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

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.