Andrea María Slachevsky Conchol

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Slachevsky Chonchol, Andrea

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Slachevsky Chonchol

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Andrea

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Andrea María Slachevsky Conchol

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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.
The first genome-wide association study in the Argentinian and Chilean populations identifies shared genetics with Europeans in Alzheimer's disease
(2024) Dalmasso, Maria; De Rojas, Itziar; Olivar, Natividad; Muchnik, Carolina; Angel, Bárbara; Gloger, Sergio; Sanchez, Mariana; Chacón, María; Aránguiz, Rafael; Orellana, Paulina; Cuesta, Carolina; Galeano, Pablo; Campanelli, Lorenzo; Novack, Gisela; Martinez, Luis; Medel, Nancy; Lisso, Julieta; Sevillano, Zulma; Irureta, Nicolás; Castaño, Eduardo; Montrreal, Laura; Thoenes, Michaela; Hanses, Claudia; Heilmann-Heimbach, Stefanie; Kairiyama, Claudia; Mintz, Inés; Villella, Ivana; Rueda, Fabiana; Romero, Amanda; Wukitsevits, Nancy; Quiroga, Ivana; Gona, Cristian; Lamber, Jean-Charles; Solis, Patricia; Politis, Daniel; Mangone, Carlos; Gonzalez, Christian; Boada, Mercè; Tàrraga, Lluís; Slachevsky Chonchol, Andrea
Introduction: Genome-wide association studies (GWAS) are fundamental for identifying loci associated with diseases. However, they require replication in other ethnicities. Methods: We performed GWAS on sporadic Alzheimer's disease (AD) including 539 patients and 854 controls from Argentina and Chile. We combined our results with those from the European Alzheimer and Dementia Biobank (EADB) in a meta-analysis and tested their genetic risk score (GRS) performance in this admixed population. Results: We detected apolipoprotein E ε4 as the single genome-wide significant signal (odds ratio = 2.93 [2.37-3.63], P = 2.6 × 10-23 ). The meta-analysis with EADB summary statistics revealed four new loci reaching GWAS significance. Functional annotations of these loci implicated endosome/lysosomal function. Finally, the AD-GRS presented a similar performance in these populations, despite the score diminished when the Native American ancestry rose. Discussion: We report the first GWAS on AD in a population from South America. It shows shared genetics modulating AD risk between the European and these admixed populations. Highlights: This is the first genome-wide association study on Alzheimer's disease (AD) in a population sample from Argentina and Chile. Trans-ethnic meta-analysis reveals four new loci involving lysosomal function in AD. This is the first independent replication for TREM2L, IGH-gene-cluster, and ADAM17 loci. A genetic risk score (GRS) developed in Europeans performed well in this population. The higher the Native American ancestry the lower the GRS values
The BrainLat project, a multimodal neuroimaging dataset of neurodegeneration from underrepresented backgrounds
(2023) Prado, Pavel; Medel, Vicente; Gonzalez, Raul; Sainz, Agustín; Vidal , Victor; Santamaría, Hernando; Moguilner, Sebastian; Mejia, Jhony; Slachevsky Chonchol, Andrea; Behrens, Maria; Aguillon, David; Lopera, Francisco; Parra, Mario; Matallana,Diana; Maito, Marcelo; Garcia, Adolfo; Custodio, Nilton; Ávila, Alberto; Piña, Stefanie; Birba, Agustina; Fittipaldi, Sol; Legaz, Agustina; Ibañez, Agustín
The Latin American Brain Health Institute (BrainLat) has released a unique multimodal neuroimaging dataset of 780 participants from Latin American. The dataset includes 530 patients with neurodegenerative diseases such as Alzheimer's disease (AD), behavioral variant frontotemporal dementia (bvFTD), multiple sclerosis (MS), Parkinson's disease (PD), and 250 healthy controls (HCs). This dataset (62.7 ± 9.5 years, age range 21-89 years) was collected through a multicentric effort across five Latin American countries to address the need for affordable, scalable, and available biomarkers in regions with larger inequities. The BrainLat is the first regional collection of clinical and cognitive assessments, anatomical magnetic resonance imaging (MRI), resting-state functional MRI (fMRI), diffusion-weighted MRI (DWI), and high density resting-state electroencephalography (EEG) in dementia patients. In addition, it includes demographic information about harmonized recruitment and assessment protocols. The dataset is publicly available to encourage further research and development of tools and health applications for neurodegeneration based on multimodal neuroimaging, promoting the assessment of regional variability and inclusion of underrepresented participants in research.
Classification of Alzheimer’s disease and frontotemporal dementia using routine clinical and cognitive measures across multicentric underrepresented samples: a cross sectional observational study
(2023) Maito, Marcelo Adrián; Santamaría-García, Hernando; Moguilner, Sebastián; Possin, Katherine L.; Godoy, María E.; Avila-Funes, José Alberto; Behrens, Maria Isabel; Brusco, Ignacio L. Maira Okada de Oliveira,b,r,s,ae Stefanie D. Pina-Escuder; Bruno, Martín A.; Cardona, Juan F.; Custodio, Nilton; García, Adolfo M.; Javandel, Shireen; Lopera, Francisco; Matallana, Diana L.; Miller, Bruce; Okada de Oliveira, Maira; Pina Escudero, Stefanie; Slachevsky Chonchol, Andrea; Ana L Sosa Ortiz; Takada, Leonel T.; Tagliazuchi, Enzo; Valcour, Victor; Yokoyama, Jennifer S.; Ibañez, Agustín
