Post-COVID-19 condition: systemic inflammation and low functional exercise capacity.

Introduction: Post-COVID-19 condition (PCC) is characterised by a plethora of symptoms, with fatigue appearing as the most frequently reported. The alterations that drive both the persistent and post-acute disease newly acquired symptoms are not yet fully described. Given the lack of robust knowledge regarding the mechanisms of PCC we have examined the impact of inflammation in PCC, by evaluating serum cytokine profile and its potential involvement in inducing the different symptoms reported. Methods: In this cross-sectional study, we recruited 227 participants who were hospitalised with acute COVID-19 in 2020 and came back for a follow-up assessment 6-12 months after hospital discharge. The participants were enrolled in two symptomatic groups: Self-Reported Symptoms group (SR, n = 96), who did not present major organ lesions, yet reported several debilitating symptoms such as fatigue, muscle weakness, and persistent loss of sense of smell and taste; and the Self-Reported Symptoms and decreased Pulmonary Function group (SRPF, n = 54), composed by individuals with the same symptoms described by SR, plus diagnosed pulmonary lesions. A Control group (n = 77), with participants with minor complaints following acute COVID-19, was also included in the study. Serum cytokine levels, symptom questionnaires, physical performance tests and general clinical data were obtained in the follow-up assessment. Results: SRPF presented lower IL-4 concentration compared with Control (q = 0.0018) and with SR (q = 0.030), and lower IFN-α2 serum content compared with Control (q = 0.007). In addition, SRPF presented higher MIP-1ß serum concentration compared with SR (q = 0.029). SR presented lower CCL11 (q = 0.012 and q = 0.001, respectively) and MCP-1 levels (q = 0.052 for both) compared with Control and SRPF. SRPF presented lower G-CSF compared to Control (q = 0.014). Female participants in SR showed lower handgrip strength in relation to SRPF (q = 0.0082). Male participants in SR and SRPF needed more time to complete the timed up-and-go test, as compared with men in the Control group (q = 0.0302 and q = 0.0078, respectively). Our results indicate that different PCC symptom profiles are accompanied by distinct inflammatory markers in the circulation. Of particular concern are the lower muscle function findings, with likely long-lasting consequences for health and quality of life, found for both PCC phenotypes.

Endocannabinoid system alterations in schizophrenia: association with cannabis use and antipsychotic medication.

Determining peripheral modulation of the endocannabinoid system (ECS) may be important for differentiating individuals with schizophrenia. Such differentiation can also be extended to subgroups of individuals, those who use cannabis and antipsychotic medications, particularly those who are treatment resistant. Patients and controls were recruited from the outpatient clinic of the Psychosis Group of the University of São Paulo, Brazil. A final sample of 93 individuals was divided into 3 groups: patients with schizophrenia using clozapine (treatment-resistant) (n = 29), patients with schizophrenia using another antipsychotic (n = 31), and controls (n = 33). By measuring the proteins and metabolites involved in the ECS pathways in the peripheral blood, AEA (anandamide), 2-AG (2-arachidonoyl ethanolamine), and CB2 receptor (peripheral) were quantified. Individuals reporting lifetime cannabis use had lower 2-AG plasma levels (p = 0.011). Regarding the CB2 receptor, the values of patients with schizophrenia and controls were similar, but those of patients using antipsychotics other than clozapine differed (p = 0.022). In generalized linear models to control for confounders, the use of cannabis remained the only factor that significantly influenced 2-AG levels. The relationship for non-clozapine antipsychotics as the only factor related to CB2 changes was marginally significant. We found for the first time that cannabis use and non-clozapine antipsychotic medication are potentially involved in the modulation of the ECS, specifically influencing 2-AG endocannabinoid and CB2 receptor levels. More studies regarding the ECS are needed since it has been increasingly related to the physiopathology of schizophrenia.

Neuropsychiatric symptoms and ApoE genotype in older adults without dementia: a cross-sectional study.

