A high reticulocyte count is a risk factor for the onset of metabolic dysfunction-associated steatotic liver disease: Cross-sectional and prospective studies of data of 310,091 individuals from the UK Biobank

Front Pharmacol. 2024 Jul 1:15:1281095. doi: 10.3389/fphar.2024.1281095. eCollection 2024.

Abstract

Background and Aims: Metabolic dysfunction-associated steatotic liver disease (MASLD) poses a considerable health risk. Nevertheless, its risk factors are not thoroughly comprehended, and the association between the reticulocyte count and MASLD remains uncertain. This study aimed to explore the relationship between reticulocyte count and MASLD. Methods: A total of 310,091 individuals from the UK Biobank were included in this cross-sectional study, and 7,316 individuals were included in this prospective study. The cross-sectional analysis categorized reticulocyte count into quartiles, considering the sample distribution. Logistic regression models examined the connection between reticulocyte count and MASLD. In the prospective analysis, Cox analysis was utilized to investigate the association. Results: Our study findings indicate a significant association between higher reticulocyte count and an elevated risk of MASLD in both the cross-sectional and prospective analyses. In the cross-sectional analysis, the adjusted odds ratios (ORs) of MASLD increased stepwise over reticulocyte count quartiles (quartile 2: OR 1.22, 95% CI 1.17-1.28, p < 0.001; quartile 3: OR 1.44; 95% CI 1.38-1.51, p < 0.001; quartile 4: OR 1.66, 95% CI 1.59-1.74, p < 0.001). The results of prospective analyses were similar. Conclusion: Increased reticulocyte count was independently associated with a higher risk of MASLD. This discovery offers new insights into the potential of reticulocytes as biomarkers for MASLD.

Keywords: NAFLD; UK Biobank; metabolic dysfunction-associated steatotic liver disease (MASLD); reticulocyte; risk factor.

Grants and funding

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This work was supported by National Key R&D Program of China (No. 2021YFF1201304), the National Nature Science Foundation of China (No. 81972897, 82172751), Guangzhou Science and Technology Project (No. 202201011183), and Guangdong Natural Science Foundation (No. 2022A1515110656).