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.
Biomarkers for dementia in Latin American countries: Gaps andopportunities
(2023) Parra, Mario A.; Orellana, Paulina; León, Tomas; Victoria, Cabello G.; Henriquez, Fernando; Gomez, Rodrigo; Avalos, Constanza; Damian, Andres; Slachevsky Chonchol, Andrea; Ibañez, Agustin; Zetterberg, Henrik; Tijms, Betty M.; Yokoyama, Jennifer S.; Piña-Escudero, Stefanie D.; Cochran, Nicholas; Matallana, Diana L.; Acosta, Daisy; Allegri, Ricardo; Arias-Suáres, Bianca P.; Barra, Bernardo; Behrens, María Isabel; Brucki, Sonia M.D.; Busatto, Geraldo; Caramelli, Paulo; Castro-Suarez, Sheila; Contreras, Valeria; Custodio, Nilton; Dansilio, Sergio; De la Cruz-Puebla, Myriam; Cruz de Souza, Leonado; Díaz, Monica M.; Duque, Lissette; Farias, Gonzalo A.; Ferreira, Sergio T.; Magrath Guimet, Nahuel; Kmaid, Ana; Lira, David; Lopera, Francisco; Mar Meza, Beatriz; Miotto, Eliane C.
Limited knowledge on dementia biomarkers in Latin American and Caribbean (LAC)countries remains a serious barrier. Here, we reported a survey to explore the ongo-ing work, needs, interests, potential barriers, and opportunities for future studiesrelated to biomarkers. The results show that neuroimaging is the most used biomarker(73%), followed by genetic studies (40%), peripheral fluids biomarkers (31%), and cere-brospinal fluid biomarkers (29%). Regarding barriers in LAC, lack of funding appears toundermine the implementation of biomarkers in clinical or research settings, followedby insufficient infrastructure and training. The survey revealed that despite the abovebarriers, the region holds a great potential to advance dementia biomarkers research.Considering the unique contributions that LAC could make to this growing field,we highlight the urgent need to expand biomarker research. These insights allowedus to propose an action plan that addresses the recommendations for a biomarkerframework recently proposed by regional experts.
Standardization and diagnostic utility of the Frontal Assessment Battery for healthy people and patients with dementia in the Chilean population
(2022) Grandi, Fabrissio; Martínez, David; Parra, Mario; Olavarria, Loreto; Huepe, David; Alegría, Patricia; Aliaga, Álvaro; Lillo, Patricia; Delgado, Carolina; Tenorio, Marcela; Rosas, Ricardo; López, Oscar; Becker, James; Slachevsky Chonchol, Andrea
The Frontal Assessment Battery (FAB) is a screening test that measures executive functions. Although this instrument has been validated in several countries, its diagnostic utility in a Chilean population has not been studied yet. Objectives: This study aimed to (1) adapt FAB in a Chilean population; (2) study the psychometric properties of the FAB in a Chilean population; (3) assess the sociodemographic influence in the performance of the FAB in a sample of healthy controls (HC); and (4) develop normative data for this healthy group. Methods: A HC (n=344) and a group of patients with dementia (n=156) were assessed with the Chilean version of FAB. Results: FAB showed good internal consistency (Cronbach's alpha=0.79) and acceptable validity based on the relationship with other variables. Factor analysis showed the unidimensionality of the instrument. Significant differences were found in the total FAB value between the HC and dementia groups. With the matched sample, the established cutoff point was 13.5, showing a sensitivity of 80.8% and a specificity of 90.4%. Regression analysis showed that education and age significantly predicted FAB performance in the healthy group. Finally, normative data are provided. Conclusions: This study shows that FAB is a useful tool to discriminate between healthy people and people with dementia. However, further studies are needed to explore the capacity of the instrument to characterize the dysexecutive syndrome in people with dementia in the Chilean population.
Validation of Picture Free and Cued Selective Reminding Test for Illiteracy in Lima, Perú
(2022) Montesinos, Rosa; Parodi, José; Díaz, Mónica; Herrera, Eder; Valeriano, Elizabeth; Soto, Ambar; Delgado, Carolina; Slachevsky Chonchol, Andrea; Custodio, Nilton
Dementia in Latin America is a crucial public health problem. Identifying brief cognitive screening (BCS) tools for the primary care setting is crucial, particularly for illiterate individuals. We evaluated tool performance characteristics and validated the free and total recall sections of the Free and Cued Selective Reminding Test-Picture version (FCSRT-Picture) to discriminate between 63 patients with early Alzheimer's disease dementia (ADD), 60 amnestic mild cognitive impairment (aMCI) and 64 cognitively healthy Peruvian individuals with illiteracy from an urban area. Clinical, functional, and cognitive assessments were performed. FCSRT-Picture performance was assessed using receiver operating characteristic curve analyses. The mean ± standard deviation scores were 7.7 ± 1.0 in ADD, 11.8 ± 1.6 in aMCI, and 29.5 ± 1.8 in controls. The FCSRT-Picture had better performance characteristics for distinguishing controls from aMCI compared with several other BCS tools, but similar characteristics between controls and early ADD. The FCSRT-Picture is a reliable BCS tool for illiteracy in Perú.
