| Title: | Plasma protein-based and polygenic risk scores serve complementary roles in predicting inflammatory bowel disease. |
| Journal: | Biocomputing |
| Published: | 1 Jan 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/39670393/ |
Publication 14817
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Abstract
Inflammatory bowel disease (IBD), encompassing Crohn's disease (CD) and ulcerative colitis (UC), has a significant genetic component and is increasingly prevalent due to environmental factors. Current polygenic risk scores (PRS) have limited predictive power and cannot inform time of symptom onset. Circulating proteomics profiling offers a novel, non-invasive approach for understanding the inflammatory state of complex diseases, enabling the creation of proteomic risk scores (ProRS). This study utilizes data from 51,772 individuals in the UK Biobank to evaluate the unique and combined contributions of PRS and ProRS to IBD risk prediction. We developed ProRS models for CD and UC, assessed their predictive performance over time, and examined the benefits of integrating PRS and ProRS for enhanced risk stratification. Our findings are the first to demonstrate that combining genetic and proteomic data improves IBD incidence prediction, with ProRS providing time-sensitive predictions and PRS offering additional long-term predictive value. We also show that the ProRS achieves better predictive performance among individuals with high PRS. This integrated approach highlights the potential for multi-omic data in precision medicine for IBD.</p>
17 Keywords
- Blood Proteins
- Colitis, Ulcerative
- Computational Biology
- Crohn Disease
- Female
- Genetic Predisposition to Disease
- Genetic Risk Score
- Humans
- Inflammatory Bowel Diseases
- Male
- Middle Aged
- Multifactorial Inheritance
- Polymorphism, Single Nucleotide
- Proteomics
- Risk Assessment
- Risk Factors
- United Kingdom
9 Authors
- Jakob Woerner
- Thomas Westbrook
- Seokho Jeong
- Manu Shivakumar
- Allison R. Greenplate
- Sokratis A. Apostolidis
- Seunggeun Lee
- Yonghyun Nam
- Dokyoon Kim
1 Application
| Application ID | Title |
|---|---|
| 45227 | Scalable and Robust methods for biobank data analysis |
Enabling scientific discoveries that improve human health