Genetic risk scores and family history as predictors of schizophrenia in Nordic registers

• Published in: Psychological medicine Vol. 48; no. 7; pp. 1201 - 1208
• Main Authors: Lu, Y., Pouget, J. G., Andreassen, O. A., Djurovic, S., Esko, T., Hultman, C. M., Metspalu, A., Milani, L., Werge, T., Sullivan, P. F.
• Format: Journal Article
• Language: English
• Published: Cambridge, UK Cambridge University Press 01.05.2018
• Subjects: Academic achievement; Adult; Autism; Behavior disorders; Bioinformatics; Bipolar disorder; Body mass index; Case-Control Studies; Clinical medicine; Consortia; Epidemiology; Estonia; Family medical history; Female; Genetic Predisposition to Disease; Genetic susceptibility; Genetics; Genome-Wide Association Study; Genomes; Genomics; Genotypes; Genotyping; Health risk assessment; Hospitals; Humans; Liability; Logistic Models; Male; Medical History Taking; Medicin och hälsovetenskap; Mental depression; Mental disorders; Mental health; Middle Aged; Multivariate Analysis; National registers; Original Articles; Psychiatry; Psychosis; Quality control; Registries; Risk assessment; Risk Assessment - methods; Risk Factors; Scandinavian and Nordic Countries; Schizophrenia; Schizophrenia - genetics; Twins; Working groups; Scandinavian and Nordic Countries; Estonia; Denmark; Sweden; United States > US; Norway; genetic risk score; GWAS; genome-wide association; schizophrenia; Family history
• ISSN: 0033-2917; 1469-8978; 1469-8978
• DOI: 10.1017/S0033291717002665

Family history is a long-standing and readily obtainable risk factor for schizophrenia (SCZ). Low-cost genotyping technologies have enabled large genetic studies of SCZ, and the results suggest the utility of genetic risk scores (GRS, direct assessments of inherited common variant risk). Few studies have evaluated family history and GRS simultaneously to ask whether one can explain away the other. We studied 5959 SCZ cases and 8717 controls from four Nordic countries. All subjects had family history data from national registers and genome-wide genotypes that were processed through the quality control procedures used by the Psychiatric Genomics Consortium. Using external training data, GRS were estimated for SCZ, bipolar disorder (BIP), major depression, autism, educational attainment, and body mass index. Multivariable modeling was used to estimate effect sizes. Using harmonized genomic and national register data from Denmark, Estonia, Norway, and Sweden, we confirmed that family history of SCZ and GRS for SCZ and BIP were risk factors for SCZ. In a joint model, the effects of GRS for SCZ and BIP were essentially unchanged, and the effect of family history was attenuated but remained significant. The predictive capacity of a model including GRS and family history neared the minimum for clinical utility. Combining national register data with measured genetic risk factors represents an important investigative approach for psychotic disorders. Our findings suggest the potential clinical utility of combining GRS and family history for early prediction and diagnostic improvements.