Assistant Professor of Medicine
Massachusetts General Hospital
Massachusetts General Hospital
S50-304 Diabetes Unit
50 Staniford Street
Boston MA 02114
Available: 02/18/22, Expires: 06/01/22
We have recently discovered a recessive variant strongly associated with type 2 diabetes (T2D) near the PELO gene. This variant is associated with three-fold T2D and 10% decrease in LDL Cholesterol levels and 20% decrease in triglyceride levels. The homozygous carriers of this variant have much lower expression of the PELO gene, suggesting that this gene could be a relevant therapeutic target to treat T2D and lipid related disorders (https://pubmed.ncbi.nlm.nih.gov/34862199/). Deep phenotyping and clinical characterization of homozygous carriers of this variant may provide an opportunity to understand the mechanism of how these individuals have higher risk of T2D and higher lipid levels. Mass General Brigham Biobank (MGBB) is a biobank with 54,000 individuals with detailed electronic health records that have been genotyped with genotyping arrays, which combined with genotype imputation can provide information of any genetic variant with minor allele frequency. MGBB is therefore a great resource to characterize carriers of this variant, and to elucidate if these individuals suffer a particular subtype of atypical diabetes. Approach: Homozygous carriers will be identified in the MGBB as this is a variant that is imputed with high quality. Manual chart review of all homozygous carriers (100) of this variant, and matched controls (100). These data will be integrated with metabolomics data performed in a subset of the same subjects. Phenome-wide association analyses of homozygous carriers across 500,000 individuals in UK Biobank including measures of adiposity, MRI data, biomarker data, metabolomics, etc. Role of the student: - Perform the manual chart review of 200 individuals, collecting several problems list, etc . - Perform statistical analyses to find differences in levels of different lab values or differences in prevalence of different conditions, medication use, visits to a particular specialist, etc - Learn to apply linear and logistic regression models for large-scale genetic datasets to test for association with quantitative and binary traits. - Present the results in group meetings and conferences. - Contribute to a manuscript with results of this work
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to make corrections and additions.
(UDLER, MIRIAM SARGON)
Jul 1, 2017 - May 31, 2022
Clinical Implications of Genetically Defined Diabetes Subtypes and Application to Electronic Health Medical Record Systems
Role: Principal Investigator
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