Browsing by Author "Hernandez, Hernan"
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Publication Author Correction: Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations(2024) Moguilner, Sebastian; Baez, Sandra; Hernandez, Hernan; Migeot, Joaquín; Legaz, Agustina; Gonzalez, Raul; Farina, Francesca; Prado, Pavel; Cuadros, Jhosmary; Tagliazucchi, Enzo; Altschuler, Florencia; Maito, Marcelo; Godoy, María; Cruzat, Josefina; Valdes, Pedro; Lopera, Francisco; Ochoa, John; Gonzalez, Alfredis; Bonilla, Jasmin; Gonzalez, Rodrigo; Anghinah, Renato; d'Almeida, Luís; Fittipaldi, Sol; Medel, Vicente; Olivares, Daniela; Yener, Görsev; Escudero, Javier; Babiloni, Claudio; Whelan, Robert; Güntekin, Bahar; Yırıkoğulları, Harun; Santamaria, Hernando; Fernández, Alberto; Huepe, David; Di Caterina, Gaetano; Soto, Marcio; Birba, Agustina; Sainz, Agustin; Coronel, Carlos; Yigezu, Amanuel; Behrens, Maria IsabelLos relojes cerebrales capturan la diversidad y las disparidades en el envejecimiento y la demencia en poblaciones geográficamente diversas. 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.Publication Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations(2024) Moguilner, Sebastian; Baez, Sandra; Hernandez, Hernan; Migeot, Joaquín; Legaz, Agustina; Gonzalez, Raul; Farina, Francesca; Prado, Pavel; Cuadros, Jhosmary; Tagliazucchi, Enzo; Altschuler, Florencia; Maito, Marcelo; Godoy, María; Cruzat, Josefina; Valdes, Pedro; Lopera, Francisco; Ochoa, John; González, Alfredis; Bonilla, Jazmín; Gonzalez, Rodrigo; Anghinah, Renato; d'Almeida, Luis; Fittipaldi, Sol; Medel, Vicente; Olivares, Daniela; Yener, Görsev; Escudero, Javier; Babiloni, Claudio; Whelan, Robert; Guntekin, Bahar; Yırıkoğulları, Harun; Santamaria, Hernando; Fernández, Alberto; Huepe, David; Di Caterina, Gaetano; Soto, Marcio; Birba, Agustina; Sainz, Agustin; Coronel, Carlos; Yigezu, Amanuel; Behrens, Maria IsabelBrain 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. Los relojes cerebrales, que cuantifican las discrepancias entre la edad cerebral y la edad cronológica, son prometedores para comprender la salud y la enfermedad cerebral. Sin embargo, se desconoce el impacto de la diversidad (incluida la geográfica, socioeconómica, sociodemográfica, sexual y neurodegenerativa) en la brecha de edad cerebral. Analizamos conjuntos de datos de 5306 participantes en 15 países (7 países de América Latina y el Caribe (ALC) y 8 países no pertenecientes a ALC). Con base en interacciones de orden superior, desarrollamos una arquitectura de aprendizaje profundo de brecha de edad cerebral para imágenes de resonancia magnética funcional (2953) y electroencefalografía (2353). Los conjuntos de datos comprendían controles sanos e individuos con deterioro cognitivo leve, enfermedad de Alzheimer y demencia frontotemporal variante conductual. Los modelos LAC evidenciaron edades cerebrales más avanzadas (imágenes por resonancia magnética funcional: error direccional medio = 5,60, error cuadrático medio (rmse) = 11,91; electroencefalografía: error direccional medio = 5,34, rmse = 9,82) asociadas con redes frontoposteriores en comparación con los modelos no LAC. La desigualdad socioeconómica estructural, la contaminación y las disparidades en la salud fueron predictores influyentes de mayores brechas de edad cerebral, especialmente en LAC (R² = 0,37, F² = 0,59, rmse = 6,9). Se encontró una brecha ascendente de edad cerebral desde controles sanos hasta deterioro cognitivo leve y enfermedad de Alzheimer. En LAC, observamos brechas de edad cerebral más grandes en mujeres en los grupos de control y enfermedad de Alzheimer en comparación con los respectivos hombres. Los resultados no se explicaron por variaciones en la calidad de la señal, la demografía o los métodos de adquisición. Estos hallazgos proporcionan un marco cuantitativo que captura la diversidad del envejecimiento cerebral acelerado.Publication Dementia prevention requires moving beyond individual choice: the costs of effort and