Heavy metal exposure and its effects on APOC3, CFAI, and ZA2G

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Despite increasing heavy metal pollution, traditional epidemiology often fails to link exposure to health outcomes. This study used multi-omics to investigate associations between heavy metal exposure and health. Blood and urine samples from 294 participants in heavy metal-exposed and control areas were analyzed, revealing key biomarkers. Meta P analysis revealed consistent trends in apolipoprotein C3 ( APOC3 ) expression, and mediation analysis showed significant effects of APOC3 and zinc-alpha-2-glycoprotein (ZA2G) on metabolites: the mediating effect of APOC3 from blood cadmium to serotonin was 0.023 (P < 0.001) and that to 3-phosphoglyceric acid (3PG) was 0.0125 (P = 0.002). Mendelian randomization confirmed the positive impact of APOC3 and Complement Factor I (CFAI) and the negative effect of ZA2G on metabolites, with apolipoprotein H (APOH) methylation significantly altering APOC3 (β = −0.22, P = 0.017), CFAI (β = 0.176, P = 0.035), and ZA2G (β = 0.139, P = 0.048) protein levels. Liver function variables, including albumin, total protein, calcium, and lactate dehydrogenase, correlated with 3PG and serotonin levels in the exposed areas. Sex-specific analysis showed that men exhibited stronger compensatory mechanisms via CFAI and myo-inositol, while women’s greater vulnerability to heavy metal exposure highlighted the need for targeted interventions. These findings suggest APOH methylation affects APOC3, CFAI, and ZA2G levels, elevating 3PG, inosine monophosphate, and serotonin levels and harming liver function via lipolysis, supporting the use of these markers in health monitoring, therapies, and policies to limit heavy metal risks. • Multi-omics analysis reveals the dynamics of heavy metal exposure on human health. • Integration of omics markers identifies key genes affected by heavy metal exposure. • Increased APOC3 , CFAI , and ZA2G levels affect metabolites, impacting liver function. • Adopting sex-specific approaches for heavy metal exposure is needed. • Relationships between clinical parameters and omics data depended on metal exposure.

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