Genomic and clinical correlates of 5 deep learning‐based neuroimaging signatures of neurodegeneration, evaluated in ADSP
We evaluated 5 recently established brain aging indices, which capture the heterogeneity of structural brain aging, in ADSP participants. R-indices replicated previously reported associations with AD groups (Yang et al., 2024), indicating the generalizability of the model. We identified different associations with genes that were previously linked to various traits. These findings provide new insights into the exploration of heterogeneity of neurodegeneration and related genetic risk factors.
Authors
- Timothy J. Hohman (ORCID: https://orcid.org/0000-0002-3377-7014)
- Christos A. Davatzikos (ORCID: https://orcid.org/0000-0002-1025-8561)
- Dhivya Srinivasan (ORCID: https://orcid.org/0000-0001-7886-9572)
- Zhijian Yang (ORCID: https://orcid.org/0000-0002-7863-827X)
- Andrew Joel Saykin
- Guray Erus
- Yuhan Cui
- Junhao Wen
- Li Shen
- Paul M. Thompson
Institutions
- University of Southern California (US)
- Center for Innovation (US)
- Artificial Intelligence in Medicine (Canada) (CA)
- Indiana University School of Medicine
- Indiana University – Purdue University Indianapolis (US)
- Columbia University (US)
- University of Pennsylvania (US)
- Vanderbilt University Medical Center (US)
Publication Details
- Journal
- Alzheimer s & Dementia
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1002/alz70855_101581
- Primary Topic
- Alzheimer's disease research and treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00