Andrea María Slachevsky Conchol

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Slachevsky Chonchol, Andrea

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Slachevsky Chonchol

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Andrea María Slachevsky Conchol

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Author Correction: the BrainLat project, a multimodal neuroimaging dataset of neurodegeneration from underrepresented backgrounds
(2024) Prado, Pavel; Medel, Vicente; González, Raúl; Sainz, Agustín; Vidal, Víctor; Santamaría, Hernando; Moguilner, Sebastián; Mejía, Jhony; Slachevsky Chonchol, Andrea; Behrens, Maria Isabel; Aguillón, David; Lopera, Francisco; Parra, Mario; Matallana, Diana; Adrián, Marcelo; García, Adolfo; Custodio, Nilton; Ávila, Alberto; Piña, Stefanie; Birba, Agustina; Fittipaldi, Sol; Legaz, Agustina; Ibáñez, Agustín
In this article the author name Maria Isabel Behrens was incorrectly written as Maria Isabel Beherens. The original article has been corrected.
Educational disparities in brain health and dementia across Latin America and the United States
(2024) Gonzalez, Raul; Legaz, Agustina; Moguilner, Sebastián; Cruzat, Josephine; Hernández, Hernán; Baez, Sandra; Cocchi, Rafael; Coronel, Carlos; Medel,Vicente; Tagliazuchi, Enzo; Migeot, Joaquín; Ochoa, Carolina; Maito, Marcelo; Reyes, Pablo; Santamaria, Hernando; Godoy, Maria; Javande, Shireen; García, Adolfo; Matallana, Diana; Avila, José; Slachevsky Chonchol, Andrea; Behrens, María; Custodio, Nilton; Cardona, Juan; Brusco, Ignacio; Bruno, Martín; Sosa, Ana; Pina, Stefanie; Takada, Leonel; França, Elisa; Valcour, Victor; Possin, Katherine; De Oliveira, Maira; Lopera, Francisco; Lawlor, Brian; Hu, Kun; Miller, Bruce; Yokoyama, Jennifer; Gonzalez, Cecilia; Ibañez, Agustin
Background: Education influences brain health and dementia. However, its impact across regions, specifically Latin America (LA) and the United States (US), is unknown. Methods: A total of 1412 participants comprising controls, patients with Alzheimer's disease (AD), and frontotemporal lobar degeneration (FTLD) from LA and the US were included. We studied the association of education with brain volume and functional connectivity while controlling for imaging quality and variability, age, sex, total intracranial volume (TIV), and recording type. Results: Education influenced brain measures, explaining 24%-98% of the geographical differences. The educational disparities between LA and the US were associated with gray matter volume and connectivity variations, especially in LA and AD patients. Education emerged as a critical factor in classifying aging and dementia across regions. Discussion: The results underscore the impact of education on brain structure and function in LA, highlighting the importance of incorporating educational factors into diagnosing, care, and prevention, and emphasizing the need for global diversity in research. Highlights: Lower education was linked to reduced brain volume and connectivity in healthy controls (HCs), Alzheimer's disease (AD), and frontotemporal lobar degeneration (FTLD). Latin American cohorts have lower educational levels compared to the those in the United States. Educational disparities majorly drive brain health differences between regions. Educational differences were significant in both conditions, but more in AD than FTLD. Education stands as a critical factor in classifying aging and dementia across regions.
