Adolfo Ibáñez University

This paper tests the granular hypothesis introduced by Gabaix (2011. “The Granular Origins of Aggregate Fluctuations.” Econometrica 79 (3): 733–72) in the US, Germany, Canada, France, Japan, and the UK. We find that firm-level idiosyncratic shocks significantly impact aggregate fluctuations in only three of the six countries analyzed. Compared to the US, Japan and Germany, the UK, France, and Canada show greater granularity, but also a negligible firm-level contribution to aggregate volatility. Additional results look at the role of the transportation sector as a potential driver of granular effects in the US, Germany and Japan.

The discovery of resting state networks shifted the focus from the role of local regions in cognitive tasks to the ongoing spontaneous dynamics in global networks. Recently, efforts have been invested to reduce the complexity of brain activity recordings through the application of nonlinear dimensionality reduction algorithms. Here, we investigate how the interaction between these networks emerges as an organising principle in human cognition. We combine deep variational auto-encoders with computational modelling to construct a dynamical model of brain networks fitted to the whole-brain dynamics measured with functional magnetic resonance imaging (fMRI). Crucially, this allows us to infer the interaction between these networks in resting state and 7 different cognitive tasks by determining the effective functional connectivity between networks. We found a high flexible reconfiguration of task-driven network interaction patterns and we demonstrate that can be used to classify different cognitive tasks. Importantly, compared to using all the nodes in a parcellation, we obtain better results by modelling the dynamics of interacting networks in both model and classification performance. These findings show the key causal role of manifolds as a fundamental organising principle of brain function, providing evidence that interacting networks are the computational engines brain during cognitive tasks.

Nitrogen contamination of water sources poses significant environmental and health risks. The sulfur-driven simultaneous nitrification and autotrophic denitrification (SNAD) process offers a cost-effective solution, as it operates in a single reactor, requires no organic carbon addition, and produces minimal sludge. However, this process remains underexplored, with microbial population dynamics, their interactions, and their implications for process efficiency not yet fully understood. To address this gap, this study analyzed microbial populations in a 0.8 L fluidized bed reactor performing sulfur-driven SNAD under increasing nitrogen loading rates (NLR), ranging from 11 to 105 g N/m3 d. The process achieved 93.5 % total nitrogen and 95.1 % ammonium removal at a hydraulic residence time (HRT) of 1.8 days. However, when the HRT was reduced to 0.96 days, nitrate removal instability occurred, reducing the nitrate removal efficiency to 42 %. Although increasing the HRT improved performance, two additional instability events were observed in subsequent stages at HRTs of 1.2 and 1.03 days, where nitrate removal efficiencies dropped to 11 % and 39 %, respectively. Functional analysis showed that NLR negatively impacted the proportion of sulfur-oxidizing bacteria, which was correlated with high nitrate levels in the effluent, although ammonium oxidation remained stable. Ecological network analysis revealed positive interactions between ammonia-oxidizing and heterotrophic bacteria, supporting nitrification stability. However, it also uncovered negative interactions between heterotrophic bacteria and sulfur-oxidizing denitrifiers, such as Dyella and Thiobacillus, suggesting these negative interactions contributed to temporary nitrogen removal problems in the system. This study highlights the importance of functional microbial and ecological network analyses over traditional metataxonomic approaches in understanding SNAD processes.

Background Socioeconomic disparities (SED) influence brain health and dementia. Latin America (LA) is characterized by high SED and a disproportionate prevalence of Alzheimer’s disease (AD) and frontotemporal lobe degeneration (FTLD) compared to high‐income populations like the United States (US). However, the impact of SED on brain reserve across neurocognitive pathways related to aging and dementia in LA remains unknown. Method We evaluated how SED impact brain volume and functional connectivity in participants with AD, FTLD, and controls from LA (Argentina, Chile, Colombia, Mexico, Peru) and US, triangulating three SED measures: (i) educational attainment (n = 1410), (ii) cross‐culturally harmonized social determinants of health (SDH; n = 2324), and (iii) structural inequality (GINI index; n = 2135). Data were obtained from the Multi‐Partner Consortium to Expand Dementia Research in Latin America [ReDLat], the Alzheimer’s Disease Neuroimaging Initiative [ADNI], and the Laboratory of Neuro Imaging [LONI]. We controlled for multiple potential confounders (e.g., scanner, TIV, age, sex). Result Across the three studies, SED was associated with impaired neurocognitive outcomes, especially in LA compared to the US. (i) Lower educational attainment was associated with reduced fronto‐temporo‐posterior brain volume and connectivity across all LA groups (Fig 1; multiple regressions and kruskall‐wallis comparisons, P<0.05 TFCE correction). (ii) Adverse SDH including childhood SDH, discriminated between controls, AD, and FTLD in LA, affecting patients’ cognition, severity, and functionality (Fig 2A‐B; XGBoost binary logistic regression). Also, adverse SDH induced reduced volume and connectivity (VBM and whole‐brain analysis, both P‐FDR<0.05) across LA groups (Fig 2C). Finally, (iii) Higher structural income inequality at both the state/country levels was associated with reduced volume and connectivity in the temporo‐parietal, cingulum‐limbic, and cerebellar regions, with more pronounced effects in LA groups (Fig 3; multiple regressions with grey matter volume [w‐maps, P‐FWE<0.05] and connectivity [wSDM coefficients, P‐Bonf<0.05]). Conclusion Findings suggest that exacerbated SED, observed in more diverse samples from LA, differentially and negatively impact neurocognitive factors in aging and dementia. This aligns with the notion that SED diminish brain and cognitive reserve, amplifying dementia burden. Tailored, local‐sensitive models are required to leverage the impact of SED in brain health and dementia, particularly in underrepresented populations like LA.

