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Standards for Quantitative Metalloproteomic Analysis Using Size Exclusion ICP-MS
Published on: April 13, 2016
Heavy metal-induced proteomic profiles associated with disease risk in environmentally vulnerable populations
Min Heo1, Sora Mun2, Nam-Eun Kim3
1Interdisciplinary Program of Bioinformatics, College of Natural Sciences, Seoul National University, Seoul 08826, Republic of Korea.
Abstract:
Heavy metal exposure is a major public health concern, yet the molecular mechanisms linking environmental toxicants to disease remain poorly understood. We applied an integrative proteomic approach to investigate the biological effects of chronic exposure in environmentally vulnerable populations from the FROM cohort. Across three exposure-control designs, we identified 11, 20, and 54 heavy metal exposure-related proteins, which were predominantly enriched in complement activation, lipid metabolism, and oxidative stress pathways. Using a meet-in-the-middle analysis, we identified 40 proteins and 14 clinical indicators involved in statistically supported exposure-protein-clinical indicator relationships. We then applied Mendelian randomization leveraging protein quantitative trait loci (pQTL) from the FROM cohort and GWAS summary statistics from East Asian populations (KoGES, BBJ) to evaluate putative causality linking proteins, clinical indicators, and environmental diseases. Among the prominent findings, apolipoprotein M (APOM) was associated with serum albumin (β [95% CI] = -0.013 [-0.022, -0.003]; P = 7.57 × 10-3) and cirrhosis (OR [95% CI] = 1.093 [1.036, 1.153]; P = 1.22 × 10-3), with serum albumin partially mediating 8.49% of the total effect. This study provides insight into how chronic exposure to heavy metals perturbs molecular pathways involved in disease development, offering a deeper understanding of environmentally driven pathophysiology.
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