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<p>Systemic inflammation contributes to the progression of heart failure (HF). However, the precise effects of platelet count (PCT), white blood cell count (WBC), neutrophil percentage (NEUT) on HF development and progression are poorly understood. Thus, in this study, we aimed to assess the associations between PCT, WBC, NEUT and HF. We utilized National Health and Nutrition Examination Survey (NHANES) data from 1999 to 2018, excluding the second round of test data from 2001 to 2002, to assess HF using questionnaires and measured blood parameters adjusted by the covariates. We employed weighted quantile sum (WQS) regression to analyze the overall impact of multiple blood markers on HF, restricted cubic spline (RCS) analysis to assess non-linear relationships, and Mendelian randomization (MR) analysis using two-sample MR methods to examine genome-wide association study data. We also further confirmed the causal direction by Steiger test. The result from WQS regression showed that significant associations between PCT, WBC, and NEUT and HF. NEUT was most strongly linked to HF (<i>P</i> = 0.001), with heightened risk at levels ≥ 58.507%. RCS analysis showed a non-linear relationship of HF with WBC, where higher counts caused a shift from protective to increasing risk. MR analysis revealed a significant causal relationship between NEUT and HF (<i>P</i> = 0.00156), which was confirmed using the Steiger test. Reverse MR analysis indicated that HF had no significant impact on NEUT (<i>P</i> = 0.772). Our study highlights a significant correlation between NEUT and HF, indicating that NEUT might potentially serve as a biomarker for predicting HF.</p>

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Genetic and epidemiological insights into the role of neutrophil percentage in heart failure risk: a Mendelian randomization and NHANES study

  • 期刊论文

  • 发表日期：

    2026年1月9日

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  • Yan Gao,
  • Fan Yang,
  • Lingyan Lei,
  • Yueqiu Qin,
  • Liuping He,
  • Xiaocong Zeng

摘要

Systemic inflammation contributes to the progression of heart failure (HF). However, the precise effects of platelet count (PCT), white blood cell count (WBC), neutrophil percentage (NEUT) on HF development and progression are poorly understood. Thus, in this study, we aimed to assess the associations between PCT, WBC, NEUT and HF. We utilized National Health and Nutrition Examination Survey (NHANES) data from 1999 to 2018, excluding the second round of test data from 2001 to 2002, to assess HF using questionnaires and measured blood parameters adjusted by the covariates. We employed weighted quantile sum (WQS) regression to analyze the overall impact of multiple blood markers on HF, restricted cubic spline (RCS) analysis to assess non-linear relationships, and Mendelian randomization (MR) analysis using two-sample MR methods to examine genome-wide association study data. We also further confirmed the causal direction by Steiger test. The result from WQS regression showed that significant associations between PCT, WBC, and NEUT and HF. NEUT was most strongly linked to HF (P = 0.001), with heightened risk at levels ≥ 58.507%. RCS analysis showed a non-linear relationship of HF with WBC, where higher counts caused a shift from protective to increasing risk. MR analysis revealed a significant causal relationship between NEUT and HF (P = 0.00156), which was confirmed using the Steiger test. Reverse MR analysis indicated that HF had no significant impact on NEUT (P = 0.772). Our study highlights a significant correlation between NEUT and HF, indicating that NEUT might potentially serve as a biomarker for predicting HF.