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Differences between multimodal brain-age and chronological-age are linked to telomere shortening
- Source :
- Neurobiol Aging
- Publication Year :
- 2022
- Publisher :
- Elsevier BV, 2022.
-
Abstract
- Telomere shortening is theorized to accelerate biological aging, however, this has not been tested in the brain and cognitive contexts. We used machine learning age-prediction models to determine brain/cognitive age and quantified the degree of accelerated aging as the discrepancy between brain/cognitive and chronological ages (i.e. age gap). We hypothesized these age gaps are associated with telomere length (TL). Using healthy participants from the ADNI-3 cohort (N=196, Age(mean)=70.7), we trained age-prediction models using four modalities of brain features and cognitive scores, as well as a ‘stacked’ model combining all brain modalities. Then, these six age-prediction models were applied to an independent sample diagnosed with mild cognitive impairment (N=91, Age(mean)=71.3) to determine, for each subject, the model-specific predicted age and age gap. TL was most strongly associated with age gaps from the resting-state functional connectivity model after controlling for confounding variables. Overall, telomere shortening was significantly related to older brain but not cognitive age gaps. In particular, functional relative to structural brain-age gaps, were more strongly implicated in telomere shortening.
Details
- ISSN :
- 01974580
- Volume :
- 115
- Database :
- OpenAIRE
- Journal :
- Neurobiology of Aging
- Accession number :
- edsair.doi.dedup.....55c0145e1cd8daca698184f1d813b90e