Extracellular vesicles, the emerging mirrors of brain physiopathology

Extracellular vesicles are secreted by a wide variety of cells, and their primary functions include intercellular communication, immune responses, human reproduction, and synaptic plasticity. Their molecular cargo reflects the physiological processes that their cells of origin are undergoing. Thus, many studies have suggested that extracellular vesicles could be a promising biomarker tool for many diseases, mainly due to their biological relevance and easy accessibility to a broad range of body fluids. Moreover, since their biological composition leads them to cross the blood-brain barrier bidirectionally, growing evidence points to extracellular vesicles as emerging mirrors of brain diseases processes. In this regard, this review explores the biogenesis and biological functions of extracellular vesicles, their role in different physiological and pathological processes, their potential in clinical practice, and the recent outstanding studies about the role of exosomes in major human brain diseases, such as Alzheimer’s disease (AD), Parkinson’s disease (PD), multiple sclerosis (MS), amyotrophic lateral sclerosis (ALS), or brain tumors.A. Cano acknowledges the support of the Instituto de Salud Carlos III (ISCIII) under the grant Sara Borrell (CD22/00125) and Ministerio de Ciencia e Innovación, Proyectos de Generación de Conocimiento grant PID2021-122473OA-I00. Authors acknowledge the services of ProofreadingServices.com for English correction. Authors acknowledge the support of the Ministerio de Ciencia e Innovación, Proyectos de Generación de Conocimiento grants PID2019-106625RB-I00 and PID2021-123462OB-I00. ISCIII Acción Estratégica en Salud, integrated in the Spanish National R+D+I Plan and financed by ISCIII Subdirección General de Evaluación and the Fondo Europeo de Desarrollo Regional (FEDER “Una manera de hacer Europa") grant PI17/01474, PI19/00335, PI22/01403 and PI22/00258. The support of CIBERNED (ISCIII) under the grants CB06/05/2004 and CB18/05/00010. The support from PREADAPT project. Joint Program for Neurodegenerative Diseases (JPND) grant Nº AC19/00097, from HARPONE Project, Agency for Innovation and Entrepreneurship (VLAIO) grant Nº PR067/21, and from DESCARTES project, German Research Foundation (DFG). The support of Fundación bancaria “La Caixa” and Grífols SA (GR@ACE project).Peer reviewe

Neuropsychiatric profiles and conversion to dementia in mild cognitive impairment, a latent class analysis

Altres ajuts: Fondo Europeo de Desarrollo Regional (FEDER)Altres ajuts: Generalitat de Catalunya. Programa CERCAAltres ajuts: Instituto de Salud Carlos III (CIBERSAM i CIBERNED)Altres ajuts: Fundació "La Caixa"Altres ajuts: Grífols SA (GR@ACE project)Neuropsychiatric symptoms (NPS) have been recently addressed as risk factors of conversion to Alzheimer's disease (AD) and other dementia types in patients diagnosed with Mild Cognitive Impairment (MCI). Our aim was to determine profiles based on the prominent NPS in MCI patients and to explore the predictive value of these profiles on conversion to specific types of dementia. A total of 2137 MCI patients monitored in a memory clinic were included in the study. Four NPS profiles emerged (classes), which were defined by preeminent symptoms: Irritability, Apathy, Anxiety/Depression and Asymptomatic. Irritability and Apathy were predictors of conversion to dementia (HR = 1.43 and 1.56, respectively). Anxiety/depression class showed no risk effect of conversion when compared to Asymptomatic class. Irritability class appeared as the most discriminant neuropsychiatric condition to identify non-AD converters (i.e., frontotemporal dementia, vascular dementia, Parkinson's disease and dementia with Lewy Bodies). The findings revealed that consistent subgroups of MCI patients could be identified among comorbid basal NPS. The preeminent NPS showed to behave differentially on conversion to dementia, beyond AD. Therefore, NPS should be used as early diagnosis facilitators, and should also guide clinicians to detect patients with different illness trajectories in the progression of MCI

Plasma extracellular vesicles reveal early molecular differences in amyloid positive patients with early-onset mild cognitive impairment

In the clinical course of Alzheimer's disease (AD) development, the dementia phase is commonly preceded by a prodromal AD phase, which is mainly characterized by reaching the highest levels of Aβ and p-tau-mediated neuronal injury and a mild cognitive impairment (MCI) clinical status. Because of that, most AD cases are diagnosed when neuronal damage is already established and irreversible. Therefore, a differential diagnosis of MCI causes in these prodromal stages is one of the greatest challenges for clinicians. Blood biomarkers are emerging as desirable tools for pre-screening purposes, but the current results are still being analyzed and much more data is needed to be implemented in clinical practice. Because of that, plasma extracellular vesicles (pEVs) are gaining popularity as a new source of biomarkers for the early stages of AD development. To identify an exosome proteomics signature linked to prodromal AD, we performed a cross-sectional study in a cohort of early-onset MCI (EOMCI) patients in which 184 biomarkers were measured in pEVs, cerebrospinal fluid (CSF), and plasma samples using multiplex PEA technology of Olink© proteomics. The obtained results showed that proteins measured in pEVs from EOMCI patients with established amyloidosis correlated with CSF p-tau181 levels, brain ventricle volume changes, brain hyperintensities, and MMSE scores. In addition, the correlations of pEVs proteins with different parameters distinguished between EOMCI Aβ( +) and Aβ(-) patients, whereas the CSF or plasma proteome did not. In conclusion, our findings suggest that pEVs may be able to provide information regarding the initial amyloidotic changes of AD. Circulating exosomes may acquire a pathological protein signature of AD before raw plasma, becoming potential biomarkers for identifying subjects at the earliest stages of AD development

Microevolution, reinfection and highly complex genomic diversity in patients with sequential isolates of Mycobacterium abscessus

Mycobacterium abscessus is an opportunistic, extensively drug-resistant non-tuberculous mycobacterium. Few genomic studies consider its diversity in persistent infections. Our aim was to characterize microevolution/reinfection events in persistent infections. Fifty-three sequential isolates from 14 patients were sequenced to determine SNV-based distances, assign resistance mutations and characterize plasmids. Genomic analysis revealed 12 persistent cases (0-13 differential SNVs), one reinfection (15,956 SNVs) and one very complex case (23 sequential isolates over 192 months), in which a first period of persistence (58 months) involving the same genotype 1 was followed by identification of a genotype 2 (76 SNVs) in 6 additional alternating isolates; additionally, ten transient genotypes (88-243 SNVs) were found. A macrolide resistance mutation was identified from the second isolate. Despite high diversity, the genotypes shared a common phylogenetic ancestor and some coexisted in the same specimens. Genomic analysis is required to access the true intra-patient complexity behind persistent infections involving M. abscessus.This work was supported by the Instituto de Salud Carlos III [AC16/00057, FIS15/01554, PI21/01823, PI19/00331, FI20/00129, PI21/01738], co-financed by European Regional Development Funds of the European Commission: “A way of making Europe”; a Miguel Servet Contract (ISCIII) CPII20/00001 to LPL. FI22/00145 contract from a PFIS (ISCIII) to SBS and Ministerio de Ciencia (MCIN/AEI/10.13039/501100011033, grant PID2020-112865RB-I00).Peer reviewe

Treatment with tocilizumab or corticosteroids for COVID-19 patients with hyperinflammatory state: a multicentre cohort study (SAM-COVID-19)

