Rate of brain aging associates with future executive function in Asian children and older adults
Brain age has emerged as a powerful tool to understand neuroanatomical aging and its link to health outcomes like cognition. However, there remains a lack of studies investigating the rate of brain aging and its relationship to cognition. Furthermore, most brain age models are trained and tested on cross-sectional data from primarily Caucasian, adult participants. It is thus unclear how well these models generalize to non-Caucasian participants, especially children. Here, we tested a previously published deep learning model on Singaporean elderly participants (55−88 years old) and children (4−11 years old). We found that the model directly generalized to the elderly participants, but model finetuning was necessary for children. After finetuning, we found that the rate of change in brain age gap was associated with future executive function performance in both elderly participants and children. We further found that lateral ventricles and frontal areas contributed to brain age prediction in elderly participants, while white matter and posterior brain regions were more important in predicting brain age of children. Taken together, our results suggest that there is potential for generalizing brain age models to diverse populations. Moreover, the longitudinal change in brain age gap reflects developing and aging processes in the brain, relating to future cognitive function.
Authors
- Ai Peng Tan (ORCID: https://orcid.org/0000-0001-7660-6322)
- Yap Seng Chong (ORCID: https://orcid.org/0000-0002-7232-8473)
- B.T. Thomas Yeo (ORCID: https://orcid.org/0000-0002-0119-3276)
- Wan Lin Yue (ORCID: https://orcid.org/0000-0003-3021-1418)
- Christopher Chen (ORCID: https://orcid.org/0000-0002-1047-9225)
- Kim‐Ngan Nguyen (ORCID: https://orcid.org/0009-0004-5968-6307)
- Ching‐Yu Cheng (ORCID: https://orcid.org/0000-0003-0655-885X)
- Juan Helen Zhou (ORCID: https://orcid.org/0000-0002-0180-8648)
- Susan F Cheng (ORCID: https://orcid.org/0000-0002-1201-2880)
- Michael J. Meaney (ORCID: https://orcid.org/0000-0002-8605-1997)
- Siwei Liu (ORCID: https://orcid.org/0000-0003-1277-484X)
- Ruth L F Leong (ORCID: https://orcid.org/0000-0001-5567-2152)
- Xing Qian (ORCID: https://orcid.org/0000-0002-6653-7121)
- Peter D. Gluckman (ORCID: https://orcid.org/0000-0002-5711-1655)
- Saima Hilal (ORCID: https://orcid.org/0000-0001-5434-5635)
- Kwun Kei Ng (ORCID: https://orcid.org/0000-0002-0584-7679)
- Evelyn Law (ORCID: https://orcid.org/0000-0003-4683-7220)
- Michael W.L. Chee (ORCID: https://orcid.org/0000-0002-6087-0548)
- Trevor WK Tan
Institutions
- Agency for Science, Technology and Research (SG)
- University of Auckland (NZ)
- National University of Singapore (SG)
- Singapore National Eye Center (SG)
- Douglas Mental Health University Institute (CA)
- University Health System (US)
- Singapore Institute for Clinical Sciences (SG)
- Singapore Eye Research Institute (SG)
- Duke-NUS Medical School (SG)
- National University Health System (SG)
- McGill University (CA)
Publication Details
- Journal
- eLife
- Published
- 2025-06-16
- DOI
- https://doi.org/10.7554/elife.97036.3
- Primary Topic
- Functional Brain Connectivity Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National University of Singapore
- Ministry of Education - Singapore
- National Medical Research Council