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Joint effects of sleep disturbance and renal function impairment on incident new‐onset severe metabolic dysfunction‐associated steatotic liver disease.

Authors :
Tian, Tian
Zeng, Jing
Li, Yuan‐Cheng
Wang, Jing
Zhang, Dan‐Feng
Wang, De‐Guang
Pan, Hai‐Feng
Fan, Jian‐Gao
Ni, Jing
Source :
Diabetes, Obesity & Metabolism. Oct2024, Vol. 26 Issue 10, p4724-4733. 10p.
Publication Year :
2024

Abstract

Aim: To elucidate the effects of sleep parameters and renal function on the risk of developing new‐onset severe metabolic dysfunction‐associated steatotic liver disease (MASLD). Materials and Methods: The primary analysis involved a cohort of 305 257 participants. Multivariable Cox models were employed to calculate hazard ratios and 95% confidence intervals. Traditional mediation and two‐step Mendelian randomization (MR) analyses were conducted to assess the associations and mediating roles of renal function indicators between sleep and new‐onset severe MASLD. Results: Poor sleep score and renal function biomarker score (RFS) were associated with an increased risk of new‐onset severe MASLD (all ptrend <0.001). Participants with poor sleep patterns and the highest RFS had a 5.45‐fold higher risk of new‐onset severe MASLD, compared to those with healthy sleep patterns and the lowest RFS (p < 0.001). The RFS could explain 10.08% of the correlations between poor sleep score and risk of new‐onset severe MASLD. Additionally, MR analyses supported a causal link between insomnia and new‐onset severe MASLD and revealed a mediating role of chronic kidney disease in the connection between insomnia and new‐onset severe MASLD risk. Conclusions: This study highlights the independent and combined associations of sleep parameters and renal function indicators with new‐onset severe MASLD, underscoring the bidirectional communication of the liver–kidney axis and providing modifiable strategies for preventing MASLD. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14628902
Volume :
26
Issue :
10
Database :
Academic Search Index
Journal :
Diabetes, Obesity & Metabolism
Publication Type :
Academic Journal
Accession number :
179713578
Full Text :
https://doi.org/10.1111/dom.15841