Comprehensive Analysis of Genetic Contributions to Alzheimer’s Disease and Frontotemporal Dementia in Admixed Latin American Populations
(2024) Acosta, Juliana; Pina, Stefanie; Cochran, Nicholas; Taylor, Jared; Warly, Caroline; Matallana, Diana; Tadao, Leonel; Bruno, Martin; Levine, Alexandra; George, Dawwod; Lopera, Francisco; Slachevsky Chonchol, Andrea; Behrens, María; Ávila, José; Zapata, Lina; Brusco, Luis; Custodio, Nilton; Ramos, Teresita; Bruna, Bárbara; Ponce, Daniela; Gelvez, Nancy; Lopez, Greizy; Gomez, Luisa; Buitrago, Carlos; Reyes, Pablo; Durón, Dafne; Pantazis, Caroline; Maito, Marcelo; Javandel, Shireen; Godoy, Maria; Bistue, Maria; Vitale, Dan; Nalls, Mike; Singleton, Andrew; Miller, Bruce; Ibáñez, Agustín; Kosik, Kenneth; Yokoyama, Jennifer; Montesinos, Rosa; França, Elisa de Paula; Multi-Partner Consortium to Expand Dementia Research in Latin America (ReDLat)
Background: Most research initiatives have emerged from high-income countries (HIC), leaving a gap in understanding the disease’s genetic basis in diverse populations like those in Latin American countries (LAC). ReDLat tackles this gap, focusing on LAC’s unique genetics and socioeconomic factors to identify specific Alzheimer’s Disease (AD) and Frontotemporal Dementia (FTD) risk factors in Mexico, Colombia, Peru, Chile, Argentina, and Brazil. Method: We employed a comprehensive genetic analysis approach, integrating Whole Genome Sequencing (WGS), Exome Sequencing, and SNP arrays to understand the cohort’s unique genetic architecture.We conducted ancestry analysis and searched for disease-causing variants with mendelian inheritance, genome-wide association studies (GWAS), rare variant enrichment, and evaluation of Polygenic Risk Scores (PRS). Results: We recruited and genotyped an initial cohort of 1046 participants with AD, 423 with FTD, and 855 healthy controls (HC) between 2020 and 2023. Analysis is ongoing, and we expect to sequence ∼600 additional samples in the coming months. Ancestry analysis revealed tri-continental admixture, except for Brazil, which showed an additional Asian component (Figure 1). Top candidate gene rare variant enrichment associations (SKAT p < 0.05) were TREM2 for FTD and ABCA7 and ABCA1 for AD. GWAS identified a robust association with the APOE locus on chromosome 19 in AD vs. HC.. We tested an AD PRS developed in European populations by Bellenguez et al (2020). on our cohort using 83 single-nucleotide polymorphisms.. The PRS modestly distinguishes between all patients and HC (p = 2.4 × 10ˆ-12), AD vs. HC (p = 2.2 × 10ˆ-12), and even FTD vs. HC (p = 4.3 × 10ˆ-5), albeit with modest separation between groups, as expected for its application in a genetically admixed population. Conclusion: Our findings represent a pivotal step in understanding the genetic landscape of AD and FTD in admixed populations. They underscore the importance of including diverse populations in genetic research, paving the way for future studies. These findings have the potential to inform more personalized approaches to the diagnosis and treatment of neurodegenerative diseases in diverse global populations, as well as identify novel targets for therapeutic development
Multi-feature computational framework for combined signatures of dementia in underrepresented settings
(2022) Moguilner, Sebastián; Birba, Agustina; Fittipaldi, Sol; Gonzalez, Cecilia; Tagliazucchi, Enzo; Reyes, Pablo; Matallana, Diana; Parra, Mario; Slachevsky Chonchol, Andrea; Farías, Gonzalo; Cruzat, Josefina; García, Adolfo; Eyre, Harris; La Joie, Renaud; Rabinovici, Gil; Whelan, Robert; Ibáñez, Agustín
Objective.The differential diagnosis of behavioral variant frontotemporal dementia (bvFTD) and Alzheimer's disease (AD) remains challenging in underrepresented, underdiagnosed groups, including Latinos, as advanced biomarkers are rarely available. Recent guidelines for the study of dementia highlight the critical role of biomarkers. Thus, novel cost-effective complementary approaches are required in clinical settings.Approach. We developed a novel framework based on a gradient boosting machine learning classifier, tuned by Bayesian optimization, on a multi-feature multimodal approach (combining demographic, neuropsychological, magnetic resonance imaging (MRI), and electroencephalography/functional MRI connectivity data) to characterize neurodegeneration using site harmonization and sequential feature selection. We assessed 54 bvFTD and 76 AD patients and 152 healthy controls (HCs) from a Latin American consortium (ReDLat).Main results. The multimodal model yielded high area under the curve classification values (bvFTD patients vs HCs: 0.93 (±0.01); AD patients vs HCs: 0.95 (±0.01); bvFTD vs AD patients: 0.92 (±0.01)). The feature selection approach successfully filtered non-informative multimodal markers (from thousands to dozens).Results. Proved robust against multimodal heterogeneity, sociodemographic variability, and missing data.Significance. The model accurately identified dementia subtypes using measures readily available in underrepresented settings, with a similar performance than advanced biomarkers. This approach, if confirmed and replicated, may potentially complement clinical assessments in developing countries
