ArticleFrontiers in endocrinology2023
Proteome profiling identifies circulating biomarkers associated with hepatic steatosis in subjects with Prader-Willi syndrome.
Article in Frontiers in endocrinology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- Proteomic Insights into Childhood Obesity: A Systematic Review of Protein Biomarkers and Advances.International journal of molecular sciences · 2025Pooled it
- Analytical Validation and Preliminary Clinical Evaluation of Plasma Carboxylesterase 1 for Ultrasound-Defined Hepatic Steatosis.Diagnostics (Basel, Switzerland) · 2026Article
- Innovative models to explore hepatic involvement in Prader-Willi syndrome.Frontiers in endocrinology · 2026Review
- Low-Abundance Proteomics Reveal Pleiotrophin and Fibroblast Growth Factor-21 as Biomarkers of Metabolic Dysfunction-Associated Steatohepatitis.International journal of molecular sciences · 2025Article
- Dissecting metabolic dysfunction- and alcohol-associated liver disease (MetALD) using proteomic and metabolomic profiles.Journal of hepatology · 2025Article
- Mesenchymal Stromal Cell Secretome and Its Key Bioactive Metabolites Induce Long-Term Neuroprotection After Traumatic Brain Injury in Mice.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Physiology, imaging and proteomics of non-ventilated vs. non-perfused lung injury: an experimental study.Intensive care medicine experimental · 2025Article
- Serum proteome signatures associated with liver steatosis in adolescents with obesity.Journal of endocrinological investigation · 2025Article
- Proteome Profiling Identifies CDH2 as a Potential Screening Marker for NAFLD and Liver Fibrosis in the Snoring Population.Nature and science of sleep · 2025Article
- Article
- Differential expression of cardiometabolic and inflammation markers and signaling pathways between overweight/obese Qatari adults with high and low plasma salivary α-amylase activity.Frontiers in endocrinology · 2024Article
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Authors and funding
10 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Prader-Willi syndrome (PWS) is a rare genetic disorder characterized by loss of expression of paternal chromosome 15q11.2-q13 genes. Individuals with PWS exhibit unique physical, endocrine, and metabolic traits associated with severe obesity. Identifying liver steatosis in PWS is challenging, despite its lower prevalence compared to non-syndromic obesity. Reliable biomarkers are crucial for the early detection and management of this condition associated with the complex metabolic profile and cardiovascular risks in PWS. Methods: Circulating proteome profiling was conducted in 29 individuals with PWS (15 with steatosis, 14 without) using the Olink Target 96 metabolism and cardiometabolic panels. Correlation analysis was performed to identify the association between protein biomarkes and clinical variables, while the gene enrichment analysis was conducted to identify pathways linked to deregulated proteins. Receiver operating characteristic (ROC) curves assessed the discriminatory power of circulating protein while a logistic regression model evaluated the potential of a combination of protein biomarkers. Results: CDH2, CTSO, QDPR, CANT1, ALDH1A1, TYMP, ADGRE, KYAT1, MCFD, SEMA3F, THOP1, TXND5, SSC4D, FBP1, and CES1 exhibited a significant differential expression in liver steatosis, with a progressive increase from grade 1 to grade 3. FBP1, CES1, and QDPR showed predominant liver expression. The logistic regression model, -34.19 + 0.85 * QDPR*QDPR + 0.75 * CANT1*TYMP - 0.46 * THOP1*ALDH1A, achieved an AUC of 0.93 (95% CI: 0.63-0.99), with a sensitivity of 93% and specificity of 80% for detecting steatosis in individuals with PWS. These biomarkers showed strong correlations among themselves and were involved in an interconnected network of 62 nodes, related to seven metabolic pathways. They were also significantly associated with cholesterol, LDL, triglycerides, transaminases, HbA1c, FLI, APRI, and HOMA, and showed a negative correlation with HDL levels. Conclusion: The biomarkers identified in this study offer the potential for improved patient stratification and personalized therapeutic protocols.
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