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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.

Limited knowledge on dementia biomarkers in Latin American and Caribbean (LAC) countries remains a serious barrier. Here, we reported a survey to explore the ongoing work, needs, interests, potential barriers, and opportunities for future studies related to biomarkers. The results show that neuroimaging is the most used biomarker (73%), followed by genetic studies (40%), peripheral fluids biomarkers (31%), and cerebrospinal fluid biomarkers (29%). Regarding barriers in LAC, lack of funding appears to undermine the implementation of biomarkers in clinical or research settings, followed by insufficient infrastructure and training. The survey revealed that despite the above barriers, 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 allowed us to propose an action plan that addresses the recommendations for a biomarker framework recently proposed by regional experts.

BackgroundGlobal 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.MethodsThis 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).FindingsA 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.InterpretationResults 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.FundingThis 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.

Latin American and Caribbean countries face complex challenges to improve brain health and reduce the impact of dementia. Regional hubs devoted to research, capacity building, implementation science, and education are critically needed. The Latin American Brain Health Institute represent an important step to address many of these needs.

Objective.The differential diagnosis of behavioral variant frontotemporal dementia (bvFTD) and Alzheimers 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.

The prevalence of dementia in Latin America and the Caribbean is growing rapidly, increasing the burden placed on caregivers. Exacerbated by fragile health-care systems, unstable economies, and extensive inequalities, caregiver burden in this region is among the highest in the world. We reviewed the major challenges to caregiving in Latin America and the Caribbean, and we propose regional and coordinated actions to drive future change. Current challenges include the scarcity of formal long-term care, socioeconomic and social determinants of health disparities, gender-biased burdens, growing dementia prevalence, and the effect of the current COVID-19 pandemic on families affected by dementia. Firstly, we propose local and regional short-term strategic recommendations, including systematic identification of specific caregiver needs, testing of evidence-based local interventions, contextual adaptation of strategies to different settings and cultures, countering gender bias, strengthening community support, provision of basic technology, and better use of available information and communications technology. Additionally, we propose brain health diplomacy (ie, global actions aimed to overcome the systemic challenges to brain health by bridging disciplines and sectors) and convergence science as frameworks for long-term coordinated responses, integrating tools, knowledge, and strategies to expand access to digital technology and develop collaborative models of care. Addressing the vast inequalities in dementia caregiving across Latin America and the Caribbean requires innovative, evidence-based solutions coordinated with the strengthening of public policies.

Across Latin American and Caribbean countries (LACs), the fight against dementia faces pressing challenges, such as heterogeneity, diversity, political instability, and socioeconomic disparities. These can be addressed more effectively in a collaborative setting that fosters open exchange of knowledge. In this work, the Latin American and Caribbean Consortium on Dementia (LAC-CD) proposes an agenda for integration to deliver a Knowledge to Action Framework (KtAF). First, we summarize evidence-based strategies (epidemiology, genetics, biomarkers, clinical trials, nonpharmacological interventions, networking, and translational research) and align them to current global strategies to translate regional knowledge into transformative actions. Then we characterize key sources of complexity (genetic isolates, admixture in populations, environmental factors, and barriers to effective interventions), map them to the above challenges, and provide the basic mosaics of knowledge toward a KtAF. Finally, we describe strategies supporting the knowledge creation stage that underpins the translational impact of KtAF.

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.

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 SARS-CoV-2 global pandemic will disproportionately impact countries with weak economies and vulnerable populations including people with dementia. Latin American and Caribbean countries (LACs) are burdened with unstable economic development, fragile health systems, massive economic disparities, and a high prevalence of dementia. Here, we underscore the selective impact of SARS-CoV-2 on dementia among LACs, the specific strain on health systems devoted to dementia, and the subsequent effect of increasing inequalities among those with dementia in the region. Implementation of best practices for mitigation and containment faces particularly steep challenges in LACs. Based upon our consideration of these issues, we urgently call for a coordinated action plan, including the development of inexpensive mass testing and multilevel regional coordination for dementia care and related actions. Brain health diplomacy should lead to a shared and escalated response across the region, coordinating leadership, and triangulation between governments and international multilateral networks.

IntroductionExpert knowledge is critical to fight dementia in inequitable regions like Latin American and Caribbean countries (LACs). However, the opinions of aging experts on public policies' accessibility and transmission, stigma, diagnostic manuals, data-sharing platforms, and use of behavioral insights (BIs) are not well known.MethodsWe investigated opinions among health professionals working on aging in LACs (N = 3365) with regression models including expertise-related information (public policies, BI), individual differences (work, age, academic degree), and location.ResultsExperts specified low public policy knowledge (X2  = 41.27, P

Dementia is a syndrome characterized by cognitive and neuropsychiatric symptoms associated with progressive functional decline (FD). FD is a core diagnostic criterion for dementia, setting the threshold between its prodromal stages and the full-blown disease. The operationalization of FD continues to generate a great deal of controversy. For instance, the threshold of FD for the diagnosis of dementia varies across diagnostic criteria, supporting the need for standardization of this construct. Moreover, there is a need to reconsider how we are measuring FD to set boundaries between normal aging, mild cognitive impairment, and dementia. In this paper, we propose a multidimensional framework that addresses outstanding issues in the assessment of FD: i) What activities of daily living (ADLs) are necessary to sustain an independent living in aging? ii) How to assess FD in individuals with suspected neurocognitive disorders? iii) To whom is the assessment directed? and iv) How much does FD differentiate healthy aging from mild and major neurocognitive disorders? Importantly, the To Whom Question introduces a person-centered approach that regards patients and caregivers as active agents in the assessment process of FD. Thus, once impaired ADLs have been identified, patients can indicate how significant such impairments are for them in daily life. We envisage that this new framework will guide future strategies to enhance functional assessment and treatment of patients with dementia and their caregivers. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Verbal fluency tasks are common in Alzheimer's disease (AD) assessments. Yet, standard valid response counts fail to reveal disease‐specific semantic memory patterns. Here, we leveraged automated word‐property analysis to capture neurocognitive markers of AD vis‐à‐vis behavioral variant frontotemporal dementia (bvFTD). METHODS: Patients and healthy controls completed two fluency tasks. We counted valid responses and computed each word's frequency, granularity, neighborhood, length, familiarity, and imageability. These features were used for group‐level discrimination, patient‐level identification, and correlations with executive and neural (magnetic resonanance imaging [MRI], functional MRI [fMRI], electroencephalography [EEG]) patterns. RESULTS: Valid responses revealed deficits in both disorders. Conversely, frequency, granularity, and neighborhood yielded robust group‐ and subject‐level discrimination only in AD, also predicting executive outcomes. Disease‐specific cortical thickness patterns were predicted by frequency in both disorders. Default‐mode and salience network hypoconnectivity, and EEG beta hypoconnectivity, were predicted by frequency and granularity only in AD. DISCUSSION: Word‐property analysis of fluency can boost AD characterization and diagnosis. Highlights: We report novel word‐property analyses of verbal fluency in AD and bvFTD.Standard valid response counts captured deficits and brain patterns in both groups.Specific word properties (e.g., frequency, granularity) were altered only in AD.Such properties predicted cognitive and neural (MRI, fMRI, EEG) patterns in AD.Word‐property analysis of fluency can boost AD characterization and diagnosis. [ABSTRACT FROM AUTHOR]