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Causal relationships between lipid and glycemic levels in an Indian population: A bidirectional Mendelian randomization approach

Research output: Contribution to journalArticle

Original languageEnglish
Pages (from-to)e0228269
JournalPLoS ONE
Issue number1
DateAccepted/In press - 12 Jan 2020
DatePublished (current) - 29 Jan 2020


BACKGROUND: Dyslipidemia and abnormal glycemic traits are leading causes of morbidity and mortality. Although the association between the two traits is well established, there still exists a gap in the evidence for the direction of causality.

OBJECTIVE: This study aimed to examine the direction of the causal relationship between lipids and glycemic traits in an Indian population using bidirectional Mendelian randomization (BMR).

METHODS: The BMR analysis was conducted on 4900 individuals (2450 sib-pairs) from the Indian Migration Study. Instrument variables were generated for each lipid and glycemic trait (fasting insulin, fasting glucose, HOMA-IR, HOMA-β, LDL-cholesterol, HDL-cholesterol, total cholesterol and triglycerides) to examine the causal relationship by applying two-stage least squares (2SLS) regression in both directions.

RESULTS: Lipid and glycemic traits were found to be associated observationally, however, results from 2SLS showed that only triglycerides, defined by weighted genetic risk score (wGRS) of 3 SNPs (rs662799 at APOAV, rs780094 at GCKR and rs4420638 at APOE/C1/C4), were observed to be causally effecting 1.15% variation in HOMA-IR (SE = 0.22, P = 0.010), 1.53% in HOMA- β (SE = 0.21, P = 0.001) and 1.18% in fasting insulin (SE = 0.23, P = 0.009). No evidence for a causal effect was observed in the reverse direction or between any other lipid and glycemic traits.

CONCLUSION: The study findings suggest that triglycerides may causally impact various glycemic traits. However, the findings need to be replicated in larger studies.


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