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Abstract Background Alzheimer’s disease (AD) stands as the leading cause of dementia worldwide, and projections estimate over 150 million patients by 2050. AD prevalence is notably higher in women, nearly twice that of men, with discernible sex differences in certain risk factors. To enhance our understanding of how sex influences the characteristics of AD patients and its potential impact on the disease trajectory, we conducted a comprehensive analysis of demographic, clinical, cognitive, and genetic data from a sizable and well-characterized cohort of AD dementia patients at a memory clinic in Barcelona, Spain. Methods The study cohort comprised individuals with probable and possible AD dementia with a Clinical Dementia Rating (CDR) score between 1 and 3 diagnosed at the Memory Unit from Ace Alzheimer Center Barcelona, Spain, between 2008 and 2018. We obtained cognitive baseline data and follow up scores for the Mini-Mental State Examination (MMSE), the CDR scale, and the neuropsychological battery used in our center (NBACE). We employed various statistical techniques to assess the impact of sex on cognitive evolution in these dementia patients, accounting for other sex-related risk factors identified through Machine Learning methods. Results The study cohort comprised a total of 6108 individuals diagnosed with AD dementia during the study period (28.4% males and 71.6% females). MMSE scores exhibited an average decline of approximately two units per year, unaffected by sex. Similarly, the decline in most neuropsychological functions assessed by NBACE did not exhibit significant differences between males and females. However, we observed that women diagnosed with mild AD dementia progressed more rapidly based on their CDR score (HR = 2.57, 95%CI:2.33–2.84) than men (HR = 2.03, 95%CI: 1.71–2.41) (p-interaction = 0.01). Conclusions Our findings do not strongly support the notion that sex significantly modifies the clinical progression of AD dementia based on cognitive data. Further research is essential to validate whether women with mild AD dementia indeed progress more rapidly than men at a similar stage and to delve into the potential underlying reasons for this finding.

Abstract Background Optical coherence tomography (OCT) enables high-resolution imaging of ocular structures in health and disease. Choroid thickness (CT) is a key vascular retinal parameter that can be assessed by OCT and might be relevant in the evaluation of the vascular component of cognitive decline. We aimed to investigate CT changes in a large cohort of individuals cognitive unimpaired (CU), with mild cognitive impairment due to Alzheimer's (MCI-AD), mild cognitive impairment due to cerebrovascular disease (MCI-Va), Alzheimer’s disease dementia (ADD), and vascular dementia (VaD). Methods Clinical, demographical, ophthalmological and OCT data from the Neuro-ophthalmological Research at Fundació ACE (NORFACE) project were analyzed. CT was assessed in the macula across nine Early Treatment Diabetic Retinopathy Study (ETDRS) quadrants, average thickness, total volume, and subfoveal choroidal thickness. Differences of CT among the five diagnostic groups were assessed in a multivariate regression model, adjusting for demographic and cardiovascular risk factors and OCT image quality. A comparison between manual and automatic CT measurements in a subset of participants was also performed. Results The study cohort comprised 1,280 participants: 301 CU, 196 MCI-AD, 112 MCI-Va, 578 ADD, and 93 VaD. CT was significantly increased in individuals with cognitive impairment compared to those CU, particularly in the VaD and MCI-Va groups and in the peripheral ETDRS regions. No significant differences were found in inner superior, center and subfoveal choroidal thickness. The interaction of sex and diagnosis had no effect in differentiating CT. Mini-Mental State Examination (MMSE) scores were not correlated to CT. Manual and automated CT measurements showed good reliability. Discussion Our findings indicated that peripheral choroidal thickening, especially in patients with cerebrovascular disease, may serve as a potential choroidal biomarker for cognitive decline and suggest different pathogenic pathways in AD and VaD. Further research is required to explore CT as a reliable ocular biomarker for cognitive impairment.