BACKGROUND: The ApoE genotype and neuropsychiatric symptoms (NPS) are known risk factors for cognitive decline in older adults. However, the interaction between these variables is still unclear. The aim of this study was to determine the association between the presence of the ApoE ε4 allele and the occurrence of NPS in older adults without dementia. METHODS: In this cross-sectional investigation we determined the apolipoprotein E (ApoE) genotype of 74 older adults who were either cognitively normal (20.3% / Clinician Dementia Rating Scale (CDR): 0) or had mild cognitive impairment (MCI: 79.7% / CDR: 0.5). We used a comprehensive cognitive assessment protocol, and NPS were estimated by the Neuropsychiatric Inventory-Clinician Rating Scale (NPI-C), Mild Behavioural Impairment-Checklist (MBI-C), Hamilton Rating Scale for Depression (HAM-D), and Apathy Inventory. RESULTS: ApoE ε4 carriers had higher MBI-C total scores than ApoE ε4 noncarriers. Correlations between NPS and ApoE genotype were observed for two NPI-C domains, although in opposite directions: the ApoE ε4 allele was associated with a 1.8 unit decrease in the estimated aberrant motor disturbance score and with a 1.3 unit increase in the estimated appetite/eating disorders score. All fitted models were significant, except for the one fitted for the domain delusions from the NPI-C. Among individuals with amnestic MCI, ε4 carriers presented higher depression score (HAM-D) than noncarriers; in turn, ε4 noncarriers exhibited higher aggression score (NPI-C) than ε4 carriers. CONCLUSIONS: Our analyses showed associations between NPS and the presence of the ApoE ε4 allele in two NPI-C domains, despite the sample size. Furthermore, compared to noncarriers, the presence of the ApoE ε4 correlated positively with appetite/eating disorders and negatively with aberrant motor disturbance domain. Examination of the amnestic MCI group displayed significant, although weak, associations. Therefore, ε4 carriers exhibited higher depression scores according to the HAM-D scale compared to ε4 noncarriers. Conversely, ε4 noncarriers had higher scores in the aggression domain of the NPI-C than ε4 carriers.

Lithium and disease modification: A systematic review and meta-analysis in Alzheimer's and Parkinson's disease.

The role of lithium as a possible therapeutic strategy for neurodegenerative diseases has generated scientific interest. We systematically reviewed and meta-analyzed pre-clinical and clinical studies that evidenced the neuroprotective effects of lithium in Alzheimer's (AD) and Parkinson's disease (PD). We followed the PRISMA guidelines and performed the systematic literature search using PubMed, EMBASE, Web of Science, and Cochrane Library. A total of 32 articles were identified. Twenty-nine studies were performed in animal models and 3 studies were performed on human samples of AD. A total of 17 preclinical studies were included in the meta-analysis. Our analysis showed that lithium treatment has neuroprotective effects in diseases. Lithium treatment reduced amyloid-ß and tau levels and significantly improved cognitive behavior in animal models of AD. Lithium increased the tyrosine hydroxylase levels and improved motor behavior in the PD model. Despite fewer clinical studies on these aspects, we evidenced the positive effects of lithium in AD patients. This study lends further support to the idea of lithium's therapeutic potential in neurodegenerative diseases.

Plasma levels of neurotrophin 4/5, NGF and pro-BDNF influence transition to mental disorders in a sample of individuals at ultra-high risk for psychosis.

