Distinct Polygenic Score Profiles in Schizophrenia Subgroups With Different Trajectories of Cognitive Development

• Published in: The American journal of psychiatry Vol. 177; no. 4; pp. 298 - 307
• Main Authors: Dickinson, Dwight, Zaidman, Sofia R, Giangrande, Evan J, Eisenberg, Daniel P, Gregory, Michael D, Berman, Karen F
• Format: Journal Article
• Language: English
• Published: United States American Psychiatric Association 01.04.2020
• Subjects: Adolescent; Adolescent Development; Adult; Attention Deficit Disorder with Hyperactivity - psychology; Attention deficit hyperactivity disorder; Case-Control Studies; Cluster Analysis; Cognition; Cognition & reasoning; Cognitive ability; Cognitive Dysfunction - genetics; Cognitive Dysfunction - psychology; Disease Progression; Educational Status; Female; Genetic Predisposition to Disease; Humans; Intelligence; Intelligence Tests; Male; Middle Aged; Multifactorial Inheritance; Psychosis; Risk; Schizophrenia; Schizophrenia - genetics; Schizophrenia - physiopathology; Schizophrenic Psychology; Siblings - psychology; Young Adult; Schizophrenia; Genetics; Premorbid IQ; Cognition; Developmental Trajectory; Polygenic Score
• ISSN: 0002-953X; 1535-7228; 1535-7228
• DOI: 10.1176/appi.ajp.2019.19050527

Objective:Different cognitive development histories in schizophrenia may reflect variation across dimensions of genetic influence. The authors derived and characterized cognitive development trajectory subgroups within a schizophrenia sample and profiled the subgroups across polygenic scores (PGSs) for schizophrenia, cognition, educational attainment, and attention deficit hyperactivity disorder (ADHD).Methods:Demographic, clinical, and genetic data were collected at the National Institute of Mental Health from 540 schizophrenia patients, 247 unaffected siblings, and 844 control subjects. Cognitive trajectory subgroups were derived through cluster analysis using estimates of premorbid and current IQ. PGSs were generated using standard methods. Associations were tested using general linear models and logistic regression.Results:Cluster analyses identified three cognitive trajectory subgroups in the schizophrenia group: preadolescent cognitive impairment (19%), adolescent disruption of cognitive development (44%), and cognitively stable adolescent development (37%). Together, the four PGSs significantly predicted 7.9% of the variance in subgroup membership. Subgroup characteristics converged with genetic patterns. Cognitively stable individuals had the best adult clinical outcomes and differed from control subjects only in schizophrenia PGSs. Those with adolescent disruption of cognitive development showed the most severe symptoms after diagnosis and were cognitively impaired. This subgroup had the highest schizophrenia PGSs and had disadvantageous cognitive PGSs relative to control subjects and cognitively stable individuals. Individuals showing preadolescent impairment in cognitive and academic performance and poor adult outcome exhibited a generalized PGS disadvantage relative to control subjects and were the only subgroup to differ significantly in education and ADHD PGSs.Conclusions:Subgroups derived from patterns of premorbid and current IQ showed different premorbid and clinical characteristics, which converged with broad genetic profiles. Simultaneous analysis of multiple PGSs may contribute to useful clinical stratification in schizophrenia.