Objectives: The objective of this study was to estimate the association between tocilizumab or corticosteroids and the risk of intubation or death in patients with coronavirus disease 19 (COVID-19) with a hyperinflammatory state according to clinical and laboratory parameters. Methods: A cohort study was performed in 60 Spanish hospitals including 778 patients with COVID-19 and clinical and laboratory data indicative of a hyperinflammatory state. Treatment was mainly with tocilizumab, an intermediate-high dose of corticosteroids (IHDC), a pulse dose of corticosteroids (PDC), combination therapy, or no treatment. Primary outcome was intubation or death; follow-up was 21 days. Propensity score-adjusted estimations using Cox regression (logistic regression if needed) were calculated. Propensity scores were used as confounders, matching variables and for the inverse probability of treatment weights (IPTWs). Results: In all, 88, 117, 78 and 151 patients treated with tocilizumab, IHDC, PDC, and combination therapy, respectively, were compared with 344 untreated patients. The primary endpoint occurred in 10 (11.4%), 27 (23.1%), 12 (15.4%), 40 (25.6%) and 69 (21.1%), respectively. The IPTW-based hazard ratios (odds ratio for combination therapy) for the primary endpoint were 0.32 (95%CI 0.22-0.47; p < 0.001) for tocilizumab, 0.82 (0.71-1.30; p 0.82) for IHDC, 0.61 (0.43-0.86; p 0.006) for PDC, and 1.17 (0.86-1.58; p 0.30) for combination therapy. Other applications of the propensity score provided similar results, but were not significant for PDC. Tocilizumab was also associated with lower hazard of death alone in IPTW analysis (0.07; 0.02-0.17; p < 0.001). Conclusions: Tocilizumab might be useful in COVID-19 patients with a hyperinflammatory state and should be prioritized for randomized trials in this situatio

Differences in macular vessel density in the superficial plexus across cognitive impairment : the NORFACE cohort

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

Establishing In-House Cutoffs of CSF Alzheimer's Disease Biomarkers for the AT(N) Stratification of the Alzheimer Center Barcelona Cohort

Altres ajuts: FACEHBI private sponsors (Grifols SA, Life Molecular Imaging GmbH, Araclon Biotech, Laboratorios Echevarne SA i ACE Alzheimer Center Barcelona).Background: Clinical diagnosis of Alzheimer's disease (AD) increasingly incorporates CSF biomarkers. However, due to the intrinsic variability of the immunodetection techniques used to measure these biomarkers, establishing in-house cutoffs defining the positivity/negativity of CSF biomarkers is recommended. However, the cutoffs currently published are usually reported by using cross-sectional datasets, not providing evidence about its intrinsic prognostic value when applied to real-world memory clinic cases. Methods: We quantified CSF Aβ1-42, Aβ1-40, t-Tau, and p181Tau with standard INNOTEST® ELISA and Lumipulse G® chemiluminescence enzyme immunoassay (CLEIA) performed on the automated Lumipulse G600II. Determination of cutoffs included patients clinically diagnosed with probable Alzheimer's disease (AD, n = 37) and subjective cognitive decline subjects (SCD, n = 45), cognitively stable for 3 years and with no evidence of brain amyloidosis in 18F-Florbetaben-labeled positron emission tomography (FBB-PET). To compare both methods, a subset of samples for Aβ1-42 (n = 519), t-Tau (n = 399), p181Tau (n = 77), and Aβ1-40 (n = 44) was analyzed. Kappa agreement of single biomarkers and Aβ1-42/Aβ1-40 was evaluated in an independent group of mild cognitive impairment (MCI) and dementia patients (n = 68). Next, established cutoffs were applied to a large real-world cohort of MCI subjects with follow-up data available (n = 647). Results: Cutoff values of Aβ1-42 and t-Tau were higher for CLEIA than for ELISA and similar for p181Tau. Spearman coefficients ranged between 0.81 for Aβ1-40 and 0.96 for p181TAU. Passing-Bablok analysis showed a systematic and proportional difference for all biomarkers but only systematic for Aβ1-40. Bland-Altman analysis showed an average difference between methods in favor of CLEIA. Kappa agreement for single biomarkers was good but lower for the Aβ1-42/Aβ1-40 ratio. Using the calculated cutoffs, we were able to stratify MCI subjects into four AT(N) categories. Kaplan-Meier analyses of AT(N) categories demonstrated gradual and differential dementia conversion rates (p = 9.815). Multivariate Cox proportional hazard models corroborated these findings, demonstrating that the proposed AT(N) classifier has prognostic value. AT(N) categories are only modestly influenced by other known factors associated with disease progression. Conclusions: We established CLEIA and ELISA internal cutoffs to discriminate AD patients from amyloid-negative SCD individuals. The results obtained by both methods are not interchangeable but show good agreement. CLEIA is a good and faster alternative to manual ELISA for providing AT(N) classification of our patients. AT(N) categories have an impact on disease progression. AT(N) classifiers increase the certainty of the MCI prognosis, which can be instrumental in managing real-world MCI subjects