BACKGROUND: Neurotrophins (NTs) and their precursors (pro-NTs) are polypeptides with important roles in neuronal development, differentiation, growth, survival and plasticity, as well as apoptosis and neuronal death. Imbalance in NT levels were observed in schizophrenia spectrum disorders, but evidence in ultra-high risk for psychosis (UHR) samples is scarce. METHODS: A naturalistic sample of 87 non-help-seeking UHR subjects and 55 healthy controls was drawn from the general population. Blood samples were collected and NT-3, NT-4/5, BDNF, pro-BDNF, NGF, pro-NGF were analyzed through enzyme linked immunosorbent assay (ELISA). Information on cannabis and tobacco use was also collected. Logistic regression models and path analysis were used to control for confounders (tobacco, age, cannabis use). RESULTS: NT-4/5 was significantly decreased, and pro-BDNF was significantly increased in UHR individuals compared to controls. Cannabis use and higher NGF levels were significantly related to transition to psychiatric disorders among UHR subjects. Increased pro-BDNF and decreased NT-4/5 influenced transition by the mediation of perceptual abnormalities. CONCLUSIONS: Our study shows for the first time that NTs are altered in UHR compared to healthy control individuals, and that they can be a predictor of transition to psychiatric illnesses in this population. Future studies should employ larger naturalistic samples to confirm the findings.

Cognitive impairment in long-COVID and its association with persistent dysregulation in inflammatory markers.

Objective: To analyze the potential impact of sociodemographic, clinical and biological factors on the long-term cognitive outcome of patients who survived moderate and severe forms of COVID-19. Methods: We assessed 710 adult participants (Mean age = 55 ± 14; 48.3% were female) 6 to 11 months after hospital discharge with a complete cognitive battery, as well as a psychiatric, clinical and laboratory evaluation. A large set of inferential statistical methods was used to predict potential variables associated with any long-term cognitive impairment, with a focus on a panel of 28 cytokines and other blood inflammatory and disease severity markers. Results: Concerning the subjective assessment of cognitive performance, 36.1% reported a slightly poorer overall cognitive performance, and 14.6% reported being severely impacted, compared to their pre-COVID-19 status. Multivariate analysis found sex, age, ethnicity, education, comorbidity, frailty and physical activity associated with general cognition. A bivariate analysis found that G-CSF, IFN-alfa2, IL13, IL15, IL1.RA, EL1.alfa, IL45, IL5, IL6, IL7, TNF-Beta, VEGF, Follow-up C-Reactive Protein, and Follow-up D-Dimer were significantly (p<.05) associated with general cognition. However, a LASSO regression that included all follow-up variables, inflammatory markers and cytokines did not support these findings. Conclusion: Though we identified several sociodemographic characteristics that might protect against cognitive impairment following SARS-CoV-2 infection, our data do not support a prominent role for clinical status (both during acute and long-stage of COVID-19) or inflammatory background (also during acute and long-stage of COVID-19) to explain the cognitive deficits that can follow COVID-19 infection.

Inflammatory cytokines and white matter microstructure in the acute phase of first-episode psychosis: A longitudinal study.

OBJECTIVES: Schizophrenia-related psychosis is associated with abnormalities in white matter (WM) microstructure and structural brain dysconnectivity. However, the pathological process underlying such changes is unknown. We sought to investigate the potential association between peripheral cytokine levels and WM microstructure during the acute phase of first-episode psychosis (FEP) in a cohort of drug-naïve patients. METHODS: Twenty-five non-affective FEP patients and 69 healthy controls underwent MRI scanning and blood collection at study entry. After achieving clinical remission, 21 FEP were reassessed; 38 age and biological sex-matched controls also had a second assessment. We measured fractional anisotropy (FA) of selected WM regions-of-interest (ROIs) and plasma levels of four cytokines (IL-6, IL-10, IFN-γ, and TNF-α). RESULTS: At baseline (acute psychosis), the FEP group showed reduced FA relative to controls in half the examined ROIs. Within the FEP group, IL-6 levels were negatively correlated with FA values. Longitudinally, patients showed increments of FA in several ROIs affected at baseline, and such changes were associated with reductions in IL-6 levels. CONCLUSIONS: A state-dependent process involving an interplay between a pro-inflammatory cytokine and brain WM might be associated with the clinical manifestation of FEP. This association suggests a deleterious effect of IL-6 on WM tracts during the acute phase of psychosis.

