1099-P: Plasma Amino Acid Profiles in Childhood Predict 10-Year Risk of Insulin Resistance in Adulthood—The BCAMS Study

Abstract

Objective Insulin resistance (IR) is the critical step in the development of type 2 diabetes. Recent cross-sectional studies in children demonstrate plasma amino acids such as branched-chain and aromatic amino acids are associated with IR, however, information is scant regarding whether these associations in childhood persist over time and predict diabetes risk in young adults. We aimed to examine whether circulating amino acids in childhood predict 10-year risk of IR in early adulthood. Research design and Methods: This was a 10-year longitudinal study from childhood to early adulthood. A total of 961 subjects aged 6-18 years at baseline participated in the Beijing Child and Adolescent Metabolic Syndrome study (BCAMS). Serum insulin was determined by in-house ELISA with no cross-reaction with proinsulin, and plasma amino acids were profiled using targeted LC-MS/MS. IR was determined by the homeostatic model assessment of insulin resistance (HOMA-IR). Results: At baseline, after adjusting for age, gender, tanner stage, diet score, exercise, residence and BMI, 17 amino acids were closely correlated with HOMA-IR and nine with impaired fasting glucose (IFG) in childhood (p < 0.05 for all). Among them, Isoleucine showed the strongest association with IR (OR=2.04, 95% CI 1.65-2.54, P<0.001), and alanine was the strongest predictor of IFG (OR =1.52, 95%CI 1.22-1.91, P<0.001). Prospectively, after adjusting for the covariates at baseline, four amino acids have a significant predictive effect on the risk of IR at 10-years follow-up, of which alanine was the strongest predictor [OR=1.38, 95% CI (1.02, 1.85), P=0.035]. Conclusion: Our findings suggest the changes in amino acid metabolism not only link IR in childhood, but also persist into adulthood and may heighten type 2 diabetes risk later in life. Disclosure S.Gao: None. M.Li: None. Bcams group: n/a. Funding National High Level Hospital Clinical Research Funding (2022-PUMCH-C-014); National Natural Science Foundation of China (81970732, 82270924); CAMS Innovation Fund for Medical Sciences (CIFMS 2021-I2M-1-016); Capital's Funds for Health Improvement and Research (2020-2Z-40117); Key Program of Beijing Municipal Science &Technology Commission (D111100000611001, D111100000611002)