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The apolipoprotein E (APOE) ε4 allele represents the strongest genetic risk factor for Alzheimer's disease (AD), but its role in genetically diverse Latin American and Caribbean (LAC) populations is underexplored. We conducted a meta‐analysis of 35 studies from 11 LAC countries, encompassing 3206 patients with AD and 5515 controls. The ε4 allele demonstrated significant association with increased AD risk (odds ratio [OR] = 3.25, 95% confidence interval [2.82–3.76]), while ε3 showed lower odds (0.42, [0.37–0.48]). Homozygous ε4/ε4 carriers had elevated risk (6.84, [5.09–9.19]), and heterozygous ε3/ε4 carriers showed moderate risk (2.59, [2.31–2.91]). Country‐level analyses revealed variability, with Ecuador showing the highest OR for ε4/ε4 (13.29, [1.56–113.4]). These results confirm APOE ε4 as a major AD risk factor in LAC populations and highlight regional differences relevant to precision medicine. Highlights This study is the largest regional apolipoprotein E meta‐analysis on Alzheimer's disease (AD) risk across Latin America. The ε4 allele is associated with AD risk, but with regional variability across Latin American and Caribbean (LAC) countries. The ε3 allele showed a protective effect in LAC populations (pooled odds ratio 0.42). The ε2 allele us not associated with protection in LAC, diverging from findings in other regions. Findings underscore the need for region‐specific dementia risk estimates.

Schadenfreude—pleasure at others’ misfortunes—is a multidetermined social emotion which involves reward processing, mentalising and perspective-taking abilities. Patients with Huntington’s disease (HD) exhibit reductions of this experience, suggesting a role of striatal degeneration in such impairment. However, no study has directly assessed the relationship between regional brain atrophy in HD and reduced schadenfreude. Here, we assessed whether grey matter (GM) atrophy in patients with HD correlates with ratings of schadenfreude. First, we compared the performance of 20 patients with HD and 23 controls on an experimental task designed to trigger schadenfreude and envy (another social emotion acting as a control condition). Second, we compared GM volume between groups. Third, we examined brain regions where atrophy might be associated with specific impairments in the patients. While both groups showed similar ratings of envy, patients with HD reported lower schadenfreude. The latter pattern was related to atrophy in regions of the reward system (ventral striatum) and the mentalising network (precuneus and superior parietal lobule). Our results shed light on the intertwining of reward and socioemotional processes in schadenfreude, while offering novel evidence about their neural correlates.

Background Behavioral variant frontotemporal dementia (bvFTD) has been related to different genetic factors. Identifying multimodal phenotypic heterogeneity triggered by various genetic influences is critical for improving diagnosis, prognosis, and treatments. However, the specific impact of different genetic levels (mutations vs. risk variants vs. sporadic presentations) on clinical and neurocognitive phenotypes is not entirely understood, specially in patites from underrepresented regions such as Colombia. Methods Here, in a multiple single cases study, we provide systematic comparisons regarding cognitive, neuropsychiatric, brain atrophy, and gene expression-atrophy overlap in a novel cohort of FTD patients ( n  = 42) from Colombia with different genetic levels, including patients with known genetic influences (G-FTD) such as those with genetic mutations (GR1) in particular genes (MAPT, TARDBP, and TREM2); patients with risk variants (GR2) in genes associated with FTD (tau Haplotypes H1 and H2 and APOE variants including ε2, ε3, ε4); and sporadic FTD patients (S-FTD (GR3)). Results We found that patients from GR1 and GR2 exhibited earlier disease onset, pervasive cognitive impairments (cognitive screening, executive functioning, ToM), and increased brain atrophy (prefrontal areas, cingulated cortices, basal ganglia, and inferior temporal gyrus) than S-FTD patients (GR3). No differences in disease duration were observed across groups. Additionally, significant neuropsychiatric symptoms were observed in the GR1. The GR1 also presented more clinical and neurocognitive compromise than GR2 patients; these groups, however, did not display differences in disease onset or duration. APOE and tau patients showed more neuropsychiatric symptoms and primary atrophy in parietal and temporal cortices than GR1 patients. The gene-atrophy overlap analysis revealed atrophy in regions with specific genetic overexpression in all G-FTD patients. A differential family presentation did not explain the results. Conclusions Our results support the existence of genetic levels affecting the clinical, neurocognitive, and, to a lesser extent, neuropsychiatric presentation of bvFTD in the present underrepresented sample. These results support tailored assessments characterization based on the parallels of genetic levels and neurocognitive profiles in bvFTD. Highlights • Different genetic levels in underrepresented FTD patients are not well understood. • We compared cognition, neuropsychiatry, and gene-atrophy overlap in FTD cases. • Mutations (MAPT-TARDBP-TREM2), variants (tau-APOE) & sporadic cases were compared. • FTD genetic level was linked to clinical & neurocognitive changes in case analysis. • Mutations showed more impairments than risk variants and sporadic presentations.