Application of Lipidomics in Psychiatry: Plasma-Based Potential Biomarkers in Schizophrenia and Bipolar Disorder.

In this study, we obtained a lipidomic profile of plasma samples from drug-naïve patients with schizophrenia (SZ) and bipolar disorder (BD) in comparison to healthy controls. The sample cohort consisted of 30 BD and 30 SZ patients and 30 control individuals. An untargeted lipidomics strategy using liquid chromatography coupled with high-resolution mass spectrometry was employed to obtain the lipid profiles. Data were preprocessed, then univariate (t-test) and multivariate (principal component analysis and orthogonal partial least squares discriminant analysis) statistical tools were applied to select differential lipids, which were putatively identified. Afterward, multivariate receiver operating characteristic tests were performed, and metabolic pathway networks were constructed, considering the differential lipids. Our results demonstrate alterations in distinct lipid pathways, especially in glycerophospholipids, sphingolipids and glycerolipids, between SZ and BD patients. The results obtained in this study may serve as a basis for differential diagnosis, which is crucial for effective treatment and improving the quality of life of patients with psychotic disorders.

A dopamine receptor D2 genetic polymorphism associated with transition to mental disorders in a cohort of individuals with at-risk mental state for psychosis.

OBJECTIVES: To test the association of 45 single nucleotide polymorphisms (SNPs) with transition to psychiatric disorders in a cohort of individuals at ultrahigh risk (UHR) mental state for psychosis. METHODS: Through general population screening, 88 non-help-seeking UHR subjects and 130 healthy control individuals were genotyped for 45 SNPs related to psychosis. They were followed for a mean of 2.5 years, and conversion to psychotic and to general psychiatric disorders was assessed. Genotype frequencies between controls, converters, and non-converters were analyzed. RESULTS: There were no differences in sociodemographics between controls and UHR. Also, UHR converters and non-converters had no differences in their baseline symptoms scores. The dopamine receptor D2 gene (DRD2) SNP rs6277 was significantly more common among UHR who transitioned to psychosis (p < 0.001) and to UHR who transitioned to any psychiatric disorders (p = 0.001) when compared to UHR who did not transition. The rs6277 T allele was related to psychiatric morbidity in a dose-response fashion, being significantly more frequent in UHR converters than UHR non-converters and control subjects (p = 0.003). CONCLUSION: Our findings suggest that rs6277 could potentially constitute a genetic marker of transition to psychiatric disorders in subjects with at-risk mental states, warranting further investigation in larger samples.

Whole-brain DTI parameters associated with tau protein and hippocampal volume in Alzheimer's disease.

The causes of the neurodegenerative processes in Alzheimer's disease (AD) are not completely known. Recent studies have shown that white matter (WM) damage could be more severe and widespread than whole-brain cortical atrophy and that such damage may appear even before the damage to the gray matter (GM). In AD, Amyloid-beta (Aß42 ) and tau proteins could directly affect WM, spreading across brain networks. Since hippocampal atrophy is common in the early phase of disease, it is reasonable to expect that hippocampal volume (HV) might be also related to WM integrity. Our study aimed to evaluate the integrity of the whole-brain WM, through diffusion tensor imaging (DTI) parameters, in mild AD and amnestic mild cognitive impairment (aMCI) due to AD (with Aß42 alteration in cerebrospinal fluid [CSF]) in relation to controls; and possible correlations between those measures and the CSF levels of Aß42 , phosphorylated tau protein (p-Tau) and total tau (t-Tau). We found a widespread WM alteration in the groups, and we also observed correlations between p-Tau and t-Tau with tracts directly linked to mesial temporal lobe (MTL) structures (fornix and hippocampal cingulum). However, linear regressions showed that the HV better explained the variation found in the DTI measures (with weak to moderate effect sizes, explaining from 9% to 31%) than did CSF proteins. In conclusion, we found widespread alterations in WM integrity, particularly in regions commonly affected by the disease in our group of early-stage disease and patients with Alzheimer's disease. Nonetheless, in the statistical models, the HV better predicted the integrity of the MTL tracts than the biomarkers in CSF.