Despite the central role attributed to neuroinflammation in the etiology and pathobiology of Alzheimer's disease (AD), the direct link between levels of inflammatory mediators in blood and cerebrospinal fluid (CSF) compartments, as well as their potential implications for AD diagnosis and progression, remains inconclusive. Moreover, there is debate on whether inflammation has a protective or detrimental effect on disease onset and progression. Indeed, distinct immunological mechanisms may govern protective and damaging effects at early and late stages, respectively.This study aims to (i) identify inflammatory mediators demonstrating robust correlations between peripheral and central nervous system (CNS) compartments by means of plasma and CSF analysis, respectively, and (ii) assess their potential significance in the context of AD and disease progression from mild cognitive impairment (MCI) to dementia. To achieve this, we have examined the inflammatory profile of a well-defined subcohort comprising 485 individuals from the Ace Alzheimer Center Barcelona (ACE). Employing a hierarchical clustering approach, we thoroughly evaluated the intercompartmental correlations of 63 distinct inflammation mediators, quantified in paired CSF and plasma samples, using advanced SOMAscan technology. Of the array of mediators investigated, only six mediators (CRP, IL1RAP, ILRL1, IL6RA, PDGFRB, and YKL-40) exhibited robust correlations between the central and peripheral compartments (proximity scores 1.3, p

Summary: Background: The identification of patients with an elevated risk of developing Alzheimer's disease (AD) dementia and eligible for the disease-modifying treatments (DMTs) in the earliest stages is one of the greatest challenges in the clinical practice. Plasma biomarkers has the potential to predict these issues, but further research is still needed to translate them to clinical practice. Here we evaluated the clinical applicability of plasma pTau181 as a predictive marker of AD pathology in a large real-world cohort of a memory clinic. Methods: Three independent cohorts (modelling [n = 991, 59.7% female], testing [n = 642, 56.2% female] and validation [n = 441, 55.1% female]) of real-world patients with subjective cognitive decline (SCD), mild cognitive impairment (MCI), AD dementia, and other dementias were included. Paired cerebrospinal fluid (CSF) and plasma samples were used to measure AT(N) CSF biomarkers and plasma pTau181. Findings: CSF and plasma pTau181 showed correlation in all phenotypes except in SCD and other dementias. Age significantly influenced the biomarker's performance. The general Aβ(+) vs Aβ(−) ROC curve showed an AUC = 0.77 [0.74–0.80], whereas the specific ROC curve of MCI due to AD vs non-AD MCI showed an AUC = 0.89 [0.85–0.93]. A cut-off value of 1.30 pg/ml of plasma pTau181 exhibited a sensitivity of 93.57% [88.72–96.52], specificity of 72.38% [62.51–79.01], VPP of 77.85% [70.61–83.54], and 8.30% false negatives in the subjects with MCI of the testing cohort. The HR of cox regression showed that patients with MCI up to this cut-off value exhibited a HR = 1.84 [1.05–3.22] higher risk to convert to AD dementia than patients with MCI below the cut-off value. Interpretation: Plasma pTau181 has the potential to be used in the memory clinics as a screening biomarker of AD pathology in subjects with MCI, presenting a valuable prognostic utility in predicting the MCI conversion to AD dementia. In the context of a real-world population, a confirmatory test employing gold-standard procedures is still advisable. Funding: This study has been mainly funded by Ace Alzheimer Center Barcelona, Instituto de Salud Carlos III (ISCIII), Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Spanish Ministry of Science and Innovation, Fundación ADEY, Fundación Echevarne and Grífols S.A.

Abstract Background Several studies have reported a relationship between retinal thickness and dementia. Therefore, optical coherence tomography (OCT) has been proposed as an early diagnosis method for Alzheimer’s disease (AD). In this study, we performed a genome-wide association study (GWAS) aimed at identifying genes associated with retinal nerve fiber layer (RNFL) and ganglion cell inner plexiform layer (GCIPL) thickness assessed by OCT and exploring the relationships between the spectrum of cognitive decline (including AD and non-AD cases) and retinal thickness. Methods RNFL and GCIPL thickness at the macula were determined using two different OCT devices (Triton and Maestro). These determinations were tested for association with common single nucleotide polymorphism (SNPs) using adjusted linear regression models and combined using meta-analysis methods. Polygenic risk scores (PRSs) for retinal thickness and AD were generated. Results Several genetic loci affecting retinal thickness were identified across the genome in accordance with previous reports. The genetic overlap between retinal thickness and dementia, however, was weak and limited to the GCIPL layer; only those observable with all-type dementia cases were considered. Conclusions Our study does not support the existence of a genetic link between dementia and retinal thickness.

