Unraveling Metabolic Dysfunction-Associated Steatotic Liver Disease Through the Use of Omics Technologies
Abstract
1. Introduction
1.1. The Evolution of Liver Disease Nomenclature: From NAFLD to MASLD
1.2. Prevalence, Race, and Ethnicity of the Disease
1.3. The Landscape of MASLD: Pathogenesis and Diagnosis
1.4. Omics Technologies
2. Genomics and MASLD
2.1. PNPLA3
2.2. TM6SF2
2.3. GCKR
2.4. MBOAT7
2.5. HSD17B13
2.6. Other Genes
3. Transcriptomics and MASLD
3.1. Micro-RNAs and Non-Coding RNAs
3.2. Long Non-Coding RNAs (lncRNAs)
3.3. Circular RNAs (circRNAs)
4. Proteomics and MASLD
5. Metabolomics and MASLD
5.1. Applied Metabolomics in MASLD
5.2. Applied Lipidomics in NAFLD
5.3. Applied Glycomics in NAFLD
6. Exposomics in NAFLD
7. Discussion
8. Concluding Remarks
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Omics | Key Contributions of Omics in MASLD Research | References |
---|---|---|
Genomics | • Identification of genetic risk factors | [46,48,49,53] |
• Understanding disease mechanisms | [51] | |
• Personalized treatment and risk stratification | [46,52] | |
• Therapeutic target identification | [51] | |
• Improved monitoring and management | [46] | |
• Addressing population-specific challenges | [52] | |
Transcriptomics | • Insight into disease mechanisms | [106] |
• Gene expression regulation | [46,106] | |
• Identification of disease pathways | [46,107,108,109,110,111,112] | |
• Stratification of disease stages | [115] | |
• Identification of biomarkers for diagnosis | [116,129,138] | |
Proteomics | • Identification of biomarkers and improved biomarker combinations | [169,179,180] |
• Non-invasive diagnostic tools | [119,171] | |
• Disease stage differentiation | [169,173,185,186] | |
• Uncover therapeutic targets | [168,172] | |
• Personalized medicine potential | [168] | |
Metabolomics | • Comprehensive insight into disease mechanisms | [205] |
• Biomarker discovery—non-invasive diagnostic | [202,205] | |
• Precision medicine applications (Algorithm development) | [215,216] | |
• Real-time physiological status | [204,205] | |
• Advancing therapeutics | [205] | |
Exposomics | • Holistic risk assessment | [243,247] |
• Insight into pathological mechanisms | [243,247,248] | |
• Targeted prevention and intervention | [243,247,249] |
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Bourganou, M.V.; Chondrogianni, M.E.; Kyrou, I.; Flessa, C.-M.; Chatzigeorgiou, A.; Oikonomou, E.; Lambadiari, V.; Randeva, H.S.; Kassi, E. Unraveling Metabolic Dysfunction-Associated Steatotic Liver Disease Through the Use of Omics Technologies. Int. J. Mol. Sci. 2025, 26, 1589. https://doi.org/10.3390/ijms26041589
Bourganou MV, Chondrogianni ME, Kyrou I, Flessa C-M, Chatzigeorgiou A, Oikonomou E, Lambadiari V, Randeva HS, Kassi E. Unraveling Metabolic Dysfunction-Associated Steatotic Liver Disease Through the Use of Omics Technologies. International Journal of Molecular Sciences. 2025; 26(4):1589. https://doi.org/10.3390/ijms26041589
Chicago/Turabian StyleBourganou, Maria V., Maria Eleni Chondrogianni, Ioannis Kyrou, Christina-Maria Flessa, Antonios Chatzigeorgiou, Evangelos Oikonomou, Vaia Lambadiari, Harpal S. Randeva, and Eva Kassi. 2025. "Unraveling Metabolic Dysfunction-Associated Steatotic Liver Disease Through the Use of Omics Technologies" International Journal of Molecular Sciences 26, no. 4: 1589. https://doi.org/10.3390/ijms26041589
APA StyleBourganou, M. V., Chondrogianni, M. E., Kyrou, I., Flessa, C.-M., Chatzigeorgiou, A., Oikonomou, E., Lambadiari, V., Randeva, H. S., & Kassi, E. (2025). Unraveling Metabolic Dysfunction-Associated Steatotic Liver Disease Through the Use of Omics Technologies. International Journal of Molecular Sciences, 26(4), 1589. https://doi.org/10.3390/ijms26041589