Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations
- Autores
- Moguilner, Sebastian; Baez, Sandra; Hernandez, Hernan; Migeot, Joaquín; Legaz, Agustina; Gonzalez Gomez, Raul; Farina, Francesca R.; Prado, Pavel; Cuadros, Jhosmary; Tagliazucchi, Enzo Rodolfo; Altschuler, Florencia; Maito, Marcelo Adrián; Godoy, María E.; Cruzat, Josephine; Valdes Sosa, Pedro A.; Lopera, Francisco; Ochoa Gómez, John Fredy; Gonzalez Hernandez, Alfredis; Bonilla Santos, Jasmin; Gonzalez Montealegre, Rodrigo A.; Anghinah, Renato; d’Almeida Manfrinati, Luís E.; Fittipaldi, Sol; Medel, Vicente; Olivares, Daniela; Yener, Görsev G.; Escudero, Javier; Babiloni, Claudio; Whelan, Robert; Güntekin, Bahar; Barttfeld, Pablo
- Año de publicación
- 2024
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- 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.
Fil: Moguilner, Sebastian. Universidad Adolfo Ibañez; Chile. Universidad de San Andrés; Argentina. Harvard Medical School; Estados Unidos
Fil: Baez, Sandra. University of California; Estados Unidos. Trinity College Dublin; Irlanda. Universidad de los Andes; Colombia
Fil: Hernandez, Hernan. Universidad Adolfo Ibañez; Chile
Fil: Migeot, Joaquín. Universidad Adolfo Ibañez; Chile
Fil: Legaz, Agustina. Universidad Adolfo Ibañez; Chile. Universidad de San Andrés; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Gonzalez Gomez, Raul. Universidad Adolfo Ibañez; Chile
Fil: Farina, Francesca R.. University of California; Estados Unidos. Trinity College Dublin; Irlanda
Fil: Prado, Pavel. Universidad San Sebastián; Chile
Fil: Cuadros, Jhosmary. Universidad Adolfo Ibañez; Chile. Universidad Nacional Experimental del Táchira; Venezuela. Universidad Técnica Federico Santa María; Chile
Fil: Tagliazucchi, Enzo Rodolfo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Adolfo Ibañez; Chile. Universidad de Buenos Aires; Argentina
Fil: Altschuler, Florencia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de San Andrés; Argentina
Fil: Maito, Marcelo Adrián. Universidad de San Andrés; Argentina. Universidad Adolfo Ibañez; Chile
Fil: Godoy, María E.. Universidad de San Andrés; Argentina. Universidad Adolfo Ibañez; Chile
Fil: Cruzat, Josephine. Universidad Adolfo Ibañez; Chile
Fil: Valdes Sosa, Pedro A.. University of Electronic Sciences and Technology of China; China. Technology of China; China. Cuban Neuroscience Center; Cuba
Fil: Lopera, Francisco. Universidad de Antioquia; Colombia
Fil: Ochoa Gómez, John Fredy. Universidad de Antioquia; Colombia
Fil: Gonzalez Hernandez, Alfredis. Universidad Surcolombiana Neiva; Colombia
Fil: Bonilla Santos, Jasmin. Universidad Cooperativa de Colombia; Colombia
Fil: Gonzalez Montealegre, Rodrigo A.. Universidad Surcolombiana Neiva; Colombia
Fil: Anghinah, Renato. Universidade de Sao Paulo; Brasil
Fil: d’Almeida Manfrinati, Luís E.. Universidade de Sao Paulo; Brasil
Fil: Fittipaldi, Sol. University of California; Estados Unidos. Trinity College Dublin; Irlanda. Universidad Adolfo Ibañez; Chile
Fil: Medel, Vicente. Universidad Adolfo Ibañez; Chile
Fil: Olivares, Daniela. Universidad Adolfo Ibañez; Chile. Universidad de Chile; Chile. Centro de Neuropsicología Clínica; Chile
Fil: Yener, Görsev G.. Izmir University of Economics; Turquía. Dokuz Eylul University; Turquía. Izmir Biomedicine and Genome Center; Turquía
Fil: Escudero, Javier. University of Edinburgh; Reino Unido
Fil: Babiloni, Claudio. Università degli Studi di Roma "La Sapienza"; Italia. Hospital San Raffaele Cassino; Italia
Fil: Whelan, Robert. University of California; Estados Unidos. Trinity College Dublin; Irlanda
Fil: Güntekin, Bahar. Istanbul Medipol University; Turquía
Fil: Barttfeld, Pablo. Universidad Nacional de Córdoba. Instituto de Investigaciones Psicológicas. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones Psicológicas; Argentina - Materia
- Brain clocks
- Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by/2.5/ar/
- Repositorio
.jpg)
