Gender Differences in Cognitive and Personality Functioning in Patients With Substance Use Disorder

Objectives: Substance abuse is associated with impairments in cognition and many serious physical and behavioral consequences both in men and women. Gender differences, however, are not clear. The aim of this study was to examine gender differences in specific neuropsychological measures and personality variables in a sample of single and polysubstance patients.Methods: A total of 164 hospitalized patients—97 men and 67 women—underwent neuropsychological tests of verbal capacity, attention, speed of processing, perceptual reasoning, memory and learning, executive functioning, and inhibitory capacity. Personality was measured using the Minnesota Multiphasic Personality Inventory. Associations between neuropsychological measures, personality variables, and gender differences were studied using multiway analysis of covariance controlled for regular substance use in years, onset age of regular substance use, polysubstance use, and education level.Results: After adjustment, all the differences between men and women disappeared in the neuropsychological tests. Men reported higher values of somatisation and emotions of depression and anxiety than women. Men were also more suspicious and elicited more disturbed thinking than women.Conclusions: Contrary to previous studies, women are not more vulnerable to the effects of substance use compared with men. Notably, men are more vulnerable to negative emotions than women.</p

Onset age of substance use and neuropsychological performance in hospital patients

Objective: Several studies have found neurocognitive deficits in adolescents following substance abuse. Predisposing risk factors may further impact vulnerability to neurocognitive deficits. Little is known about the cognitive performance of adult onset substance users compared to earlier onset users. This study aims to explore differencesin neuropsychological functioning between early (EOAs) and late onset substance abusers (LOAs) when the effects of confounding factors are controlled.Method: Data for this cross-sectional study was collected from hospital patients. A total of 164 patients with substance use disorder (SUD) aged 19 to 65, 76 with single-drug diagnosis and 88 with multidrug diagnosis, underwent neuropsychological tests for verbal capacity, attention, speed of processing, perceptual reasoning, memory and learning, executive functioning, and inhibitory capacity. Associations between regular onset age and neuropsychological measures were analysed using in multi-way ANCOVA, and the effect of age, multiple substance abuse, education level and learning difficulties were controlled.Results: Compared with LOAs, EOAs had weaker performance in the Digit Symbol test for mono-substance users. Meanwhile, compared with EOAs, LOAs had weaker performance in the Delayed Visual Memory test and the Raven test for mono-substance users, and the Block Design test for poly-substance users. From the confounding factors, early onset age of substance use is heightened among individuals with learning disabilities.Conclusions: Onset age of substance use is related to the deterioration of performance in neuropsychological tests. Premorbid poor learning and inhibitory capacity may be important predisposing risk factors of SUD. Conversely, high level of education may be a protective factor for cognitive performance in patients with SUD

A study on the association of psychiatric diagnoses and childhood adversities with suicide risk

Background: In addition to psychiatric disorders, childhood adversities may increase the risk of suicidal behavior. In previous studies, the effects of clinical co-morbidity and overlap of childhood adversities has rarely been taken into account. Aim: The study aims to search associations of psychiatric diagnoses and childhood adversities and trauma (CAT) with suicide risk. Methods: Altogether 415 adult patients attending primary and psychiatric outpatient care filled in the Trauma and Distress Scale, including assessment of five core CAT domains (emotional, physical and sexual abuse, and emotional and physical neglect). The study patients' current psychiatric disorders and suicide risk were assessed by the Mini International Neuropsychiatric Interview. Results: Age, poor perceived health, poor social support, current psychiatric treatment, all psychiatric disorders, except hypomania, emotional and physical abuse, and emotional neglect did associate significantly with suicide risk. Number of psychiatric disorders and CAT domains had dose-dependent effects on suicide risk. In multivariate analysis, current psychiatric treatment, current and life-time major depression, social phobia, alcohol, and drug dependency, as well as emotional abuse had direct associations with suicide risk. In females, manic disorders and drug dependence, and in males, dysthymia, social phobia, and emotional abuse associated with suicide risk. Conclusions: Psychiatric disorders and most CAT domains associate with suicide risk. However, when the effect of co-morbidity and overlap of CAT domains is controlled, major depression, social phobia, alcohol, and drug dependency and emotional abuse seem to increase the risk of suicide. The risk profile varies between the genders.</div

