Alias
UMLS CUI [1,1]
C2348585
UMLS CUI [1,2]
C0026591
Sex
Description

SEX

Data type

text

Alias
UMLS CUI [1,1]
C0079399
Twin ID
Description

TWINID

Data type

text

Alias
UMLS CUI [1,1]
C0041427
UMLS CUI [1,2]
C2348585

Similar models

The data table contains pedigree, gender and twin information of study participants.

Name
Type
Description | Question | Decode (Coded Value)
Data type
Alias
Item Group
pht002434
FAMID
Item
Family ID
text
C0015576 (UMLS CUI [1,1])
C2348585 (UMLS CUI [1,2])
SUBJID
Item
Unique subject ID
text
C2348585 (UMLS CUI [1,1])
FATHER
Item
Father's subject ID
text
C2348585 (UMLS CUI [1,1])
C0015671 (UMLS CUI [1,2])
MOTHER
Item
Mother's subject ID
text
C2348585 (UMLS CUI [1,1])
C0026591 (UMLS CUI [1,2])
Item
Sex
text
C0079399 (UMLS CUI [1,1])
Code List
Sex
CL Item
Female (F)
C0086287 (UMLS CUI [1,1])
CL Item
Male (M)
C0086582 (UMLS CUI [1,1])
CL Item
Unknown (UNK)
C0439673 (UMLS CUI [1,1])
TWINID
Item
Twin ID
text
C0041427 (UMLS CUI [1,1])
C2348585 (UMLS CUI [1,2])

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