Abstract Introduction Optical coherence tomography angiography (OCT-A) is a novel tool that allows the detection of retinal vascular changes. We investigated the association of macular vessel density (VD) in the superficial plexus assessed by OCT-A with measures of cerebrovascular pathology and atrophy quantified by brain magnetic resonance imaging (MRI) in non-demented individuals. Methods Clinical, demographical, OCT-A, and brain MRI data from non-demented research participants were included. We analyzed the association of regional macular VD with brain vascular burden using the Fazekas scale assessed in a logistic regression analysis, and the volume of white matter hyperintensities (WMH) assessed in a multiple linear regression analysis. We also explored the associations of macular VD with hippocampal volume, ventricle volume and Alzheimer disease cortical signature (ADCS) thickness assessed in multiple linear regression analyses. All analyses were adjusted for age, sex, syndromic diagnosis and cardiovascular variables. Results The study cohort comprised 188 participants: 89 with subjective cognitive decline and 99 with mild cognitive impairment. No significant association of regional macular VD with the Fazekas categories (all, p > 0.111) and WMH volume (all, p > 0.051) were detected. VD in the nasal quadrant was associated to hippocampal volume (p = 0.007), but no other associations of macular VD with brain atrophy measures were detected (all, p > 0.05). Discussion Retinal vascular measures were not a proxy of cerebrovascular damage in non-demented individuals, while VD in the nasal quadrant was associated with hippocampal atrophy independently of the amyloid status.

Abstract Background Advancement in screening tools accessible to the general population for the early detection of Alzheimer’s disease (AD) and prediction of its progression is essential for achieving timely therapeutic interventions and conducting decentralized clinical trials. This study delves into the application of Machine Learning (ML) techniques by leveraging paralinguistic features extracted directly from a brief spontaneous speech (SS) protocol. We aimed to explore the capability of ML techniques to discriminate between different degrees of cognitive impairment based on SS. Furthermore, for the first time, this study investigates the relationship between paralinguistic features from SS and cognitive function within the AD spectrum. Methods Physical-acoustic features were extracted from voice recordings of patients evaluated in a memory unit who underwent a SS protocol. We implemented several ML models evaluated via cross-validation to identify individuals without cognitive impairment (subjective cognitive decline, SCD), with mild cognitive impairment (MCI), and with dementia due to AD (ADD). In addition, we established models capable of predicting cognitive domain performance based on a comprehensive neuropsychological battery from Fundació Ace (NBACE) using SS-derived information. Results The results of this study showed that, based on a paralinguistic analysis of sound, it is possible to identify individuals with ADD (F1 = 0.92) and MCI (F1 = 0.84). Furthermore, our models, based on physical acoustic information, exhibited correlations greater than 0.5 for predicting the cognitive domains of attention, memory, executive functions, language, and visuospatial ability. Conclusions In this study, we show the potential of a brief and cost-effective SS protocol in distinguishing between different degrees of cognitive impairment and forecasting performance in cognitive domains commonly affected within the AD spectrum. Our results demonstrate a high correspondence with protocols traditionally used to assess cognitive function. Overall, it opens up novel prospects for developing screening tools and remote disease monitoring.

