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 91 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
91 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
- Genetic-exposome interactions and aging clocks in dementia: the ReDLat2 initiative.Nature medicine · 2026Article
- Article
- Linking the exposome to the brain-behaviour phenotype.Nature reviews. Neuroscience · 2026Review
- 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
- 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
- Aging beyond diagnosis: the MRI brain age gap across disorders.GeroScience · 2026Review
- The exposome of brain aging across 34 countries.Nature medicine · 2026Article
- 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 Perioperative Neurocognitive Disorder Prediction Based on AI-Assisted EEG Dynamic Features in Anesthetized Mice.Diagnostics (Basel, Switzerland) · 2026Article
- Exposome-wide patterns predict brain health in aging.Nature communications · 2026Article
- Neural embedding of frailty in cognitively unimpaired aging and dementia across Latin America.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Derivation of machine learning brain aging biomarkers for a set of forty thousand functional connectomes.Brain research bulletin · 2026Article
- Metabolomic signatures reveal an association between healthy dietary patterns and brain aging.The journal of nutrition, health & aging · 2026Article
31 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.
Indexed as
Identifiers
What Socratic holds
Registered trials
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 Socratic graph.