Background Chronic pain (CP) is defined as the persistence of pain beyond the expected recovery period of an injury, or alternatively, with a duration exceeding three months. It has been recognized as a risk factor for dementia in European and North American cohorts. However, in Latin America (LA), there remains a significant gap in understanding CP prevalence, its risk factors, and its association with Alzheimer’s disease (AD) and frontotemporal dementia (FTD). Our study aims to shed light on the impact of CP on the LA population, along with its implications for AD and FTD. Method We analyzed data from the National Health Survey (NHS) conducted in Chile in 2009‐2010 and 2016‐2017. This study comprised 2179 subjects from the 2009‐2010 survey and 1447 subjects from the 2016‐2017 survey. Additionally, we assessed CP in LA patients with dementia (AD and FTD) using a concise 6‐question survey, which evaluated the presence, duration, frequency, location, and intensity of pain. Our patients are from Chile, Peru, Argentina, and Colombia, all of whom actively participate in the Multicenter Consortium to Expand Dementia Research in Latin America (ReDLat). Result Our analysis revealed from the Chilean NHS that the prevalence of CP increased by approximately 30% across both surveys among individuals aged 20 to 70. Key factors associated with CP in the Chilean population include reduced mobility, anxiety, depression, malnutrition, socioeconomic disadvantage, and lower educational attainment. The results also suggest an association between CP and the presence of dementia in the Chilean population that warrants further detailed investigation. In the analysis of the ReDLat cohort, we observed that patients with AD report experiencing CP at a higher proportion (53.6%) than patients with FTD (31.3%) and control subjects (34.8%). Conclusion This study highlights the substantial impact of CP on the LA population, particularly in AD patients. To our knowledge, this is the first study in LA to investigate the prevalence and risk factors associated with CP. Additionally, our findings suggest that CP is associated with the pathology of dementia, emphasizing the critical need for further research in this area.

Background Commissural tracts are the white matter fibre bundles intercommunicating left and right brain hemispheres. They integrate many cognitive functions such as memory, verbal processing, motor and perceptual skills. Also, commissures connect specific layers of cortical neurons that are also lost in Alzheimer’s disease (AD) and other neurodegenerative disorders. Although highly heritable, commissures´ specific genetic determinants remain obscure. We aim to investigate the genetic determinants of the human anterior commissure. Given its presumed role in neurodegeneration, we aim to further provide mechanistic insights into neurological conditions that may result from its dysfunction. Method Two‐stage genome‐wide association study, (GWAS) (N=18,828) of the size of the anterior commissure. The discovery sample included seven cohorts (N=7,935) and was meta‐analyzed with ten replication cohorts (N=10,893). The size of the anterior commissure was manually derived from magnetic resonance imaging (1.5T/3T) with at least T1/T2‐weighted sequences. The genetic data was assessed through genotyping using SNP microarrays. We used voxel‐based morphometry to determine which regions are connected by the anterior commissure. To prove a functional validation of the identified variants, we performed a series of in silico experiments, including the study of the spatial expression patterns in human brains, quantitative trait loci (QTL), enrichment analysis and pleiotropy with neurodegenerative diseases. Result we identified six independent variants at four loci (p‐values from 4.1x10‐8 to 9.4x10‐22). We mapped the loci to probable causal genes involved in axon guidance (EPHA3 and SEMA6A), cognitive disorders (CTNND2), and growth factor signaling (RIT2). Voxel‐based morphometry revealed distinct associations of the variants with connected grey matter regions in the brain. We found enrichment for H3K4me1 peaks (marking enhancer sites), introns, and conserved sequences, as well as cell‐type‐specific annotations from the central nervous system and cardiovascular system. Furthermore, we identified pleiotropy between genes known to increase risk of neurodegenerative conditions including frontotemporal lobar degeneration gene TMEM106B. Variants associated to this gene have been related to dementia development. Conclusion these results shed light on the genetic architecture of commissural tracts and establish the size of the anterior commissure as a relevant biomarker of neurodegeneration.

