Associations between aversive learning processes and transdiagnostic psychiatric symptoms in a general population sample.
Ontology highlight
ABSTRACT:
SUBMITTER: Wise T
PROVIDER: S-EPMC7443146 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Non-intrusive, easy-to-use and pragmatic collection of biological processes is warranted to evaluate potential biomarkers of psychiatric symptoms. Prior work with relatively modest sample sizes suggests that under highly-controlled sampling conditions, volatile organic compounds extracted from the human breath (exhalome), often measured by an electronic nose ("e-nose"), may be related to physical and mental health. The present study utilized a streamlined data collection approach and attempted to replicate and extend prior e-nose links to mental health in a standard research setting within large transdiagnostic community dataset (N = 1207; 746 females; 18-61 years) who completed a screening visit at the Laureate Institute for Brain Research between 07/2016 and 05/2018. Factor analysis was used to obtain latent exhalome variables, and machine learning approaches were employed using these latent variables to predict three types of symptoms independent of each other (depression, anxiety, and substance use disorder) within separate training and a test sets. After adjusting for age, gender, body mass index, and smoking status, the best fitting algorithm produced by the training set accounted for nearly 0% of the test set's variance. In each case the standard error included the zero line, indicating that models were not predictive of clinical symptoms. Although some sample variance was predicted, findings did not generalize to out-of-sample data. Based on these findings, we conclude that the exhalome, as measured by the e-nose within a less-controlled environment than previously reported, is not able to provide clinically useful assessments of current depression, anxiety or substance use severity.
| S-EPMC7524957 | biostudies-literature
Project description:Psychiatric disorders show heterogeneous symptoms and trajectories, with current nosology not accurately reflecting their molecular etiology and the variability and symptomatic overlap within and between diagnostic classes. This heterogeneity impedes timely and targeted treatment. Our study aimed to identify psychiatric patient clusters that share clinical and genetic features and may profit from similar therapies. We used high-dimensional data clustering on deep clinical data to identify transdiagnostic groups in a discovery sample (N = 1250) of healthy controls and patients diagnosed with depression, bipolar disorder, schizophrenia, schizoaffective disorder, and other psychiatric disorders. We observed five diagnostically mixed clusters and ordered them based on severity. The least impaired cluster 0, containing most healthy controls, showed general well-being. Clusters 1-3 differed predominantly regarding levels of maltreatment, depression, daily functioning, and parental bonding. Cluster 4 contained most patients diagnosed with psychotic disorders and exhibited the highest severity in many dimensions, including medication load. Depressed patients were present in all clusters, indicating that we captured different disease stages or subtypes. We replicated all but the smallest cluster 1 in an independent sample (N = 622). Next, we analyzed genetic differences between clusters using polygenic scores (PGS) and the psychiatric family history. These genetic variables differed mainly between clusters 0 and 4 (prediction area under the receiver operating characteristic curve (AUC) = 81%; significant PGS: cross-disorder psychiatric risk, schizophrenia, and educational attainment). Our results confirm that psychiatric disorders consist of heterogeneous subtypes sharing molecular factors and symptoms. The identification of transdiagnostic clusters advances our understanding of the heterogeneity of psychiatric disorders and may support the development of personalized treatments.
| S-EPMC8429672 | biostudies-literature
Project description:IntroductionThe present study examines the relationships between processing speed (PS), mental health disorders, and learning disorders. Prior work has tended to explore relationships between PS deficits and specific diagnoses in isolation of one another. Here, we simultaneously investigated PS associations with five diagnoses (i.e., anxiety, autism, ADHD, depressive, specific learning) in a large-scale, transdiagnostic, community self-referred sample.Method843 children, ages 8-16 were included from the Healthy Brain Network (HBN) Biobank. Principal component analysis (PCA) was employed to create a composite measure of four PS tasks, referred to as PC1. Intraclass correlation coefficient (ICC) between the four PS measures, as well as PC1, were calculated to assess reliability.ResultsICCs were moderate between WISC-V tasks (0.663), and relatively modest between NIH Toolbox Pattern Comparison and other PS scales (0.14-0.27). Regression analyses revealed specific significant relationships between PS and reading and math disabilities, ADHD-inattentive presentation (ADHD-I), and ADHD-combined presentation (ADHD-C). After accounting for inattention, the present study did not find a significant relationship with Autism Spectrum Disorder.DiscussionOur examination of PS in a large, transdiagnostic sample suggested more specific associations with ADHD and learning disorders than the literature currently suggests. Implications for understanding how PS interacts with a highly heterogeneous childhood sample are discussed.