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/244705
Ver los metadatos del registro completo
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Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populationsMoguilner, SebastianBaez, SandraHernandez, HernanMigeot, JoaquínLegaz, AgustinaGonzalez Gomez, RaulFarina, Francesca R.Prado, PavelCuadros, JhosmaryTagliazucchi, Enzo RodolfoAltschuler, FlorenciaMaito, Marcelo AdriánGodoy, María E.Cruzat, JosephineValdes Sosa, Pedro A.Lopera, FranciscoOchoa Gómez, John FredyGonzalez Hernandez, AlfredisBonilla Santos, JasminGonzalez Montealegre, Rodrigo A.Anghinah, Renatod’Almeida Manfrinati, Luís E.Fittipaldi, SolMedel, VicenteOlivares, DanielaYener, Görsev G.Escudero, JavierBabiloni, ClaudioWhelan, RobertGüntekin, BaharBarttfeld, PabloBrain clockshttps://purl.org/becyt/ford/3.1https://purl.org/becyt/ford/3Brain 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.Fil: Moguilner, Sebastian. Universidad Adolfo Ibañez; Chile. Universidad de San Andrés; Argentina. Harvard Medical School; Estados UnidosFil: Baez, Sandra. University of California; Estados Unidos. Trinity College Dublin; Irlanda. Universidad de los Andes; ColombiaFil: Hernandez, Hernan. Universidad Adolfo Ibañez; ChileFil: Migeot, Joaquín. Universidad Adolfo Ibañez; ChileFil: Legaz, Agustina. Universidad Adolfo Ibañez; Chile. Universidad de San Andrés; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Gonzalez Gomez, Raul. Universidad Adolfo Ibañez; ChileFil: Farina, Francesca R.. University of California; Estados Unidos. Trinity College Dublin; IrlandaFil: Prado, Pavel. Universidad San Sebastián; ChileFil: Cuadros, Jhosmary. Universidad Adolfo Ibañez; Chile. Universidad Nacional Experimental del Táchira; Venezuela. Universidad Técnica Federico Santa María; ChileFil: Tagliazucchi, Enzo Rodolfo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Adolfo Ibañez; Chile. Universidad de Buenos Aires; ArgentinaFil: Altschuler, Florencia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de San Andrés; ArgentinaFil: Maito, Marcelo Adrián. Universidad de San Andrés; Argentina. Universidad Adolfo Ibañez; ChileFil: Godoy, María E.. Universidad de San Andrés; Argentina. Universidad Adolfo Ibañez; ChileFil: Cruzat, Josephine. Universidad Adolfo Ibañez; ChileFil: Valdes Sosa, Pedro A.. University of Electronic Sciences and Technology of China; China. Technology of China; China. Cuban Neuroscience Center; CubaFil: Lopera, Francisco. Universidad de Antioquia; ColombiaFil: Ochoa Gómez, John Fredy. Universidad de Antioquia; ColombiaFil: Gonzalez Hernandez, Alfredis. Universidad Surcolombiana Neiva; ColombiaFil: Bonilla Santos, Jasmin. Universidad Cooperativa de Colombia; ColombiaFil: Gonzalez Montealegre, Rodrigo A.. Universidad Surcolombiana Neiva; ColombiaFil: Anghinah, Renato. Universidade de Sao Paulo; BrasilFil: d’Almeida Manfrinati, Luís E.. Universidade de Sao Paulo; BrasilFil: Fittipaldi, Sol. University of California; Estados Unidos. Trinity College Dublin; Irlanda. Universidad Adolfo Ibañez; ChileFil: Medel, Vicente. Universidad Adolfo Ibañez; ChileFil: Olivares, Daniela. Universidad Adolfo Ibañez; Chile. Universidad de Chile; Chile. Centro de Neuropsicología Clínica; ChileFil: Yener, Görsev G.. Izmir University of Economics; Turquía. Dokuz Eylul University; Turquía. Izmir Biomedicine and Genome Center; TurquíaFil: Escudero, Javier. University of Edinburgh; Reino UnidoFil: Babiloni, Claudio. Università degli Studi di Roma "La Sapienza"; Italia. Hospital San Raffaele Cassino; ItaliaFil: Whelan, Robert. University of California; Estados Unidos. Trinity College Dublin; IrlandaFil: Güntekin, Bahar. Istanbul Medipol University; TurquíaFil: Barttfeld, Pablo. Universidad Nacional de Córdoba. Instituto de Investigaciones Psicológicas. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones Psicológicas; ArgentinaNature Publishing Group2024-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/244705Moguilner, Sebastian; Baez, Sandra; Hernandez, Hernan; Migeot, Joaquín; Legaz, Agustina; et al.; Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations; Nature Publishing Group; Nature Medicine; 8-2024; 1-271078-8956CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1038/s41591-024-03209-xinfo:eu-repo/semantics/altIdentifier/url/https://www.nature.com/articles/s41591-024-03209-xinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T10:07:56Zoai:ri.conicet.gov.ar:11336/244705instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 10:07:56.583CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
| dc.title.none.fl_str_mv |
Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations |
| title |
Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations |
| spellingShingle |
Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations Moguilner, Sebastian Brain clocks |
| title_short |
Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations |
| title_full |
Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations |
| title_fullStr |
Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations |
| title_full_unstemmed |
Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations |
| title_sort |
Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations |
| dc.creator.none.fl_str_mv |
Moguilner, Sebastian Baez, Sandra Hernandez, Hernan Migeot, Joaquín Legaz, Agustina Gonzalez Gomez, Raul Farina, Francesca R. Prado, Pavel Cuadros, Jhosmary Tagliazucchi, Enzo Rodolfo Altschuler, Florencia Maito, Marcelo Adrián Godoy, María E. Cruzat, Josephine Valdes Sosa, Pedro A. Lopera, Francisco Ochoa Gómez, John Fredy Gonzalez Hernandez, Alfredis Bonilla Santos, Jasmin Gonzalez Montealegre, Rodrigo A. Anghinah, Renato d’Almeida Manfrinati, Luís E. Fittipaldi, Sol Medel, Vicente Olivares, Daniela Yener, Görsev G. Escudero, Javier Babiloni, Claudio Whelan, Robert Güntekin, Bahar Barttfeld, Pablo |
| author |
Moguilner, Sebastian |
| author_facet |
Moguilner, Sebastian Baez, Sandra Hernandez, Hernan Migeot, Joaquín Legaz, Agustina Gonzalez Gomez, Raul Farina, Francesca R. Prado, Pavel Cuadros, Jhosmary Tagliazucchi, Enzo Rodolfo Altschuler, Florencia Maito, Marcelo Adrián Godoy, María E. Cruzat, Josephine Valdes Sosa, Pedro A. Lopera, Francisco Ochoa Gómez, John Fredy Gonzalez Hernandez, Alfredis Bonilla Santos, Jasmin Gonzalez Montealegre, Rodrigo A. Anghinah, Renato d’Almeida Manfrinati, Luís E. Fittipaldi, Sol Medel, Vicente Olivares, Daniela Yener, Görsev G. Escudero, Javier Babiloni, Claudio Whelan, Robert Güntekin, Bahar Barttfeld, Pablo |
| author_role |
author |
| author2 |
Baez, Sandra Hernandez, Hernan Migeot, Joaquín Legaz, Agustina Gonzalez Gomez, Raul Farina, Francesca R. Prado, Pavel Cuadros, Jhosmary Tagliazucchi, Enzo Rodolfo Altschuler, Florencia Maito, Marcelo Adrián Godoy, María E. Cruzat, Josephine Valdes Sosa, Pedro A. Lopera, Francisco Ochoa Gómez, John Fredy Gonzalez Hernandez, Alfredis Bonilla Santos, Jasmin Gonzalez Montealegre, Rodrigo A. Anghinah, Renato d’Almeida Manfrinati, Luís E. Fittipaldi, Sol Medel, Vicente Olivares, Daniela Yener, Görsev G. Escudero, Javier Babiloni, Claudio Whelan, Robert Güntekin, Bahar Barttfeld, Pablo |
| author2_role |
author author author author author author author author author author author author author author author author author author author author author author author author author author author author author author |
| dc.subject.none.fl_str_mv |
Brain clocks |
| topic |
Brain clocks |
| purl_subject.fl_str_mv |
https://purl.org/becyt/ford/3.1 https://purl.org/becyt/ford/3 |
| dc.description.none.fl_txt_mv |