Background The human brain integrity relies on the synergistic interplay between neural activity and supporting vascular and metabolic processes throughout life. This relationship, ruled by allostatic mechanisms, regulates brain architecture and activity. White matter hyperintensities (WMH) serve as indicators of the vascular impact on brain structure. While the strong association between vascular/metabolic systems and brain structure/function is established, the precise mechanisms linking allostasis to WMH remain elusive. We hypothesized that allostasis influences white matter through neuroinflammatory mechanisms, and WMH mediate neuroinflammatory effects on EEG measures. Method To test this hypothesis we conducted a comprehensive analysis on MRI, EEG, and multisystemic data from 196 subjects (20 to 75 years, 69 females) sourced from the LEMON database in Leipzig, Germany. Using the lesion segmentation tool (LST) on SPM12, we automatically identified WMH in fluid‐attenuated inversion recovery (FLAIR) images. FastSurfer was employed to determine the volumes of the bilateral hippocampus (HV) and lateral ventricles (VV), representing proxies for neurodegenerative and neuroinflammatory processes, respectively. Volumetric corrections were applied using total intracranial volume. Furthermore, a regression analysis was conducted to discern and subtract the shared contributions of VH and VV on each other. EEG data underwent spectral analysis for oscillatory (alpha waves) and aperiodic (1/f) components using NeuroDSP and FOOOF, respectively. An allostatic load index (ALI), incorporating lipid profile, inflammation, metabolic factors, and blood pressure, was computed. All measures were age, sex, and education level‐corrected. Result We found age differences in every metric of interest, but importantly just ALI, VV and 1/f correlated with WMH number and those effects survived age correction (Figure 1 A and B). VV, but not HV mediates the relationship between ALI and WMH. Also, WMH completely mediate the effects of neuroinflammation over the 1/f (Figure 1 C). Conclusion Our findings reveal that allostasis affects white matter through neuroinflammatory pathways, with WMH serving as crucial mediators of neuroinflammatory impact on EEG measures. This research provides key insights into the intricate interplay of vascular and metabolic factors with brain structure. Identified relationships and mediators open avenues for targeted interventions and personalized treatments in neurodegenerative and neuroinflammatory conditions.

Background It is estimated that at least two‐thirds of the world lacks access to neuroimaging, including Magnetic Resonance Imaging (MRI). Yet neuroimaging is one of the most informative tools for neuroscience, potentially biasing advances toward populations with access to this technology. This is evident in Alzheimer’s disease (AD) research, where genetics and environment play important roles in disease development and treatment. Recent advances in low field MRI (LFMRI) have demonstrated the utility of this affordable and portable technology, despite lower image quality. Of the existing technologies, the OSII ONE developed by the open‐source imaging initiative is the only device that has been reproduced in low resource settings using primarily local resources. Here we highlight two pilot studies in Uganda and Paraguay to build and sustain OSII ONE devices for neuroimaging studies. We present preliminary results regarding construction, sustainability, and image processing for use in AD and offer suggestions for its inclusion as a tool to increase access to neuroimaging in low‐resource populations. Method An OSII ONE system was reproduced in Uganda and Paraguay. In Uganda, all system components were importanted and local human resource guided by international experts was used to complete the build. In Paraguay, only key physical components not available locally were imported and all available local components (including exclusively local human resources) were used for construction. Result While the Uganda build was completed more quickly (11 days in Uganda, 6 months in Paraguay), quality was maintained across sites despite difference in personnel and the use of local components in Paraguay. Both projects are maintained locally and current image processing methods could provide adequate quality for brain analysis in AD. Conclusion We show the feasibility LFMRI in lower resource settings. Despite the reduction in image quality, valuable structural information can be obtained, extending access to rural populations. This has significant implications for the future of AD imaging in global settings especially considering recent approval of disease modifying therapies that require safety monitoring with MRI. Future work collecting paired LFMRI and conventional MRI with AD patients in South America will further demonstrate the utility of this technology in the field.