Abstract Background Alzheimer’s disease (AD) diagnosis relies on clinical symptoms complemented with biological biomarkers, the Amyloid Tau Neurodegeneration (ATN) framework. Small non-coding RNA (sncRNA) in the blood have emerged as potential predictors of AD. We identified sncRNA signatures specific to ATN and AD, and evaluated both their contribution to improving AD conversion prediction beyond ATN alone. Methods This nested case–control study was conducted within the ACE cohort and included MCI patients matched by sex. Patients free of type 2 diabetes underwent cerebrospinal fluid (CSF) and plasma collection and were followed-up for a median of 2.45-years. Plasma sncRNAs were profiled using small RNA-sequencing. Conditional logistic and Cox regression analyses with elastic net penalties were performed to identify sncRNA signatures for A+(T|N)+ and AD. Weighted scores were computed using cross-validation, and the association of these scores with AD risk was assessed using multivariable Cox regression models. Gene ontology (GO) and Kyoto encyclopaedia of genes and genomes (KEGG) enrichment analysis of the identified signatures were performed. Results The study sample consisted of 192 patients, including 96 A+(T|N)+ and 96 A-T-N- patients. We constructed a classification model based on a 6-miRNAs signature for ATN. The model could classify MCI patients into A-T-N- and A+(T|N)+ groups with an area under the curve of 0.7335 (95% CI, 0.7327 to 0.7342). However, the addition of the model to conventional risk factors did not improve the prediction of AD beyond the conventional model plus ATN status (C-statistic: 0.805 [95% CI, 0.758 to 0.852] compared to 0.829 [95% CI, 0.786, 0.872]). The AD-related 15-sncRNAs signature exhibited better predictive performance than the conventional model plus ATN status (C-statistic: 0.849 [95% CI, 0.808 to 0.890]). When ATN was included in this model, the prediction further improved to 0.875 (95% CI, 0.840 to 0.910). The miRNA-target interaction network and functional analysis, including GO and KEGG pathway enrichment analysis, suggested that the miRNAs in both signatures are involved in neuronal pathways associated with AD. Conclusions The AD-related sncRNA signature holds promise in predicting AD conversion, providing insights into early AD development and potential targets for prevention.

Objectives To analyse the differences between nurses with and without substance use disorders (SUDs) admitted to a specialised mental health programme.Design Retrospective, observational study.Setting Specialised mental health treatment programme for nurses in Catalonia, Spain.Participants 1091 nurses admitted to the programme from 2000 to 2021.Interventions None.Primary and secondary outcomes Sociodemographic, occupational and clinical variables were analysed. Diagnoses followed Diagnostic and Statistical Manual of Mental Disorders, 4th edition, Text Revision criteria.Results Most nurses admitted to the programme were women (88%, n=960) and came voluntarily (92.1%, n=1005). The mean age at admission was 45 (SD=10.4) years. The most common diagnoses were adjustment disorders (36.6%, n=399), unipolar mood disorders (25.8%, n=282), anxiety disorders (16.4%, n=179) and SUDs (13.8%, n=151). Only 19.2% (n=209) of the sample were hospitalised during their first treatment episode. After multivariate analysis, suffering from a SUD was significantly associated with being a man (OR=4.12; 95% CI 2.49 to 6.82), coming after a directed referral (OR=4.55; 95% CI 2.5 to 7.69), being on sick leave at admission (OR=2.21; 95% CI 1.42 to 3.45) and needing hospitalisation at the beginning of their treatment (OR=12.5; 95% CI 8.3 to 20).Conclusions Nurses with SUDs have greater resistance to voluntarily asking for help from specialised mental health treatment programmes and have greater clinical severity compared with those without addictions. SUDs are also more frequent among men. More actions are needed to help prevent and promote earlier help-seeking behaviours among nurses with this type of mental disorder.