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. Fil: Moguilner, Sebastian. Universidad Adolfo Ibañez; Chile. Universidad de San Andrés; Argentina. Harvard Medical School; Estados Unidos Fil: Baez, Sandra. University of California; Estados Unidos. Trinity College Dublin; Irlanda. Universidad de los Andes; Colombia Fil: Hernandez, Hernan. Universidad Adolfo Ibañez; Chile Fil: Migeot, Joaquín. Universidad Adolfo Ibañez; Chile Fil: Legaz, Agustina. Universidad Adolfo Ibañez; Chile. Universidad de San Andrés; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Gonzalez Gomez, Raul. Universidad Adolfo Ibañez; Chile Fil: Farina, Francesca R.. University of California; Estados Unidos. Trinity College Dublin; Irlanda Fil: Prado, Pavel. Universidad San Sebastián; Chile Fil: Cuadros, Jhosmary. Universidad Adolfo Ibañez; Chile. Universidad Nacional Experimental del Táchira; Venezuela. Universidad Técnica Federico Santa María; Chile Fil: Tagliazucchi, Enzo Rodolfo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Adolfo Ibañez; Chile. Universidad de Buenos Aires; Argentina Fil: Altschuler, Florencia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de San Andrés; Argentina Fil: Maito, Marcelo Adrián. Universidad de San Andrés; Argentina. Universidad Adolfo Ibañez; Chile Fil: Godoy, María E.. Universidad de San Andrés; Argentina. Universidad Adolfo Ibañez; Chile Fil: Cruzat, Josephine. Universidad Adolfo Ibañez; Chile Fil: Valdes Sosa, Pedro A.. University of Electronic Sciences and Technology of China; China. Technology of China; China. Cuban Neuroscience Center; Cuba Fil: Lopera, Francisco. Universidad de Antioquia; Colombia Fil: Ochoa Gómez, John Fredy. Universidad de Antioquia; Colombia Fil: Gonzalez Hernandez, Alfredis. Universidad Surcolombiana Neiva; Colombia Fil: Bonilla Santos, Jasmin. Universidad Cooperativa de Colombia; Colombia Fil: Gonzalez Montealegre, Rodrigo A.. Universidad Surcolombiana Neiva; Colombia Fil: Anghinah, Renato. Universidade de Sao Paulo; Brasil Fil: d’Almeida Manfrinati, Luís E.. Universidade de Sao Paulo; Brasil Fil: Fittipaldi, Sol. University of California; Estados Unidos. Trinity College Dublin; Irlanda. Universidad Adolfo Ibañez; Chile Fil: Medel, Vicente. Universidad Adolfo Ibañez; Chile Fil: Olivares, Daniela. Universidad Adolfo Ibañez; Chile. Universidad de Chile; Chile. Centro de Neuropsicología Clínica; Chile Fil: Yener, Görsev G.. Izmir University of Economics; Turquía. Dokuz Eylul University; Turquía. Izmir Biomedicine and Genome Center; Turquía Fil: Escudero, Javier. University of Edinburgh; Reino Unido Fil: Babiloni, Claudio. Università degli Studi di Roma "La Sapienza"; Italia. Hospital San Raffaele Cassino; Italia Fil: Whelan, Robert. University of California; Estados Unidos. Trinity College Dublin; Irlanda Fil: Güntekin, Bahar. Istanbul Medipol University; Turquía Fil: Barttfeld, Pablo. Universidad Nacional de Córdoba. Instituto de Investigaciones Psicológicas. - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Investigaciones Psicológicas; Argentina |
| description |
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. |
| publishDate |
2024 |
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2024-08 |
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info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
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http://hdl.handle.net/11336/244705 Moguilner, Sebastian; Baez, Sandra; Hernandez, Hernan; Migeot, Joaquín; Legaz, Agustina; et al.; Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations; Nature Publishing Group; Nature Medicine; 8-2024; 1-27 1078-8956 CONICET Digital CONICET |
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http://hdl.handle.net/11336/244705 |
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Moguilner, Sebastian; Baez, Sandra; Hernandez, Hernan; Migeot, Joaquín; Legaz, Agustina; et al.; Brain clocks capture diversity and disparities in aging and dementia across geographically diverse populations; Nature Publishing Group; Nature Medicine; 8-2024; 1-27 1078-8956 CONICET Digital CONICET |
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eng |
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Nature Publishing Group |
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