| Title: | Obesity phenotypes, omics signatures, and risk of adverse liver outcomes |
| Journal: | Journal of the National Cancer Institute |
| Published: | 21 Jul 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/42482169/ |
| DOI: | https://doi.org/10.1093/jnci/djag242 |
Publication 21350
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Abstract
BACKGROUND: Obesity increases risks of chronic liver disease (CLD) and liver cancer, but risks across obesity phenotypes and related molecular signatures remain incompletely characterized. We evaluated associations of obesity phenotypes and obesity-related omics signatures with adverse liver outcomes.</p>
DESIGN: We analyzed 451,463 UK Biobank participants aged 40-69 years. General and central obesity were defined by body mass index (BMI) and waist circumference. Metabolically unhealthy obesity (MUO) was defined as obesity plus ≥1 metabolic abnormality. Liver outcomes (metabolic dysfunction-associated steatotic liver disease, cirrhosis, liver cancer, severe liver disease, and CLD mortality) were ascertained from hospital inpatient records, cancer and death registries. Cox models estimated hazard ratios (HRs) for obesity measures and internally validated NMR metabolomic and Olink proteomic signatures derived using elastic-net regression.</p>
RESULTS: During a median 11-year follow-up, general obesity, central obesity, and MUO were associated with higher risks of adverse liver outcomes (HRs 1.53-3.68). Participants with both general and central obesity had the highest risks. Omics signatures of MUO were more strongly associated with liver outcomes than general or central obesity signatures (HRs, 1.58-6.13 vs 1.43-4.72). NMR metabolomic biomarkers (albumin, glutamine, triglycerides) and proteomic biomarkers (FABP4, CDHR2, TGFBR2, IL1RN) were consistently associated with multiple liver outcomes.</p>
CONCLUSION: Obesity phenotypes, particularly MUO, and obesity-related omics signatures were associated with higher risks of liver cancer and other adverse liver outcomes. Findings highlight metabolic dysfunction beyond adiposity as an important dimension of obesity-related liver risk and suggest that metabolomic and proteomic profiles may provide molecular insight.</p>
18 Authors
- Longgang Zhao
- Yun Chen
- Jun Li
- Cong Wang
- Tamar H Taddei
- Xiaomei Ma
- Shuangge Ma
- Olga Demler
- Azam Yazdani
- Oluwafeyisola Osifala
- Diego Martínez Urbistondo
- Miguel A Martínez-González
- Deirdre K Tobias
- Edward Giovannucci
- Howard D Sesso
- JoAnn E Manson
- Frank Hu
- Xuehong Zhang
1 Application
| Application ID | Title |
|---|---|
| 87303 | Improving liver health in humans: Elucidating the role of genetics, biomarkers, and environment in liver biology, etiology, progression, and prognosis |
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