Analysis of gene polymorphisms in patients with pulmonary infections based on next-generation sequencing technology and their prognostic predictive value

TL;DR

This study uses next-generation sequencing to identify gene variations linked to severe pulmonary infections and poor outcomes, suggesting potential for personalized treatment strategies.

Contribution

The study identifies specific gene polymorphisms associated with infection severity and prognosis in pulmonary infections using NGS and introduces a polygenic risk score.

Findings

TLR4 rs4986790 polymorphism is linked to severe infections and longer hospital stays.

IL-10 rs1800896 is associated with higher complication rates like respiratory failure and sepsis.

A polygenic risk score correlates with increased 30-day mortality and complications.

Abstract

Pulmonary infections are a leading cause of morbidity and mortality worldwide, particularly among vulnerable populations such as children and the older adult. Gene polymorphisms play a critical role in disease susceptibility, progression, and prognosis, yet their specific contributions to pulmonary infections remain underexplored. This study utilized next-generation sequencing (NGS) technology to analyze gene polymorphisms in 200 patients with pulmonary infections and evaluate their prognostic value. Key findings include significant associations between polymorphisms in TLR4 (rs4986790), IL-10 (rs1800896), TNF-α (rs1800629), and MBL2 (rs1800450) with infection susceptibility, disease severity, and survival outcomes. Notably, carriers of the TLR4 rs4986790 mutation exhibited increased risk of severe infections and prolonged hospital stays, while IL-10 rs1800896 was linked to higher complication rates, particularly respiratory failure and sepsis. A polygenic risk score (PRS) revealed that high-risk patients had significantly elevated 30-day mortality and complication rates. These results highlight the potential of gene polymorphisms as prognostic biomarkers and personalized treatment targets. Future research should validate these findings in larger, diverse cohorts and explore functional mechanisms.

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