L'infezione da HIV nell'era della terapia antiretrovirale combinata: le neoplasie non-AIDS-definenti nella casistica della U.O.C. Malattie Infettive di Pisa

La sindrome da immunodeficienza acquisita fu descritta per la prima volta nel 1981 tra le comunità di omosessuali a San Francisco. L’agente responsabile, il virus dell’immunodeficienza umana (HIV) venne isolato due anni più tardi e si sarebbe configurato come un agente a trasmissione precipuamente sessuale. Fino alla prima metà degli anni ’90 l’infezione aveva un decorso inesorabilmente fatale in capo ad alcuni anni attraverso la forte compromissione del sistema immunitario che risultava nello sviluppo di infezioni opportunistiche e di alcuni specifici tumori. Nel 1996 l’introduzione di nuovi farmaci ad attività antiretrovirale inaugurò l’inizio di una nuova terapia di combinazione che avrebbe riscritto la storia dell’infezione, da malattia inesorabilmente fatale a condizione cronica trattabile per lo meno nei paesi dove sia garantito l’accesso alla terapia. La terapia antiretrovirale combinata non rappresenta tuttavia una cura e va proseguita per tutta la vita, inoltre non restituisce il paziente ad una condizione di salute pari a quella della popolazione generale. A distanza di quasi due decadi dall’introduzione della terapia antiretrovirale combinata, con l’invecchiamento della popolazione sieropositiva, si sta delineando un nuovo scenario in cui le condizioni AIDS-definenti hanno un minore peso in termini di morbilità e mortalità ma emergono nuove affezioni, prima inedite, che fanno del paziente con HIV un paziente particolarmente complesso. Tra queste sono le neoplasie non-AIDS-definenti; la loro origine si pone all’intersezioni di numerosi fenomeni: invecchiamento, disregolazione immunitaria, fattori ambientali (fumo e alcol), coinfezione con virus trasformanti

Genetics of resilience: Implications from genome‐wide association studies and candidate genes of the stress response system in posttraumatic stress disorder and depression

n/

Genetic basis of psychopathological dimensions shared between schizophrenia and bipolar disorder

Shared genetic vulnerability between schizophrenia (SCZ) and bipolar disorder (BP) was demonstrated, but the genetic underpinnings of specific symptom domains are unclear. This study investigated which genes and gene sets may modulate specific psychopathological domains and if genome-wide significant loci previously associated with SCZ or BP may play a role. Genome-wide data were available in patients with SCZ (n = 226) or BP (n = 228). Phenotypes under investigation were depressive and positive symptoms severity, suicidal ideation, onset age and substance use disorder comorbidity. Genome-wide analyses were performed at gene and gene set level, while 148 genome-wide significant loci previously associated with SCZ and/or BP were investigated. Each sample was analyzed separately then a meta-analysis was performed. SH3GL2 and CLVS1 genes were associated with suicidal ideation in SCZ (p = 5.62e-08 and 0.01, respectively), the former also in the meta-analysis (p = .01). SHC4 gene was associated with depressive symptoms severity in BP (p = .003). A gene set involved in cellular differentiation (GO:0048661) was associated with substance disorder comorbidity in the meta-analysis (p = .03). Individual loci previously associated with SCZ or BP did not modulate the phenotypes of interest. This study provided confirmatory and new findings. SH3GL2 (endophilin A1) showed a role in suicidal ideation that may be due to its relevance to the glutamate system. SHC4 regulates BDNF-induced MAPK activation and was previously associated with depression. CLVS1 is involved in lysosome maturation and was for the first time associated with a psychiatric trait. GO:0048661 may mediate the risk of substance disorder through an effect on neurodevelopment/neuroplasticity

Deconstructing major depressive episodes across unipolar and bipolar depression by severity and duration: a cross-diagnostic cluster analysis on a large, international, observational study

A cross-diagnostic, post-hoc analysis of the BRIDGE-II-MIX study was performed to investigate how unipolar and bipolar patients suffering from an acute major depressive episode (MDE) cluster according to severity and duration. Duration of index episode, Clinical Global Impression-Bipolar Version-Depression (CGI-BP-D) and Global Assessment of Functioning (GAF) were used as clustering variables. MANOVA and post-hoc ANOVAs examined between-group differences in clustering variables. A stepwise backward regression model explored the relationship with the 56 clinical-demographic variables available. Agglomerative hierarchical clustering with two clusters was shown as the best fit and separated the study population (n = 2314) into 65.73% (Cluster 1 (C1)) and 34.26% (Cluster 2 (C2)). MANOVA showed a significant main effect for cluster group (p < 0.001) but ANOVA revealed that significant between-group differences were restricted to CGI-BP-D (p < 0.001) and GAF (p < 0.001), showing greater severity in C2. Psychotic features and a minimum of three DSM-5 criteria for mixed features (DSM-5-3C) had the strongest association with C2, that with greater disease burden, while non-mixed depression in bipolar disorder (BD) type II had negative association. Mixed affect defined as DSM-5-3C associates with greater acute severity and overall impairment, independently of the diagnosis of bipolar or unipolar depression. In this study a pure, non-mixed depression in BD type II significantly associates with lesser burden of clinical and functional severity. The lack of association for less restrictive, researched-based definitions of mixed features underlines DSM-5-3C specificity. If confirmed in further prospective studies, these findings would warrant major revisions of treatment algorithms for both unipolar and bipolar depression

