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Protocol Details

Analysis of the Utility of Polygenic Scores for Prediction of Incident Type 2 Diabetes Across Multiple Ancestry Groups

This study is NOT currently recruiting participants.

Summary | Eligibility | Citations | Contacts

Summary

Number

000748-DK

Sponsoring Institute

National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)

Recruitment Detail

Type: Completed Study; data analyses ongoing
Gender: Male & Female
Min Age: 18 Years
Max Age: 99 Years

Referral Letter Required

Yes

Population Exclusion(s)

None

Keywords

Type 2 Diabetes;
Diabetes;
polygenic score;
Natural History

Recruitment Keyword(s)

None

Condition(s)

Type 2 Diabetes

Investigational Drug(s)

None

Investigational Device(s)

None

Intervention(s)

None

Supporting Site

National Institute of Diabetes and Digestive and Kidney Diseases

Study Description:

Polygenic scores for type 2 diabetes (T2D) may be useful for identifying individuals for preventive interventions, but there is little information on how these scores predict T2D incidence across diverse ancestry groups. In these analyses, we will assess the extent to which T2D polygenic score predicts subsequent diabetes incidence in individuals who are initially nondiabetic among those of African American, East Asian, European American, Hispanic American, Indigenous American and South Asian ancestry. De-identified data will be obtained from publicly available sources or from other investigators for these analyses. Within each ancestry group, we will assess whether polygenic score associates with diabetes incidence (as quantified by the hazard ratio); we will also assess whether polygenic score provides additional information for classifying risk for diabetes beyond clinical risk factors (as quantified by net reclassification index), and whether polygenic score provides an improvement in net benefit for instituting a preventive intervention across a range of clinical action thresholds (by decision curve analysis). Differences in predictive properties among ancestry groups will also be assessed. These analyses may provide useful information for planning prevention strategies for type 2 diabetes.

Objectives:

Primary Objectives:

To examine the ability of polygenic scores for type 2 diabetes to longitudinally predict incidence of diabetes in diverse ancestry groups; to assess the extent to which polygenic score provides additional information beyond clinical risk factors for classifying individuals according to risk of developing future diabetes and to quantify potential clinical benefits of using polygenic scores to select individuals for diabetes prevention efforts.

Secondary Objectives:

To examine the extent to which predictive properties of type 2 diabetes polygenic scores differ across ancestry groups, and to identify reasons for potential heterogeneity across ancestry groups in ability of polygenic scores to select individuals for preventive interventions.

Study Population and Source of Specimens and Data:

Data will be obtained from publicly available sources (i.e., the NCBI, dbGAP repository) for longitudinal studies that assessed diabetes incidence and that also have genomic data available. De-identified data may also be obtained from other investigators who have collected information on diabetes incidence in longitudinal studies, along with genomic data.

Aggregate data from NIH protocol OH76-DK-0256 will also be analyzed, as will aggregate data from some studies outside of NIH. These data will be analyzed for those who did not have T2D at their first examination to determine the extent to which polygenic score predicts subsequent occurrence of diabetes.

Description of Sites/Facilities conducting research:

Analyses will be conducted at the NIDDK facilities, Phoenix, AZ. Aggregate data may be provided from some investigators outside of NIH.

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Eligibility

Data will be obtained from publicly available sources (i.e., the NCBI, dbGAP repository) for longitudinal studies that assessed diabetes incidence and that also have genomic data available. De-identified data may also be obtained from other investigators who have collected information on diabetes incidence in longitudinal studies, along with genomic data.

Aggregate data from NIH protocol OH76-DK-0256 will also be analyzed, as will aggregate data from some studies outside of NIH. These data will be analyzed for those who did not have T2D at their first examination to determine the extent to which polygenic score predicts subsequent occurrence of diabetes.


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Citations:

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Contacts:

Principal Investigator

Referral Contact

For more information:

Robert L. Hanson, M.D.
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
PECRB BG RM 606
1550 E INDIAN SCHOOL RD
PHOENIX AZ 85014
(602) 200-5207
rhanson@phx.niddk.nih.gov

Robert L. Hanson, M.D.
National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK)
PECRB BG RM 606
1550 E INDIAN SCHOOL RD
PHOENIX AZ 85014
(602) 200-5207
rhanson@phx.niddk.nih.gov

Robert L. Hanson, M.D.
PECRB BG RM 606
1550 E INDIAN SCHOOL RD
PHOENIX AZ 85014
(602) 200-5207
rhanson@phx.niddk.nih.gov

Clinical Trials Number:

N/A

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