9 research outputs found

    Brain clocks capture diversity and disparities in aging and dementia

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    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.</p

    Systematic review : genetic, neuroimaging and fluids biomarkers for frontotemporal dementia across Latin America Countries

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    Frontotemporal dementia (FTD) includes a group of clinically, genetically, and pathologically heterogeneous neurodegenerative disorders, affecting the fronto-insular-temporal regions of the brain. Clinically, FTD is characterized by progressive deficits in behavior, executive function, and language and its diagnosis relies mainly on the clinical expertise of the physician/consensus group and the use of neuropsychological tests and/or structural/functional neuroimaging, depending on local availability. The modest correlation between clinical findings and FTD neuropathology makes the diagnosis difficult using clinical criteria and often leads to underdiagnosis or misdiagnosis, primarily due to lack of recognition or awareness of FTD as a disease and symptom overlap with psychiatric disorders. Despite advances in understanding the underlying neuropathology of FTD, accurate and sensitive diagnosis for this disease is still lacking. One of the major challenges is to improve diagnosis in FTD patients as early as possible. In this context, biomarkers have emerged as useful methods to provide and/or complement clinical diagnosis for this complex syndrome, although more evidence is needed to incorporate most of them into clinical practice. However, most biomarker studies have been performed using North American or European populations, with little representation of the Latin American and the Caribbean (LAC) region. In the LAC region, there are additional challenges, particularly the lack of awareness and knowledge about FTD, even in specialists. Also, LAC genetic heritage and cultures are complex, and both likely influence clinical presentations and may modify baseline biomarker levels. Even more, due to diagnostic delay, the clinical presentation might be further complicated by both neurological and psychiatric comorbidity, such as vascular brain damage, substance abuse, mood disorders, among others. This systematic review provides a brief update and an overview of the current knowledge on genetic, neuroimaging, and fluid biomarkers for FTD in LAC countries. Our review highlights the need for extensive research on biomarkers in FTD in LAC to contribute to a more comprehensive understanding of the disease and its associated biomarkers. Dementia research is certainly reduced in the LAC region, highlighting an urgent need for harmonized, innovative, and cross-regional studies with a global perspective across multiple areas of dementia knowledge

    Classification of Alzheimer's disease and frontotemporal dementia using routine clinical and cognitive measures across multicentric underrepresented samples: a cross sectional observational studyResearch in context

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    Summary: Background: Global brain health initiatives call for improving methods for the diagnosis of Alzheimer's disease (AD) and frontotemporal dementia (FTD) in underrepresented populations. However, diagnostic procedures in upper-middle-income countries (UMICs) and lower-middle income countries (LMICs), such as Latin American countries (LAC), face multiple challenges. These include the heterogeneity in diagnostic methods, lack of clinical harmonisation, and limited access to biomarkers. Methods: This cross-sectional observational study aimed to identify the best combination of predictors to discriminate between AD and FTD using demographic, clinical and cognitive data among 1794 participants [904 diagnosed with AD, 282 diagnosed with FTD, and 606 healthy controls (HCs)] collected in 11 clinical centres across five LAC (ReDLat cohort). Findings: A fully automated computational approach included classical statistical methods, support vector machine procedures, and machine learning techniques (random forest and sequential feature selection procedures). Results demonstrated an accurate classification of patients with AD and FTD and HCs. A machine learning model produced the best values to differentiate AD from FTD patients with an accuracy = 0.91. The top features included social cognition, neuropsychiatric symptoms, executive functioning performance, and cognitive screening; with secondary contributions from age, educational attainment, and sex. Interpretation: Results demonstrate that data-driven techniques applied in archival clinical datasets could enhance diagnostic procedures in regions with limited resources. These results also suggest specific fine-grained cognitive and behavioural measures may aid in the diagnosis of AD and FTD in LAC. Moreover, our results highlight an opportunity for harmonisation of clinical tools for dementia diagnosis in the region. Funding: This work was supported by the Multi-Partner Consortium to Expand Dementia Research in Latin America (ReDLat), funded by NIA/NIH (R01AG057234), Alzheimer's Association (SG-20-725707-ReDLat), Rainwater Foundation, Takeda (CW2680521), Global Brain Health Institute; as well as CONICET; FONCYT-PICT (2017-1818, 2017-1820); PIIECC, Facultad de Humanidades, Usach; Sistema General de Regalías de Colombia (BPIN2018000100059), Universidad del Valle (CI 5316); ANID/FONDECYT Regular (1210195, 1210176, 1210176); ANID/FONDAP (15150012); ANID/PIA/ANILLOS ACT210096; and Alzheimer's Association GBHI ALZ UK-22-865742

    The Multi-Partner Consortium to Expand Dementia Research in Latin America (ReDLat): Driving Multicentric Research and Implementation Science.

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    Dementia is becoming increasingly prevalent in Latin America, contrasting with stable or declining rates in North America and Europe. This scenario places unprecedented clinical, social, and economic burden upon patients, families, and health systems. The challenges prove particularly pressing for conditions with highly specific diagnostic and management demands, such as frontotemporal dementia. Here we introduce a research and networking initiative designed to tackle these ensuing hurdles, the Multi-partner consortium to expand dementia research in Latin America (ReDLat). First, we present ReDLat's regional research framework, aimed at identifying the unique genetic, social, and economic factors driving the presentation of frontotemporal dementia and Alzheimer's disease in Latin America relative to the US. We describe ongoing ReDLat studies in various fields and ongoing research extensions. Then, we introduce actions coordinated by ReDLat and the Latin America and Caribbean Consortium on Dementia (LAC-CD) to develop culturally appropriate diagnostic tools, regional visibility and capacity building, diplomatic coordination in local priority areas, and a knowledge-to-action framework toward a regional action plan. Together, these research and networking initiatives will help to establish strong cross-national bonds, support the implementation of regional dementia plans, enhance health systems' infrastructure, and increase translational research collaborations across the continent