Abstract INTRODUCTION Individuals with Alzheimer's disease (AD) commonly experience neuropsychiatric symptoms of psychosis (AD+P) and/or affective disturbance (depression, anxiety, and/or irritability, AD+A). This study's goal was to identify the genetic architecture of AD+P and AD+A, as well as their genetically correlated phenotypes. METHODS Genome‐wide association meta‐analysis of 9988 AD participants from six source studies with participants characterized for AD+P AD+A, and a joint phenotype (AD+A+P). RESULTS AD+P and AD+A were genetically correlated. However, AD+P and AD+A diverged in their genetic correlations with psychiatric phenotypes in individuals without AD. AD+P was negatively genetically correlated with bipolar disorder and positively with depressive symptoms. AD+A was positively correlated with anxiety disorder and more strongly correlated than AD+P with depressive symptoms. AD+P and AD+A+P had significant estimated heritability, whereas AD+A did not. Examination of the loci most strongly associated with the three phenotypes revealed overlapping and unique associations. DISCUSSION AD+P, AD+A, and AD+A+P have both shared and divergent genetic associations pointing to the importance of incorporating genetic insights into future treatment development. Highlights It has long been known that psychotic and affective symptoms are often comorbid in individuals diagnosed with Alzheimer's disease. Here we examined for the first time the genetic architecture underlying this clinical observation, determining that psychotic and affective phenotypes in Alzheimer's disease are genetically correlated. Nevertheless, psychotic and affective phenotypes in Alzheimer's disease diverged in their genetic correlations with psychiatric phenotypes assessed in individuals without Alzheimer's disease. Psychosis in Alzheimer's disease was negatively genetically correlated with bipolar disorder and positively with depressive symptoms, whereas the affective phenotypes in Alzheimer's disease were positively correlated with anxiety disorder and more strongly correlated than psychosis with depressive symptoms. Psychosis in Alzheimer's disease, and the joint psychotic and affective phenotype, had significant estimated heritability, whereas the affective in AD did not. Examination of the loci most strongly associated with the psychotic, affective, or joint phenotypes revealed overlapping and unique associations.

Abstract Although beta-amyloid (Aβ) and phosphorylated tau remain the preferred targets for disease-modifying treatments (DMT) against Alzheimer’s disease (AD), part of the pathophysiological mechanisms of cognitive impairment are related to neuroinflammation and oxidative stress. In mild cognitive impairment (MCI), a prodromal stage of AD and other neurodegenerative conditions, the joint appearance of inflammation, oxidative stress, and metabolic alterations are the common pathways of neurotoxicity and neurodegeneration. The standardized extract of Ginkgo biloba EGb 761 interferes with the pathogenic mechanisms involved in both the development of cognitive impairment due to AD and that of vascular origin. The primary objective of this study is to compare changes in the levels of blood markers of inflammation and oxidative stress after treatment with EGb 761 in a cohort of 100 patients with MCI. In addition, we aim to assess changes in these blood markers during an additional 12-month extension phase in which patients in the control group will also receive EGb 761 and patients in the active group will extend their treatment duration. Secondary objectives include comparing changes in neuropsychiatric and cognitive test scores between the baseline (v0) and 12-month visits (v2). This study is a Phase IV, single-center, randomized, open-label, parallel-group clinical trial consisting of the 12-month follow-up of a cohort of participants with MCI [Global Deterioration Scale (GDS) = 3] and an extension with an additional 12-month follow-up. During the first 12 months, participants will be randomized into two arms: in one arm, patients will receive 1 daily tablet of EGb 761 240 mg orally (study group, n = 50), while in the other arm, patients will not receive EGb 761 and will undergo the same assessments as the treated group (control group, n = 50). After the first 12 months of the study, patients in the EGb 761-treated group will continue treatment, and patients in the control group will be offered one EGb 761 240 mg tablet per day orally. All participants will be monitored for an additional 12 months. A battery of blood markers of inflammation and oxidative stress will be quantified at v0, v1, v2, v3, and v4. The Olink Proteomics panel of inflammation markers ( https://www.olink.com/products/inflammation/ ) will be used to evaluate 92 proteins associated with inflammatory diseases and related biological processes. The second panel measures 92 proteins involved in neurological processes. At v0, v2, and v4, neuropsychological and neurological evaluations will be conducted in addition to vital signs and anthropometric studies using a body composition monitor with bioimpedance technology (Tanita). Sixty percent of the 100 MCI patients recruited were women. The mean age was 73.1 years, and the mean time between symptom onset and MCI diagnosis was 2.9 years. The mean Mini-Mental State Examination (MMSE) score was 26.7. Depressive and anxiety disorders, as well as vascular risk factors, were the most frequent comorbidities among the cohort. The study is still ongoing, and results for the first year of treatment (v0, v1, v2) are expected by 2023. Individuals with MCI have an elevated risk of developing dementia. EGb 761 is used worldwide for the symptomatic treatment of cognitive disorders due to its neuroprotective effects. In experimental models and clinical observational studies, EGb 761 has shown strong antioxidant and anti-inflammatory activity. As a result, this study has been proposed to evaluate the antioxidant and anti-inflammatory effects on plasma markers and their potential clinical correlation with the progression of cognitive decline in patients with MCI. Trial registration: Registro Español de estudios clínicos (REec) number 2020-003776-41, ClinicalTrials.gov Identifier: NCT05594355.