Revisiting global cognitive and functional state 13 years after a clinical trial of lithium for mild cognitive impairment

Objectives: To re-evaluate a sample of older adults enrolled in a randomized controlled trial of lithium for amnestic mild cognitive impairment (MCI) after 11 to 15 years, re-assessing their current (or last available) global cognitive and functional state. Methods: We recalled all former participants of the Lithium-MCI trial conducted by our group between 2009 and 2012 to perform a single-blinded, cross-sectional evaluation of their global clinical state to compare the long-term outcome of those who received lithium vs. those who received placebo. Results: Of the original sample (n=61), we were able to reach 36 participants (59% of retention), of whom 22 had previously received lithium (61% of the recall sample) and 14 (39%) had received placebo. Since 30.5% of the recalled sample was deceased, psychometric data were collected only for 69.5% of the participants. We found statistically significant differences in current mean Mini Mental State Examination score according to previous treatment group (25.5 [SD, 5.3] vs. 18.3 [SD, 10.9], p = 0.04). The lithium group also had better performance in the phonemic Verbal Fluency Test than the control group (34.4 [SD, 14.4] vs. 11.6 [SD, 10.10], p < 0.001). Differences in these measures also had large effect sizes, as shown by Cohen's d values of 0.92 and 1.78, respectively. Conclusion: This data set suggests that older adults with amnestic MCI who had been treated with lithium during a previous randomized controlled trial had a better long-term global cognitive outcome than those from a matched sample who did not receive the intervention.

BDNF blood levels after electroconvulsive therapy in patients with mood disorders: An updated systematic review and meta-analysis.

OBJECTIVES: Studies have suggested Brain-Derived Neurotrophic Factors (BDNF) increase after electroconvulsive therapy (ECT) although they were methodologically limited and enrolled small sample sizes. We aimed at updating a systematic review and meta-analysis to explore BDNF changes after ECT for the treatment of depression. METHODS: PubMed, PsycInfo, Embase and Global health were searched (March, 2021). Clinical trials that measured BDNF in the blood before and after ECT in adults (≥ 18 years old) with depression (major depressive disorder or bipolar disorder) were eligible. Data were pooled through random-effects meta-analyses. RESULTS: Twenty-eight studies involving 778 participants were included. Meta-analysis showed a significant increase in BDNF levels after ECT (Hedges' g = 0.28; 95% CI: 0.10, 0.46) while there was evidence of significant heterogeneity (I2 = 67.64%) but not publication bias/small-study effect. Subgroup analyses and meta-regressions were underpowered to detect significant differences. Meta-analysis of depression severity scores demonstrated a considerable larger treatment effect in reducing depressive symptoms after ECT (Hedge's g = -3.72 95% CI: -4.23, -3.21). CONCLUSION: This updated review showed that BDNF blood levels increased after ECT treatment. However, there was still evidence of substantial heterogeneity and there were limited sample sizes to investigate factors driving the variability of effects across studies. Importantly, the increase in BDNF levels was substantially smaller than the observed in depressive symptomatology, which could be indicative that the former was independent than the latter. Additional studies with larger sample sizes are currently required.

Cholinesterase Inhibitors Response Might Be Related to Right Hippocampal Functional Connectivity in Mild Alzheimer's Disease.