Multimodal mechanisms of human sociallyreinforced learning across neurodegenerative diseases
(2022) Legaz, Agustina; Abrevaya, Sofía; Dottori, Martín; González, Cecilia; Birba, Agustina; Martorell, Miguel; Aguirre, Julieta; Slachevsky Chonchol, Andrea; Aranguiz, Rafael; Serrano, Cecilia; Gillan, Claire; Leroi, Iracema; García, Adolfo; Fittipaldi, Sol; Ibañez, Agustín
Social feedback can selectively enhance learning in diverse domains. Relevant neurocognitive mechanisms have been studied mainly in healthy persons, yielding correlational findings. Neurodegenerative lesion models, coupled with multimodal brain measures, can complement standard approaches by revealing direct multidimensional correlates of the phenomenon. To this end, we assessed socially reinforced and non-socially reinforced learning in 40 healthy participants as well as persons with behavioural variant frontotemporal dementia (n = 21), Parkinson's disease (n = 31) and Alzheimer's disease (n = 20). These conditions are typified by predominant deficits in social cognition, feedback-based learning and associative learning, respectively, although all three domains may be partly compromised in the other conditions. We combined a validated behavioural task with ongoing EEG signatures of implicit learning (medial frontal negativity) and offline MRI measures (voxel-based morphometry). In healthy participants, learning was facilitated by social feedback relative to non-social feedback. In comparison with controls, this effect was specifically impaired in behavioural variant frontotemporal dementia and Parkinson's disease, while unspecific learning deficits (across social and non-social conditions) were observed in Alzheimer's disease. EEG results showed increased medial frontal negativity in healthy controls during social feedback and learning. Such a modulation was selectively disrupted in behavioural variant frontotemporal dementia. Neuroanatomical results revealed extended temporo-parietal and fronto-limbic correlates of socially reinforced learning, with specific temporo-parietal associations in behavioural variant frontotemporal dementia and predominantly fronto-limbic regions in Alzheimer's disease. In contrast, non-socially reinforced learning was consistently linked to medial temporal/hippocampal regions. No associations with cortical volume were found in Parkinson's disease. Results are consistent with core social deficits in behavioural variant frontotemporal dementia, subtle disruptions in ongoing feedback-mechanisms and social processes in Parkinson's disease and generalized learning alterations in Alzheimer's disease. This multimodal approach highlights the impact of different neurodegenerative profiles on learning and social feedback. Our findings inform a promising theoretical and clinical agenda in the fields of social learning, socially reinforced learning and neurodegeneration.
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
Multimodal Neurocognitive Markers of Naturalistic Discourse Typify Diverse Neurodegenerative Diseases
(2022) Birba, Agustina; Fittipaldi, Sol; Cediel Escobar, Judith C.; Gonzalez Campo, Cecilia; Legaz, Agustina; Galiani, Agostina; Díaz Rivera, Mariano N.; Martorell Caro, Miquel; Alifano, Florencia; Piña-Escudero, Stefanie D.; Cardona, Juan Felipe; Neely, Alejandra; Forno, Gonzalo; Carpinella , Mariela; Slachevsky Chonchol, Andrea; Serrano, Cecilia; Sedeño, Lucas; Ibáñez, Agustín; García, Adolfo M.
Neurodegeneration has multiscalar impacts, including behavioral, neuroanatomical, and neurofunctional disruptions. Can disease-differential alterations be captured across such dimensions using naturalistic stimuli? To address this question, we assessed comprehension of four naturalistic stories, highlighting action, nonaction, social, and nonsocial events, in Parkinson's disease (PD) and behavioral variant frontotemporal dementia (bvFTD) relative to Alzheimer's disease patients and healthy controls. Text-specific correlates were evaluated via voxel-based morphometry, spatial (fMRI), and temporal (hd-EEG) functional connectivity. PD patients presented action-text deficits related to the volume of action-observation regions, connectivity across motor-related and multimodal-semantic hubs, and frontal hd-EEG hypoconnectivity. BvFTD patients exhibited social-text deficits, associated with atrophy and spatial connectivity patterns along social-network hubs, alongside right frontotemporal hd-EEG hypoconnectivity. Alzheimer's disease patients showed impairments in all stories, widespread atrophy and spatial connectivity patterns, and heightened occipitotemporal hd-EEG connectivity. Our framework revealed disease-specific signatures across behavioral, neuroanatomical, and neurofunctional dimensions, highlighting the sensitivity and specificity of a single naturalistic task. This investigation opens a translational agenda combining ecological approaches and multimodal cognitive neuroscience for the study of neurodegeneration.