Person: Behrens, Maria Isabel
Loading...
Email Address
Birth Date
Research Projects
Organizational Units
Job Title
Last Name
Behrens
First Name
Maria Isabel
Name
2 results
¿Qué estás buscando?
Search Results
Now showing 1 - 2 of 2
Publication Cancer History Avoids the Increase of Senescence Markers in Peripheral Cells of Amnestic Mild Cognitive Impaired Patients(2023) SanMartín, Carol D.; Salech, Felipe; Ponce, Daniela Paz; Concha-Cerda, Jorge; Romero-Hernández, Esteban; Liabeuf, Gianella; Rogers, Nicole K.; Murgas, Paola; Bruna, Bárbara; More, Jamileth; Behrens, Maria IsabelEpidemiological studies show that having a history of cancer protects from the development of Alzheimer’s Disease (AD), and vice versa, AD protects from cancer. The mechanism of this mutual protection is unknown. We have reported that the peripheral blood mononuclear cells (PBMC) of amnestic cognitive impairment (aMCI) and Alzheimer’s Disease (AD) patients have increased susceptibility to oxidative cell death compared to control subjects, and from the opposite standpoint a cancer history is associated with increased resistance to oxidative stress cell death in PBMCs, even in those subjects who have cancer history and aMCI (Ca + aMCI). Cellular senescence is a regulator of susceptibility to cell death and has been related to the pathophysiology of AD and cancer. Recently, we showed that cellular senescence markers can be tracked in PBMCs of aMCI patients, so we here investigated whether these senescence markers are dependent on having a history of cancer. Senescence-associated βeta-galactosidase (SA-β-Gal) activity, G0-G1 phase cell-cycle arrest, p16 and p53 were analyzed by flow cytometry; phosphorylated H2A histone family member X (γH2AX) by immunofluorescence; IL-6 and IL-8 mRNA by qPCR; and plasmatic levels by ELISA. Senescence markers that were elevated in PBMCs of aMCI patients, such as SA-β-Gal, Go-G1 arrested cells, IL-6 and IL-8 mRNA expression, and IL-8 plasmatic levels, were decreased in PBMCs of Ca + aMCI patients to levels similar to those of controls or of cancer survivors without cognitive impairment, suggesting that cancer in the past leaves a fingerprint that can be peripherally traceable in PBMC samples. These results support the hypothesis that the senescence process might be involved in the inverse association between cancer and AD.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.