<p>This study aimed to identify key genes and immune features associated with keratoconus (KC), a progressive eye disorder, by integrating genomic and transcriptomic data using Mendelian randomization (MR) methods. We employed summary data-based Mendelian randomization (SMR) and inverse-variance weighted Mendelian randomization (IVW-MR) to analyze genetic variations from public databases. The study included expression quantitative trait loci (eQTL) data for 16,987 genes and GWAS summary statistics for 19,942 gene traits and 731 immune traits. We also utilized gene expression data from keratoconus patients and controls to validate findings and explore causal relationships. We identified 715 genes associated with KC, including 371 risk genes and 344 protective genes. Pathway over-representation analyses indicated that risk genes are involved in the regulation of the cytoskeleton, while protective genes are related to metabolic processes. Differential expression analysis showed significant overexpression of risk genes in KC samples. Additionally, we found 21 immune phenotypes with causal effects on KC, highlighting the role of immune cells in the disease’s pathogenesis. The study revealed multiple risk and protective genes linked to KC, providing new insights into its pathophysiological mechanisms. The findings underscore the importance of cytoskeletal remodeling and immune regulation in KC and suggest potential targets for future diagnostic and therapeutic strategies. Further research is needed to validate these genes and immune traits’ functions and their clinical application potential.</p>

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Genetic and immune landscape of keratoconus: insights from Mendelian randomization analysis

  • Yuhui Yu,
  • Qiang Liu,
  • Chen Zhou,
  • Juan Jiang,
  • Yanchun Li

摘要

This study aimed to identify key genes and immune features associated with keratoconus (KC), a progressive eye disorder, by integrating genomic and transcriptomic data using Mendelian randomization (MR) methods. We employed summary data-based Mendelian randomization (SMR) and inverse-variance weighted Mendelian randomization (IVW-MR) to analyze genetic variations from public databases. The study included expression quantitative trait loci (eQTL) data for 16,987 genes and GWAS summary statistics for 19,942 gene traits and 731 immune traits. We also utilized gene expression data from keratoconus patients and controls to validate findings and explore causal relationships. We identified 715 genes associated with KC, including 371 risk genes and 344 protective genes. Pathway over-representation analyses indicated that risk genes are involved in the regulation of the cytoskeleton, while protective genes are related to metabolic processes. Differential expression analysis showed significant overexpression of risk genes in KC samples. Additionally, we found 21 immune phenotypes with causal effects on KC, highlighting the role of immune cells in the disease’s pathogenesis. The study revealed multiple risk and protective genes linked to KC, providing new insights into its pathophysiological mechanisms. The findings underscore the importance of cytoskeletal remodeling and immune regulation in KC and suggest potential targets for future diagnostic and therapeutic strategies. Further research is needed to validate these genes and immune traits’ functions and their clinical application potential.