An Investigation of Psychosis Subgroups With Prognostic Validation and Exploration of Genetic Underpinnings - The PsyCourse Study
Standard
An Investigation of Psychosis Subgroups With Prognostic Validation and Exploration of Genetic Underpinnings - The PsyCourse Study. / Dwyer, Dominic B; Kalman, Janos L; Budde, Monika; Kambeitz, Joseph; Ruef, Anne; Antonucci, Linda A; Kambeitz-Ilankovic, Lana; Hasan, Alkomiet; Kondofersky, Ivan; Anderson-Schmidt, Heike; Gade, Katrin; Reich-Erkelenz, Daniela; Adorjan, Kristina; Senner, Fanny; Schaupp, Sabrina; Andlauer, Till F M; Comes, Ashley L; Schulte, Eva C; Klöhn-Saghatolislam, Farah; Gryaznova, Anna; Hake, Maria; Bartholdi, Kim; Flatau-Nagel, Laura; Reitt, Markus; Quast, Silke; Stegmaier, Sophia; Meyers, Milena; Emons, Barbara; Haußleiter, Ida Sybille; Juckel, Georg; Nieratschker, Vanessa; Dannlowski, Udo; Yoshida, Tomoya; Schmauß, Max; Zimmermann, Jörg; Reimer, Jens; Wiltfang, Jens; Reininghaus, Eva; Anghelescu, Ion-George; Arolt, Volker; Baune, Bernhard T; Konrad, Carsten; Thiel, Andreas; Fallgatter, Andreas J; Figge, Christian; von Hagen, Martin; Koller, Manfred; Lang, Fabian U; Wigand, Moritz E; Becker, Thomas; Jäger, Markus; Dietrich, Detlef E; Scherk, Harald; Spitzer, Carsten; Folkerts, Here; Witt, Stephanie H; Degenhardt, Franziska; Forstner, Andreas J; Rietschel, Marcella; Nöthen, Markus M; Mueller, Nikola; Papiol, Sergi; Heilbronner, Urs; Falkai, Peter; Schulze, Thomas G; Koutsouleris, Nikolaos.
In: JAMA PSYCHIAT, Vol. 77, No. 5, 01.05.2020, p. 523-533.Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review
Harvard
APA
Vancouver
Bibtex
}
RIS
TY - JOUR
T1 - An Investigation of Psychosis Subgroups With Prognostic Validation and Exploration of Genetic Underpinnings - The PsyCourse Study
AU - Dwyer, Dominic B
AU - Kalman, Janos L
AU - Budde, Monika
AU - Kambeitz, Joseph
AU - Ruef, Anne
AU - Antonucci, Linda A
AU - Kambeitz-Ilankovic, Lana
AU - Hasan, Alkomiet
AU - Kondofersky, Ivan
AU - Anderson-Schmidt, Heike
AU - Gade, Katrin
AU - Reich-Erkelenz, Daniela
AU - Adorjan, Kristina
AU - Senner, Fanny
AU - Schaupp, Sabrina
AU - Andlauer, Till F M
AU - Comes, Ashley L
AU - Schulte, Eva C
AU - Klöhn-Saghatolislam, Farah
AU - Gryaznova, Anna
AU - Hake, Maria
AU - Bartholdi, Kim
AU - Flatau-Nagel, Laura
AU - Reitt, Markus
AU - Quast, Silke
AU - Stegmaier, Sophia
AU - Meyers, Milena
AU - Emons, Barbara
AU - Haußleiter, Ida Sybille
AU - Juckel, Georg
AU - Nieratschker, Vanessa
AU - Dannlowski, Udo
AU - Yoshida, Tomoya
AU - Schmauß, Max
AU - Zimmermann, Jörg
AU - Reimer, Jens
AU - Wiltfang, Jens
AU - Reininghaus, Eva
AU - Anghelescu, Ion-George
AU - Arolt, Volker
AU - Baune, Bernhard T
AU - Konrad, Carsten
AU - Thiel, Andreas
AU - Fallgatter, Andreas J
AU - Figge, Christian
AU - von Hagen, Martin
AU - Koller, Manfred
AU - Lang, Fabian U
AU - Wigand, Moritz E
AU - Becker, Thomas
AU - Jäger, Markus
AU - Dietrich, Detlef E
AU - Scherk, Harald
AU - Spitzer, Carsten
AU - Folkerts, Here
AU - Witt, Stephanie H
AU - Degenhardt, Franziska
AU - Forstner, Andreas J
AU - Rietschel, Marcella
AU - Nöthen, Markus M
AU - Mueller, Nikola
AU - Papiol, Sergi
AU - Heilbronner, Urs
AU - Falkai, Peter
AU - Schulze, Thomas G
AU - Koutsouleris, Nikolaos
PY - 2020/5/1
Y1 - 2020/5/1
N2 - 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 η2 = 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.
AB - 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 η2 = 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.
U2 - 10.1001/jamapsychiatry.2019.4910
DO - 10.1001/jamapsychiatry.2019.4910
M3 - SCORING: Journal article
C2 - 32049274
VL - 77
SP - 523
EP - 533
JO - JAMA PSYCHIAT
JF - JAMA PSYCHIAT
SN - 2168-622X
IS - 5
ER -