: To study the extent to which neuropsychiatric symptoms (NPS) influence the cognitive and functional decline in frontotemporal degeneration (FTD) and Alzheimer's disease (AD). : We assessed the progression of NPS and their influence on cognitive and functional progression in a group of FTD ( = 36) and AD patients ( = 47) at two different stages of the disease (2.5 years). A standardized scale was used to assess NPS-the Columbia University Scale for Psychopathology in Alzheimer's Disease (CUSPAD)-which tracks different symptoms including depression, psychotic symptoms, as well as sleep and conduct problems. In addition, in a subsample of patients (AD = 14 and FTD = 14), we analyzed another group of NPS by using the Neuropsychiatric Inventory (NPI). Cognitive declines were tracked by using the Montreal Cognitive Assessment (MoCA) and the Mini-Mental State Examination (MMSE), while functionality was tracked by using the Lawton scale and the Barthel Index. : The presence of NPS impacts cognitive and functional decline in both groups of patients 2.5 years after disease onset. However, we observed a dissociable profile of the affectation of NPS in each group. In the AD group, results indicate that the progression of depressive symptoms and sleep problems predict cognitive and functional decline. In contrast, the progression of a mixed group of NPS, including conduct problems and delusions, predicts cognitive and functional decline in FTD. : The presence of NPS has a critical impact on the prediction of cognitive decline in FTD and AD patients after 2.5 years of disease progression. Our results demonstrate the importance of assessing different types of NPS in neurodegenerative disorders which, in turn, predict disease progression. Future studies should assess the role of NPS in predicting different neurocognitive pathways and in neurodegeneration.

Background Structural income inequality – the uneven income distribution across regions or countries – could affect brain structure and function, beyond individual differences. However, the impact of structural income inequality on the brain dynamics and the roles of demographics and cognition in these associations remains unexplored. Methods Here, we assessed the impact of structural income inequality, as measured by the Gini coefficient on multiple EEG metrics, while considering the subject‐level effects of demographic (age, sex, education) and cognitive factors. Resting‐state EEG signals were collected from a diverse sample (countries = 10; healthy individuals = 1394 from Argentina, Brazil, Colombia, Chile, Cuba, Greece, Ireland, Italy, Turkey and United Kingdom). Complexity (fractal dimension, permutation entropy, Wiener entropy, spectral structure variability), power spectral and aperiodic components (1/f slope, knee, offset), as well as graph‐theoretic measures were analysed. Findings Despite variability in samples, data collection methods, and EEG acquisition parameters, structural inequality systematically predicted electrophysiological brain dynamics, proving to be a more crucial determinant of brain dynamics than individual‐level factors. Complexity and aperiodic activity metrics captured better the effects of structural inequality on brain function. Following inequality, age and cognition emerged as the most influential predictors. The overall results provided convergent multimodal metrics of biologic embedding of structural income inequality characterised by less complex signals, increased random asynchronous neural activity, and reduced alpha and beta power, particularly over temporoposterior regions. Conclusion These findings might challenge conventional neuroscience approaches that tend to overemphasise the influence of individual‐level factors, while neglecting structural factors. Results pave the way for neuroscience‐informed public policies aimed at tackling structural inequalities in diverse populations. We analysed EEG data from 1394 participants across 10 countries, using the Gini coefficient and sociodemographic variables to predict EEG metrics. Four categories of EEG metrics were computed: complexity, aperiodic spectral components, power spectrum, and connectivity. ROC curves, feature importance rankings, and topographical brain region information were reported. Structural income inequality consistently predicts EEG metrics, surpassing individual demographic factors.

