Produção Nacional
Revisado por pares
Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations
2024; Nature Portfolio; Volume: 30; Issue: 12 Linguagem: Inglês
10.1038/s41591-024-03209-x
ISSN1546-170X
AutoresSebastián Moguilner, Sandra Báez, Hernán Hernandez, Joaquín Migeot, Agustina Legaz, Raúl González-Gómez, Francesca R Farina, Pável Prado, Jhosmary Cuadros, Enzo Tagliazucchi, Florencia Altschuler, Marcelo Maito, Maria Eugenia Godoy, Josephine Cruzat, Pedro A. Valdés‐Sosa, Francisco Lopera, John Fredy Ochoa-Gómez, Alfredis González‐Hernández, Jasmin Bonilla‐Santos, Rodrigo A. Gonzalez‐Montealegre, Renato Anghinah, Luís E. d’Almeida Manfrinati, Sol Fittipaldi, Vicente Medel, Daniela Olivares, Görsev Yener, Javier Escudero, Claudio Babiloni, Robert Whelan, Bahar Güntekin, Harun Yırıkoğulları, Hernando Santamaría‐García, Alberto Fernández, David Huepe, Gaetano Di Caterina, Marcio Soto‐Añari, Agustina Birba, Agustín Sainz‐Ballesteros, Carlos Coronel‐Oliveros, Amanuel Yigezu, Eduar Herrera, Daniel Abásolo, Kerry Kilborn, Nicolás Rubido, Ruaridh Clark, Rubén Herzog, Deniz Yerlikaya, Kun Hu, Mario A. Parra, Pablo Reyes, Adolfo M. García, Diana Matallana, José Alberto Ávila‐Funes, Andrea Slachevsky, María Isabel Behrens, Nilton Custodio, Juan F. Cardona, Pablo Barttfeld, Ignacio L. Brusco, Martín A. Bruno, Ana L. Sosa Ortiz, Stefanie Danielle Piña‐Escudero, Leonel Tadao Takada, Elisa de Paula França Resende, Katherine L. Possin, Maira Okada de Oliveira, Alejandro López Valdés, Brian Lawlor, Ian H. Robertson, Kenneth S. Kosik, Claudia Duran‐Aniotz, Victor Valcour, Jennifer S. Yokoyama, Bruce Miller, Agustín Ibáñez,
Tópico(s)Health, Environment, Cognitive Aging
ResumoAbstract 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 ( R ² = 0.37, F 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.
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