Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations

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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Publication Details

Journal
Nature Medicine
Published
2024-08-26
DOI
https://doi.org/10.1038/s41591-024-03209-x
Citations
97
Primary Topic
Functional Brain Connectivity Studies
Type
article
Field-Weighted Citation Impact
33.24

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article

Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations

Agustina Birba, David Huepe, Nilton Custodio, Carlos Coronel‐Oliveros et al.
97 citations
Nature Medicine
Functional Brain Connectivity Studies
33.24
article

Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations

Agustina Birba, David Huepe, Nilton Custodio, Carlos Coronel‐Oliveros, Pedro A. Valdés‐Sosa, Stefanie Danielle Piña‐Escudero, Leonel Tadao Takada, Ruben A Herzog, Gaetano Di Caterina, Harun Yırıkoğulları, Pablo Reyes, Agustín M. Ibáñez, Maria Eugenia Godoy, Kenneth S. Kosik, Sandra Báez, Nicolás Rubido, Renato Anghinah, Deniz Yerlikaya, Amanuel Yigezu, Vicente Medel, John Fredy Ochoa-Gómez, Pablo Barttfeld, Claudio Babiloni, Francisco Lopera, Sebastián Moguilner, Juan F. Cardona, Kun Hu, Jasmin Bonilla‐Santos, María Isabel Behrens, Hernando A Santamaría‐García, Joaquín Migeot, Sol Fittipaldi, Kerry Kilborn, Ana L. Sosa Ortiz, Claudia A. Duran-Aniotz, Ignacio L. Brusco, Rodrigo A. Gonzalez‐Montealegre, Maira Okada de Oliveira, Pavel Prado, Agustina Legaz, Marcelo Adrián Maito, Robert Whelan, Raúl González-Gómez, Victor Valcour, Florencia Altschuler, Enzo Tagliazucchi, Javier Escudero, Jennifer S. Yokoyama, Martín A. Bruno, Daniela Olivares, Marcio Soto‐Añari, Andrea Slachevsky, Hernán Hernandez, Bahar Güntekin, Eduar Herrera, Ruaridh Clark, Francesca R Farina, Daniel Abásolo, Josephine Cruzat, Jhosmary Cuadros, Agustín Sainz‐Ballesteros, Görsev Yener, Bruce Miller, Elisa de Paula França Resende, Katherine L. Possin, Ian H. Robertson, Alfredis González‐Hernández, Adolfo M. García, Diana Matallana, José Alberto Ávila‐Funes, Mario A. Parra, Alejandro López Valdés, Alberto Fernández, Luís E. d’Almeida Manfrinati, Brian Lawlor
article en
97 citations

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.

Nature MedicineVol. 30(12)
Universidad de Santiago de Chile (CL), Universidade Federal de Minas Gerais (BR), Universidad Complutense de Madrid (ES), Universidad Nacional Experimental del Táchira (VE), Centre National de la Recherche Scientifique (FR), Izmir University (TR), Universidad del Desarrollo (CL), Harvard University (US), University of Electronic Science and Technology of China (CN), İzmir University of Economics (TR), Consejo Nacional de Investigaciones Científicas y Técnicas (AR), Inserm (FR), University of California, Santa Barbara (US), Universidad de Los Andes (CO), Universidad Nacional de Córdoba (AR), Universidade de São Paulo (BR), University of California, San Francisco (US), University of Strathclyde (GB), Università degli studi di Cassino e del Lazio Meridionale (IT), Dokuz Eylül University (TR), University of Aberdeen (GB), Trinity College Dublin (IE), Adolfo Ibáñez University (CL), Pontificia Universidad Javeriana (CO), Universidad de Buenos Aires (AR), Clínica Alemana (CL), Cuban Neuroscience Center (CU), University of Surrey (GB), San Sebastián University (CL), Istanbul Medipol University (TR), Universidad de Antioquia (CO), Sorbonne Université (FR), University of Chicago (US), University of San Andrés (AR), Massachusetts General Hospital (US), Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán (MX), Hospital del Salvador (CL), Centro de Recursos Educativos Avanzados (CL), Instituto de Neurología Cognitiva (AR), Hospital Clínico de la Universidad de Chile (CL), Clínica MEDS (Chile) (CL), Fundación Santa Fe de Bogotá (CO), Institute of Peruvian Studies (PE), Universidad Católica San Pablo (PE), Instituto de Neurociencia Biomédica (CL), Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo (BR), Instituto Nacional de Neurología y Neurocirugía (MX), Center for Climate and Resilience Research (CL), Universidad Cooperativa de Colombia (CO), Institut du Cerveau (FR), Hospital Universitario San Ignacio (CO), Global Brain Health Institute (US), University of Chile (CL), Federico Santa María Technical University (CL), Universidad Surcolombiana (CO), Icesi University (CO), University of Glasgow (GB), University of Valparaíso (CL), Sapienza University of Rome (IT), Universidad Nacional Autónoma de México (MX), Universidad del Valle (CO), University of Edinburgh (GB)
Alzheimer's Association, Universidad de Santiago de Chile, Agencia Nacional de Investigación y Desarrollo, National Institutes of Health, Departamento de Investigaciones Científicas y Tecnológicas, Universidad de Santiago de Chile, Fogarty International Center, Fondo de Financiamiento de Centros de Investigación en Áreas Prioritarias
Openalex Percentile: Top 0%
Functional Brain Connectivity Studies
33.24
DOIOpen Access PDFOpenAlex
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