Heavy Metal Index
Ask the IndexAboutIndex Pro

Association of heavy metal mixtures with liver function biomarkers: multi-model analysis identifies cadmium as the primary driver

Cite this pageVersion history

Overview

Cross-sectional study of 451 participants from the Dongdagou Xinglong cohort in Northwest China, examining associations between blood heavy metal concentrations and liver function biomarkers. Multiple linear regression, BKMR, WQS, and quantile g-computation (Qgcomp) were applied. A subchronic cadmium exposure rat model was established to validate population-based findings. The Dongdagou watershed is described as severely heavy-metal-polluted due to industrial activity.

Key numbers

n=451 participants, Dongdagou Xinglong cohort, Northwest China.

Blood cadmium (single-metal) associations by multiple linear regression:

  • GGT: beta=0.236 (p below 0.05).
  • TBA (total bile acids): beta=0.162 (p below 0.05).
  • ALT: beta=0.142 (p below 0.05).
  • AST: beta=0.114 (p below 0.05).
  • DBil (direct bilirubin): beta=negative 0.207 (p below 0.05) — inverse association.
  • TBil (total bilirubin): beta=negative 0.166 (p below 0.05) — inverse association.
  • IBil (indirect bilirubin): beta=negative 0.157 (p below 0.05) — inverse association.

Mixture findings: all three mixture models (BKMR, WQS, Qgcomp) consistently identified cadmium as the dominant factor associated with liver function biomarkers across positive (ALT, AST, GGT, CHE, TBA) and negative (TBil, DBil, IBil) liver function endpoints.

Animal validation: subchronic cadmium exposure in rats elevated serum GGT and ALP; histopathological alterations in liver tissue consistent with human findings; transcriptomic sequencing indicated involvement of hepatic lipid metabolism pathways.

Evidence Fitness

Context only. Cross-sectional design in a known heavy-metal-polluted area; exposure levels likely higher than general population. The Dongdagou setting means findings may not generalize to the general population but represent a demonstration of the cadmium-liver pathway in heavily exposed adults. The multi-model convergence (all three mixture models identifying cadmium as primary driver) and the animal validation increase confidence in the cadmium-liver function association.

Methods (brief)

Cross-sectional cohort study, Dongdagou Xinglong, Northwest China. Blood metals by ICP-MS (RF power 1200 W; plasma gas flow 9.0 L/min; nebulizer gas flow 0.7 L/min). Liver enzymes by standard enzymatic assays. Multiple linear regression, BKMR, WQS, Qgcomp. Rat model: subchronic cadmium exposure via drinking water; transcriptomics by RNA sequencing.

Implications

Certification: Cadmium’s dominant role in liver toxicity across multiple mixture models, confirmed in an animal model, supports its Tier-1 status in HMT&C monitoring.

Courses: Excellent example of how multi-model convergence strengthens causal inference and how animal models can validate population-based mixture findings.

App: No food concentration data applicable to contamination_profile.

Microbiome: Hepatic lipid metabolism pathway identified by transcriptomics; potential gut-liver axis thread for WikiBiome.

Update history

No substantive edit history is available in this build. The full commit record is available in git.

Referenced by