| S-EPMC7308370 | biostudies-literature
Project description:In psychiatric disorders, comorbid depressive symptoms are associated with clinically important issues such as reduced quality of life, a poor prognosis, and increased suicide risk. Previous studies have found a close relationship between insomnia and depressive symptoms in major depressive disorder (MDD), and that actively improving insomnia heightens the improvement of depressive symptoms. This study aimed to investigate whether the association between insomnia and depressive symptoms is also found in other psychiatric disorders besides MDD. The subjects were 144 patients with MDD (n = 71), schizophrenia (n = 25), bipolar disorder (n = 22), or anxiety disorders (n = 26). Sleep status was assessed subjectively and objectively using the Athens Insomnia Scale (AIS) and sleep electroencephalography (EEG), respectively. Sleep EEG was performed using a portable EEG device. Depressive symptoms were assessed using the Beck Depression Inventory. Subjective insomnia, as defined by the AIS, was associated with depressive symptoms in all disorders. Moreover, in schizophrenia, a relation between depressive symptoms and insomnia was also found by objective sleep assessment methods using sleep EEG. Our findings suggest that the association between subjective insomnia and depressive symptoms is a transdiagnostic feature in major psychiatric disorders. Further studies are needed to clarify whether therapeutic interventions for comorbid insomnia can improve depressive symptoms in major psychiatric disorders, similar to MDD.
| S-EPMC10165079 | biostudies-literature
Project description:BACKGROUND:Patients with psychiatric disorders, such as major depressive disorder, schizophrenia or obsessive-compulsive disorder, often suffer from cognitive dysfunction. The nature of these dysfunctions and their relation with clinical symptoms and biological parameters is not yet clear. Traditionally, cognitive dysfunction is studied in patients with specific psychiatric disorders, disregarding the fact that cognitive deficits are shared across disorders. The Across study aims to investigate cognitive functioning and its relation with psychiatric symptoms and biological parameters transdiagnostically and longitudinally. METHODS:The study recruits patients diagnosed with a variety of psychiatric disorders and has a longitudinal cohort design with an assessment at baseline and at one-year follow-up. The primary outcome measure is cognitive functioning. The secondary outcome measures include clinical symptoms, electroencephalographic, genetic and blood markers (e.g., fatty acids), and hair cortisol concentration levels. DISCUSSION:The Across study provides an opportunity for a transdiagnostic, bottom-up, data-driven approach of investigating cognition in relation to symptoms and biological parameters longitudinally in patients with psychiatric disorders. The study may help to find new clusters of symptoms, biological markers, and cognitive dysfunctions that have better prognostic value than the current diagnostic categories. Furthermore, increased insight into the relationship among cognitive deficits, biological parameters, and psychiatric symptoms can lead to new treatment possibilities. TRIAL REGISTRATION:Netherlands Trial Register (NTR): NL8170.
| S-EPMC7216345 | biostudies-literature
Project description:ObjectivesAssociations between androgens and depressive symptoms were mostly reported from cross-sectional and patient-based studies.Study design/main outcome measuresLongitudinal data from 4,110 participants of the Study of Health in Pomerania were used to assess sex-specific associations of baseline total and free testosterone, androstenedione and sex hormone-binding globulin with incident depressive symptoms and cognitive status at 5- and 10-year follow-up.ResultsDespite sex-specific differences in depressive symptoms prevalence at baseline (women: 17.4%, men: 8.1%), cross-sectional analyses showed no associations between sex hormones and depressive symptoms. In age-adjusted longitudinal analyses, total testosterone was associated with incident depressive symptoms (relative risk at 5-year follow-up: 0.73, 95% confidence interval: 0.58-0.92). Similarly, age-adjusted analyses showed a positive association between sex hormone-binding globulin and cognitive status in men (β-coefficient per standard deviation: 0.44, 95% confidence interval: 0.13-0.74). In women, age-adjusted associations of androstenedione with baseline depressive symptoms (relative risk: 0.88, 95% confidence interval: 0.77-0.99) were found. None of the observed associations remained after multivariable adjustment.ConclusionsThe present population-based, longitudinal study revealed inverse associations between sex hormones and depressive symptoms. However, the null finding after multivariable adjustment suggests, that the observed associations were not independent of relevant confounders including body mass index, smoking and physical inactivity. Furthermore, the low number of incident endpoints in our non-clinical population-based sample limited the statistical power and reduced the chance to detect a statistically significant effect.
