Rosalia Dacosta-Aguayo

Cognitive aging trajectories differ widely across individuals, and genetic factors such as APOE and BDNF polymorphisms may contribute to this variability. While APOE ε4 has been widely studied, the influence of APOE ε2, particularly in interaction with sex, remains underexplored. This study aims to examine the longitudinal trajectory of APOE ε2 individuals on cognitive performance, and their interactions with sex, age, and BDNF Val66Met polymorphism, in a population-based cohort of older adults with vascular risk. We analyzed data from 386 participants (mean age: 71.8) from the Barcelona-AsIA Neuropsychology Study, followed over a 7-year period. Verbal memory, verbal fluency, and visuospatial domains were assessed. Linear regression models tested associations between cognitive change and genotypes, controlling for age, sex, education, depression, and vascular risk. Interaction terms and permutation testing were applied. Regression to the mean (RTM) effects were assessed. BDNF showed no significant associations with cognitive performance. RTM effects were evident across subgroups, particularly among ε2 carriers, suggesting this phenomenon partly explains the divergent results over time. APOE ε2 does not confer a consistent protective effect on cognition over time. Our results highlight that APOE ε2 may be detrimental to verbal memory in aging males.

Background/Objectives: Stroke often leads to persistent cognitive and emotional impairments, which rehabilitation may mitigate. However, the biological mechanisms underlying such improvements remain unclear. This study investigated whether supplementing computerized cognitive training (CCT) with mindfulness-based stress reduction (MBSR) or physical exercise (PE) modulated biomarkers of neuroplasticity, inflammation, and stress in patients with chronic stroke compared to CCT alone. We also explored whether biomarker changes mediated or correlated with behavioral improvements. Methods: In a three-arm, single-blind, randomized controlled trial (NCT04759950), 141 patients with chronic stroke were randomized (1:1:1) to MBSR+CCT, PE+CCT, or CCT-only for 12 weeks. Plasma levels of brain-derived neurotrophic factor (BDNF), insulin-like growth factor-1 (IGF-1), vascular endothelial growth factor (VEGF), C-reactive protein (CRP), interleukin-6 (IL-6), and cortisol were measured at baseline and post-intervention. Cognitive, mental health, mindfulness, and fitness outcomes were also assessed. Between- and within-group changes were analyzed using ANCOVA and paired t-tests. Per-protocol and complete-case analyses were conducted. Results: Among the 109 participants with ≥80% adherence, the only significant between-group difference was for VEGF: it remained stable in the MBSR+CCT group but declined in PE+CCT and CCT-only. Within-group analyses showed significant decreases in cortisol in MBSR+CCT and PE+CCT, while IGF-1 levels declined across all groups. In contrast, BDNF, IL-6, and CRP did not show significant changes, and biomarker changes were not significantly associated with behavioral improvements. Complete-case analysis (n = 126) yielded similar findings. Conclusions: Our findings suggest that combining MBSR or PE with CCT may modulate certain biological processes relevant to stroke recovery. MBSR may help maintain VEGF levels, which could support vascular health, while MBSR and PE may contribute to lowering cortisol levels. However, since no clear association with behavioral improvements was found, further research is needed to determine the clinical relevance of these biomarker changes in stroke recovery.

