A model for predicting celiac disease among undiagnosed subjects established with data from the HUNT4 study
Mohammad Sayeef Alam, Rebecka Hjort, Iris H. Jonkers, Sebo Withoff, Kristian Hveem, Knut E. A. Lundin, Ludvig M. Sollid, Eivind Ness-Jensen · 2026
Read A model for predicting celiac disease among undiagnosed subjects established with data from the HUNT4 study by Mohammad Sayeef Alam, Rebecka Hjort, Iris H. Jonkers, Sebo Withoff, Kristian Hveem, Knut E. A. Lundin, Ludvig M. Sollid, Eivind Ness-Jensen (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13224532.txt.
Description
Mohammad Sayeef Alam and seven co-authors build a model to flag hidden celiac disease, in this 2026 paper. Celiac disease is an immune reaction to gluten that often goes undiagnosed in adults with vague symptoms. Testing everyone is costly, so the team sought a tool to pick who should be tested, using a huge Norwegian health study.
The model drew on data from 52,000 adults, among whom 465 new cases were found. It weighed genes, lifestyle, symptoms, other illnesses, and blood markers. A polygenic risk score, built from many small gene effects, proved the strongest single predictor, joined by diabetes history, kidney function, chronic discomfort, and self-rated health. The model sorted cases well and beat blanket screening, above all at low risk cutoffs. The authors ask for outside validation and cost studies before clinic use.
Catalog record
| CREATOR | Mohammad Sayeef Alam, Rebecka Hjort, Iris H. Jonkers, Sebo Withoff, Kristian Hveem, Knut E. A. Lundin, Ludvig M. Sollid, Eivind Ness-Jensen |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 37 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |