| Title: | Polygenic transcriptome risk scores enhance predictive accuracy in atopic dermatitis |
| Journal: | Journal of Translational Medicine |
| Published: | 23 May 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/40410830/ |
| DOI: | https://doi.org/10.1186/s12967-025-06570-8 |
| URL: | https://translational-medicine.biomedcentral.com/counter/pdf/10.1186/s12967-025-06570-8 |
Publication 15227
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Abstract
BackgroundIncorporation of gene expression when estimating polygenic risk scores (PRS) in atopic dermatitis (AD) may provide additional insights in disease pathogenesis and enhance predictive accuracy. In this study, we developed polygenic transcriptome risk scores (PTRSs) derived from AD-enriched tissues and evaluated their performance against traditional PRS models and a baseline risk model incorporating eosinophil and lymphocyte counts in the prediction of AD.MethodsWe conducted transcriptome-wide association studies (TWAS) using the PrediXcan framework to construct tissue-specific PTRSs. Risk score performance was assessed in 256,888 Europeans (10,816 cases) and validated in an independent cohort of 64,152 Europeans (2669 cases) from the UK Biobank.ResultsWe observed a modest correlation between PRS and PTRS, exerting independent effects on AD risk. While PRS demonstrated superior predictive performance compared to single-tissue PTRSs, combining both models significantly enhanced prediction accuracy, yielding a c-statistic of 0.646 (95% confidence intervals: 0.634-0.656). Notably, tissue-specific PTRSs revealed stronger associations with baseline risk factors, where Eppstein-Bar virus (EBV)-transformed lymphocytes and unexposed skin PTRSs tissues reported positive associations with lymphocyte counts.ConclusionsOur findings highlight the value of integrating transcriptome-based risk models to incorporating additional omics layer to refine risk prediction and enhance our understanding of genetic architecture of complex traits.</p>
10 Keywords
- Adult
- Dermatitis, Atopic
- Female
- Genetic Predisposition to Disease
- Humans
- Male
- Middle Aged
- Multifactorial Inheritance
- Risk Factors
- Transcriptome
10 Authors
- Charalabos Antonatos
- Ashley Budu-Aggrey
- Alexandros Pontikas
- Adam Akritidis
- Efstathia Pasmatzi
- Aikaterini Tsiogka
- Stamatis Gregoriou
- Katerina Grafanaki
- Lavinia Paternoster
- Yiannis Vasilopoulos
1 Application
| Application ID | Title |
|---|---|
| 285697 | Dissecting the polygenic architecture of non-communicable diseases and comorbidities |
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