Metabolic pathways mediating insulin resistance and gestational diabetes mellitus discovered by high-dimensional systematic Mendelian randomization

通过高维系统孟德尔随机化方法发现介导胰岛素抵抗和妊娠期糖尿病的代谢通路

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Abstract

BACKGROUND: Gestational diabetes mellitus (GDM), characterized by insulin resistance (IR) and β-cell dysfunction, is one of the most common complications of pregnancy with unmet needs of prevention methods. OBJECTIVE: To investigate the causal role of insulin resistance and metabolic pathways in the pathogenesis of GDM with our proposed high-dimensional systematic Mendelian randomization (hdsMR) framework. METHODS: Cases with GDM and controls with normal glucose tolerance were recruited at the University of Hong Kong-Shenzhen Hospital from 2015 to 2018. A total of 566 participants (aged > 18 years), including 274 with GDM, were enrolled after excluding subjects with major chronic diseases or long-term use of medications affecting glycolipid metabolism. Clinical characteristics and serum samples were collected during the GDM screening stage, and the genome and metabolome were tested. A novel hdsMR framework was proposed to estimate the causal role of IR index (Homeostasis Model Assessment of Insulin Resistance, HOMA-IR) and metabolic pathways in the pathogenesis of GDM. RESULTS: Our hdsMR method confirmed that HOMA-IR was causal to GDM (odds ratio, 1.17; 95% confidence interval, 1.04-1.32) and revealed that two metabolic pathways (glyoxylate and dicarboxylate metabolism pathway and lysine degradation pathway) mediated 14.6% and 8.4%, respectively, between HOMA-IR and GDM. In an independent validation cohort comprising 255 pre-diabetic individuals, we showed that both pathways could be intervened through diet (P < 0.05). Furthermore, glyoxylate and dicarboxylate metabolism pathway was significantly associated with adverse pregnancy outcomes in GDM. CONCLUSIONS: These results indicated that targeting specific metabolic pathways through dietary intervention is worth exploring as a possible GDM prevention approach, and hdsMR is more efficient in finding causal mediating metabolic pathways than traditional MR methods.

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