Background Previous studies on sex differences in amyloid burden have shown inconsistent findings. We examined the effect of sex on amyloid‐PET outcomes in a large, real‐world, cohort of individuals with cognitive impairment. Method The IDEAS study evaluated the clinical utility of amyloid‐PET in 18,295 Medicare beneficiaries age ≥65 years with MCI or dementia. All scans were visually interpreted as positive or negative at each site by a local radiologist or nuclear medicine physician. A subset of 10,361 scans were centrally processed and quantified in Centiloids. We used multivariate logistic regression to calculate odds ratios of amyloid‐PET positivity (based on visual read) for males and females, adjusting for demographic and clinical risk factors. We used linear regression to assess the association between sex and amyloid burden quantified in Centiloids. Result Of 10,361 included individuals, 51% were females. Compared to males, females were slightly younger (75 versus 76 median age, p=0.008) and had higher rates of dementia (39.3% versus 35.2%, p<0.001). Rates of vascular risk factors were significantly higher in males than females, whereas females had significantly higher rates of history of depression and family history of AD. Females had higher rates of amyloid‐PET positivity than males (63% versus 59%, p<.001) and higher Centiloid values (median=48.7 versus 36.9, p<.01); see Figure 1 and Table 1 model 1. Sex differences remained significant in models adjusted for demographics and clinical risk factors (Table 1, models 2‐3). In an analysis that included only individuals with visually positive amyloid‐PET, females exhibited higher Centiloid values than males (Table 1 multivariable linear models). In amyloid‐positive individuals, we found a significant interaction between sex and age, with greatest sex differences in amyloid burden found in the youngest females (Figure 2A). We also found a significant interaction between sex and race, with greatest differences found in Black females vs. males (Figure 2B). Conclusion Females with cognitive impairment exhibited a higher frequency of amyloid‐PET positivity and higher amyloid burden. Our findings shed light on sex‐specific biological and potential sociocultural differences in Alzheimer's disease pathology.

Background Commissural tracts are the white matter fibre bundles intercommunicating left and right brain hemispheres. They integrate many cognitive functions such as memory, verbal processing, motor and perceptual skills. Also, commissures connect specific layers of cortical neurons that are also lost in Alzheimer’s disease (AD) and other neurodegenerative disorders. Although highly heritable, commissures´ specific genetic determinants remain obscure. We aim to investigate the genetic determinants of the human anterior commissure. Given its presumed role in neurodegeneration, we aim to further provide mechanistic insights into neurological conditions that may result from its dysfunction. Method Two‐stage genome‐wide association study, (GWAS) (N=18,828) of the size of the anterior commissure. The discovery sample included seven cohorts (N=7,935) and was meta‐analyzed with ten replication cohorts (N=10,893). The size of the anterior commissure was manually derived from magnetic resonance imaging (1.5T/3T) with at least T1/T2‐weighted sequences. The genetic data was assessed through genotyping using SNP microarrays. We used voxel‐based morphometry to determine which regions are connected by the anterior commissure. To prove a functional validation of the identified variants, we performed a series of in silico experiments, including the study of the spatial expression patterns in human brains, quantitative trait loci (QTL), enrichment analysis and pleiotropy with neurodegenerative diseases. Result we identified six independent variants at four loci (p‐values from 4.1x10‐8 to 9.4x10‐22). We mapped the loci to probable causal genes involved in axon guidance (EPHA3 and SEMA6A), cognitive disorders (CTNND2), and growth factor signaling (RIT2). Voxel‐based morphometry revealed distinct associations of the variants with connected grey matter regions in the brain. We found enrichment for H3K4me1 peaks (marking enhancer sites), introns, and conserved sequences, as well as cell‐type‐specific annotations from the central nervous system and cardiovascular system. Furthermore, we identified pleiotropy between genes known to increase risk of neurodegenerative conditions including frontotemporal lobar degeneration gene TMEM106B. Variants associated to this gene have been related to dementia development. Conclusion these results shed light on the genetic architecture of commissural tracts and establish the size of the anterior commissure as a relevant biomarker of neurodegeneration.

Background Verbal fluency tasks are routinely employed in screening for mild cognitive impairment (MCI). Yet, traditional outcome measures focus on the number of valid responses, failing to reveal which specific semantic memory dimensions may be altered and limiting analyses to univariate methods. Building on recent findings on Alzheimer’s disease, we employed automated methods to establish which linguistic and speech timing features better discriminate MCI patients from healthy controls (HCs), including machine learning analyses, comparisons with standard neuropsychological tests, and brain‐behavior correlations. Method We recruited 106 native Spanish speakers (52 with MCI, 54 HCs), who completed phonemic and semantic fluency tasks as well as standard tests of attention (Trail Making Test‐A) and episodic memory (Free and Cued Selective Reminding Test). Responses in the fluency tasks were audio‐recorded and transcribed for automatic extraction of word properties (granularity, frequency, phonological neighborhood, word length, imageability, familiarity) and speech timing features (number of syllables, pauses, pause duration, phonation time, articulation rate, average syllable duration). These variables were compared between groups through a generalized linear model (GLM, with standard cognitive test scores as covariates) and fed into a binary classifier for subject‐level discrimination. Structural and functional brain measures were obtained from 63 participants and subjected to voxel‐based morphometry and seed‐to‐voxel resting‐state connectivity analyses. Correlations between behavioral and brain features were examined via multiple regressions. Result GLM analysis revealed significant group differences in specific word properties (granularity, frequency, word length, imageability), but not in speech timing features. Subject‐level classification was better when based on word properties (AUC = 0.72) than on speech timing features (AUC = 0.63), with maximal discrimination upon combining both dimensions (AUC = 0.78). MCI patients exhibited atrophy left temporal atrophy and altered connectivity between the right parahippocampus and fronto‐posterior cortical regions. Word frequency was negatively correlated with insular volume and granularity was positively correlated with the volume of fusiform and parahippocampal regions. Conclusion Automated analyses of word properties and timing features in verbal fluency tasks offer novel insights into cognitive decline, surpassing traditional tests in identifying MCI. Their widespread implementation could inaugurate a promising avenue to establish scalable markers of the condition.

