» Articles » PMID: 38354871

BrainAGE, Brain Health, and Mental Disorders: A Systematic Review

Overview
Date 2024 Feb 14
PMID 38354871
Authors
Affiliations
Soon will be listed here.
Abstract

The imaging-based method of brainAGE aims to characterize an individual's vulnerability to age-related brain changes. The present study systematically reviewed brainAGE findings in neuropsychiatric conditions and discussed the potential of brainAGE as a marker for biological age. A systematic PubMed search (from inception to March 6th, 2023) identified 273 articles. The 30 included studies compared brainAGE between neuropsychiatric and healthy groups (n≥50). We presented results qualitatively and adapted a bias risk assessment questionnaire. The imaging modalities, design, and input features varied considerably between studies. While the studies found higher brainAGE in neuropsychiatric conditions (11 mild cognitive impairment/ dementia, 11 schizophrenia spectrum/ other psychotic and bipolar disorder, six depression/ anxiety, two multiple groups), the associations with clinical characteristics were mixed. While brainAGE is sensitive to group differences, limitations include the lack of diverse training samples, multi-modal studies, and external validation. Only a few studies obtained longitudinal data, and all have used algorithms built solely to predict chronological age. These limitations impede the validity of brainAGE as a biological age marker.

Citing Articles

Investigating dynamic brain functional redundancy as a mechanism of cognitive reserve.

Schwarz J, Zistler F, Usheva A, Fix A, Zinn S, Zimmermann J Front Aging Neurosci. 2025; 17:1535657.

PMID: 39968125 PMC: 11832541. DOI: 10.3389/fnagi.2025.1535657.


Machine Learning and Deep Learning Approaches in Lifespan Brain Age Prediction: A Comprehensive Review.

Wu Y, Gao H, Zhang C, Ma X, Zhu X, Wu S Tomography. 2024; 10(8):1238-1262.

PMID: 39195728 PMC: 11359833. DOI: 10.3390/tomography10080093.

References
1.
Lim A, Barnes L, Weissberger G, Lamar M, Nguyen A, Fenton L . Quantification of race/ethnicity representation in Alzheimer's disease neuroimaging research in the USA: a systematic review. Commun Med (Lond). 2023; 3(1):101. PMC: 10368705. DOI: 10.1038/s43856-023-00333-6. View

2.
Franke K, Gaser C . Ten Years of as a Neuroimaging Biomarker of Brain Aging: What Insights Have We Gained?. Front Neurol. 2019; 10:789. PMC: 6702897. DOI: 10.3389/fneur.2019.00789. View

3.
Vidal-Pineiro D, Wang Y, Krogsrud S, Amlien I, Baare W, Bartres-Faz D . Individual variations in 'brain age' relate to early-life factors more than to longitudinal brain change. Elife. 2021; 10. PMC: 8580481. DOI: 10.7554/eLife.69995. View

4.
Ballester P, Suh J, Nogovitsyn N, Hassel S, Strother S, Arnott S . Accelerated brain aging in major depressive disorder and antidepressant treatment response: A CAN-BIND report. Neuroimage Clin. 2021; 32:102864. PMC: 8556529. DOI: 10.1016/j.nicl.2021.102864. View

5.
Cole J, Ritchie S, Bastin M, Valdes Hernandez M, Munoz Maniega S, Royle N . Brain age predicts mortality. Mol Psychiatry. 2017; 23(5):1385-1392. PMC: 5984097. DOI: 10.1038/mp.2017.62. View