Sebastian MoguilnerSandra BaezHernan HernandezJoaquín MigeotAgustina LegazRaul Gonzalez-GomezFrancesca R. FarinaPavel PradoJhosmary CuadrosEnzo TagliazucchiFlorencia AltschulerMarcelo Adrián MaitoMaría E. GodoyJosephine CruzatPedro A. Valdes-SosaFrancisco LoperaJohn Fredy Ochoa-GómezAlfredis Gonzalez HernandezJasmin Bonilla-SantosRodrigo A. Gonzalez-MontealegreRenato AnghinahLuís E. d’Almeida ManfrinatiSol FittipaldiVicente MedelDaniela OlivaresGörsev G. YenerJavier EscuderoClaudio BabiloniRobert WhelanBahar GüntekinHarun YırıkoğullarıHernando Santamaria-GarciaAlberto Fernández LucasDavid HuepeGaetano Di CaterinaMarcio Soto-AñariAgustina BirbaAgustin Sainz-BallesterosCarlos Coronel-OliverosAmanuel YigezuEduar HerreraDaniel AbasoloKerry KilbornNicolás RubidoRuaridh A. ClarkRuben HerzogDeniz YerlikayaKun HuMario A. ParraPablo ReyesAdolfo M. GarcíaDiana L. MatallanaJosé Alberto Avila-FunesAndrea SlachevskyBEHRENS PELLEGRINO, MARIA ISABELMARIA ISABELBEHRENS PELLEGRINONilton CustodioJuan F. CardonaPablo BarttfeldIgnacio L. BruscoMartín A. BrunoAna L. Sosa OrtizStefanie D. Pina-EscuderoLeonel T. TakadaElisa ResendeKatherine L. PossinMaira Okada de OliveiraAlejandro Lopez-ValdesBrian LawlorIan H. RobertsonKenneth S. KosikClaudia Duran-AniotzVictor ValcourJennifer S. YokoyamaBruce MillerAgustin Ibanez2024-10-222024-10-222024Moguilner, S., Baez, S., Hernandez, H., Migeot, J., Legaz, A., Gonzalez-Gomez, R., Farina, F. R., Prado, P., Cuadros, J., Tagliazucchi, E., Altschuler, F., Maito, M. A., Godoy, M. E., Cruzat, J., Valdes-Sosa, P. A., Lopera, F., Ochoa-Gómez, J. F., Hernandez, A. G., Bonilla-Santos, J., … Ibanez, A. (2024). Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations. Nature Medicine. https://doi.org/10.1038/s41591-024-03209-xhttps://investigadores.udd.cl/handle/123456789/1029610.1038/s41591-024-03209-x2-s2.0-85202073322WOS:001298718200001<jats:title>Abstract</jats:title><jats:p>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 (<jats:italic>R</jats:italic>² = 0.37, <jats:italic>F</jats:italic>² = 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.</jats:p>Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populationsjournal-article