BMC medical genomics · 2024
Blood cell parameters and risk of nonalcoholic fatty liver disease: a comprehensive Mendelian randomization study.
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Zhu Nan, Wang Xiaoliang, Zhu Huiting, Zheng Yue
Аннотация
BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) is on the rise globally, and past research suggests a significant association with various blood cell components. Our goal is to explore the potential correlation between whole blood cell indices and NAFLD risk using Mendelian randomization (MR).
METHODS: We analyzed data from 4,198 participants in the 2017-2018 National Health and Nutrition Examination Survey to investigate the link between blood cell indicators and NAFLD. Using various methods like weighted quantile sum and multivariate logistic regression, we assessed the association. Additionally, two-sample Mendelian randomization were employed to infer causality for 36 blood cell indicators and NAFLD.
RESULTS: Multivariate logistic regression identified 10 NAFLD risk factors. Weighted quantile sum revealed a positive correlation (p = 6.03e-07) between total blood cell indices and NAFLD, with hemoglobin and lymphocyte counts as key contributors. Restricted cubic spline analysis found five indicators with significant nonlinear correlations to NAFLD. Mendelian randomization showed a notable association between reticulocyte counts and NAFLD using the inverse-variance weighted method.
CONCLUSIONS: Hematological markers pose an independent NAFLD risk, with a positive causal link found for reticulocyte count. These results emphasize the importance of monitoring NAFLD and investigating specific underlying mechanisms further.
METHODS: We analyzed data from 4,198 participants in the 2017-2018 National Health and Nutrition Examination Survey to investigate the link between blood cell indicators and NAFLD. Using various methods like weighted quantile sum and multivariate logistic regression, we assessed the association. Additionally, two-sample Mendelian randomization were employed to infer causality for 36 blood cell indicators and NAFLD.
RESULTS: Multivariate logistic regression identified 10 NAFLD risk factors. Weighted quantile sum revealed a positive correlation (p = 6.03e-07) between total blood cell indices and NAFLD, with hemoglobin and lymphocyte counts as key contributors. Restricted cubic spline analysis found five indicators with significant nonlinear correlations to NAFLD. Mendelian randomization showed a notable association between reticulocyte counts and NAFLD using the inverse-variance weighted method.
CONCLUSIONS: Hematological markers pose an independent NAFLD risk, with a positive causal link found for reticulocyte count. These results emphasize the importance of monitoring NAFLD and investigating specific underlying mechanisms further.