Highlights The pEVs proteome revealed early molecular differences between EOMCI Aβ( +) and Aβ(-) subjects. Olink© neurology proteins from pEVs of EOMCI Aβ( +) patients exhibited a strong negative correlation with CSF p-tau181. The levels of pEVs and CSF Olink© proteins correlated with CSF p-tau181 levels and age. Brain MRI characteristics of EOMCI Aβ( +) patients correlated with pEVs protein levels. pEVs biomarkers only linked early signs of inflammation to brain atrophy in EOMCI Aβ( +) individuals. The correlation of cognitive status and pEVs biomarkers differed between EOMCI Aβ( +) and Aβ(-) patients.

Abstract Background Medically serious suicide attempts (MSSA) represent a subgroup of clinically heterogeneous suicidal behaviours very close to deaths by suicide. A simple definition of an MSSA is a suicide attempt with life-threatening consequences, regardless of the severity of the attempter’s mental disorder. Few studies have specifically analysed the heterogeneity of MSSA. Therefore, the aim of this study is to describe the profile of individuals who made a highly severe MSSA and to compare those admitted to Intensive Care Units (ICU) – including Burn Units– with other MSSA admitted to other medical and surgical units. Methods The study sample consisted of 168 patients consecutively admitted to non-psychiatric wards from two public hospitals in Barcelona after an MSSA during a 3-year period. In order to select more severe MSSA, the minimum hospital stay was expanded from Beautrais’ definition of ≥ 24 h to ≥ 48 h. Mean hospital stay was 23.68 (SD = 41.14) days. Patients needing ICU treatment (n = 99) were compared to other MSSArs (n = 69) that were admitted to other medical and surgical units, not requiring intensive care treatment, with an initial bivariant analysis followed by a logistic regression analysis using conditional entrance. Results Medically serious suicide attempters (MSSArs) spent more time hospitalized, more frequently reported recent stressful life events, were more likely to have at least one prior suicide attempt (SA) and their current attempt was more frequently non-planned, compared to the profile of MSSArs reported in previous studies. The most frequent method was medication overdose (67.3%) and jumping from heights (23.2%). Among those who chose more than one method (37.6%), the most frequent combination was medication overdose and drug use. Affective disorders and personality disorders were the most frequent diagnoses. Higher educational level, history of previous mental disorders and prior lifetime suicide attempts were significantly more frequent among those admitted to ICU compared to other MSSArs. Patients needing admission to ICU less frequently used self-poisoning and cuts. Conclusions MSSA needing ICU admission can be regarded clinically as similar to attempts resulting in suicide. More research on this type of highly severe suicide behaviour is needed due to its serious implications both from a clinical and public health perspective.

Alzheimer's disease (AD) is a neurodegenerative condition characterized by a gradual decline in cognitive functions. Currently, there are no effective treatments for AD, underscoring the importance of identifying individuals in the preclinical stages of mild cognitive impairment (MCI) to enable early interventions. Among the neuropathological events associated with the onset of the disease is the accumulation of amyloid protein in the brain, which correlates with decreased levels of Aβ42 peptide in the cerebrospinal fluid (CSF). Consequently, the development of non-invasive, low-cost, and easy-to-administer proxies for detecting Aβ42 positivity in CSF becomes particularly valuable. A promising approach to achieve this is spontaneous speech analysis, which combined with machine learning (ML) techniques, has proven highly useful in AD. In this study, we examined the relationship between amyloid status in CSF and acoustic features derived from the description of the Cookie Theft picture in MCI patients from a memory clinic. The cohort consisted of fifty-two patients with MCI (mean age 73 years, 65% female, and 57% positive amyloid status). Eighty-eight acoustic parameters were extracted from voice recordings using the extended Geneva Minimalistic Acoustic Parameter Set (eGeMAPS), and several ML models were used to classify the amyloid status. Furthermore, interpretability techniques were employed to examine the influence of input variables on the determination of amyloid-positive status. The best model, based on acoustic variables, achieved an accuracy of 75% with an area under the curve (AUC) of 0.79 in the prediction of amyloid status evaluated by bootstrapping and Leave-One-Out Cross Validation (LOOCV), outperforming conventional neuropsychological tests (AUC = 0.66). Our results showed that the automated analysis of voice recordings derived from spontaneous speech tests offers valuable insights into AD biomarkers during the preclinical stages. These findings introduce novel possibilities for the use of digital biomarkers to identify subjects at high risk of developing AD.