Background: The response to cholinesterase inhibitors (ChEIs) treatment is variable in patients with Alzheimer's disease (AD). Patients and physicians would benefit if these drugs could be targeted at those most likely to respond in a clinical setting. Therefore, this study aimed to evaluate the ability of cerebrospinal fluid (CSF) AD biomarkers, hippocampal volumes, and Default Mode Network functional connectivity to predict clinical response to ChEIs treatment in mild AD. Methods: We followed up on 39 mild AD patients using ChEIs at therapeutic doses. All subjects underwent clinical evaluation, neuropsychological assessment, magnetic resonance imaging examination, and CSF biomarkers quantification at the first assessment. The Mini-Mental Status Examination (MMSE) was used to measure the global cognitive status before and after the follow-up. "Responders" were considered as those who have remained stable or improved the MMSE score between evaluations and "Nonresponders" as those who have worsened the MMSE score. We performed univariate and multivariate logistic regressions to predict the clinical response from each biomarker. Results: About 35.89% of patients were classified as "Responders" to ChEIs treatment after the follow-up. The multivariate model with measures of Right Hippocampus (RHIPPO), adjusted for gender and interval between assessments, was significant (odds ratio: 1.09 [95% confidence interval, 1.00-1.19], p = 0.0392). This model achieved an accuracy of 77.60%. Conclusion: Our findings suggest that the functional connectivity of RHIPPO might be an early imaging biomarker to predict clinical response to ChEIs drugs in mild AD. Impact statement The functional connectivity of the right hippocampus showed a direct relationship with the clinical response to cholinesterase inhibitors (ChEIs) treatment in patients with mild Alzheimer's disease. Transposing our findings to clinical settings could allow physicians to prescribe ChEIs for patients for whom treatment would be most beneficial.

Revisiting global cognitive and functional state 13 years after a clinical trial of lithium for mild cognitive impairment.

OBJECTIVES: To re-evaluate a sample of older adults enrolled in a randomized controlled trial of lithium for amnestic mild cognitive impairment (MCI) after 11 to 15 years, re-assessing their current (or last available) global cognitive and functional state. METHODS: We recalled all former participants of the Lithium-MCI trial conducted by our group between 2009 and 2012 to perform a single-blinded, cross-sectional evaluation of their global clinical state to compare the long-term outcome of those who received lithium vs. those who received placebo. RESULTS: Of the original sample (n=61), we were able to reach 36 participants (59% of retention), of whom 22 had previously received lithium (61% of the recall sample) and 14 (39%) had received placebo. Since 30.5% of the recalled sample was deceased, psychometric data were collected only for 69.5% of the participants. We found statistically significant differences in current mean Mini Mental State Examination score according to previous treatment group (25.5 [SD, 5.3] vs. 18.3 [SD, 10.9], p = 0.04). The lithium group also had better performance in the phonemic Verbal Fluency Test than the control group (34.4 [SD, 14.4] vs. 11.6 [SD, 10.10], p < 0.001). Differences in these measures also had large effect sizes, as shown by Cohen's d values of 0.92 and 1.78, respectively. CONCLUSION: This data set suggests that older adults with amnestic MCI who had been treated with lithium during a previous randomized controlled trial had a better long-term global cognitive outcome than those from a matched sample who did not receive the intervention.

A dopamine receptor D2 genetic polymorphism associated with transition to mental disorders in a cohort of individuals with at-risk mental state for psychosis

Objectives: To test the association of 45 single nucleotide polymorphisms (SNPs) with transition to psychiatric disorders in a cohort of individuals at ultrahigh risk (UHR) mental state for psychosis. Methods: Through general population screening, 88 non-help-seeking UHR subjects and 130 healthy control individuals were genotyped for 45 SNPs related to psychosis. They were followed for a mean of 2.5 years, and conversion to psychotic and to general psychiatric disorders was assessed. Genotype frequencies between controls, converters, and non-converters were analyzed. Results: There were no differences in sociodemographics between controls and UHR. Also, UHR converters and non-converters had no differences in their baseline symptoms scores. The dopamine receptor D2 gene (DRD2) SNP rs6277 was significantly more common among UHR who transitioned to psychosis (p < 0.001) and to UHR who transitioned to any psychiatric disorders (p = 0.001) when compared to UHR who did not transition. The rs6277 T allele was related to psychiatric morbidity in a dose-response fashion, being significantly more frequent in UHR converters than UHR non-converters and control subjects (p = 0.003). Conclusion: Our findings suggest that rs6277 could potentially constitute a genetic marker of transition to psychiatric disorders in subjects with at-risk mental states, warranting further investigation in larger samples.