Automated free speech analysis reveals distinct markers of Alzheimer's and frontotemporal dementia
(2024) Lopes da Cunha, Pamela; Ruiz, Fabián; Ferrante, Franco; Sterpin, Lucas; Ibáñez, Agustín; Slachevsky Chonchol, Andrea; Matallana, Diana; Martínez, Ángela; Hesse, Eugenia; García, Adolfo
Dementia can disrupt how people experience and describe events as well as their own role in them. Alzheimer's disease (AD) compromises the processing of entities expressed by nouns, while behavioral variant frontotemporal dementia (bvFTD) entails a depersonalized perspective with increased third-person references. Yet, no study has examined whether these patterns can be captured in connected speech via natural language processing tools. To tackle such gaps, we asked 96 participants (32 AD patients, 32 bvFTD patients, 32 healthy controls) to narrate a typical day of their lives and calculated the proportion of nouns, verbs, and first- or third-person markers (via part-of-speech and morphological tagging). We also extracted objective properties (frequency, phonological neighborhood, length, semantic variability) from each content word. In our main study (with 21 AD patients, 21 bvFTD patients, and 21 healthy controls), we used inferential statistics and machine learning for group-level and subject-level discrimination. The above linguistic features were correlated with patients' scores in tests of general cognitive status and executive functions. We found that, compared with HCs, (i) AD (but not bvFTD) patients produced significantly fewer nouns, (ii) bvFTD (but not AD) patients used significantly more third-person markers, and (iii) both patient groups produced more frequent words. Machine learning analyses showed that these features identified individuals with AD and bvFTD (AUC = 0.71). A generalizability test, with a model trained on the entire main study sample and tested on hold-out samples (11 AD patients, 11 bvFTD patients, 11 healthy controls), showed even better performance, with AUCs of 0.76 and 0.83 for AD and bvFTD, respectively. No linguistic feature was significantly correlated with cognitive test scores in either patient group. These results suggest that specific cognitive traits of each disorder can be captured automatically in connected speech, favoring interpretability for enhanced syndrome characterization, diagnosis, and monitoring.
The impacts of social determinants of health and cardiometabolic factors on cognitive and functional aging in Colombian underserved populations
(2023) Santamaria, Hernando; Moguilner, Sebastian; Rodriguez, Odir; Botero, Felipe; Pina, Stefanie; O’Donovan, Gary; Albala, Cecilia; Matallana, Diana; Schulte, Michael; Slachevsky Chonchol, Andrea; Yokoyama, Jennifer; Possin, Katherine; Ndhlovu, Lishomwa; Al‑Rousan, Tala; Corley, Michael; Kosik, Kenneth; Muniz, Graciela; Miranda, J. Jaime; Ibanez, Agustin
Global initiatives call for further understanding of the impact of inequity on aging across underserved populations. Previous research in low- and middle-income countries (LMICs) presents limitations in assessing combined sources of inequity and outcomes (i.e., cognition and functionality). In this study, we assessed how social determinants of health (SDH), cardiometabolic factors (CMFs), and other medical/social factors predict cognition and functionality in an aging Colombian population. We ran a cross-sectional study that combined theory- (structural equation models) and data-driven (machine learning) approaches in a population-based study (N = 23,694; M = 69.8 years) to assess the best predictors of cognition and functionality. We found that a combination of SDH and CMF accurately predicted cognition and functionality, although SDH was the stronger predictor. Cognition was predicted with the highest accuracy by SDH, followed by demographics, CMF, and other factors. A combination of SDH, age, CMF, and additional physical/psychological factors were the best predictors of functional status. Results highlight the role of inequity in predicting brain health and advancing solutions to reduce the cognitive and functional decline in LMICs.