Lithium therapy and weight change in people with bipolar disorder: A systematic review and meta-analysis

Lithium remains the gold standard maintenance treatment for Bipolar Disorder (BD). However, weight gain is a side effect of increasing relevance due to its metabolic implications. We conducted a systematic review and metaanalysis aimed at summarizing evidence on the use of lithium and weight change in BD. We followed the PRISMA methodology, searching Pubmed, Scopus and Web of Science. From 1003 screened references, 20 studies were included in the systematic review and 9 included in the meta-analysis. In line with the studies included in the systematic review, the meta-analysis revealed that weight gain with lithium was not significant, noting a weight increase of 0.462 Kg (p = 0158). A shorter duration of treatment was significantly associated with more weight gain. Compared to placebo, there were no significant differences in weight gain. Weight gain was significantly lower with lithium than with active comparators. This work reveals a low impact of lithium on weight change, especially compared to some of the most widely used active comparators. Our results could impact clinical decisions

Exploring digital biomarkers of illness activity in mood episodes:Hypotheses generating and model development study

Background: Depressive and manic episodes within bipolar disorder (BD) and major depressive disorder (MDD) involve altered mood, sleep, and activity, alongside physiological alterations wearables can capture. Objective: Firstly, we explored whether physiological wearable data could predict (aim 1) the severity of an acute affective episode at the intra-individual level and (aim 2) the polarity of an acute affective episode and euthymia among different individuals. Secondarily, we explored which physiological data were related to prior predictions, generalization across patients, and associations between affective symptoms and physiological data.Methods: We conducted a prospective exploratory observational study including patients with BD and MDD on acute affective episodes (manic, depressed, and mixed) whose physiological data were recorded using a research-grade wearable (Empatica E4) across 3 consecutive time points (acute, response, and remission of episode). Euthymic patients and healthy controls were recorded during a single session (approximately 48 h). Manic and depressive symptoms were assessed using standardized psychometric scales. Physiological wearable data included the following channels: acceleration (ACC), skin temperature, blood volume pulse, heart rate (HR), and electrodermal activity (EDA). Invalid physiological data were removed using a rule-based filter, and channels were time aligned at 1-second time units and segmented at window lengths of 32 seconds, as best-performing parameters. We developed deep learning predictive models, assessed the channels’ individual contribution using permutation feature importance analysis, and computed physiological data to psychometric scales’ items normalized mutual information (NMI). We present a novel, fully automated method for the preprocessing and analysis of physiological data from a research-grade wearable device, including a viable supervised learning pipeline for time-series analyses.Results: Overall, 35 sessions (1512 hours) from 12 patients (manic, depressed, mixed, and euthymic) and 7 healthy controls (mean age 39.7, SD 12.6 years; 6/19, 32% female) were analyzed. The severity of mood episodes was predicted with moderate (62%-85%) accuracies (aim 1), and their polarity with moderate (70%) accuracy (aim 2). The most relevant features for the former tasks were ACC, EDA, and HR. There was a fair agreement in feature importance across classification tasks (Kendall W=0.383). Generalization of the former models on unseen patients was of overall low accuracy, except for the intra-individual models. ACC was associated with “increased motor activity” (NMI&gt;0.55), “insomnia” (NMI=0.6), and “motor inhibition” (NMI=0.75). EDA was associated with “aggressive behavior” (NMI=1.0) and “psychic anxiety” (NMI=0.52).Conclusions: Physiological data from wearables show potential to identify mood episodes and specific symptoms of mania and depression quantitatively, both in BD and MDD. Motor activity and stress-related physiological data (EDA and HR) stand out as potential digital biomarkers for predicting mania and depression, respectively. These findings represent a promising pathway toward personalized psychiatry, in which physiological wearable data could allow the early identification and intervention of mood episodes

Cariprazine specificity profile in the treatment of acute schizophrenia: A meta-Analysis and meta-regression of randomized-controlled trials

Cariprazine is a new dopamine D2 and D3 receptor partial agonist antipsychotic. Meta-Analytic evidence of efficacy in acute schizophrenia and specific groups of patients is lacking. We carried out a meta-Analysis in patients with acute schizophrenia to evaluate the efficacy of cariprazine over placebo and active comparators in overall symptoms, positive and negative symptoms and quality of life. Low and high (\ue2\u89\ua56 mg/day) doses were tested separately. The possible effect of clinical-demographic modulators was also tested. Four studies (2144 patients) were included. Both high and low cariprazine doses proved superior to placebo in all symptom domains. The standardized mean difference (SMD) to placebo showed a modest impact on overall symptoms compared with meta-Analytic results for other antipsychotics (SMD was similar to lurasidone, asenapine, ziprasidone and aripiprazole, but lower than risperidone, quetiapine and olanzapine). The SMD to placebo on negative symptoms was superior to many antipsychotics including aripiprazole, with a slightly more relevant effect of cariprazine low doses. This effect was probably on secondary negative symptoms since the short-Term follow-up of the studies included. Meta-regression data further refined the compound clinical profile, suggesting that cariprazine may be particularly useful in young patients with a relatively short duration of disease

Genetics of resilience: Implications from genome‐wide association studies and candidate genes of the stress response system in posttraumatic stress disorder and depression

n/