Background: As the vaccination campaign against COVID-19 progresses, it becomes crucial to comprehend the lasting effects of vaccination on safeguarding against new infections or reinfections. Objective: This study aimed to assess the risk of new SARS-CoV-2 infections based on the number of vaccine doses, prior infections, and other clinical characteristics. Methods: We defined a cohort of 800 health care workers in a 24-month study (March 2020 to December 2022) in northern Barcelona to determine new infections by SARS-CoV-2. We used extended Cox models, specifically Andersen-Gill (AG) and Prentice-Williams-Peterson, and we examined the risk of new infections. The AG model incorporated variables such as sex, age, job title, number of chronic conditions, vaccine doses, and prior infections. Additionally, 2 Prentice-Williams-Peterson models were adjusted, one for those individuals with no or 1 infection and another for those with 2 or 3 infections, both with the same covariates as the AG model. Results: The 800 participants (n=605, 75.6% women) received 1, 2, 3, and 4 doses of the vaccine. Compared to those who were unvaccinated, the number of vaccine doses significantly reduced (P<.001) the risk of infection by 66%, 81%, 89%, and 99%, respectively. Unit increase in the number of prior infections reduced the risk of infection by 75% (P<.001). When separating individuals by number of previous infections, risk was significantly reduced for those with no or 1 infection by 61% (P=.02), and by 88%, 93%, and 99% (P<.001) with 1, 2, 3, or 4 doses, respectively. In contrast, for those with 2 or 3 previous infections, the reduction was only significant with the fourth dose, at 98% (P<.001). The number of chronic diseases only increased the risk by 28%‐31% (P<.001) for individuals with 0‐1 previous infections. Conclusions: The study suggests that both prior infections and vaccination status significantly contribute to SARS-CoV-2 immunity, supporting vaccine effectiveness in reducing risk of reinfection for up to 24 months after follow-up from the onset of the pandemic. These insights contribute to our understanding of long-term immunity dynamics and inform strategies for mitigating the impact of COVID-19.

The diagnosis of the post-COVID condition is usually achieved by excluding other diseases; however, cognitive changes are often found in the post-COVID disorder. Therefore, monitoring and treating the recovery from the post-COVID condition is necessary to establish biomarkers to guide the diagnosis of symptoms, including cognitive impairment. Our study employs a prospected cohort and nested case–control design with mixed methods, including statistical analyses, interviews, and focus groups. Our main aim is to identify biomarkers (functional and structural neural changes, inflammatory and immune status, vascular and vestibular signs and symptoms) easily applied in primary care to detect cognitive changes in post-COVID cases. The results will open up a new line of research to inform diagnostic and therapeutic decisions with special considerations for cognitive impairment in the post-COVID condition.

Behavioral interventions have shown promising neuroprotective effects, but the cascade of molecular, brain and behavioral changes involved in these benefits remains poorly understood. Projecte Moviment is a 12-week (5 days per week—45 min per day) multi-domain, single-blind, proof-of-concept randomized controlled trial examining the cognitive effect and underlying mechanisms of an aerobic exercise (AE), computerized cognitive training (CCT) and a combined (COMB) groups compared to a waitlist control group. Adherence was > 80% for 82/109 participants recruited (62% female; age = 58.38 ± 5.47). In this study we report intervention-related changes in plasma biomarkers (BDNF, TNF-α, HGF, ICAM-1, SDF1-α) and structural-MRI (brain volume) and how they related to changes in physical activity and individual variables (age and sex) and their potential role as mediators in the cognitive changes. Our results show that although there were no significant changes in molecular biomarker concentrations in any intervention group, changes in ICAM-1 and SDF1-α were negatively associated with changes in physical activity outcomes in AE and COMB groups. Brain volume changes were found in the CCT showing a significant increase in precuneus volume. Sex moderated the brain volume change in the AE and COMB groups, suggesting that men may benefit more than women. Changes in molecular biomarkers and brain volumes did not significantly mediate the cognitive-related benefits found previously for any group. This study shows crucial initial molecular and brain volume changes related to lifestyle interventions at early stages and highlights the value of examining activity parameters, individual difference characteristics and using a multi-level analysis approach to address these questions.

