Clinical and Translational Research
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Hepatol. Aug 27, 2024; 16(8): 1145-1155
Published online Aug 27, 2024. doi: 10.4254/wjh.v16.i8.1145
Blood cell counts and nonalcoholic fatty liver disease: Evidence from Mendelian randomization analysis
Bin Hu, Ai-Hong Wan, Xi-Qiao Xiang, Yuan-Hao Wei, Yi Chen, Zhen Tang, Chang-De Xu, Zi-Wei Zheng, Shao-Ling Yang, Kun Zhao
Bin Hu, Department of Laboratory Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital South Campus, Shanghai 201499, China
Ai-Hong Wan, Department of Cardiology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital South Campus, Shanghai 201499, China
Xi-Qiao Xiang, Yi Chen, Zhen Tang, Chang-De Xu, Kun Zhao, Department of Positron Emission Tomography-Computed Tomography Imaging Center, Shanghai Jiao Tong University Affiliated Sixth People's Hospital South Campus, Shanghai 201499, China
Yuan-Hao Wei, Department of School of Public Health, Harbin Medical University, Harbin 150081, Heilongjiang Province, China
Zi-Wei Zheng, Shao-Ling Yang, Department of Cardiovascular Ultrasound Medicine Center, Shanghai Eighth People's Hospital, Shanghai 200235, China
Co-first authors: Bin Hu and Ai-Hong Wan.
Co-corresponding authors: Shao-Ling Yang and Kun Zhao.
Author contributions: Yang SL and Zhao K conceptualized and designed the research; Hu B and Wan AH wrote the original draft of the manuscript, contributed equally to this work and share first authorship; Xiang XQ and Wei YH performed the statistical analysis; Chen Y, Tang Z, Xu CD, and Zheng ZW contributed to the acquisition, analysis, or interpretation of the data. Both Yang SL and Zhao K have played important and indispensable roles in the study design, data interpretation, and manuscript preparation as the co-corresponding authors. Yang SL was instrumental in conceptualizing the study's framework, devising innovative methodologies, and overseeing the experimental design., and also obtained the funds for this research project. Zhao K excelled in leading the data analysis process, applying sophisticated statistical techniques to interpret the results. This collaboration between Yang SL and Zhao K is crucial for the publication of this manuscript and other manuscripts still in preparation.
Supported by the Shanghai Natural Science Foundation of China, No. 23ZR1447800; and the Fengxian District Science and Technology Commission Project, China, No. 20211838.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/licenses/by-nc/4.0/
Corresponding author: Kun Zhao, MD, Doctor, Department of Positron Emission Tomography-Computed Tomography Imaging Center, Shanghai Jiao Tong University Affiliated Sixth People's Hospital South Campus, No. 6600 Nanfeng Highway, Shanghai 201499, China. zzleaning@163.com
Received: May 19, 2024
Revised: July 3, 2024
Accepted: July 23, 2024
Published online: August 27, 2024
Processing time: 94 Days and 10 Hours
Abstract
BACKGROUND

Previous research has highlighted correlations between blood cell counts and chronic liver disease. Nonetheless, the causal relationships remain unknown.

AIM

To evaluate the causal effect of blood cell traits on liver enzymes and nonalcoholic fatty liver disease (NAFLD) risk.

METHODS

Independent genetic variants strongly associated with blood cell traits were extracted from a genome-wide association study (GWAS) conducted by the Blood Cell Consortium. Summary-level data for liver enzymes were obtained from the United Kingdom Biobank. NAFLD data were obtained from a GWAS meta-analysis (8434 cases and 770180 controls, discovery dataset) and the Fingen GWAS (2275 cases and 372727 controls, replication dataset). This analysis was conducted using the inverse-variance weighted method, followed by various sensitivity analyses.

RESULTS

One SD increase in the genetically predicted haemoglobin concentration (HGB) was associated with a β of 0.0078 (95%CI: 0.0059-0.0096), 0.0108 (95%CI: 0.0080-0.0136), 0.0361 (95%CI: 0.0156-0.0567), and 0.0083 (95%CI: 00046-0.0121) for alkaline phosphatase (ALP), alanine aminotransferase (ALT), aspartate aminotransferase, and gamma-glutamyl transferase, respectively. Genetically predicted haematocrit was associated with ALP (β = 0.0078, 95%CI: 0.0052-0.0104) and ALT (β = 0.0057, 95%CI: 0.0039-0.0075). Genetically determined HGB and the reticulocyte fraction of red blood cells increased the risk of NAFLD [odds ratio (OR) = 1.199, 95%CI: 1.087-1.322] and (OR = 1.157, 95%CI: 1.071-1.250). The results of the sensitivity analyses remained significant.

CONCLUSION

Novel causal blood cell traits related to liver enzymes and NAFLD development were revealed through Mendelian randomization analysis, which may facilitate the diagnosis and prevention of NAFLD.

Keywords: Blood cell counts; Liver enzymes; Nonalcoholic fatty liver disease; Genome-wide association; Mendelian randomization study; Causal relationship

Core Tip: Mendelian randomization analysis revealed a novel evidence for a causal role of genetically predicted blood cell traits in liver injury and nonalcoholic fatty liver disease (NAFLD). The study found that genetically determined increases in hemoglobin concentration (HGB) and hematocrit levels were associated with elevated levels of liver enzymes. In addition, genetic determinants of HGB and reticulocyte ratio are associated with an increased risk of NAFLD. These findings may help in the diagnosis and prevention of NAFLD.