Integrative proteo-transcriptomic characterization of advanced fibrosis in chronic liver disease across etiologies
Creators
- Yang, Hong1
- Atak, Dila2
- Yuan, Meng1
- Li, Mengzhen1
- Altay, Ozlem1
- Demirtas, Elif3
- Peltek, Ibrahim Batuhan3
- Ulukan, Burge2
- Yigit, Buket2
- Sipahioglu, Tarik2
- Alvez, Maria Bueno1
- Meng, Lingqi
- Yuksel, Bayram4
- Turkez, Hasan5
- Kirimlioglu, Hale6
- Saka, Burcu7
- Yurdaydin, Cihan2
- Akyildiz, Murat2
- Dayangac, Murat8
- Uhlen, Mathias1
- 1. KTH Royal Inst Technol, Sci Life Lab, Stockholm, Sweden
- 2. Koc Univ, Sch Med, Dept Gastroenterol & Hepatol, TR-34010 Istanbul, Turkiye
- 3. Koc Univ, Sch Med, TR-34450 Istanbul, Turkiye
- 4. SZAOMICS Biotechnol R&D, TR-34010 Istanbul, Turkiye
- 5. Ataturk Univ, Fac Med, Dept Med Biol, TR-25240 Erzurum, Turkiye
- 6. Acibadem Mehmet Ali Aydinlar Univ, Sch Med, Dept Pathol, TR-34752 Istanbul, Turkiye
- 7. Koc Univ, Sch Med, Dept Pathol, TR-34010 Istanbul, Turkiye
- 8. Medipol Univ, Int Sch Med, Dept Gen Surg, TR-34010 Istanbul, Turkiye
Description
Chronic hepatic injury and inflammation from various causes can lead to fibrosis and cirrhosis, potentially predisposing to hepatocellular carcinoma. The molecular mechanisms underlying fibrosis and its progression remain incompletely understood. Using a proteo-transcriptomics approach, we analyze liver and plasma samples from 330 individuals, including 40 healthy individuals and 290 patients with histologically characterized fibrosis due to chronic viral infection, alcohol consumption, or metabolic dysfunction-associated steatotic liver disease. Our findings reveal dysregulated pathways related to extracellular matrix, immune response, inflammation, and metabolism in advanced fibrosis. We also identify 132 circulating proteins associated with advanced fibrosis, with neurofascin and growth differentiation factor 15 demonstrating superior predictive performance for advanced fibrosis(area under the receiver operating characteristic curve [AUROC] 0.89 [95% confidence interval (CI) 0.81-0.97]) compared to the fibrosis-4 model (AUROC 0.85 [95% CI 0.78- 0.93]). These findings provide insights into fibrosis pathogenesis and highlight the potential for more accurate non-invasive diagnosis.
Files
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