Chronic pain (CP) is a global public health issue and a critical factor in the aging process. Chile, as one of the most aged countries in Latin America, presents a unique context for exploring CP and its associated factors. Despite its significance in aging, previous studies in the region often fail to comprehensively address key variables such as age, income, mood, mobility, diet, and cognitive skills, nor do they systematically investigate the relationship between CP and cognitive impairment. This study presents a comprehensive analysis of CP prevalence, related sociodemographic and health variables, and its link to cognitive impairment, using representative data of the Chilean population 15 years and older from the 2009-2010 and 2016

Frontostriatal disorders, such as Parkinson’s disease (PD), are characterized by progressive disruption of cortico-subcortical dopaminergic loops involved in diverse higher-order domains, including language. Indeed, syntactic and emotional language tasks have emerged as potential biomarkers of frontostriatal disturbances. However, relevant studies and models have typically considered these linguistic dimensions in isolation, overlooking the potential advantages of targeting multidimensional markers. Here, we examined whether patient classification can be improved through the joint assessment of both dimensions using sentential stimuli. We evaluated 31 early PD patients and 24 healthy controls via two syntactic measures (functional-role assignment, parsing of long-distance dependencies) and a verbal task tapping social emotions (envy, Schadenfreude ) and compared their classification accuracy when analyzed in isolation and in combination. Complementarily, we replicated our approach to discriminate between patients on and off medication. Results showed that specific measures of each dimension were selectively impaired in PD. In particular, joint analysis of outcomes in functional-role assignment and Schadenfreude improved the classification accuracy of patients and controls, irrespective of their overall cognitive and affective state. These results suggest that multidimensional linguistic assessments may better capture the complexity and multi-functional impact of frontostriatal disruptions, highlighting their potential contributions in the ongoing quest for sensitive markers of PD.

Timely diagnosis of behavioral variant frontotemporal dementia (bvFTD) remains challenging because it depends on clinical expertise and potentially ambiguous diagnostic guidelines. Recent recommendations highlight the role of multimodal neuroimaging and machine learning methods as complementary tools to address this problem. We developed an automatic, cross-center, multimodal computational approach for robust classification of patients with bvFTD and healthy controls. We analyzed structural magnetic resonance imaging and resting-state functional connectivity from 44 patients with bvFTD and 60 healthy controls (across three imaging centers with different acquisition protocols) using a fully automated processing pipeline, including site normalization, native space feature extraction, and a random forest classifier. Our method successfully combined multimodal imaging information with high accuracy (91%), sensitivity (83.7%), and specificity (96.6%). This multimodal approach enhanced the system's performance and provided a clinically informative method for neuroimaging analysis. This underscores the relevance of combining multimodal imaging and machine learning as a gold standard for dementia diagnosis. •A multimodal computational approach was implemented to identify patients with bvFTD.•We combined features from structural MRI data and fMRI-based functional connectivity.•Our approach was validated over 103 subjects from three different centers.•Our multimodal approach yielded high classification accuracy (91%) across centers.•Multimodal computational approaches may be useful complements for dementia diagnosis.

: Adolescent offenders (AOs) are characterized by social-norm transgression and aggressive behaviors. Those traits have been associated with alterations in socio-cognitive processes, including facial emotion recognition. While this would suggest that AOs tend to interpret negative emotional cues as threatening information, most research has relied on context-free stimuli, thus failing to directly track integrative processes typical of everyday cognition. : In this study, we assessed the impact of body language and surrounding context on facial emotion recognition in AOs and non-offenders (NOs). We recruited 35 AOs from a reform school for young male offenders and 30 NOs matched for age and sex with the former group. All participants completed a well-validated task aimed to determine how contextual cues (i.e., emotional body language and surrounding context) influence facial emotion recognition through the use of congruent and incongruent combinations of facial and bodily emotional information. : This study showed that AOs tend to overvalue bodily and contextual signals in emotion recognition, with poorer facial-emotion categorization and increased sensitivity to context information in incongruent face-body scenarios. This pattern was associated with executive dysfunctions and disruptive behaviors, as well as with gray matter (GM) of brain regions supporting body-face recognition [fusiform gyrus (FG)], emotion processing [cingulate cortex (CC), superior temporal gyrus (STG)], contextual integration (precuneus, STG), and motor resonance [cerebellum, supplementary motor area (SMA)]. : Together, our results pave the way for a better understanding of the neurocognitive association between contextual emotion recognition, behavioral regulation, cognitive control, and externalized behaviors in AOs.