Polygenic risk score analyses of symptoms and treatment response in an antipsychotic-naive first episode of psychosis cohort

Abstract

In this study, we aimed to test if the schizophrenia (SCZ) polygenic risk score (PRS) was associated with clinical symptoms in (a) the first episode of psychosis pre-treatment (FEP), (b) at nine weeks after initiation of risperidone treatment (FEP-9W) and (c) with the response to risperidone. We performed a detailed clinical assessment of 60 FEP patients who were antipsychotic-naive and, again, after nine weeks of standardized treatment with risperidone. After blood collection and DNA isolation, the samples were genotyped using the Illumina PsychArrayChip and then imputed. To calculate PRS, we used the latest available GWAS summary statistics from the Psychiatric Genomics Consortium wave-2 SCZ group as a training set. We used Poisson regression to test association between PRS and clinical measurements correcting for the four principal components (genotyping). We considered a p-value < 0.0014 (Bonferroni correction) as significant. First, we verified that the schizophrenia PRS was also able to distinguish cases from controls in this south-eastern Brazilian sample, with a similar variance explained to that seen in Northern European populations. In addition, within-cases analyses, we found that PRS is significantly correlated with baseline (pre-treatment) symptoms, as measured by lower clinical global assessment of functioning (−GAF), higher depressive symptoms and higher scores on a derived excitement factor. After standardized treatment for nine weeks, the correlation with GAF and the excitement factor disappeared while depressive symptoms became negatively associated with PRS. We conclude that drug (and other treatments) may confound attempts to understand the aetiological influence on symptomatology of polygenic risk scores. These results highlight the importance of studying schizophrenia, and other disorders, pre-treatment to understand the relationship between polygenic risk and phenotypic features.

Polygenic Risk for Schizophrenia and Global Assessment of Functioning—A Comparison with In-Silico Data

“…PRSs based on the GWAS results of one phenotype in a large-scale sample (discovery) can also be used to quantify the degree of variance explained by the PRS in another, possibly much smaller sample with the exact same or sufficiently correlated phenotype (target). The PRS for the phenotype schizophrenia (SZ), denoted as SZ-PRS, has been used for example to unveil the polygenetic model behind several psychiatric phenotypes such as first episode psychosis (FEP) [8][9][10] and bipolar disorder (BPD) [11].…”

“…Substantial evidence from well-powered GWAS revealed a considerable shared genetic etiology among distinct psychotic phenotypes such as SZ and BPD [11]. However, it is well known that psychotic disorders are highly heterogeneous in their symptoms and genetic architecture [8][9][10]. Owing to the presence of considerable overlap in the dimensions and severity of symptoms, numerous clinical scales have been developed that altogether allow us to assess the functioning of patients with various distinct psychiatric phenotypes.…”

“…GAF is often adjusted by PANSS, so that it is less influenced by acute symptoms. The correlation among different symptom dimension scores such as GAF and PANSS varies with the specific clinical diagnosis [8,9]. Recently, SZ-PRS has been exploited to explain the shared polygenic basis of GAF and PANSS for distinct diagnostic groups in FEP patients with schizophrenia [8,9].…”

“…The correlation among different symptom dimension scores such as GAF and PANSS varies with the specific clinical diagnosis [8,9]. Recently, SZ-PRS has been exploited to explain the shared polygenic basis of GAF and PANSS for distinct diagnostic groups in FEP patients with schizophrenia [8,9]. However, the prediction of these distinct genetic components in phenotypes with respect to symptoms remains a challenge and the degree of genetic correlation between psychiatric phenotypes and the severity of symptoms is yet not completely understood.…”

“…We examined the properties of PRS for correlated quantitative phenotypes with complete overlap of causal genetic markers with a focus on the distribution of explained variance (R 2 ) and optimal p-value threshold (p 0 ) in the replications. Our second goal was to interpret our simulation results in view of the SZ-PRS applied to phenotypes in the PsyCourse dataset (version 2.0.1) [14] including 653 psychotic and affective individuals and to compare our findings with previous studies [8,9]. We analyzed the symptoms and severity in terms of the association between GAF and SZ-PRS.…”