| Title: | Novel metabolic classification for extrahepatic complication of metabolic associated fatty liver disease: A data-driven cluster analysis with international validation |
| Journal: | Metabolism |
| Published: | 20 Aug 2022 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/35995280/ |
| DOI: | https://doi.org/10.1016/j.metabol.2022.155294 |
| URL: | http://www.metabolismjournal.com/article/S002604952200172X/pdf |
| Citations: | 19 (19 in last 2 years) as of 8 Aug 2024 |
Publication 12265
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Abstract
BACKGROUND: Traditional classification systems of metabolic-associated fatty liver disease (MAFLD) do not account for the high rate of extrahepatic complications. To create a new classification of MAFLD using metabolic parameters to identify risks of complications more accurately.</p>
METHODS: The retrospective study included MAFLD patients from the First Affiliated Hospital of Sun Yat-sen University for model development, and the model was validated respectively using Chinese cohort and UK Biobank database. Cluster analysis with k-means cluster was built using age, body mass index (BMI), glycosylated hemoglobin (HbA1c), total cholesterol/high density lipoprotein cholesterol (HDL-C) ratio, triglyceride, and lipoprotein(a) [Lp(a)] levels. Cox regression models were used to compare the risk of type 2 diabetes (T2DM), chronic heart disease (CHD), stroke and mortality between the clusters.</p>
RESULTS: 1038 MAFLD patients from cross-sectional population were recruited for the model derivation, with 10,451 cases (33.4 % of MAFLD) from Chinese cohort and 304,141 cases (34.9 % of MAFLD, 1010 cases with magnetic resonance imaging proton density fat fraction measurement [MRI-PDFF]) from the international cohort validated. Five replicable clusters of MAFLD patients were identified: Cluster 1(mild obesity and dyslipidemia-related), Cluster 2 (age related), Cluster 3 (severe insulin resistance-related), Cluster 4[high Lp(a)-related], and Cluster 5 (severe mixed hyperlipidemia-related). Patients in different clusters exhibited differences in the development of T2DM, CHD, stroke and all-causes mortality. Patients in Cluster 3 had significantly worst survival outcomes and higher risks of T2DM and CVD than those in other clusters.</p>
CONCLUSION: The novel classification offers improved discrimination of new-onset MAFLD patients with different metabolic complications.</p>
13 Keywords
- Cholesterol, HDL
- Cluster Analysis
- Cross-Sectional Studies
- Diabetes Mellitus, Type 2
- Glycated Hemoglobin
- Humans
- Lipoprotein(a)
- Liver Diseases
- Non-alcoholic Fatty Liver Disease
- Protons
- Retrospective Studies
- Stroke
- Triglycerides
9 Authors
- Junzhao Ye
- Xiaodong Zhuang
- Xin Li
- Xiaorong Gong
- Yanhong Sun
- Wei Wang
- Shiting Feng
- Tingfeng Wu
- Bihui Zhong
1 Application
| Application ID | Title |
|---|---|
| 56925 | Uncovering genetic and biological causes of cardio-metabolic disease and traits by integrated genetic, functional genomic, clinical, and imaging data |
Enabling scientific discoveries that improve human health