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School of Medicine Publications and Presentations

Diabetes

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Full-Text Articles in Medicine and Health Sciences

Whole Genome Sequence Association Analysis Of Fasting Glucose And Fasting Insulin Levels In Diverse Cohorts From The Nhlbi Topmed Program, Daniel Dicorpo, Sheila M. Gaynor, Emily M. Russell, Kenneth E. Westerman, Laura M. Raffield, Marcio Almeida, Juan M. Peralta, John Blangero, Joanne E. Curran, Ravindranath Duggirala Jul 2022

Whole Genome Sequence Association Analysis Of Fasting Glucose And Fasting Insulin Levels In Diverse Cohorts From The Nhlbi Topmed Program, Daniel Dicorpo, Sheila M. Gaynor, Emily M. Russell, Kenneth E. Westerman, Laura M. Raffield, Marcio Almeida, Juan M. Peralta, John Blangero, Joanne E. Curran, Ravindranath Duggirala

School of Medicine Publications and Presentations

The genetic determinants of fasting glucose (FG) and fasting insulin (FI) have been studied mostly through genome arrays, resulting in over 100 associated variants. We extended this work with high-coverage whole genome sequencing analyses from fifteen cohorts in NHLBI’s Trans-Omics for Precision Medicine (TOPMed) program. Over 23,000 non-diabetic individuals from five race-ethnicities/populations (African, Asian, European, Hispanic and Samoan) were included. Eight variants were significantly associated with FG or FI across previously identified regions MTNR1B, G6PC2, GCK, GCKR and FOXA2. We additionally characterize suggestive associations with FG or FI near previously identified SLC30A8, TCF7L2, and ADCY5 regions as well …


Lipidomic Risk Score Independently And Cost-Effectively Predicts Risk Of Future Type 2 Diabetes: Results From Diverse Cohorts, Manju Mamtani, Hemant Kulkarni, Gerard Wong, Jacquelyn M. Weir, Christopher K. Barlow, Thomas D. Dyer, Laura Almasy, Michael C. Mahaney, Anthony G. Comuzzie, David C. Glahn, Sarah Williams-Blangero, Ravindranath Duggirala, John Blangero, Joanne E. Curran Jan 2016

Lipidomic Risk Score Independently And Cost-Effectively Predicts Risk Of Future Type 2 Diabetes: Results From Diverse Cohorts, Manju Mamtani, Hemant Kulkarni, Gerard Wong, Jacquelyn M. Weir, Christopher K. Barlow, Thomas D. Dyer, Laura Almasy, Michael C. Mahaney, Anthony G. Comuzzie, David C. Glahn, Sarah Williams-Blangero, Ravindranath Duggirala, John Blangero, Joanne E. Curran

School of Medicine Publications and Presentations

Background: Detection of type 2 diabetes (T2D) is routinely based on the presence of dysglycemia. Although disturbed lipid metabolism is a hallmark of T2D, the potential of plasma lipidomics as a biomarker of future T2D is unknown. Our objective was to develop and validate a plasma lipidomic risk score (LRS) as a biomarker of future type 2 diabetes and to evaluate its cost-effectiveness for T2D screening.

Methods: Plasma LRS, based on significantly associated lipid species from an array of 319 lipid species, was developed in a cohort of initially T2D-free individuals from the San Antonio Family Heart Study (SAFHS). The …