Dataset Information

Protocol Across study: longitudinal transdiagnostic cognitive functioning, psychiatric symptoms, and biological parameters in patients with a psychiatric disorder.

ABSTRACT: 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.

SUBMITTER: Nieman DH

PROVIDER: S-EPMC7216345 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Protocol Across study: longitudinal transdiagnostic cognitive functioning, psychiatric symptoms, and biological parameters in patients with a psychiatric disorder.

Nieman Dorien H DH Chavez-Baldini UnYoung U Vulink Nienke C NC Smit Dirk J A DJA van Wingen Guido G de Koning Pelle P Sutterland Arjen L AL Mocking Roel J T RJT Bockting Claudi C Verweij Karin J H KJH Lok Anja A Denys Damiaan D

BMC psychiatry 20200511 1

<h4>Background</h4>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 inve ...[more]

PMID: 32393362

Similar Datasets

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.

Project description:BackgroundEarlier age of pubertal maturation in females is associated with increased risk for mental health problems in adolescence, compared with on-time or later maturation. However, most investigations of pubertal timing and mental health consider risk for individual disorders and fail to account for comorbidity. A latent-modeling approach using a large, nationally representative sample could better explain the transdiagnostic nature of the consequences of early-onset puberty.MethodsData on age of menarche and mental disorders were drawn from a population-representative sample of adolescents (n=4925), ages 13-17. Confirmatory factor analysis was used to fit four latent disorder categories: distress, eating, and externalizing, and fear disorders. Timing of menarche included those with earlier (age≤10, age 11) and later age of onset (age 13, 14+), relative to those with average timing of menarche (age 12). Associations between timing of menarche and latent disorders were estimated in a structural equation model (SEM), adjusted for age, income, race, parent marital status, BMI, and childhood adversity.ResultsThe measurement model evidenced acceptable fit (CFI=0.91; RMSEA=0.02). Onset of menarche before age 11 was significantly associated with distress disorders (coefficient=0.096; p<0.0001), fear disorders (coefficient=0.09; p<0.0001), and externalizing disorders (coefficient=0.039; p=0.049) as compared to on-time or late menarche. No residual associations of early menarche with individual disorders over and above the latent disorders were observed.ConclusionThe latent modeling approach illuminated meaningful transdiagnostic psychiatric associations with early timing of menarche. Biological processes initiated at puberty can influence cognitive and affective processes as well as social relationships for adolescents. Under developmentally normative conditions, these changes may be adaptive. However, for those out of sync with their peers, researchers and clinicians should recognize the potential for these processes to influence liability to a broad array of psychopathological consequences in adolescence.

Dataset Information

Protocol Across study: longitudinal transdiagnostic cognitive functioning, psychiatric symptoms, and biological parameters in patients with a psychiatric disorder.

Publications

Protocol Across study: longitudinal transdiagnostic cognitive functioning, psychiatric symptoms, and biological parameters in patients with a psychiatric disorder.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets