Communications MedicineGenetic & Genomic MedicinePeer-reviewed journal article
Estimating Heritability of Glycaemic Response to Metformin using Nationwide Electronic Health Records and Population-Sized Pedigree
Iris N. KalkaiD, Amir Gavrieli, Smadar ShiloiD, Hagai RossmaniD, Nitzan Shalom ArtziiD, Nancy‐Sarah YacovzadaiD, Eran SegaliD
Abstract
Variability of response to medication is a well known phenomenon, determined by both environmental and genetic factors. Understanding the heritable component of the response to medication is of great interest but challenging due to several reasons, including small study cohorts and computational limitations. Here, we studied the heritability of variation in the glycaemic response to metformin, first-line therapeutic agent for type 2 diabetes (T2D), by leveraging 17 years of electronic health records (EHR) data from Israels largest healthcare service provider, consisting of over five million patients of diverse ethnicities and socio-economic background. Our cohort consisted of 74,871 T2D patients treated with metformin, with an accumulated number of 1,358,776 HbA1C measurements and 323,260 metformin prescriptions. We estimated the explained variance of glycated hemoglobin (HbA1c%) reduction due to heritability by constructing a six-generation population-size pedigree from pedigree information linked to medical health records. Using a Linear Mixed Model-based framework, a common-practice method for heritability estimation, we calculated a heritability measure of h2 = 10.5% (95% CI, 3.5%-17.5%) for absolute reduction of HbA1c% after metformin treatment, which remained unchanged after adjusting for pre-treatment HbA1c%, and h2 = 12.2% (95% CI, 5.2%-19.3%) for proportional reduction in HbA1c%. To the best of our knowledge, our work is the first to estimate heritability of drug response using EHR data. We demonstrated that while response to metformin treatment has a heritable component, most of the variation is likely due to other factors, further motivating non-genetic analyses aimed at unraveling metformins mechanism of action.
- organism: human
- assay: electronic health records
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 2
- FWCI
- 0.14
- Field percentile
- 46th percentile
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