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Background <p>Sepsis is characterized by organ dysfunction as a response to infection and is one of the leading causes of mortality and loss of health. The heterogeneous nature of sepsis, along with ethnic differences in susceptibility, challenges a thorough understanding of its etiology. This study aimed to propose prediction models by leveraging genetic-risk scores and clinical variables that can assist in risk stratification of patients.</p> Methods <p>A total of 1,403 patients from Taiwan, diagnosed with sepsis, were utilized. Genome-wide survival analysis was conducted, with death within 28&#xa0;days from sepsis onset, as the primary event to report significantly associated SNPs. A polygenic risk score (PRS-sepsis) was constructed via clumping and thresholding method which was added to clinical-only models to generate better performing prognostic models for identifying high-risk patients. Kaplan–Meier analysis was conducted using PRS-sepsis.</p> Results <p>A total of five single-nucleotide-polymorphisms (SNPs) reached genome-wide significance (<i>p</i> &lt; 5e-8), and 86 SNPs reached suggestive significance (<i>p</i> &lt; 1e-5). The prognostic model using PRS-sepsis showed significantly improved performance with c-index [confidence interval (CI)] of 0.79 [0.62–0.96] and area&#xa0;under receiver&#xa0;operating&#xa0;characteristic curve (AUROC) [CI] of 0.78 [0.75–0.80], in comparison to clinical-only prognostic models (c-index&#xa0;[CI] = 0.63 [0.45– 0.81], AUROC&#xa0;[CI] = 0.61 [0.58–0.64]). The ethnic specificity was established for our proposed models by comparing it with models generated using significant SNPs from prior European studies (c-index&#xa0;[CI] = 0.63 [0.42–0.85], AUROC&#xa0;[CI] = 0.60 [0.58–0.63]). Kaplan–Meier plots showed that patient groups with higher PRSs have inferior survival probability compared to those with lower PRSs.</p> Conclusions <p>This study proposed genetic-risk models specific for Taiwanese populations that outperformed clinical-only models. Also it established a strong racial-effect on the underlying genetics of sepsis-related mortality. The model can potentially be used in real clinical setting for deciding precise treatment courses for patients at high-risk thereby reducing the possibility of worse outcomes.</p>

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Population-specific genetic-risk scores enable improved prediction of mortality within 28 days of sepsis onset: a retrospective Taiwanese cohort study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年2月26日

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  • Ming-Shun Hsieh,
  • Pei-Hsuan Wu,
  • Kuan-Chih Chiu,
  • Shu-Hui Liao,
  • Che-Shao Chen,
  • Tzu-Hung Hsiao,
  • Yi-Ming Chen,
  • Sung-Yuan Hu,
  • Chorng-Kuang How,
  • Amrita Chattopadhyay,
  • Tzu-Pin Lu

摘要

Background

Sepsis is characterized by organ dysfunction as a response to infection and is one of the leading causes of mortality and loss of health. The heterogeneous nature of sepsis, along with ethnic differences in susceptibility, challenges a thorough understanding of its etiology. This study aimed to propose prediction models by leveraging genetic-risk scores and clinical variables that can assist in risk stratification of patients.

Methods

A total of 1,403 patients from Taiwan, diagnosed with sepsis, were utilized. Genome-wide survival analysis was conducted, with death within 28 days from sepsis onset, as the primary event to report significantly associated SNPs. A polygenic risk score (PRS-sepsis) was constructed via clumping and thresholding method which was added to clinical-only models to generate better performing prognostic models for identifying high-risk patients. Kaplan–Meier analysis was conducted using PRS-sepsis.

Results

A total of five single-nucleotide-polymorphisms (SNPs) reached genome-wide significance (p < 5e-8), and 86 SNPs reached suggestive significance (p < 1e-5). The prognostic model using PRS-sepsis showed significantly improved performance with c-index [confidence interval (CI)] of 0.79 [0.62–0.96] and area under receiver operating characteristic curve (AUROC) [CI] of 0.78 [0.75–0.80], in comparison to clinical-only prognostic models (c-index [CI] = 0.63 [0.45– 0.81], AUROC [CI] = 0.61 [0.58–0.64]). The ethnic specificity was established for our proposed models by comparing it with models generated using significant SNPs from prior European studies (c-index [CI] = 0.63 [0.42–0.85], AUROC [CI] = 0.60 [0.58–0.63]). Kaplan–Meier plots showed that patient groups with higher PRSs have inferior survival probability compared to those with lower PRSs.

Conclusions

This study proposed genetic-risk models specific for Taiwanese populations that outperformed clinical-only models. Also it established a strong racial-effect on the underlying genetics of sepsis-related mortality. The model can potentially be used in real clinical setting for deciding precise treatment courses for patients at high-risk thereby reducing the possibility of worse outcomes.