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. 2023 Jan 6:13:1056562.
doi: 10.3389/fendo.2022.1056562. eCollection 2022.

Sequential algorithm to stratify liver fibrosis risk in overweight/obese metabolic dysfunction-associated fatty liver disease

Chi-Ho Lee  1   2 , David Tak-Wai Lui  1 , Raymond Hang-Wun Li  3 , Michele Mae-Ann Yuen  1 , Carol Ho-Yi Fong  1 , Ambrose Pak-Wah Leung  1 , Justin Chiu-Man Chu  1 , Loey Lung-Yi Mak  1 , Tai-Hing Lam  4 , Jean Woo  5 , Yu-Cho Woo  1 , Aimin Xu  1   2 , Hung-Fat Tse  1 , Kathryn Choon-Beng Tan  1 , Bernard Man-Yung Cheung  1 , Man-Fung Yuen  1   6 , Karen Siu-Ling Lam  1   2
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Sequential algorithm to stratify liver fibrosis risk in overweight/obese metabolic dysfunction-associated fatty liver disease

Chi-Ho Lee et al. Front Endocrinol (Lausanne). .

Abstract

Background: Non-diabetic overweight/obese metabolic dysfunction-associated fatty liver disease (MAFLD) represents the largest subgroup with heterogeneous liver fibrosis risk. Metabolic dysfunction promotes liver fibrosis. Here, we investigated whether incorporating additional metabolic risk factors into clinical evaluation improved liver fibrosis risk stratification among individuals with non-diabetic overweight/obese MAFLD.

Materials and methods: Comprehensive metabolic evaluation including 75-gram oral glucose tolerance test was performed in over 1000 participants from the New Hong Kong Cardiovascular Risk Factor Prevalence Study (HK-NCRISPS), a contemporary population-based study of HK Chinese. Hepatic steatosis and fibrosis were evaluated based on controlled attenuation parameter and liver stiffness (LS) measured using vibration-controlled transient elastography, respectively. Clinically significant liver fibrosis was defined as LS ≥8.0 kPa. Our findings were validated in an independent pooled cohort comprising individuals with obesity and/or polycystic ovarian syndrome.

Results: Of the 1020 recruited community-dwelling individuals, 312 (30.6%) had non-diabetic overweight/obese MAFLD. Among them, 6.4% had LS ≥8.0 kPa. In multivariable stepwise logistic regression analysis, abnormal serum aspartate aminotransferase (AST) (OR 7.95, p<0.001) and homeostasis model assessment of insulin resistance (HOMA-IR) ≥2.5 (OR 5.01, p=0.008) were independently associated with LS ≥8.0 kPa, in a model also consisting of other metabolic risk factors including central adiposity, hypertension, dyslipidaemia and prediabetes. A sequential screening algorithm using abnormal AST, followed by elevated HOMA-IR, was developed to identify individuals with LS ≥8.0 kPa, and externally validated with satisfactory sensitivity (>80%) and negative predictive value (>90%).

Conclusion: A sequential algorithm incorporating AST and HOMA-IR levels improves fibrosis risk stratification among non-diabetic overweight/obese MAFLD individuals.

Keywords: MAFLD (metabolic associated fatty liver disease); fatty liver disease; obesity; overweight; population based study.

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Conflict of interest statement

C-HL received speaker’s fees from AstraZeneca, Bayer, Boehringer Ingelheim, Eli Lilly and Sanofi Aventis. M-FY reports grant/research support from AbbVie, Assembly Biosciences, Arrowhead Pharmaceuticals, Bristol Myers Squibb, Fujirebio Incorporation, Gilead Sciences, Immuncore, Merck Sharp and Dohme, Springbank Pharmaceuticals, Sysmex Corporation and Roche, consultancy for AbbVie, Aligos Therapeutics, AiCuris, Antios Therapeutics, Arbutus Biopharma, Arrowhead Pharmaceuticals, Assembly Biosciences, Bristol Myers Squibb, Clear B Therapeutics, Dicerna Pharmaceuticals, Finch Therapeutics, Fujirebio Incorporation, GSK, Gilead Sciences, Immunocore, Janssen, Merck Sharp and Dohme, Roche, Springbank Pharmaceuticals, Silverback Therapeutics, Sysmex Corporation and Vir Biotechnology, and lecture fees from AbbVie, Dicerna Pharmaceuticals, Fujirebio Incorporation, Gilead Sciences, Merck Sharp and Dohme, Roche and Sysmex Corporation. KL is an advisory board member of Merck Sharp and Dohme. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be constructed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Sequential clinical algorithm for identifying overweight/obese participants with MAFLD at risk of clinically significant liver fibrosis (i.e. LS ≥8.0 kPa) (N=312). MAFLD, metabolic dysfunction-associated fatty liver disease; cACLD, compensated advanced chronic liver disease; LS, liver stiffness; AST, aspartate aminotransferase; HOMA-IR, homeostasis model assessment of insulin resistance.
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