Extrapyramidal symptoms predict cognitive performance after first-episode psychosis

Publisher Copyright: © 2022, The Author(s).Extrapyramidal (EP) symptoms such as tremor, rigidity, and bradykinesia are common side effects of most antipsychotics, and may associate with impaired performance in neurocognitive testing. We studied EP symptoms in first-episode psychosis (FEP; n = 113). Cognitive testing and EP symptoms (three items of the Simpson-Angus Scale) were assessed at baseline and follow-up (mean follow-up time 12 months). Mild EP symptoms were present at treatment onset in 40% of the participants. EP symptoms were related with lower performance in neurocognitive testing at baseline and at follow-up, especially among those with nonaffective psychotic disorder, and especially in tasks requiring speed of processing. No associations between EP symptoms and social cognition were detected. In linear regression models, when positive and negative symptom levels and chlorpromazine equivalents were accounted for, baseline EP symptoms were associated with worse baseline global neurocognition and visuomotor performance. Baseline EP symptoms also longitudinally predicted global, verbal, and visuomotor cognition. However, there were no cross-sectional associations between EP symptoms and cognitive performance at follow-up. In sum, we found both cross-sectional and longitudinal associations between EP symptoms and neurocognitive task performance in the early course of psychosis. Those without EP symptoms at the start of treatment had higher baseline and follow-up neurocognitive performance. Even mild EP symptoms may represent early markers of long-term neurocognitive impairment.Peer reviewe

Metabolic trajectories in childhood and adolescence : Effects on risk for schizophrenia

Abnormal glucose and lipid metabolism is common in antipsychotic-naive first-episode patients with schizophrenia, but it is unclear whether these changes can already be seen in premorbid or prodromal period, before the first psychotic episode. We examined insulin, total cholesterol, low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, and triglyceride trajectories in children and adolescents (9–18 years old), who were later diagnosed with schizophrenia, any non-affective psychosis (NAP) or affective disorder (AD). The study population consisted of a general population-based cohort “The Cardiovascular Risk in Young Finns Study”, started in 1980 (n = 3596). Psychiatric diagnoses were derived from the Health Care Register up to the year 2018. Multivariate statistical analysis indicated no significant differences in insulin or lipid levels in children and adolescents who later developed schizophrenia (n = 41) compared to the cohort control group (n = 3202). In addition, no changes in these parameters were seen in the NAP (n = 74) or AD (n = 156) groups compared to the controls, but lower triglyceride levels in childhood/adolescence associated with earlier diagnosis of psychotic disorder in the NAP group. Taken together, our results do not support any gross-level insulin or lipid changes during childhood and adolescence in individuals with later diagnosis of schizophrenia-spectrum disorder. Since changes in glucose and lipid metabolism can be observed in neuroleptic-naive patients with schizophrenia, we hypothesize that the more marked metabolic changes develop during the prodrome closer to the onset of the first psychotic episode. The findings have relevance for studies on developmental hypotheses of schizophrenia.publishedVersionPeer reviewe

The impact of visual dysfunctions in recent-onset psychosis and clinical high-risk state for psychosis.

Subtle subjective visual dysfunctions (VisDys) are reported by about 50% of patients with schizophrenia and are suggested to predict psychosis states. Deeper insight into VisDys, particularly in early psychosis states, could foster the understanding of basic disease mechanisms mediating susceptibility to psychosis, and thereby inform preventive interventions. We systematically investigated the relationship between VisDys and core clinical measures across three early phase psychiatric conditions. Second, we used a novel multivariate pattern analysis approach to predict VisDys by resting-state functional connectivity within relevant brain systems. VisDys assessed with the Schizophrenia Proneness Instrument (SPI-A), clinical measures, and resting-state fMRI data were examined in recent-onset psychosis (ROP, n = 147), clinical high-risk states of psychosis (CHR, n = 143), recent-onset depression (ROD, n = 151), and healthy controls (HC, n = 280). Our multivariate pattern analysis approach used pairwise functional connectivity within occipital (ON) and frontoparietal (FPN) networks implicated in visual information processing to predict VisDys. VisDys were reported more often in ROP (50.34%), and CHR (55.94%) than in ROD (16.56%), and HC (4.28%). Higher severity of VisDys was associated with less functional remission in both CHR and ROP, and, in CHR specifically, lower quality of life (Qol), higher depressiveness, and more severe impairment of visuospatial constructability. ON functional connectivity predicted presence of VisDys in ROP (balanced accuracy 60.17%, p = 0.0001) and CHR (67.38%, p = 0.029), while in the combined ROP + CHR sample VisDys were predicted by FPN (61.11%, p = 0.006). These large-sample study findings suggest that VisDys are clinically highly relevant not only in ROP but especially in CHR, being closely related to aspects of functional outcome, depressiveness, and Qol. Findings from multivariate pattern analysis support a model of functional integrity within ON and FPN driving the VisDys phenomenon and being implicated in core disease mechanisms of early psychosis states

