Dataset Information

An Investigation of Psychosis Subgroups With Prognostic Validation and Exploration of Genetic Underpinnings: The PsyCourse Study.

ABSTRACT:

Importance

Identifying psychosis subgroups could improve clinical and research precision. Research has focused on symptom subgroups, but there is a need to consider a broader clinical spectrum, disentangle illness trajectories, and investigate genetic associations.

Objective

To detect psychosis subgroups using data-driven methods and examine their illness courses over 1.5 years and polygenic scores for schizophrenia, bipolar disorder, major depression disorder, and educational achievement.

Design, setting, and participants

This ongoing multisite, naturalistic, longitudinal (6-month intervals) cohort study began in January 2012 across 18 sites. Data from a referred sample of 1223 individuals (765 in the discovery sample and 458 in the validation sample) with DSM-IV diagnoses of schizophrenia, bipolar affective disorder (I/II), schizoaffective disorder, schizophreniform disorder, and brief psychotic disorder were collected from secondary and tertiary care sites. Discovery data were extracted in September 2016 and analyzed from November 2016 to January 2018, and prospective validation data were extracted in October 2018 and analyzed from January to May 2019.

Main outcomes and measures

A clinical battery of 188 variables measuring demographic characteristics, clinical history, symptoms, functioning, and cognition was decomposed using nonnegative matrix factorization clustering. Subtype-specific illness courses were compared with mixed models and polygenic scores with analysis of covariance. Supervised learning was used to replicate results in validation data with the most reliably discriminative 45 variables.

Results

Of the 765 individuals in the discovery sample, 341 (44.6%) were women, and the mean (SD) age was 42.7 (12.9) years. Five subgroups were found and labeled as affective psychosis (n?=?252), suicidal psychosis (n?=?44), depressive psychosis (n?=?131), high-functioning psychosis (n?=?252), and severe psychosis (n?=?86). Illness courses with significant quadratic interaction terms were found for psychosis symptoms (R2?=?0.41; 95% CI, 0.38-0.44), depression symptoms (R2?=?0.28; 95% CI, 0.25-0.32), global functioning (R2?=?0.16; 95% CI, 0.14-0.20), and quality of life (R2?=?0.20; 95% CI, 0.17-0.23). The depressive and severe psychosis subgroups exhibited the lowest functioning and quadratic illness courses with partial recovery followed by reoccurrence of severe illness. Differences were found for educational attainment polygenic scores (mean [SD] partial ?2?=?0.014 [0.003]) but not for diagnostic polygenic risk. Results were largely replicated in the validation cohort.

Conclusions and relevance

Psychosis subgroups were detected with distinctive clinical signatures and illness courses and specificity for a nondiagnostic genetic marker. New data-driven clinical approaches are important for future psychosis taxonomies. The findings suggest a need to consider short-term to medium-term service provision to restore functioning in patients stratified into the depressive and severe psychosis subgroups.

SUBMITTER: Dwyer DB

PROVIDER: S-EPMC7042925 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Publications

An Investigation of Psychosis Subgroups With Prognostic Validation and Exploration of Genetic Underpinnings: The PsyCourse Study.

Dwyer Dominic B DB Kalman Janos L JL Budde Monika M Kambeitz Joseph J Ruef Anne A Antonucci Linda A LA Kambeitz-Ilankovic Lana L Hasan Alkomiet A Kondofersky Ivan I Anderson-Schmidt Heike H Gade Katrin K Reich-Erkelenz Daniela D Adorjan Kristina K Senner Fanny F Schaupp Sabrina S Andlauer Till F M TFM Comes Ashley L AL Schulte Eva C EC Klöhn-Saghatolislam Farah F Gryaznova Anna A Hake Maria M Bartholdi Kim K Flatau-Nagel Laura L Reitt Markus M Quast Silke S Stegmaier Sophia S Meyers Milena M Emons Barbara B Haußleiter Ida Sybille IS Juckel Georg G Nieratschker Vanessa V Dannlowski Udo U Yoshida Tomoya T Schmauß Max M Zimmermann Jörg J Reimer Jens J Wiltfang Jens J Reininghaus Eva E Anghelescu Ion-George IG Arolt Volker V Baune Bernhard T BT Konrad Carsten C Thiel Andreas A Fallgatter Andreas J AJ Figge Christian C von Hagen Martin M Koller Manfred M Lang Fabian U FU Wigand Moritz E ME Becker Thomas T Jäger Markus M Dietrich Detlef E DE Scherk Harald H Spitzer Carsten C Folkerts Here H Witt Stephanie H SH Degenhardt Franziska F Forstner Andreas J AJ Rietschel Marcella M Nöthen Markus M MM Mueller Nikola N Papiol Sergi S Heilbronner Urs U Falkai Peter P Schulze Thomas G TG Koutsouleris Nikolaos N

JAMA psychiatry 20200501 5

<h4>Importance</h4>Identifying psychosis subgroups could improve clinical and research precision. Research has focused on symptom subgroups, but there is a need to consider a broader clinical spectrum, disentangle illness trajectories, and investigate genetic associations.<h4>Objective</h4>To detect psychosis subgroups using data-driven methods and examine their illness courses over 1.5 years and polygenic scores for schizophrenia, bipolar disorder, major depression disorder, and educational ach ...[more]

PMID: 32049274

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Dataset Information

An Investigation of Psychosis Subgroups With Prognostic Validation and Exploration of Genetic Underpinnings: The PsyCourse Study.

Importance

Objective

Design, setting, and participants

Main outcomes and measures

Results

Conclusions and relevance

Publications

An Investigation of Psychosis Subgroups With Prognostic Validation and Exploration of Genetic Underpinnings: The PsyCourse Study.

Similar Datasets

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