Abstract
Several observational investigations have documented correlations between circulating metabolic biomarkers and hyperthyroidism; nevertheless, the implications of blood lipids, amino acids, and blood glucose in hyperthyroidism remain elusive. Employing summary-level data from the most recent large-scale genome-wide association study(N = 136,016) for 233 circulating metabolic biomarkers, along with data on hyperthyroidism from the R10 dataset released by the FinnGen consortium(N = 412,181), we performed a bidirectional two-sample Mendelian randomization (MR) analysis. We computed the impacts of both utilizing the inverse variance weighted, MR Egger, weighted median, simple mode, and weighted mode techniques, and evaluated the dependability of the findings utilizing Cochran Q test, MR-Egger intercept regression analysis, and MR-PRESSO. Subsequently, a reverse MR analysis was conducted on the circulating metabolic biomarkers identified to exhibit an association with hyperthyroidism in the forward MR analysis. The inverse variance-weighted analysis revealed that for each 1-standard deviation increase in alanine levels, glucose levels, and the cholesteryl esters to total lipids ratio in large very low-density lipoprotein particles, the risk of hyperthyroidism decreased by 14%, 19%, and 15%, respectively. The reverse MR analysis did not identify any significant effect of hyperthyroidism on circulating metabolic biomarkers. Alanine levels, glucose levels, cholesteryl esters to total lipids ratio in large very low-density lipoprotein levels, and the free cholesterol to total lipids ratio in large low-density lipoprotein levels were differentially associated with the risk of hyperthyroidism, and have the potential to be used as biomarkers of hyperthyroidism. The findings of this study may offer novel insights into the prevention and management of hyperthyroidism.