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<p>Stroke is a leading cause of global morbidity and mortality. Genetic variation, particularly single nucleotide polymorphisms (SNPs), has been implicated not only in stroke susceptibility but also in post-stroke outcomes and recurrence. However, evidence remains fragmented across populations, stroke subtypes, and clinical endpoints. We conducted a systematic review in accordance with PRISMA guidelines, searching PubMed, Scopus, Web of Science, Embase, Cochrane Library, and Google Scholar through January 2025. Eligible studies included case–control, cohort, genome-wide association, and Mendelian randomization studies examining associations between SNPs and incident stroke risk, post-stroke outcomes, or recurrence. Data were extracted on study design, population, genetic variants, and effect estimates. Study quality was assessed using the Newcastle–Ottawa Scale, supplemented by qualitative consideration of genetic-study–specific biases. Twenty-seven studies were included, encompassing diverse populations and stroke-related outcomes. SNPs in genes related to inflammation (e.g., <i>TNF-α</i>, <i>HMGB1</i>), lipid metabolism (<i>ANGPTL4</i>, <i>DIAPH1</i>), oxidative stress (<i>MTHFR</i>), and regulatory RNAs (<i>MIAT</i>, microRNAs) were associated with stroke susceptibility, subtype-specific risk, post-stroke recovery, or recurrence. Associations varied substantially by study design, population, and outcome, with most findings derived from candidate-gene studies and limited independent replication. Genetic variants across multiple biological pathways are associated with stroke-related phenotypes, including susceptibility, prognosis, and recurrence. However, heterogeneity of outcomes and study designs limits causal inference and clinical translation. Larger multi-ethnic studies with replication and functional validation are required before SNP-based risk stratification can be routinely applied.</p>

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Single Nucleotide Polymorphisms in Stroke: Evidence Across Susceptibility, Prognosis, and Recurrence; A Systematic Review

  • 期刊论文

  • 发表日期：

    2026年3月16日

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  • Nicholas Aderinto,
  • Ibiyinka Daramola,
  • Chiamaka Norah Ezeagu,
  • Gbolahan Olatunji,
  • Emmanuel Kokori,
  • Bonaventure Michael Ukoaka,
  • Adetola Emmanuel Babalola,
  • Olamide Asifat,
  • Aditya Gaur,
  • Israel Charles Abraham,
  • Faisal Hamed Aljamea

摘要

Stroke is a leading cause of global morbidity and mortality. Genetic variation, particularly single nucleotide polymorphisms (SNPs), has been implicated not only in stroke susceptibility but also in post-stroke outcomes and recurrence. However, evidence remains fragmented across populations, stroke subtypes, and clinical endpoints. We conducted a systematic review in accordance with PRISMA guidelines, searching PubMed, Scopus, Web of Science, Embase, Cochrane Library, and Google Scholar through January 2025. Eligible studies included case–control, cohort, genome-wide association, and Mendelian randomization studies examining associations between SNPs and incident stroke risk, post-stroke outcomes, or recurrence. Data were extracted on study design, population, genetic variants, and effect estimates. Study quality was assessed using the Newcastle–Ottawa Scale, supplemented by qualitative consideration of genetic-study–specific biases. Twenty-seven studies were included, encompassing diverse populations and stroke-related outcomes. SNPs in genes related to inflammation (e.g., TNF-α, HMGB1), lipid metabolism (ANGPTL4, DIAPH1), oxidative stress (MTHFR), and regulatory RNAs (MIAT, microRNAs) were associated with stroke susceptibility, subtype-specific risk, post-stroke recovery, or recurrence. Associations varied substantially by study design, population, and outcome, with most findings derived from candidate-gene studies and limited independent replication. Genetic variants across multiple biological pathways are associated with stroke-related phenotypes, including susceptibility, prognosis, and recurrence. However, heterogeneity of outcomes and study designs limits causal inference and clinical translation. Larger multi-ethnic studies with replication and functional validation are required before SNP-based risk stratification can be routinely applied.