Background The content of circulating exosomes has been observed to be altered in response to changes in physiological and pathological conditions, and they are detectable in different human fluids such as blood. Studies focused on the quantification of Aβ and tau proteins, as molecules contained within exosomes, suggest that they are related with Alzheimer disease (AD) and frontotemporal dementia (FTD) development, demonstrated that plasma‐derived exosome analysis is a good approach for searching for biomarkers in the development of dementia. Our aim is to identify new blood biomarkers to detect the AD or FTD in the Chilean population using machine learning based on exosomal miRNAs. Method miRNAs were extracted from circulating exosomes from plasma samples of 25 healthy controls (HC), 25 AD patients and 10 FTD patients. miRNAs were sequencing to identify and measure the expression levels. Dysregulated miRNAs were analyzed to create machine learning algorithms. miRNAs obtained from algorithms were validated in a new population of subjects 30 HC, 30 AD and 10 FTD using qRT‐PCR. Result After the sequencing and machine learning analysis, we identified 8 miRNAs as potential predictors of AD and FTD. These miRNAs were further assessed in new samples using the qRT‐PCR technique. We identified 4 miRNAs with variable expression in patients with AD and FTD, with three miRNAs downregulated in AD and one upregulated in FTD. For the four miRNAs, significant differences in expression are observed between AD and FTD. Conclusion This is the first study in the Chilean population that evaluates miRNAs in patients with AD and FTD. The study of miRNAs as biomarkers of dementia provides the opportunity to develop low‐cost and easy‐to‐obtain diagnostic methods, in addition to the possibility of being implemented in a greater number of health centers, making them more accessible to the population.

Background Predicting Alzheimer's disease (AD) and frontotemporal dementia (FTD) using polygenic risk scores (PRS) for late‐onset forms holds promise, but its accuracy might be influenced by social determinants of health (SDOH). This study explores how considering SDOH alongside genes can improve prediction, focusing on potential differences for each disease. Methods Employing logistic regression in 677 individuals (287 AD, 102 FTD, and 288 controls) aged 40‐80 from the ReDLat study across six Latin American countries, we investigated the potential for SDOH to modify the association between PRS and susceptibility to AD and FTD. Analyses were adjusted for a probabilistic score derived from models comparing disease groups to controls with SDOH data (education, occupation, economic stability, healthcare access and quality, and social context) and APOE ε4 carrier status to account for confounding effects. Results Although univariate association tests revealed robust links between PRS and both diseases, adjusted models presented a nuanced picture. In AD, the SDOH score and APOE ε4 carrier status significantly attenuated the PRS effect (p=0.14), suggesting these factors modify genetic risk. In FTD, however, SDOH did not influence the PRS contribution. These findings highlight the potentially distinct roles of social factors in different neurodegenerative pathways. Conclusion The significant modification of PRS effects in AD by SDOH and APOE ε4 underscores the need for comprehensive approaches in future research and interventions in Latin America. Conversely, the unaltered PRS contribution in FTD emphasizes distinct intricacies in gene‐environment interactions. These findings necessitate considering both realms in future efforts, paving the way for targeted strategies in AD and FTD prevention and treatment.