Establishing In-House Cutoffs of CSF Alzheimer&rsquo;s Disease Biomarkers for the AT(N) Stratification of the Alzheimer Center Barcelona Cohort

Background: Clinical diagnosis of Alzheimer&rsquo;s disease (AD) increasingly incorporates CSF biomarkers. However, due to the intrinsic variability of the immunodetection techniques used to measure these biomarkers, establishing in-house cutoffs defining the positivity/negativity of CSF biomarkers is recommended. However, the cutoffs currently published are usually reported by using cross-sectional datasets, not providing evidence about its intrinsic prognostic value when applied to real-world memory clinic cases. Methods: We quantified CSF A&beta;1-42, A&beta;1-40, t-Tau, and p181Tau with standard INNOTEST&reg; ELISA and Lumipulse G&reg; chemiluminescence enzyme immunoassay (CLEIA) performed on the automated Lumipulse G600II. Determination of cutoffs included patients clinically diagnosed with probable Alzheimer&rsquo;s disease (AD, n = 37) and subjective cognitive decline subjects (SCD, n = 45), cognitively stable for 3 years and with no evidence of brain amyloidosis in 18F-Florbetaben-labeled positron emission tomography (FBB-PET). To compare both methods, a subset of samples for A&beta;1-42 (n = 519), t-Tau (n = 399), p181Tau (n = 77), and A&beta;1-40 (n = 44) was analyzed. Kappa agreement of single biomarkers and A&beta;1-42/A&beta;1-40 was evaluated in an independent group of mild cognitive impairment (MCI) and dementia patients (n = 68). Next, established cutoffs were applied to a large real-world cohort of MCI subjects with follow-up data available (n = 647). Results: Cutoff values of A&beta;1-42 and t-Tau were higher for CLEIA than for ELISA and similar for p181Tau. Spearman coefficients ranged between 0.81 for A&beta;1-40 and 0.96 for p181TAU. Passing&ndash;Bablok analysis showed a systematic and proportional difference for all biomarkers but only systematic for A&beta;1-40. Bland&ndash;Altman analysis showed an average difference between methods in favor of CLEIA. Kappa agreement for single biomarkers was good but lower for the A&beta;1-42/A&beta;1-40 ratio. Using the calculated cutoffs, we were able to stratify MCI subjects into four AT(N) categories. Kaplan&ndash;Meier analyses of AT(N) categories demonstrated gradual and differential dementia conversion rates (p = 9.815&minus;27). Multivariate Cox proportional hazard models corroborated these findings, demonstrating that the proposed AT(N) classifier has prognostic value. AT(N) categories are only modestly influenced by other known factors associated with disease progression. Conclusions: We established CLEIA and ELISA internal cutoffs to discriminate AD patients from amyloid-negative SCD individuals. The results obtained by both methods are not interchangeable but show good agreement. CLEIA is a good and faster alternative to manual ELISA for providing AT(N) classification of our patients. AT(N) categories have an impact on disease progression. AT(N) classifiers increase the certainty of the MCI prognosis, which can be instrumental in managing real-world MCI subjects