Neurobiologically Based Stratification of Recent Onset Depression and Psychosis: Identification of Two Distinct Transdiagnostic Phenotypes

Background Identifying neurobiologically based transdiagnostic categories of depression and psychosis may elucidate heterogeneity, and provide better candidates for predictive modelling. We aimed to identify clusters across patients with recent onset depression (ROD) and recent onset psychosis (ROP) based on structural neuroimaging data. We hypothesized that these transdiagnostic clusters would identify patients with poor outcome and allow more accurate prediction of symptomatic remission than traditional diagnostic structures. Methods HYDRA (HeterogeneitY through DiscRiminant Analysis) was trained on whole brain volumetric measures from 577 participants from the discovery sample of the multi-site PRONIA study to identify neurobiologically driven clusters which were then externally validated in the PRONIA replication sample (n=404) and three datasets of chronic samples (COBRE, n=146; MCIC, n=202; MUC, n=470). Results The optimal clustering solution was two transdiagnostic clusters (Cluster 1, n=153, 67 ROP, 86 ROD and Cluster 2, n=149, 88 ROP, 61 ROD; ARI=.618). The two clusters contained both ROP and ROD. One cluster had widespread GMV deficits, more positive, negative, and functional deficits (impaired cluster) and one cluster revealed a more preserved neuroanatomical signature and more ‘core’ depressive symptomatology (preserved cluster). The clustering solution was internally and externally validated and assessed for clinical utility in predicting 9-month symptomatic remission -outperforming traditional diagnostic structures. Conclusions We identified two transdiagnostic neuroanatomically informed clusters which are clinically and biologically distinct, challenging current diagnostic boundaries in recent onset mental health disorders. These results may aid understanding of aetiology of poor outcome patients transdiagnostically and improve development of stratified treatments

Traces of trauma – a multivariate pattern analysis of childhood trauma, brain structure and clinical phenotypes

Background: Childhood trauma (CT) is a major yet elusive psychiatric risk factor, whose multidimensional conceptualization and heterogeneous effects on brain morphology might demand advanced mathematical modeling. Therefore, we present an unsupervised machine learning approach to characterize the clinical and neuroanatomical complexity of CT in a larger, transdiagnostic context. Methods: We used a multicenter European cohort of 1076 female and male individuals (discovery: n = 649; replication: n = 427) comprising young, minimally medicated patients with clinical high-risk states for psychosis; patients with recent-onset depression or psychosis; and healthy volunteers. We employed multivariate sparse partial least squares analysis to detect parsimonious associations between combinations of items from the Childhood Trauma Questionnaire and gray matter volume and tested their generalizability via nested cross-validation as well as via external validation. We investigated the associations of these CT signatures with state (functioning, depressivity, quality of life), trait (personality), and sociodemographic levels. Results: We discovered signatures of age-dependent sexual abuse and sex-dependent physical and sexual abuse, as well as emotional trauma, which projected onto gray matter volume patterns in prefronto-cerebellar, limbic, and sensory networks. These signatures were associated with predominantly impaired clinical state- and trait-level phenotypes, while pointing toward an interaction between sexual abuse, age, urbanicity, and education. We validated the clinical profiles for all three CT signatures in the replication sample. Conclusions: Our results suggest distinct multilayered associations between partially age- and sex-dependent patterns of CT, distributed neuroanatomical networks, and clinical profiles. Hence, our study highlights how machine learning approaches can shape future, more fine-grained CT research