    The Multi-Partner Consortium to Expand Dementia Research in Latin America (ReDLat): Driving Multicentric Research and Implementation Science

    No full text
    Dementia is becoming increasingly prevalent in Latin America, contrasting with stable or declining rates in North America and Europe. This scenario places unprecedented clinical, social, and economic burden upon patients, families, and health systems. The challenges prove particularly pressing for conditions with highly specific diagnostic and management demands, such as frontotemporal dementia. Here we introduce a research and networking initiative designed to tackle these ensuing hurdles, the Multi-partner consortium to expand dementia research in Latin America (ReDLat). First, we present ReDLat's regional research framework, aimed at identifying the unique genetic, social, and economic factors driving the presentation of frontotemporal dementia and Alzheimer's disease in Latin America relative to the US. We describe ongoing ReDLat studies in various fields and ongoing research extensions. Then, we introduce actions coordinated by ReDLat and the Latin America and Caribbean Consortium on Dementia (LAC-CD) to develop culturally appropriate diagnostic tools, regional visibility and capacity building, diplomatic coordination in local priority areas, and a knowledge-to-action framework toward a regional action plan. Together, these research and networking initiatives will help to establish strong cross-national bonds, support the implementation of regional dementia plans, enhance health systems' infrastructure, and increase translational research collaborations across the continent.Fil: Ibañez, Agustin Mariano. University of California; Estados Unidos. Trinity College Dublin; Irlanda. Universidad de San Andrés; Argentina. Universidad Adolfo Ibañez; Chile. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Yokoyama, Jennifer S.. University of California; Estados Unidos. Trinity College Dublin; IrlandaFil: Possin, Katherine L.. University of California; Estados Unidos. Trinity College Dublin; IrlandaFil: Matallana, Diana. Pontificia Universidad Javeriana; Colombia. Hospital Universitario San Ignacio; Colombia. Hospital Universitario Santa Fe de Bogotá; ColombiaFil: Lopera, Francisco. Universidad de Antioquia; ColombiaFil: Nitrini, Ricardo. Universidade de Sao Paulo; BrasilFil: Takada, Leonel T.. Universidade de Sao Paulo; BrasilFil: Custodio, Nilton. Instituto Peruano de Neurociencias; PerúFil: Sosa Ortiz, Ana Luisa. Universidad Nacional Autónoma de México; MéxicoFil: Avila Funes, José Alberto. Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán; México. Université de Bordeaux; FranciaFil: Behrens, Maria Isabel. Universidad de Chile; Chile. Universidad del Desarrollo; ChileFil: Slachevsky, Andrea. Universidad del Desarrollo; Chile. Centro de Gerociencia para la Salud Cerebral y el Metabolismo; Chile. Instituto de Ciencias Biomédicas, Neurociencias y Neurociencias de Oriente; Chile. Universidad de Chile; ChileFil: Myers, Richard M.. Hudson Alpha Institute for Biotechnology; Estados UnidosFil: Cochran, J. Nicholas. Hudson Alpha Institute for Biotechnology; Estados UnidosFil: Brusco, Luis Ignacio. Universidad de Buenos Aires. Facultad de Medicina; Argentina. ALZAR; ArgentinaFil: Brusco, Luis Ignacio. Universidad de Buenos Aires. Facultad de Medicina; Argentina. ALZAR; ArgentinaFil: Bruno, Martin. Universidad Nacional de Cuyo. Facultad de Ciencias Medicas. Departamento de Neurociencias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Juan; ArgentinaFil: Brucki, Sonia M. D.. Hospital Santa Marcelina; Brasil. Universidade de Sao Paulo; BrasilFil: Pina Escudero, Stefanie Danielle. University of California; Estados Unidos. Trinity College Dublin; IrlandaFil: Okada de Oliveira, Maira. University of California; Estados Unidos. Trinity College Dublin; Irlanda. Universidade de Sao Paulo; Brasil. Hospital Santa Marcelina; BrasilFil: Donnelly Kehoe, Patricio Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas. Universidad Nacional de Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y de Sistemas; ArgentinaFil: García, Adolfo Martín. University of California; Estados Unidos. Trinity College Dublin; Irlanda. Universidad de San Andrés; Argentina. Universidad Catolica de Cuyo. Facultad de Educacion.; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Cardona Londoño, Juan Felipe. Universidad del Valle; Colombia. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Santamaria Garcia, Hernando. Hospital Universitario San Ignacio; Colombia. Pontificia Universidad Javeriana; Colombia. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Moguilner, Sebastian. University of California; Estados Unidos. Trinity College Dublin; IrlandaFil: Duran Aniotz, Claudia. Universidad Adolfo Ibañez; ChileFil: Tagliazucchi, Enzo Rodolfo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Maito, Marcelo. Universidad de San Andrés; ArgentinaFil: Longoria Ibarrola, Erika Mariana. Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán; MéxicoFil: Pintado Caipa, Maritza. Trinity College Dublin; Irlanda. University of California; Estados Unidos. Instituto Peruano de Neurociencias; PerúFil: Godoy, Maria Eugenia. Universidad de San Andrés; ArgentinaFil: Bakman, Vera. University of California; Estados Unidos. Trinity College Dublin; IrlandaFil: Javandel, Shireen. University of California; Estados UnidosFil: Kosik, Kenneth. University of California; Estados UnidosFil: Valcour, Victor. University of California; Estados Unidos. Trinity College Dublin; IrlandaFil: Miller, Bruce L.. University of California; Estados Unidos. Trinity College Dublin; Irland

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

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    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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