time intersect with social determinants of health(2025) Migeot, Joaquín; Araya, Daniel; Montecinos, Matias; Baez, Sandra; Behrens, Maria Isabel; Castaner, Olga; Cruzat, Josephine; Delgado, Carolina; De Jong- Bambagioni, David; Duran, Claudia; Durón, Dafne; Evans, Tavia; Gonzalez, Raul; Gutiérrez, Myriam; Hayden, Katheen; Hernandez, Hernan; Ibañez, Agustin; Legaz, Agustina; Miller, Johnny; Ma iulskyt, Sonata; Putthinun, Pongpat; Santamaría, Hernando; Slachevsky Chonchol, Andrea; Trépel, DominicSocial determinants of health strongly influence modifiable risk factors for dementia, yet prevention frameworks list only individual-level behaviours and conditions, overlooking the impact of social and environmental factors on the risk of dementia. In this perspective, we introduce the concept of non-monetary costs as a central mechanism through which social determinants shape modifiable risk factors by influencing individuals' ability to adopt healthy behaviours. Drawing from economic theory, we define non-monetary costs as the time and metabolic cost, perceived by individuals as physical and cognitive effort, required to engage in healthy behaviours. Under adverse social determinants of health, individuals effectively lack choice, as the non-monetary costs required to engage in healthy behaviours become prohibitively high. We propose a framework that links social determinants of health adversity to increased dementia risk through non-monetary costs. We apply this framework to each of the fourteen modifiable risk factors for dementia identified by the Lancet Commission, demonstrating how these costs systematically elevate risk in populations facing social adversity. Finally, we explore the implications of incorporating non-monetary cost assessments across research, interventions, clinical care, and public policy. We propose that quantifying and addressing these costs is essential for designing equitable, scalable, and contextually grounded strategies for dementia prevention across socially diverse populations.Publication Social exposome and brain health outcomes of dementia across Latin America(2025) Migeot, Joaquin; Pina, Stefanie; Hernandez, Hernan; Gonzalez, Raul; Legaz, Agustina; Fittipaldi, Sol; Resende, Elisa de Paula França; Duran, Claudia; Avila, Jose; Behrens, Maria Isabel; Bruno, Martin; Cardona, Juan; Custodio, Nilton; García, Adolfo; Godoy, Maria; Hu, Kun; Lanata, Serggio; Lawlor, Brian; Lopera, Francisco; Maito, Marcelo; Matallana, Diana; Miller, Bruce; Miranda, J Jaime; Okada, Maira; Reyes, Pablo; Santamaria, Hernando; Slachevsky Chonchol, Andrea; Sosa, Ana; Takada, Leonel; Torres, Jacqueline; Vanneste, Sven; Valcour, Victor; Wen, Olivia; Yokoyama, Jennifer; Possin, Katherine; Ibañez, AgustinA multidimensional social exposome (MSE)-the combined lifespan measures of education, food insecurity, financial status, access to healthcare, childhood experiences, and more-may shape dementia risk and brain health over the lifespan, particularly in underserved regions like Latin America. However, the MSE effects on brain health and dementia are unknown. We evaluated 2211 individuals (controls, Alzheimer's disease, and frontotemporal lobar degeneration) from a non-representative sample across six Latin American countries. Adverse exposomes associate with poorer cognition in healthy aging. In dementia, more complex exposomes correlate with lower cognitive and functional performance, higher neuropsychiatric symptoms, and brain structural and connectivity alterations in frontal-temporal-limbic and cerebellar regions. Food insecurity, financial resources, subjective socioeconomic status, and access to healthcare emerge as critical predictors. Cumulative exposome measures surpass isolated factors in predicting clinical-cognitive profiles. Multiple sensitivity analyses confirm our results. Findings highlight the need for personalized approaches integrating MSE across the lifespan, emphasizing prevention and interventions targeting social disparities.