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<p>This study investigates the causal association between genetic prediction of iron status and subarachnoid hemorrhage (SAH). A two-sample MR analysis was conducted using genome-wide association study (GWAS) summary data for four iron biomarkers: serum iron, serum ferritin, total iron-binding capacity (TIBC), and transferrin saturation (TSAT). Genetic variants were selected as instrumental variables (IVs) to minimize confounding. Causal estimates were obtained using inverse variance weighting (IVW), MR-Egger, weighted median, and weighted mode methods. Sensitivity analyses, including Cochran’s Q-test, MR-Egger regression, MR-PRESSO, and leave-one-out analysis, were performed to assess heterogeneity and pleiotropy. IVW analysis revealed a significant association between increased genetically predicted TIBC and higher SAH risk (OR = 1.71, 95% CI: 1.21–2.41, <i>P</i> = 0.002), while higher TSAT was associated with lower SAH risk (OR = 0.76, 95% CI: 0.62–0.93, <i>P</i> = 0.01). No causal association was found between serum iron, serum ferritin, and SAH. Sensitivity analyses confirmed the robustness of the results, with no evidence of horizontal pleiotropy. However, heterogeneity was detected in serum ferritin, suggesting potential variability in its effect. This MR study provides genetic evidence for the causal relationship between TIBC, TSAT, and SAH risk. These findings highlight the potential role of iron metabolism in SAH pathophysiology, warranting further investigation.</p>

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Exploring the causal relationship between iron status and subarachnoid hemorrhage based on two sample mendelian randomization

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年5月3日

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  • Qian Chen,
  • Weiling Shou,
  • Li Zhang,
  • Jiaying Fang,
  • Ye Guo

摘要

This study investigates the causal association between genetic prediction of iron status and subarachnoid hemorrhage (SAH). A two-sample MR analysis was conducted using genome-wide association study (GWAS) summary data for four iron biomarkers: serum iron, serum ferritin, total iron-binding capacity (TIBC), and transferrin saturation (TSAT). Genetic variants were selected as instrumental variables (IVs) to minimize confounding. Causal estimates were obtained using inverse variance weighting (IVW), MR-Egger, weighted median, and weighted mode methods. Sensitivity analyses, including Cochran’s Q-test, MR-Egger regression, MR-PRESSO, and leave-one-out analysis, were performed to assess heterogeneity and pleiotropy. IVW analysis revealed a significant association between increased genetically predicted TIBC and higher SAH risk (OR = 1.71, 95% CI: 1.21–2.41, P = 0.002), while higher TSAT was associated with lower SAH risk (OR = 0.76, 95% CI: 0.62–0.93, P = 0.01). No causal association was found between serum iron, serum ferritin, and SAH. Sensitivity analyses confirmed the robustness of the results, with no evidence of horizontal pleiotropy. However, heterogeneity was detected in serum ferritin, suggesting potential variability in its effect. This MR study provides genetic evidence for the causal relationship between TIBC, TSAT, and SAH risk. These findings highlight the potential role of iron metabolism in SAH pathophysiology, warranting further investigation.