Predicting incident type 2 diabetes using wearable activity and polygenic risk: A survival-modeling study in All of Us
Step-count thresholds for reducing T2D risk varied across genetic risk groups, indicating that step counts do not confer uniform protection. Step counts and PRS provided independent, complementary predictive information, and their combination improved prediction of incident T2D.
Authors
- Mohammad Rifat Haider (ORCID: https://orcid.org/0000-0002-0690-8242)
- Shahrin Emdad Rayna (ORCID: https://orcid.org/0000-0003-4309-672X)
- Hasan Shahriar (ORCID: https://orcid.org/0000-0002-1625-0229)
- Saira Tasmin
- Ridwana Maher Manna (ORCID: https://orcid.org/0000-0002-3782-7859)
- Humayera Islam (ORCID: https://orcid.org/0000-0003-4915-4062)
- Hafizur Rahman (ORCID: https://orcid.org/0000-0002-2742-049X)
- Shazia Farzana (ORCID: https://orcid.org/0000-0002-7780-0183)
- Ash Arian
- Habibul Ahsan
- Muhammad Ashique Haider Chowdhury
- Sreenivas Konda
- Laura A. McGuinn
Institutions
- University of Georgia (US)
- Chicago Department of Public Health (US)
- International Centre for Diarrhoeal Disease Research (BD)
- University of Chicago (US)
Publication Details
- Journal
- The Journal of Clinical Endocrinology & Metabolism
- Published
- 2025-12-14
- DOI
- https://doi.org/10.1210/clinem/dgaf673
- Citations
- 1
- Primary Topic
- Genetic Associations and Epidemiology
- Type
- article
- Field-Weighted Citation Impact
- 1.82