Background Understanding humoral responses and seroprevalence in SARS-CoV-2 infection is essential for guiding vaccination strategies in both infected and uninfected individuals. Methods We determine the kinetics of IgM against the nucleocapsid (N) and IgG against the spike (S) and N proteins of SARS-CoV-2 in a cohort of 860 health professionals (healthy and infected) in northern Barcelona. We model the kinetics of IgG and IgM at nine time points over 13.5 months from infection, using non-linear mixed models by sex and clinical disease severity. Results Of the 781 participants who were followed up, 478 (61.2%) became infected with SARS-CoV-2. Significant differences were found for the three antibodies by disease severity and sex. At day 270 after diagnosis, median IgM(N) levels were already below the positivity threshold in patients with asymptomatic and mild-moderate disease, while IgG(N, S) levels remained positive to days 360 and 270, respectively. Kinetic modelling showed a general rise in both IgM(N) and IgG(N) levels up to day 30, followed by a decay whose rate depended on disease severity. IgG(S) levels increased at day 15 and remained relatively constant over time. Conclusions We describe kinetic models of IgM(N) and IgG(N, S) SARS-CoV-2 antibodies at 13.5 months from infection and disease spectrum. Our analyses delineate differences in the kinetics of IgM and IgG over a year and differences in the levels of IgM and IgG as early as 15 days from symptoms onset in severe cases. These results can inform public health policies around vaccination criteria. Funded by the regional Ministry of Health of the Generalitat de Catalunya (Call COVID19-PoC SLT16_04; NCT04885478)

Personality is the characteristic set of an individual’s behavioral and emotional patterns that evolve from biological and environmental factors. The recognition of personality profiles is crucial in making human–computer interaction (HCI) applications realistic, more focused, and user friendly. The ability to recognize personality using neuroscientific data underpins the neurobiological basis of personality. This paper aims to automatically recognize personality, combining scalp electroencephalogram (EEG) and machine learning techniques. As the resting state EEG has not so far been proven efficient for predicting personality, we used EEG recordings elicited during emotion processing. This study was based on data from the AMIGOS dataset reflecting the response of 37 healthy participants. Brain networks and graph theoretical parameters were extracted from cleaned EEG signals, while each trait score was dichotomized into low- and high-level using the k-means algorithm. A feature selection algorithm was used afterwards to reduce the feature-set size to the best 10 features to describe each trait separately. Support vector machines (SVM) were finally employed to classify each instance. Our method achieved a classification accuracy of 83.8% for extraversion, 86.5% for agreeableness, 83.8% for conscientiousness, 83.8% for neuroticism, and 73% for openness.

Introduction: Age-related health, brain, and cognitive impairment is a great challenge in current society. Cognitive training, aerobic exercise and their combination have been shown to benefit health, brain, cognition and psychological status in healthy older adults. Inconsistent results across studies may be related to several variables. We need to better identify cognitive changes, individual variables that may predict the effect of these interventions, and changes in structural and functional brain outcomes as well as physiological molecular correlates that may be mediating these effects. Projecte Moviment is a multi-domain randomized trial examining the effect of these interventions applied 5 days per week for 3 months compared to a passive control group. The aim of this paper is to describe the sample, procedures and planned analyses. Methods: One hundred and forty healthy physically inactive older adults will be randomly assigned to computerized cognitive training (CCT), aerobic exercise (AE), combined training (COMB), or a control group. The intervention consists of a 3 month home-based program 5 days per week in sessions of 45 min. Data from cognitive, physical, and psychological tests, cardiovascular risk factors, structural and functional brain scans, and blood samples will be obtained before and after the intervention. Results: Effects of the interventions on cognitive outcomes will be described in intention-to-treat and per protocol analyses. We will also analyze potential genetic, demographic, brain, and physiological molecular correlates that may predict the effects of intervention, as well as the association between cognitive effects and changes in these variables using the per protocol sample. Discussion: Projecte Moviment is a multi-domain intervention trial based on prior evidence that aims to understand the effects of CCT, AE, and COMB on cognitive and psychological outcomes compared to a passive control group, and to determine related biological correlates and predictors of the intervention effects. Clinical Trial Registration: www.ClinicalTrials.gov, identifier NCT03123900.

Previous studies in patients with Parkinson’s disease (PD) and impulse control disorders (ICDs) have produced heterogeneous results regarding striatal dopamine transporter (DaT) binding and activity in the mesocorticolimbic network. Our aim here was to study the relationship between striatal DaT availability and cortical metabolism, as well as motor, behavioural and cognitive features of PD patients with ICD.