Background Dementia, encompassing Alzheimer's disease (AD) and frontotemporal dementia (FTD), poses a substantial public health challenge in Latin America. Barriers such as a shortage of healthcare professionals, limited medical accessibility, and underdiagnosis contribute to the complexity. While biomarkers aligned with the ATN framework (Amyloid, Tau, Neurodegeneration) have revolutionized diagnosis, their cost limits adoption in Latin America. Existing research focuses predominantly on North American or European cohorts, leaving a significant gap for the region. Our groundbreaking study aims to investigate, for the first time, ATN‐related proteins in AD, FTD, and control subjects using blood samples from the ReDLat cohort. This research addresses critical gaps in dementia diagnosis specific to Latin America, guided by insights from the ATN framework. Method We enrolled 500 participants (AD, FTD, and healthy controls‐HC) from Argentina, Chile, Colombia, Mexico, and Peru through the Multi‐Partner Consortium to Expand Dementia Research in Latin America (ReDLat). Plasma samples were collected in EDTA tubes, aliquoted, shipped on dry ice, and stored at ‐80°C following standard methods. We assess the plasma levels of Aβ40, Aβ42, p‐tau181, and NfL across groups (AD, FTD, HC) using Lumipulse G600II from Fujirebio, an advanced automated system which detects proteins via chemiluminescence. Result Our analysis revealed a significant decrease in the Aβ1‐42/40 ratio between AD and FTD patients compared to HC. Additionally, we observed a significant increase in p‐tau181 levels in both AD and FTD patients relative to HC, with a significant difference between AD and FTD. NfL levels were significantly higher in AD and FTD patients compared to HC. Conclusion Our findings demonstrate substantial differences in Aβ1‐42/40 ratio, phosphorylated Tau, and NfL levels between AD, FTD, and control subjects. These distinct biomarker profiles hold promise for distinguishing between various forms of dementia and healthy individuals. Importantly, our study addresses the critical gap in dementia research within LA populations, offering valuable insights into the potential impact of regional factors on biomarker dynamics.

Background During the pandemic, Social Isolation (SI) and the perception of loneliness emerged as critical factors associated with significant psychological and physical impacts (Tyrrell, C. & Williams, N., 2020; González, D., 2021). This study examines gender differences and explores the impact of social isolation and the perception of loneliness on self‐sufficient older people in Santiago, Chile, in the post‐pandemic period (March to November 2022). The focus is on understanding the relationship between these factors and psychiatric symptoms, utilizing specific scales to evaluate these variables. The pandemic introduced three main variables that affected older individuals: the severity of the disease and the fear of contagion; the effects of social isolation, and the perception of vulnerability, which was amplified by the media (NCHS, 2020; CEVE‐UC, 2022; Smith, B. & Lim, M., 2020; Ayalon et al., 2020; Monahan et al., 2020; Vervaeke & Meisner, 2020). Method A descriptive cross‐sectional study included 150 participants (ages 60‐87). Surveys administered were the Steptoe Social Isolation Index, Three‐Item UCLA Loneliness Scale, Yesavage Geriatric Depression Scale (GDS‐15), current concern about the pandemic (Likert Scale, 1‐10), and gender differences in these variables. JAMOVI software version 2.36 was utilized for data processing and statistical analysis. Result From March to December 2022, 150 older adults were surveyed (Mean = 69.5, Median = 69, SD = 5.93, Variance = 35.11). The sample comprised 68% women and 32% men (Women = 102, Men = 48). Of the variables analyzed, 42% of the sample experienced Social Isolation (Chi‐square = 3.2, p = 0.696 / U = 2395.0, p = 0.825). 26% perceived Loneliness (Chi‐square = 6.10, p = 0.412 / U = 2210.0, p = 0.290), 30% indicated depression (Chi‐square = 7.94, p = 0.848 / U = 2270.0, p = 0.470), and 91% expressed concern about the pandemic (Chi‐square = 0.10, p = 1 / U = 2442, p = 0.980). Conclusion The results suggest that, although there are no significant gender differences in individual variables, there are significant correlations between all combinations of the variables (Social Isolation, Loneliness, GDS‐15, and Pandemic Concern). Among men, significant correlations were found between Social Isolation and Loneliness (rho = 0.432, p = 0.002), Loneliness and GDS‐15 (rho = 0.299, p = 0.03), and Loneliness and Age (rho = 0.381, p = 0.008). In women, all correlations were significant, except with age, between Social Isolation and Loneliness (rho = 0.419, p≤0.001), Social Isolation and GDS‐15 (rho = 0.279, p = 0.005), and Loneliness and GDS‐15 (rho = 0.474, p≤0.001).