Advancements in dementia research, diagnostics, and care in Latin America: Highlights from the 2023 Alzheimer's Association International conference satellite symposium in Mexico City
(2024) Sosa, Ana; Brucki; Sonia; Crivelli, Lucia; Lopera, Francisco; Acosta, Daisy; Acosta, Juliana; Aguilar, Diego; Aguilar.Sara; Allegri, Ricardo; Bertolucci, Paulo; Calandri, Ismael; Carrillo, Maria; Chrem , Patricio; Cornejo, Mario; Custodio, Nilton; Damian, Andrés; Cruz , Leonardo; Duran, Claudia; García, Adolfo; García, Carmen; Gonzales, Mitzi; Grinberg, Lea; Ibanez, Agustin; Illanes, Maryenela; Jack, Clifford; Leon, Jorge; Llibre, Jorge; Luna, José; Matallana, Diana; Miller, Bruce; Naci, Lorina; Parra, Mario; Pericak, Margaret; Piña, Stefanie; França, Elisa de Paula; Ringman, John; Sevlever, Gustavo; Slachevsky Chonchol, Andrea; Kimie, Claudia; Valcour, Victor; Villegas, Andres
Introduction: While Latin America (LatAm) is facing an increasing burden of dementia due to the rapid aging of the population, it remains underrepresented in dementia research, diagnostics, and care. Methods: In 2023, the Alzheimer's Association hosted its eighth satellite symposium in Mexico, highlighting emerging dementia research, priorities, and challenges within LatAm. Results: Significant initiatives in the region, including intracountry support, showcased their efforts in fostering national and international collaborations; genetic studies unveiled the unique genetic admixture in LatAm; researchers conducting emerging clinical trials discussed ongoing culturally specific interventions; and the urgent need to harmonize practices and studies, improve diagnosis and care, and use affordable biomarkers in the region was highlighted. Discussion: The myriad of topics discussed at the 2023 AAIC satellite symposium highlighted the growing research efforts in LatAm, providing valuable insights into dementia biology, genetics, epidemiology, treatment, and care.
Cardiovascular risk factors and the allostatic interoceptive network in dementia
(2025) Hazelton, Jessica; Migeot, Joaquín; Gonzalez, Raul; Altschuler, Florencia; Duran, Claudia; Wen, Olivia; Galván, Dante; Barttfeld, Pablo; Medel , Vicente; González, Cecilia; Castro, Ana; Hernández, Hernán; Gonzalez, Carolina; Castaner, Olga; Hu, Kun; Li, Peng; Maria Isabel Behrens; Behrens, Maria Isabel; Bruno, Martin; Cardona, Juan; Custodio, Nilton; Santamaria, Hernando; Garcia, Adolfo; Godoy, Maria; Avila, José; Maito, Marce; Matallana, Diana; Miller, Bruce; Lopera, Francisco; Okada , Maira; Pina, Stefanie; Possin, Katherine; France, Elisa de Paula; Reyes, Pablo; Slachevsky Chonchol, Andrea; Sosa, Ana; Takada, Leonel; Yokoyama, Jennifer; Ibanez, Agustin
Aims: Cardiovascular risk factors, such diabetes, hypertension, blood pressure, obesity, and smoking, are linked with allostatic-interoception-the continuous monitoring of internal bodily states in anticipation of environmental demands. These risk factors are associated with dementia risk. How these factors affect brain networks vulnerable to neurodegeneration and involved in allostatic-interoception, such as the Allostatic-Interoceptive Network (AIN), is unknown. We investigated the relationship between cardiovascular risk and AIN structure and function in frontotemporal lobar degeneration (FTLD) and Alzheimer's disease (AD). Methods and results: We recruited 1501 participants (304 with FTLD, 512 with AD, and 685 healthy controls) from the Multi-Partner Consortium to Expand Dementia Research in Latin America (ReDLat). A cardiovascular risk score was calculated based on: age, sex, diabetes, hypertension, systolic blood pressure, body mass index, and smoking status. Cardiovascular risk was associated with grey matter integrity and functional connectivity in age- and sex-matched patient-control groups focusing on predefined regions of interest within the AIN. Higher cardiovascular risk was associated with reduced structural integrity and functional connectivity within the AIN in both FTLD and AD. FTLD patients showed more extensive structural and functional connectivity disruptions throughout the AIN. In AD patients, structural reductions in the AIN were prominent, with functional connectivity restricted to the hippocampus, parahippocampal gyrus, and orbitofrontal regions. Conclusion: Cardiovascular risk factors appear to adversely impact the AIN structure and function, with disease-specific patterns of vulnerability. Results underscore the importance of integrating cardiovascular health into models of neurodegenerative disease and managing cardiovascular health to support brain integrity in dementia.
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, Agustin
A 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.