Ontology highlight
ABSTRACT:
SUBMITTER: Smigielski L
PROVIDER: S-EPMC8626446 | biostudies-literature | 2021 Nov
REPOSITORIES: biostudies-literature

Smigielski Lukasz L Papiol Sergi S Theodoridou Anastasia A Heekeren Karsten K Gerstenberg Miriam M Wotruba Diana D Buechler Roman R Hoffmann Per P Herms Stefan S Adorjan Kristina K Anderson-Schmidt Heike H Budde Monika M Comes Ashley L AL Gade Katrin K Heilbronner Maria M Heilbronner Urs U Kalman Janos L JL Klöhn-Saghatolislam Farahnaz F Reich-Erkelenz Daniela D Schaupp Sabrina K SK Schulte Eva C EC Senner Fanny F Anghelescu Ion-George IG Arolt Volker V Baune Bernhard T BT Dannlowski Udo U Dietrich Detlef E DE Fallgatter Andreas J AJ Figge Christian C Jäger Markus M Juckel Georg G Konrad Carsten C Nieratschker Vanessa V Reimer Jens J Reininghaus Eva E Schmauß Max M Spitzer Carsten C von Hagen Martin M Wiltfang Jens J Zimmermann Jörg J Gryaznova Anna A Flatau-Nagel Laura L Reitt Markus M Meyers Milena M Emons Barbara B Haußleiter Ida Sybille IS Lang Fabian U FU Becker Thomas T Wigand Moritz E ME Witt Stephanie H SH Degenhardt Franziska F Forstner Andreas J AJ Rietschel Marcella M Nöthen Markus M MM Andlauer Till F M TFM Rössler Wulf W Walitza Susanne S Falkai Peter P Schulze Thomas G TG Grünblatt Edna E
Translational psychiatry 20211126 1
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 ...[more]