Background In Chile, the cases of cognitive impairment and dementia are on the rise and are expected to triple by 2050. Additionally, older adults face life changes that may contribute to depression onset. We studied the relationship between cognitive impairment (CI), functional decline (FD) and depression with the risk of all‐cause and cardiovascular event mortality in the Chilean population aged ≥60 years. Method Prospective cohort study based on the Chilean National Health Survey 2009‐2010, a nationally representative prevalence study. Data on mortality status were available until 2020. We included n = 1,227 participants aged ≥60 years. A case of CI was defined as a score <13 in the abbreviated Mini‐Mental State Examination (score from 1‐19). FD in daily activities was defined as a score >6 in the Pfeffer Functional Activities Questionnaire test (score from 0‐33). Depression was defined as the presence of ≥5 depressive symptoms during the last year, assessed with the CIDI‐SF scale. Survival probabilities were obtained through Kaplan‐Meier estimators. The associations of CI, FD, and depression (independent variables) with all‐cause and cardiovascular mortality (dependent variables) were investigated using multivariate Cox proportional hazard models. Results were expressed as Hazard Ratios and 95%CI (HR; 95%CI). Result Participants were on average 71.7 years old and 60.3% were women. During the follow‐up, 431 individuals died from any cause and 107 from a cardiovascular event. Survival probabilities were lower among those with CI, FD and depression (Figure 1). CI was associated with higher risk of all‐cause and cardiovascular mortality by 60% (HR:1.60; 95%CI 1.25‐2.05) and 107% (2.07; 1.28‐3.34), respectively. FD and depression were associated with higher all‐cause mortality risk by 89% (1.89; 1.19‐3.01) and 69% (1.69; 1.25‐2.28), respectively. No significant associations were observed for FD and depression with cardiovascular mortality. Conclusion This is the first study in the Chilean elderly population to link CI, FD or depression with a higher risk of premature mortality. Public health policies aimed to preserve mental and cognitive health in this age group are warranted to promote healthy aging.

Background White matter hyperintensities (WMH) are very common brain MRI signal abnormalities linked to age, small vessel cerebrovascular disease, cognitive impairment, and dementia. Despite extensive research on WMH in Alzheimer's disease (AD), their prevalence in behavioral variant Frontotemporal dementia (bvFTD) remains less explored. Additionally, Latin American countries (LA) exhibit a higher prevalence of cerebrovascular disease due to distinct demographic, socioeconomic, cultural, and ethno‐racial factors. However, limited research on WMH exists in this context. Our aim was to characterize the WMH burden and its relationship with neurodegeneration and cognition in healthy aging and dementia subjects from LA in comparison to the United States (US). Methods This cross‐sectional multicenter study involved 638 LA and 355 US subjects from the ReDLat consortium, including healthy controls (HC), bvFTD, and AD patients. Participants underwent brain MRI and neuropsychological assessments. Voxel‐based morphometry analysis was performed to calculate WMH load and distribution from T2‐FLAIR images, and gray matter (GM) atrophy from T1 images. To assess the differences in the spatial distribution of WMH, two sample t‐tests were run between HC and neurodegenerative groups (AD and bvFTD) for each region (LA and US). The association between total load of WMH with regional GM volume and the association between cognitive performance (MMSE) with tract‐specific WMH load was tested via voxel‐wise regression analyses. In all analysis significance was set at p<0.05 family‐wise error‐corrected for multiple comparisons with a cluster extent threshold of 50 voxels. Age, years of education, sex, TIV and scanner were included as covariates of no interest. Results bvFTD exhibited higher WMH load than AD in both regions (LA and US, Figure 1). Notably, the association between WMH burden and GM atrophy was substantially stronger for all LA groups (bvFTD, AD, and HC) compared to the US (Figure 2). Additionally, an association between WMH burden and cognitive impairment (MMSE) was found in all pathological groups (Figure 3). Conclusion This study highlights regional and disease‐specific effects of WMH burden in brain atrophy and cognition, emphasizing the importance of region‐adapted dementia research for a comprehensive understanding of these disparities.

Background Dementia impacts the way individuals perceive and describe everyday events. Alzheimer's disease (AD) notably affects processing of entities manifested by nouns, while behavioral variant frontotemporal dementia (bvFTD) often presents a detached, third‐person perspective. Yet, the potential of natural language processing tools (NLP) to detect these variations in spontaneous speech remains explored. To tackle this gap, we analyzed both patterns via automated discourse‐level metrics in individuals with AD and bvFTD, contrasting them with healthy controls (HCs). Methods Persons with AD (n = 21), bvFTD (n = 21), as well as HCs (n = 21), narrated a typical day of their lives. We analyzed the frequency of nouns and verbs, along with first‐ or third‐person usage, via part‐of‐speech and morphological tagging, respectively. Inferential statistics and machine learning were used to examine whether these features were useful for discriminating patients from HCs at both the group and the subject level. We further evaluated whether such features correlated with cognitive symptom severity, as captured through the Montreal Cognitive Assessment (MoCA). Results Compared with HCs, AD (but not bvFTD) patients exhibited a lower proportion of nouns, without differences in verb ratio. Conversely, persons with bvFTD (but not those with AD) had a greater proportion of third‐person markers and a reduced proportion of first‐person markers. Machine learning analyses showed that these features robustly identified individuals within each group (AUCs = 0.75). No linguistic feature was significantly correlated with MoCA scores in either patient group. Conclusions Spontaneous daily narratives offer distinct markers for AD and bvFTD, detectable through automated analysis. Focusing on specific linguistic attributes relevant to each type of dementia not only aids in understanding but also enhances diagnosis and tracking of these conditions. Overall, our findings attest to the relevance of NLP tools as a viable, cost‐effective means to identify scalable dementia markers.

