Associations of plasma proteomics and age-related outcomes with brain age in a diverse cohort.
Alzheimer’s disease
Brain age
Machine learning
Mortality
Proteomics
Journal
GeroScience
ISSN: 2509-2723
Titre abrégé: Geroscience
Pays: Switzerland
ID NLM: 101686284
Informations de publication
Date de publication:
04 Mar 2024
04 Mar 2024
Historique:
received:
07
12
2023
accepted:
26
02
2024
medline:
5
3
2024
pubmed:
5
3
2024
entrez:
4
3
2024
Statut:
aheadofprint
Résumé
Machine learning models are increasingly being used to estimate "brain age" from neuroimaging data. The gap between chronological age and the estimated brain age gap (BAG) is potentially a measure of accelerated and resilient brain aging. Brain age calculated in this fashion has been shown to be associated with mortality, measures of physical function, health, and disease. Here, we estimate the BAG using a voxel-based elastic net regression approach, and then, we investigate its associations with mortality, cognitive status, and measures of health and disease in participants from Atherosclerosis Risk in Communities (ARIC) study who had a brain MRI at visit 5 of the study. Finally, we used the SOMAscan assay containing 4877 proteins to examine the proteomic associations with the MRI-defined BAG. Among N = 1849 participants (age, 76.4 (SD 5.6)), we found that increased values of BAG were strongly associated with increased mortality and increased severity of the cognitive status. Strong associations with mortality persisted when the analyses were performed in cognitively normal participants. In addition, it was strongly associated with BMI, diabetes, measures of physical function, hypertension, prevalent heart disease, and stroke. Finally, we found 33 proteins associated with BAG after a correction for multiple comparisons. The top proteins with positive associations to brain age were growth/differentiation factor 15 (GDF-15), Sushi, von Willebrand factor type A, EGF, and pentraxin domain-containing protein 1 (SEVP 1), matrilysin (MMP7), ADAMTS-like protein 2 (ADAMTS), and heat shock 70 kDa protein 1B (HSPA1B) while EGF-receptor (EGFR), mast/stem-cell-growth-factor-receptor (KIT), coagulation-factor-VII, and cGMP-dependent-protein-kinase-1 (PRKG1) were negatively associated to brain age. Several of these proteins were previously associated with dementia in ARIC. These results suggest that circulating proteins implicated in biological aging, cellular senescence, angiogenesis, and coagulation are associated with a neuroimaging measure of brain aging.
Identifiants
pubmed: 38438772
doi: 10.1007/s11357-024-01112-4
pii: 10.1007/s11357-024-01112-4
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : NIH HHS
ID : U01HL096812
Pays : United States
Organisme : NIH HHS
ID : P30 AG021332
Pays : United States
Informations de copyright
© 2024. The Author(s).
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