Burns : journal of the International Society for Burn Injuries · 2026
Plasma metabolomics and scar pathogenesis: Insights from Mendelian randomization analysis.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Gong Song, Liang Chen, Wu Haibin, Xu Kai, Yang Ting
Аннотация
BACKGROUND: Scar formation following significant tissue injury remains a major clinical challenge, with metabolic processes and inflammation critically influencing tissue remodeling and fibrotic outcomes.
OBJECTIVE: This study aims to elucidate the causal relationships between plasma metabolites and scar pathogenesis using Mendelian randomization (MR).
METHODS: By employing a two-sample MR approach, we analyzed genetic variants from GWAS as instrumental variables (IVs) to assess the impact of plasma metabolites on scar formation. Data on metabolite levels were sourced from a GWAS database of 8299 individuals, and scar outcome data involved 463,010 European skin tissue samples. Five MR methods were utilized to ensure robust causal inference, including inverse variance weighting, MR-Egger regression, and weighted median, complemented by sensitivity analyses to address potential confounding factors and pleiotropy.
RESULTS: The analysis of MR identified a total of four metabolites significantly associated with scar risk. Among them, (S)-α-amino-ω-caprolactam, N-acetylalanine and glycochenodeoxycholate 3-sulfate were linked to increased scar formation, while alliin demonstrated protective effects. Consistency across different MR methods underscored the robustness of these findings. Sensitivity analyses confirmed the absence of pleiotropy and the stability of causal estimates.
CONCLUSION: The identified causal relationships between specific plasma metabolites and scar formation suggest that metabolic modulation may offer new therapeutic avenues for managing scar development.
OBJECTIVE: This study aims to elucidate the causal relationships between plasma metabolites and scar pathogenesis using Mendelian randomization (MR).
METHODS: By employing a two-sample MR approach, we analyzed genetic variants from GWAS as instrumental variables (IVs) to assess the impact of plasma metabolites on scar formation. Data on metabolite levels were sourced from a GWAS database of 8299 individuals, and scar outcome data involved 463,010 European skin tissue samples. Five MR methods were utilized to ensure robust causal inference, including inverse variance weighting, MR-Egger regression, and weighted median, complemented by sensitivity analyses to address potential confounding factors and pleiotropy.
RESULTS: The analysis of MR identified a total of four metabolites significantly associated with scar risk. Among them, (S)-α-amino-ω-caprolactam, N-acetylalanine and glycochenodeoxycholate 3-sulfate were linked to increased scar formation, while alliin demonstrated protective effects. Consistency across different MR methods underscored the robustness of these findings. Sensitivity analyses confirmed the absence of pleiotropy and the stability of causal estimates.
CONCLUSION: The identified causal relationships between specific plasma metabolites and scar formation suggest that metabolic modulation may offer new therapeutic avenues for managing scar development.