Background The human brain integrity relies on the synergistic interplay between neural activity and supporting vascular and metabolic processes throughout life. This relationship, ruled by allostatic mechanisms, regulates brain architecture and activity. White matter hyperintensities (WMH) serve as indicators of the vascular impact on brain structure. While the strong association between vascular/metabolic systems and brain structure/function is established, the precise mechanisms linking allostasis to WMH remain elusive. We hypothesized that allostasis influences white matter through neuroinflammatory mechanisms, and WMH mediate neuroinflammatory effects on EEG measures. Method To test this hypothesis we conducted a comprehensive analysis on MRI, EEG, and multisystemic data from 196 subjects (20 to 75 years, 69 females) sourced from the LEMON database in Leipzig, Germany. Using the lesion segmentation tool (LST) on SPM12, we automatically identified WMH in fluid‐attenuated inversion recovery (FLAIR) images. FastSurfer was employed to determine the volumes of the bilateral hippocampus (HV) and lateral ventricles (VV), representing proxies for neurodegenerative and neuroinflammatory processes, respectively. Volumetric corrections were applied using total intracranial volume. Furthermore, a regression analysis was conducted to discern and subtract the shared contributions of VH and VV on each other. EEG data underwent spectral analysis for oscillatory (alpha waves) and aperiodic (1/f) components using NeuroDSP and FOOOF, respectively. An allostatic load index (ALI), incorporating lipid profile, inflammation, metabolic factors, and blood pressure, was computed. All measures were age, sex, and education level‐corrected. Result We found age differences in every metric of interest, but importantly just ALI, VV and 1/f correlated with WMH number and those effects survived age correction (Figure 1 A and B). VV, but not HV mediates the relationship between ALI and WMH. Also, WMH completely mediate the effects of neuroinflammation over the 1/f (Figure 1 C). Conclusion Our findings reveal that allostasis affects white matter through neuroinflammatory pathways, with WMH serving as crucial mediators of neuroinflammatory impact on EEG measures. This research provides key insights into the intricate interplay of vascular and metabolic factors with brain structure. Identified relationships and mediators open avenues for targeted interventions and personalized treatments in neurodegenerative and neuroinflammatory conditions.

Background The Alzheimer's Disease (AD) continuum is composed of Subjective Cognitive Decline (SCD), Mild Cognitive Impairment (MCI), and Alzheimer's Disease Dementia (ADD). Changes in grey matter volume (GMV), characteristic of the AD continuum, are related to cognitive and activities of daily living (ADL) impairments. ADLs are divided into three domains: i) Basic (BADL), ii) Instrumental (IADL), and iii) Advanced (AADL), and their study is critical for understanding the evolution and adequate follow‐up of patients. To date, the neuroanatomical basis of impairment in ADL has not been addressed. This work aimed to study the relationship between GMV and the ADL domains in the AD continuum. Method A cross‐sectional study of 77 SCD, 30 MCI, and 23 ADD, matched for age, sex, and education, was conducted. ADLs were assessed with the Technology‐Activities of Daily Living Questionnaire (T‐ADLQ). A voxel‐wise regression analysis (with the SPM module) was performed to explore the association between GMV and the domains of ADLs. Total Intracranial Volume (TIV) was entered as a covariate. The analysis was performed for each patient group (MCI and ADD) in tandem with the SCD group to increase sample size, data variance, and statistical power. Result Regression analysis for ADD‐SCD (Figure 1a) shows that in ADD patients (Table 1), AADLs were associated with decreased GMV in temporal, frontal, parietal, and insular regions. IADLs were also associated with temporal, frontal, parietal, and insular areas but were more widely distributed. BADLs were associated with temporal, frontal, and insular structures. The MCI‐SCD analysis (Figure 1b) shows that in patients with MCI (Table 2), AADLs were associated with temporal areas and IADLs with temporal, frontal, and parietal regions. BADLs had no significant associations. Conclusion Associations between ADL domains with decreased GMV were more widely distributed in ADD compared to the MCI group, with a pattern similar to the neurodegenerative progression in the AD continuum. This finding highlights the potential of diverse neuroanatomical markers of functional capacity at different stages of the AD continuum. Such markers could hold significant relevance for the classification and follow‐up of patients from an ADL perspective, thereby improving the understanding of the consequences in daily life.