Decision tree-based classification as a support to diagnosis in the Alzheimer's disease continuum using cerebrospinal fluid biomarkers: insights from automated analysis

Objective: Cerebrospinal fluid (CSF) biomarkers add accuracy to the diagnostic workup of cognitive impairment by illustrating Alzheimer's disease (AD) pathology. However, there are no universally accepted cutoff values for the interpretation of AD biomarkers. The aim of this study is to determine the viability of a decision-tree method to analyse CSF biomarkers of AD as a support for clinical diagnosis. Methods: A decision-tree method (automated classification analysis) was applied to concentrations of AD biomarkers in CSF as a support for clinical diagnosis in older adults with or without cognitive impairment in a Brazilian cohort. In brief, 272 older adults (68 with AD, 122 with mild cognitive impairment [MCI], and 82 healthy controls) were assessed for CSF concentrations of Aβ1-42, total-tau, and phosphorylated-tau using multiplexed Luminex assays; biomarker values were used to generate decision-tree algorithms (classification and regression tree) in the R statistical software environment. Results: The best decision tree model had an accuracy of 74.65% to differentiate the three groups. Cluster analysis supported the combination of CSF biomarkers to differentiate AD and MCI vs. controls, suggesting the best cutoff values for each clinical condition. Conclusion: Automated analyses of AD biomarkers provide valuable information to support the clinical diagnosis of MCI and AD in research settings.

Decision tree-based classification as a support to diagnosis in the Alzheimer's disease continuum using cerebrospinal fluid biomarkers: insights from automated analysis.

OBJECTIVE: Cerebrospinal fluid (CSF) biomarkers add accuracy to the diagnostic workup of cognitive impairment by illustrating Alzheimer's disease (AD) pathology. However, there are no universally accepted cutoff values for the interpretation of AD biomarkers. The aim of this study is to determine the viability of a decision-tree method to analyse CSF biomarkers of AD as a support for clinical diagnosis. METHODS: A decision-tree method (automated classification analysis) was applied to concentrations of AD biomarkers in CSF as a support for clinical diagnosis in older adults with or without cognitive impairment in a Brazilian cohort. In brief, 272 older adults (68 with AD, 122 with mild cognitive impairment [MCI], and 82 healthy controls) were assessed for CSF concentrations of Aß1-42, total-tau, and phosphorylated-tau using multiplexed Luminex assays; biomarker values were used to generate decision-tree algorithms (classification and regression tree) in the R statistical software environment. RESULTS: The best decision tree model had an accuracy of 74.65% to differentiate the three groups. Cluster analysis supported the combination of CSF biomarkers to differentiate AD and MCI vs. controls, suggesting the best cutoff values for each clinical condition. CONCLUSION: Automated analyses of AD biomarkers provide valuable information to support the clinical diagnosis of MCI and AD in research settings.

Functional Connectome Analysis in Mild Cognitive Impairment: Comparing Alzheimer's Disease Continuum and Suspected Non-Alzheimer Pathology.