| S-EPMC5428943 | biostudies-literature
Project description:Classifying eating disorders in youth is challenging in light of developmental considerations and high rates of diagnostic migration. Understanding the transactional relationships among eating disorder symptoms, both across the transdiagnostic spectrum and within specific diagnostic categories, may clarify which core eating disorder symptoms contribute to, and maintain, eating-related psychopathology in youth. We utilized network analysis to investigate interrelationships among eating disorder symptoms in 636 treatment-seeking children and adolescents (90.3% female) ages 6-18 years (M age = 15.4 ± 2.2). An undirected, weighted network of eating disorder symptoms was created using behavioral and attitudinal items from the Eating Disorder Examination. Across diagnostic groups, symptoms reflecting appearance-related concerns (e.g., dissatisfaction with shape and weight) and dietary restraint (e.g., a desire to have an empty stomach) were most strongly associated with other eating disorder symptoms in the network. Binge eating and compensatory behaviors (e.g., self-induced vomiting) were strongly connected to one another but not to other symptoms in the network. Network connectivity was similar across anorexia nervosa, bulimia nervosa, and otherwise specified feeding or eating disorder subgroups. Among treatment-seeking children and adolescents, dietary restraint and shape- and weight-related concerns appear to play key roles in the psychopathology of eating disorders, supporting cognitive-behavioral theories of onset and maintenance. Similarities across diagnostic categories provide support for a transdiagnostic classification scheme. Clinical interventions should seek to disrupt these symptoms early in treatment to achieve maximal outcomes. (PsycINFO Database Record
| S-EPMC5851474 | biostudies-literature
Project description:Maladaptive behavior during approach-avoidance conflict (AAC) is common to multiple psychiatric disorders. Using computational modeling, we previously reported that individuals with depression, anxiety, and substance use disorders (DEP/ANX; SUDs) exhibited differences in decision uncertainty and sensitivity to negative outcomes versus reward (emotional conflict) relative to healthy controls (HCs). However, it remains unknown whether these computational parameters and group differences are stable over time. We analyzed 1-year follow-up data from a subset of the same participants (N = 325) to assess parameter stability and relationships to other clinical and task measures. We assessed group differences in the entire sample as well as a subset matched for age and IQ across HCs (N = 48), SUDs (N = 29), and DEP/ANX (N = 121). We also assessed 2-3 week reliability in a separate sample of 30 HCs. Emotional conflict and decision uncertainty parameters showed moderate 1-year intra-class correlations (.52 and .46, respectively) and moderate to excellent correlations over the shorter period (.84 and .54, respectively). Similar to previous baseline findings, parameters correlated with multiple response time measures (ps < .001) and self-reported anxiety (r = .30, p < .001) and decision difficulty (r = .44, p < .001). Linear mixed effects analyses revealed that patients remained higher in decision uncertainty (SUDs, p = .009) and lower in emotional conflict (SUDs, p = .004, DEP/ANX, p = .02) relative to HCs. This computational modelling approach may therefore offer relatively stable markers of transdiagnostic psychopathology.
| S-EPMC8175390 | biostudies-literature
Project description:ObjectivesNegative psychiatric symptoms are often resistant to treatments, regardless of the disorder in which they appear. One model for a cause of negative symptoms is impairment in higher-order cognition. The current study examined how particular bottom-up and top-down mechanisms of selective attention relate to severity of negative symptoms across a transdiagnostic psychiatric sample.MethodsThe sample consisted of 130 participants: 25 schizophrenia-spectrum disorders, 26 bipolar disorders, 18 unipolar depression, and 61 nonpsychiatric controls. The relationships between attentional event-related potentials following rare visual targets (i.e., N1, N2b, P2a, and P3b) and severity of the negative symptom domains of anhedonia, avolition, and blunted affect were evaluated using frequentist and Bayesian analyses.ResultsP3b and N2b mean amplitudes were inversely related to the Positive and Negative Syndrome Scale-Negative Symptom Factor severity score across the entire sample. Subsequent regression analyses showed a significant negative transdiagnostic relationship between P3b amplitude and blunted affect severity.ConclusionsResults indicate that negative symptoms, and particularly blunted affect, may have a stronger association with deficits in top-down mechanisms of selective attention.SignificanceThis suggests that people with greater severity of blunted affect, independent of diagnosis, do not allocate sufficient cognitive resources when engaging in activities requiring selective attention.
| S-EPMC8223322 | biostudies-literature
Project description:ObjectiveAn integral part of the genetic counselling process is the assessment of psychiatric morbidity. The objectives of this study were first to assess psychometric properties of the General Health Questionnaire (GHQ-28items) in a Spanish sample at increased risk of hereditary cancer, and second evaluated the prevalence of psychiatric morbidity and the contribution of socio-demographic and clinical characteristics to predict distress.MethodsA cross-sectional study was designed with 766 patients. Psychometric analysis with exploratory factor analysis was performed. The influences of socio-demographic characteristics were investigated by multiple linear regression analyses.ResultsFactor analysis supported the four-factor solution of the original GHQ-28; Depression and Social dysfunction scales were more stable than Anxiety and Somatic symptom scales. Psychiatric morbidity was detected in 212 (27.9%) patients. The variables predicting psychiatric morbidity were gender, age, patient affected by cancer, previous psychiatric treatment, and patients with relatives affected by cancer. The higher prevalence of psychiatric symptoms was in the age group from 41 to 59 years (16.73%), women (24.37%), patients affected by cancer (19.89%), patients without previous psychiatric treatment (20.82%), and patients with relatives affected by cancer (21.74%).ConclusionScreening psychological distress should consider socio-demographic and clinical characteristics with reference to improve the quality of care.Trial registrationClinical trials identifier: NCT04428710.
| S-EPMC9270520 | biostudies-literature