| Title: | Integrated Plasma Proteomics and Functional Analyses Reveal Hepatic CDHR2 as a Potential Therapeutic Target in MASLD |
| Journal: | Diabetes Obesity and Metabolism |
| Published: | 10 Mar 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/41804813/ |
| DOI: | https://doi.org/10.1111/dom.70623 |
Publication 17428
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Abstract
AIMS: Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) is a highly prevalent chronic liver condition, and effective therapeutic targets remain urgently needed. This study integrated multiple data sources to identify and functionally validate protein targets implicated in MASLD.</p>
MATERIALS AND METHODS: In the UK Biobank, we identified participants with MASLD, and selected those with imaging-derived corrected T1 (cT1) and plasma proteomic data. Proteins significantly associated with cT1 were identified through association analyses. Two-sample bidirectional Mendelian randomisation (MR) was then conducted to assess the causal effects of candidate proteins on MASLD and cirrhosis. Hepatic expression of the candidate gene was assessed using bulk and single-cell RNA-seq datasets, complemented by immunostaining. Functional validation was performed in vitro by silencing or overexpressing Cadherin-Related Family Member 2 (CDHR2) in FFA-treated primary hepatocytes as well as HepG2 and AML12 cells, followed by evaluation of lipid accumulation and related signalling pathways.</p>
RESULTS: A total of 36 proteins were identified as significantly associated with cT1 in patients with fatty liver. MR analysis revealed that only genetically predicted higher levels of CDHR2 were causally associated with an increased risk of both MASLD and liver cirrhosis. CDHR2 was up-regulated in MASLD patients primarily in hepatocytes compared with healthy controls. In vitro, CDHR2 knockdown significantly alleviated adipogenesis and enhanced the antioxidant response in steatotic hepatocytes.</p>
CONCLUSIONS: These findings identify CDHR2 as a novel regulator of MASLD development and progression, and highlight it as a potential therapeutic target.</p>
9 Authors
- Yuanping Shi
- Qi Huang
- Yingning Liu
- Xinlei Zhang
- Feng Liu
- Huiying Rao
- Xueyao Han
- Linong Ji
- Xiantong Zou
1 Application
| Application ID | Title |
|---|---|
| 145819 | Elucidate the correlation between features derived from abdominal MRI and the incidence and outcomes of metabolic diseases using multimodal data |
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