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Background <p>The study of facial skin aging has attracted significant attention not only for its esthetic implications but also for its potential to shed light on the mechanisms underlying the development of age-related diseases. The purpose of this research was to systematically investigate potential drug targets for facial skin aging through multi-omics genetic methods.</p> Methods <p>We utilized expression quantitative trait loci (eQTLs) and protein quantitative trait loci (pQTLs) as instruments to explore the therapeutic potential for facial skin aging. This was supplemented with transcriptome analysis and in vitro experiments, including siRNA knockdown in human HaCaT and NIH 3T3 cells, which confirmed the genetic results. Additionally, we conducted two-sample Mendelian randomization (MR) to investigate the causal effect of facial aging on skin neoplasms and performed metabolome-wide MR to screen for metabolic biomarkers associated with facial aging.</p> Results <p>Through integrated analysis of eQTLs and colocalization, five potential druggable genes were identified, including BRSK2, IL20RB, NEK10, RAB35, and SEMA7A. Of these, SEMA7A showed strong evidence with facial skin aging through subsequent pQTL and colocalization analysis. Additionally, genetically determined facial skin aging exhibited a significant causal effect on basal cell carcinoma (BCC) (OR = 3.973, 95% CI: 1.284, 12.290, <i>p</i> = 0.016 [inverse-variance weighted, IVW]), while no causal effect was found on malignant melanoma and squamous cell carcinoma. Subsequent transcriptome and in vitro experiment suggested that SEMA7A played an important role in the pathogenesis of skin aging. The metabolome-wide MR identified several circulating metabolic traits as biomarkers for facial skin aging, implicating lipoprotein subfractions (HDL, LDL, and VLDL) and fatty acid profiles.</p> Conclusion <p>This study demonstrates the genetic significance of targeting SEMA7A for facial skin aging, providing new insights into the disease mechanism and aiding the development of future drug therapies.</p>

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Multi-omics Mendelian randomization revealing SEMA7A as potential drug target for facial skin aging

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月20日

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  • Xueyao Cai,
  • Weidong Li,
  • Wenjun Shi,
  • Yuchen Cai,
  • Jianda Zhou

摘要

Background

The study of facial skin aging has attracted significant attention not only for its esthetic implications but also for its potential to shed light on the mechanisms underlying the development of age-related diseases. The purpose of this research was to systematically investigate potential drug targets for facial skin aging through multi-omics genetic methods.

Methods

We utilized expression quantitative trait loci (eQTLs) and protein quantitative trait loci (pQTLs) as instruments to explore the therapeutic potential for facial skin aging. This was supplemented with transcriptome analysis and in vitro experiments, including siRNA knockdown in human HaCaT and NIH 3T3 cells, which confirmed the genetic results. Additionally, we conducted two-sample Mendelian randomization (MR) to investigate the causal effect of facial aging on skin neoplasms and performed metabolome-wide MR to screen for metabolic biomarkers associated with facial aging.

Results

Through integrated analysis of eQTLs and colocalization, five potential druggable genes were identified, including BRSK2, IL20RB, NEK10, RAB35, and SEMA7A. Of these, SEMA7A showed strong evidence with facial skin aging through subsequent pQTL and colocalization analysis. Additionally, genetically determined facial skin aging exhibited a significant causal effect on basal cell carcinoma (BCC) (OR = 3.973, 95% CI: 1.284, 12.290, p = 0.016 [inverse-variance weighted, IVW]), while no causal effect was found on malignant melanoma and squamous cell carcinoma. Subsequent transcriptome and in vitro experiment suggested that SEMA7A played an important role in the pathogenesis of skin aging. The metabolome-wide MR identified several circulating metabolic traits as biomarkers for facial skin aging, implicating lipoprotein subfractions (HDL, LDL, and VLDL) and fatty acid profiles.

Conclusion

This study demonstrates the genetic significance of targeting SEMA7A for facial skin aging, providing new insights into the disease mechanism and aiding the development of future drug therapies.