TY  - JOUR
AU  - Smigielski, Lukasz
AU  - Papiol, Sergi
AU  - Theodoridou, Anastasia
AU  - Heekeren, Karsten
AU  - Gerstenberg, Miriam
AU  - Wotruba, Diana
AU  - Buechler, Roman
AU  - Hoffmann, Per
AU  - Herms, Stefan
AU  - Adorjan, Kristina
AU  - Anderson-Schmidt, Heike
AU  - Budde, Monika
AU  - Comes, Ashley L.
AU  - Gade, Katrin
AU  - Heilbronner, Maria
AU  - Heilbronner, Urs
AU  - Kalman, Janos L.
AU  - Klöhn-Saghatolislam, Farahnaz
AU  - Reich-Erkelenz, Daniela
AU  - Schaupp, Sabrina K.
AU  - Schulte, Eva C.
AU  - Senner, Fanny
AU  - Anghelescu, Ion-George
AU  - Arolt, Volker
AU  - Baune, Bernhard T.
AU  - Dannlowski, Udo
AU  - Dietrich, Detlef E.
AU  - Fallgatter, Andreas J.
AU  - Figge, Christian
AU  - Jäger, Markus
AU  - Juckel, Georg
AU  - Konrad, Carsten
AU  - Nieratschker, Vanessa
AU  - Reimer, Jens
AU  - Reininghaus, Eva
AU  - Schmauß, Max
AU  - Spitzer, Carsten
AU  - von Hagen, Martin
AU  - Wiltfang, Jens
AU  - Zimmermann, Jörg
AU  - Gryaznova, Anna
AU  - Flatau-Nagel, Laura
AU  - Reitt, Markus
AU  - Meyers, Milena
AU  - Emons, Barbara
AU  - Haußleiter, Ida Sybille
AU  - Lang, Fabian U.
AU  - Becker, Thomas
AU  - Wigand, Moritz E.
AU  - Witt, Stephanie H.
AU  - Degenhardt, Franziska
AU  - Forstner, Andreas J.
AU  - Rietschel, Marcella
AU  - Nöthen, Markus M.
AU  - Andlauer, Till F. M.
AU  - Rössler, Wulf
AU  - Walitza, Susanne
AU  - Falkai, Peter
AU  - Schulze, Thomas G.
AU  - Grünblatt, Edna
TI  - Polygenic risk scores across the extended psychosis spectrum
JO  - Translational Psychiatry
VL  - 11
IS  - 1
SN  - 2158-3188
CY  - London
PB  - Nature Publishing Group
M1  - FZJ-2021-05143
SP  - 600
PY  - 2021
AB  - As early detection of symptoms in the subclinical to clinical psychosis spectrum may improve health outcomes, knowing the probabilistic susceptibility of developing a disorder could guide mitigation measures and clinical intervention. In this context, polygenic risk scores (PRSs) quantifying the additive effects of multiple common genetic variants hold the potential to predict complex diseases and index severity gradients. PRSs for schizophrenia (SZ) and bipolar disorder (BD) were computed using Bayesian regression and continuous shrinkage priors based on the latest SZ and BD genome-wide association studies (Psychiatric Genomics Consortium, third release). Eight well-phenotyped groups (n = 1580; 56% males) were assessed: control (n = 305), lower (n = 117) and higher (n = 113) schizotypy (both groups of healthy individuals), at-risk for psychosis (n = 120), BD type-I (n = 359), BD type-II (n = 96), schizoaffective disorder (n = 86), and SZ groups (n = 384). PRS differences were investigated for binary traits and the quantitative Positive and Negative Syndrome Scale. Both BD-PRS and SZ-PRS significantly differentiated controls from at-risk and clinical groups (Nagelkerke’s pseudo-R2: 1.3–7.7%), except for BD type-II for SZ-PRS. Out of 28 pairwise comparisons for SZ-PRS and BD-PRS, 9 and 12, respectively, reached the Bonferroni-corrected significance. BD-PRS differed between control and at-risk groups, but not between at-risk and BD type-I groups. There was no difference between controls and schizotypy. SZ-PRSs, but not BD-PRSs, were positively associated with transdiagnostic symptomology. Overall, PRSs support the continuum model across the psychosis spectrum at the genomic level with possible irregularities for schizotypy. The at-risk state demands heightened clinical attention and research addressing symptom course specifiers. Continued efforts are needed to refine the diagnostic and prognostic accuracy of PRSs in mental healthcare.
LB  - PUB:(DE-HGF)16
C6  - pmid:34836939
UR  - <Go to ISI:>//WOS:000722844000001
DO  - DOI:10.1038/s41398-021-01720-0
UR  - https://juser.fz-juelich.de/record/903471
ER  -