Abstract Optical coherence tomography angiography (OCT-A) allows the detection of retinal vessel density (VD) loss, which is a reflection of brain vascular pathology. We aimed to investigate differences in macular VD in the superficial plexus in a large cohort of individuals cognitively unimpaired (CU), with mild cognitive impairment due to Alzheimer´s disease (MCI-AD), MCI due to cerebrovascular pathology (MCI-Va), probable Alzheimer´s disease dementia (ADD) and Vascular Dementia (VaD). Clinical, demographical, ophthalmological and OCT-A data from the Neuro-ophthalmology Research at Fundació ACE (NORFACE) project were analyzed. Differences of macular VD in four quadrants (superior, nasal, inferior and temporal) among the five diagnostic groups were assessed in a multivariate regression model, adjusted by age, sex, education, hypertension, diabetes mellitus, heart disease and stroke. The study cohort comprised 672 participants: 128 CU, 120 MCI-AD, 111 MCI-Va, 257 ADD and 56 VaD. Regression analysis showed a significantly higher VD in the temporal quadrant in MCI-AD compared to CU participants (49.05 ± 4.91 vs 47.27 ± 4.17, p = 0.02, d = 0.40), and a significantly lower VD in the inferior quadrant in MCI-Va compared to CU participants (48.70 ± 6.57 vs 51.27 ± 6.39, p = 0.02, d = 0.40). Individuals with heart disease presented significantly lower VD in the inferior quadrant than those without (p = 0.01). The interaction of sex and diagnosis had no effect in differentiating VD. Mini-Mental State Examination (MMSE) scores were not correlated to VD (all r 0.07). In conclusion, our study showed that the MCI-AD and MCI-Va groups had significant differences in macular VD in opposite directions in the temporal and inferior quadrants, respectively, compared to CU participants, suggesting that macular VD might be able to differentiate two pathogenic pathways (AD- and cerebrovascular-related) in early stages of cognitive decline.

Abstract Background FACEmemory® is the first computerized, self-administered verbal episodic memory test with voice recognition. It can be conducted under minimal supervision and contains an automatic scoring system to avoid administrator errors. Moreover, it is suitable for discriminating between cognitively healthy and amnestic mild cognitive impairment (MCI) individuals, and it is associated with Alzheimer’s disease (AD) cerebrospinal fluid (CSF) biomarkers. This study aimed to determine whether FACEmemory scoring is related to performance on classical memory tests and to AD biomarkers of brain magnetic resonance imaging (MRI) and CSF in patients with early-onset MCI (EOMCI). Methods Ninety-four patients with EOMCI from the BIOFACE study completed FACEmemory, classical memory tests (the Spanish version of the Word Free and Cued Selective Reminding Test -FCSRT-, the Word List from the Wechsler Memory Scale, third edition, and the Spanish version of the Rey–Osterrieth Complex Figure Test), and a brain MRI. Eighty-two individuals also underwent a lumbar puncture. Results FACEmemory scoring was moderately correlated with FCSRT scoring. With regard to neuroimaging MRI results, worse execution on FACEmemory was associated with lower cortical volume in the right prefrontal and inferior parietal areas, along with the left temporal and associative occipital areas. Moreover, the total FACEmemory score correlated with CSF AD biomarkers (Aβ1-42/Aβ1-40 ratio, p181-tau, and Aβ1-42/p181-tau ratio). When performance on FACEmemory was compared among the ATN classification groups, significant differences between the AD group and normal and SNAP groups were found. Conclusions FACEmemory is a promising tool for detecting memory deficits sensitive to early-onset AD, but it also allows the detection of memory-impaired cases due to other etiologies. Our findings suggest that FACEmemory scoring can detect the AD endophenotype and that it is also associated with AD-related changes in MRI and CSF in patients with EOMCI. The computerized FACEmemory tool might be an opportunity to facilitate early detection of MCI in younger people than 65, who have a growing interest in new technologies.

BackgroundOptical coherence tomography angiography (OCT-A) is a novel method in the dementia field that allows the detection of retinal vascular changes. The comparison of OCT-A measures with established Alzheimer’s disease (AD)-related biomarkers is essential to validate the former as a marker of cerebrovascular impairment in the AD continuum. We aimed to investigate the association of macular vessel density (VD) in the superficial plexus quantified by OCT-A with the AT(N) classification based on cerebrospinal fluid (CSF) Aβ1-42, p181-tau and t-tau measurements in individuals with mild cognitive impairment (MCI).Materials and methodsClinical, demographic, ophthalmological, OCT-A and CSF core biomarkers for AD data from the Neuro-ophthalmology Research at Fundació ACE (NORFACE) project were analyzed. Differences in macular VD in four quadrants (superior, nasal, inferior, and temporal) among three AT(N) groups [Normal, Alzheimer and Suspected non-Alzheimer pathology (SNAP)] were assessed in a multivariate regression model, adjusted for age, APOE ε4 status, hypertension, diabetes mellitus, dyslipidemia, heart disease, chronic obstructive pulmonary disease and smoking habit, using the Normal AT(N) group as the reference category.ResultsThe study cohort comprised 144 MCI participants: 66 Normal AT(N), 45 Alzheimer AT(N) and 33 SNAP AT(N). Regression analysis showed no significant association of the AT(N) groups with any of the regional macular VD measures (all, p > 0.16). The interaction between sex and AT(N) groups had no effect on differentiating VD. Lastly, CSF Aβ1-42, p181-tau and t-tau measures were not correlated to VD (all r < 0.13; p > 0.13).DiscussionOur study showed that macular VD measures were not associated with the AT(N) classification based on CSF biomarkers in patients with MCI, and did not differ between AD and other underlying causes of cognitive decline in our cohort.

IntroductionThis study examined, for the first time, the prevalence of mental disorders and comorbidities among inmates who were about to be released, and their association with criminal history.MethodsA Spanish sample of 140 prisoners at the end of their sentence was recruited from an occupational program. Psychiatric disorders were determined according to the Diagnostic and Statistical Manual of Mental Disorders criteria. Bivariate analyses followed by multivariate regression models were conducted to identify significant variables for repeat incarceration and violent offending.ResultsThe lifetime prevalence of Axis I disorders was 81.4%, with substance use disorders (SUD) and attention deficit/hyperactivity disorder (ADHD) being the most common diagnoses (51.4 and 31.4%, respectively). The current prevalence of Axis I disorders was 59.0%, including learning disorders (38.6%), ADHD (16.4%), and SUD (5.71%) among the most frequent syndromes. Thirty-six (26.5%) participants met criteria for a current Axis II disorder, which commonly was an antisocial personality disorder (12.5%). The majority of the sample (60.8%) suffered from two or more comorbid disorders during their lifetime, although the current prevalence fell to 23.3%. Childhood ADHD increased the number of imprisonments, while inmates convicted of a violent crime were more likely to present a learning disorder. Having a lifetime diagnosis of SUD or multiple psychiatric disorders appeared to be associated with both repeat incarceration and violent offending.ConclusionGiven the high rate of mental disorders still present among subjects completing prison sentences and the challenges they may encounter to benefit from vocational programs, our results suggest that appropriate psychiatric care should be provided during imprisonment and after release to facilitate their community reintegration.