Circulating Rhythmic Metabolites and Causal Risk of Type 2 Diabetes in Adults in the Canadian Longitudinal Study on Aging

AIMS: Circadian regulation of metabolism is an important factor in metabolic health, yet the role of rhythmic metabolites in Type 2 diabetes development remains poorly understood. This study investigated associations between circulating rhythmic metabolites and incident Type 2 diabetes risk and evaluated causal relationships using two-sample Mendelian randomisation. MATERIALS AND METHODS: We analysed longitudinal data from 9992 community-dwelling adults aged 45-85 years (49.1% male) in the Canadian Longitudinal Study on Aging with baseline (2012-2015) serum metabolomics data. Untargeted metabolomics profiling was conducted using ultrahigh-performance liquid chromatography-tandem mass spectrometry. Incident Type 2 diabetes at 3-year follow-up was assessed based on diabetes medication use and HbA1c level. Associations between rhythmic metabolites and diabetes risk were evaluated using multivariable binomial regression. Pathway and network analyses were conducted to explore underlying biological mechanisms. Causality was assessed using two-sample Mendelian randomisation for rhythmic metabolites significantly associated with diabetes risk. RESULTS: Altogether, 20 rhythmic metabolites were associated with Type 2 diabetes risk, including a subset overlapping with genetic predisposition to chronotype, suggesting potential circadian regulation. Key pathways included leucine, isoleucine and valine biosynthesis and degradation, and glycine, serine and threonine metabolism. Mendelian randomisation analyses revealed causal associations between higher levels of mannose, valine, isoleucine, threonine and sphingomyelin (d18:0/18:0, d19:0/17:0) and higher Type 2 diabetes risk, whereas creatine, glycine, 1-linoleoyl-GPC (18:2), 1-palmitoyl-2-oleoyl-GPE, 1-palmitoyl-2-linoleoyl-GPE (16:0/18:2) and 1-stearoyl-2-oleoyl-GPE (18:0/18:1) were protective. CONCLUSIONS: Disruptions in rhythmic metabolites are implicated in Type 2 diabetes pathophysiology through specific metabolic pathways, highlighting the potential for biomarkers to support circadian-based prevention strategies.