Introduction: Research in brain resting-state functional connectivity (FC) analysis in mild cognitive impairment (MCI) has conflicting results. This work intends to find differences in resting-state FC of 2 groups of MCI subjects due to Alzheimer's disease (MCI-AD) continuum or to suspected non-Alzheimer pathology (MCI-SNAP). Materials and Methods: Ninety-two subjects older than 55 years were enrolled. MCI and controls were grouped using clinical dementia rating and neuropsychological data. Cerebrospinal fluid biomarkers were collected from MCI subjects, resulting in 32 MCI-AD, 25 MCI-SNAP, and 35 controls. A region of interest (ROI)-to-ROI analysis was carried out looking at inter- and intranetwork interactions selecting the following networks: default mode network (DMN), salience network (SN), visuospatial network (VN), and executive network. Pearson correlation coefficients, converted to Z-scores, were compared by T-tests with alpha set to 0.05, and false discovery rate corrected. Results: Groups were similar in age, education, and demographic measures, there were no differences in neuropsychological data between the MCI groups. The ROI-to-ROI analysis of MCI-AD versus MCI-SNAP showed no differences. MCI-AD versus controls showed decreased FC between ROIs of the SN and between ROIs from SN and VN. MCI-SNAP versus controls showed increased FC between an ROI of DMN and VN. Discussion: SN, DMN, and VN are multimodal networks with high value/high cost and may be more vulnerable to AD pathogenic processes. SN and VN were affected in the MCI-AD group, with maintained anticorrelation between DMN and VN. This may indicate subthreshold DMN dysfunction. The result in MCI-SNAP, although discrete, reflects a rearrangement of brain FC, as DMN and VN are expected to be anticorrelated. More research is necessary to confirm these findings.

Plasmatic endocannabinoids are decreased in subjects with ultra-high risk of psychosis.

The onset of frank psychosis is usually preceded by a prodromal phase characterized by attenuated psychotic symptoms. Currently, research on schizophrenia prodromal phase (ultra-high risk for psychosis [UHR]) has focused on the risk of developing psychosis, on the transition to full blown psychosis and on its prediction. Neurobiological differences between UHR individuals who fully recover (remitters) versus those who show persistent/progressive prodromal symptoms (nonremitters) have been little explored. The endocannabinoid system constitutes a neuromodulatory system that plays a major role in brain development, synaptic plasticity, emotional behaviours and cognition. It comprises two cannabinoid receptors (CB1/CB2), two endocannabinoid ligands, arachidonylethanolamide (AEA) and 2-arachidonoylglycerol (2AG) along with their inactivation enzymes. Despite much evidence that the endocannabinoid system is imbalanced during psychosis, very little is known about it in UHR. Therefore, we aimed to quantify the plasma endocannabinoid levels in UHR and healthy controls (HC) and verify if these metabolites could differentiate between remitters and nonremitters. Circulating concentrations of AEA (p = .003) and 2AG (p < .001) were lower in UHR when compared with HC, with no difference between remitters and nonremitters. Regarding clinical evolution, it was observed that out of 91 UHRs initially considered, 16 had psychiatric complaints (3 years of follow-up). Considering those subjects, there were weak correlations between clinical parameters and plasma concentrations of endocannabinoids. Our results suggest that the endocannabinoids are imbalanced before frank psychosis and that changes can be seen in plasma of UHR individuals. These molecules proved to be potential biomarkers to identify individuals in the prodromal phase of psychosis.

Use of a Bayesian Network Model to predict psychiatric illness in individuals with 'at risk mental states' from a general population cohort.

The 'at risk mental state' (ARMS) paradigm has been introduced in psychiatry to study prodromal phases of schizophrenia. With time it was seen that the ARMS state can also precede mental disorders other than schizophrenia, such as depression and anxiety. However, several problems hamper the paradigm's use in preventative medicine, such as varying transition rates across studies, the use of non-naturalistic samples, and the multifactorial nature of psychiatric disorders. To strengthen ARMS predictive power, there is a need for a holistic model incorporating-in an unbiased fashion-the small-effect factors that cause mental disorders. Bayesian networks, a probabilistic graphical model, was used in a populational cohort of 83 ARMS individuals to predict conversion to psychiatric illness. Nine predictors-including state, trait, biological and environmental factors-were inputted. Dopamine receptor 2 polymorphism, high private religiosity, and childhood trauma remained in the final model, which reached an 85.51% (SD = 0.1190) accuracy level in predicting conversion. This is the first time a robust model was produced with Bayesian networks to predict psychiatric illness among at risk individuals from the general population. This could be an important tool to strengthen predictive measures in psychiatry which should be replicated in larger samples to provide the model further learning.