ArticleNature medicine2024
Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations.
Article in Nature medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 102 papers, 1 of them a synthesis that pooled it.
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Who cites it
102 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Sex differences in Alzheimer's disease: a systematic review of two decades of neuroimaging research.The British journal of radiology · 2026Pooled it
- Trial
- Speech clocks decode dementia phenotypes, social exposome, and biological aging.Science advances · 2026Article
- Integration of functional magnetic resonance imaging and artificial intelligence in Alzheimer's disease.Neural regeneration research · 2026Article
- Sex-specific aging clocks from a large-scale human phenome reveal distinct aging transitions and circulating signatures.Nature aging · 2026Article
- Genetic-exposome interactions and aging clocks in dementia: the ReDLat2 initiative.Nature medicine · 2026Article
- Generalizability of EEG-Based DEMENTIA Classifiers: A Multicenter study of Alzheimer's, MCI, and FTD.medRxiv : the preprint server for health sciences · 2026Article
- Article
- Biological aging clocks in health and disease.Nature medicine · 2026Review
- Reply to "Shifting the emphasis of brain health literacy from individuals to systems to reduce inequalities".Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Artificial Intelligence That Changes Clinical Neurology Practice: Translating Algorithms Into Actionable Care.Journal of clinical neurology (Seoul, Korea) · 2026Review
- Linking the exposome to the brain-behaviour phenotype.Nature reviews. Neuroscience · 2026Review
- Metabolomic signatures of brain aging: A multimodal and genetic study.Molecular psychiatry · 2026Article
- A multi-modal foundation model for brain disease diagnosis and medical imaging.Patterns (New York, N.Y.) · 2026Article
- Social vulnerability shapes deep clinical phenotypes and brain health in aging and dementia across Latin America.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Source-space EEG alpha activity reveals brain age gaps due to neurodegeneration and disparity.Communications biology · 2026Article
- Aging beyond diagnosis: the MRI brain age gap across disorders.GeroScience · 2026Review
- Exposure to negative physical and social factors accelerates brain aging.Nature medicine · 2026Article
- Global Socioeconomic Context and Brain Ageing in Epilepsy: an ENIGMA-Epilepsy study.medRxiv : the preprint server for health sciences · 2026Article
- The exposome of brain aging across 34 countries.Nature medicine · 2026Article
42 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
- Update of
Authors and funding
75 authors.
Funding
Abstract
Brain clocks, which quantify discrepancies between brain age and chronological age, hold promise for understanding brain health and disease. However, the impact of diversity (including geographical, socioeconomic, sociodemographic, sex and neurodegeneration) on the brain-age gap is unknown. We analyzed datasets from 5,306 participants across 15 countries (7 Latin American and Caribbean countries (LAC) and 8 non-LAC countries). Based on higher-order interactions, we developed a brain-age gap deep learning architecture for functional magnetic resonance imaging (2,953) and electroencephalography (2,353). The datasets comprised healthy controls and individuals with mild cognitive impairment, Alzheimer disease and behavioral variant frontotemporal dementia. LAC models evidenced older brain ages (functional magnetic resonance imaging: mean directional error = 5.60, root mean square error (r.m.s.e.) = 11.91; electroencephalography: mean directional error = 5.34, r.m.s.e. = 9.82) associated with frontoposterior networks compared with non-LAC models. Structural socioeconomic inequality, pollution and health disparities were influential predictors of increased brain-age gaps, especially in LAC (R² = 0.37, F² = 0.59, r.m.s.e. = 6.9). An ascending brain-age gap from healthy controls to mild cognitive impairment to Alzheimer disease was found. In LAC, we observed larger brain-age gaps in females in control and Alzheimer disease groups compared with the respective males. The results were not explained by variations in signal quality, demographics or acquisition methods. These findings provide a quantitative framework capturing the diversity of accelerated brain aging.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.