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Genetic Data Explains Treatment Resistant Schizophrenia

Between 20-30% of patients with schizophrenia do not respond to the first-line antipsychotic treatment.

A new analysis of patients with schizophrenia might help explain why some in this patient population do not adequately respond to medication.

A team, led by Antonio F. Pardiñas, PhD, MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, examined the genetic architecture of treatment resistant schizophrenia (TRS) through the reassessment of genetic data from schizophrenia studies and its validation in ascertained clinical samples.

The Problem

Treatment response for patients with schizophrenia can be low, with about 20-30% of patients not responding adequately to first-line antipsychotic treatments. The true caused of treatment resistant schizophrenia and their relationship with causes underlying the disease are largely unknown, mainly due to a lack of adequately powered genetic studies of treatment resistant schizophrenia because of the difficulty in collecting data from well-characterized TRS.

In the study, the investigators examined a pair of case-control genome-wide association trials of patients with schizophrenia. The studies were performed where the case samples were defined as patients with TRS (n = 10,501) and a control group (n = 20,325). There was a total of 85,490 participants in the study, 56.9% were male.

The team determined the differences in effect sizes for allelic associations between both studies because the differences reflect treatment resistance rather than schizophrenia. They also retrieved genotype data from the CLOZUK and Psychiatric Genomics Consortium (PGC) schizophrenia studies.

The investigators then validated the output using polygenic risk scores of 2 independent schizophrenia cohorts with TRS and non-TRS, which was a prevalence sample with 817 participants (Cardiff Cognition in Schizophrenia) and an incidence sample of 563 individuals (Genetics Workstream of the Schizophrenia Treatment Resistance and Therapeutic Advances).

The investigators sought main outcomes of genome-wide associations of treatment resistance in schizophrenia and compared the results with complex polygenic traits through a genetic correlation approach. This was used for PRS analysis on the independent validation cohorts using the same TRS definition.


The results show treatment resistance is generally a polygenic trait with detectable heritability of 1-4%. Several traits also emerged as related to intelligence and cognition that were genetically correlated with it (genetic correlation, 0.41-0.69).

In the further PRS analysis, the investigators found in the CardiffCOGS prevalence sample there was a positive association between TRS and a history of taking clozapine (r2 = 2.03%; P = .001).

This was replicated in the STRATA-G incidence sample (r2 = 1.09%; P = .04).

“In this GWAS, common genetic variants were differentially associated with TRS, and these associations may have been obscured through the amalgamation of large GWAS samples in previous studies of broadly defined schizophrenia,” the authors wrote. “Findings of this study suggest the validity of meta-analytic approaches for studies on patient outcomes, including treatment resistance.”

The results of the study could go a long way toward implementing more of a precision-based medicine approach in treating schizophrenia.

“Precision psychiatry provides a potential pathway to improve psychiatric classification and develop treatments that are better tailored to specific patients,” the authors wrote. “Major advances in determining the role of genetic variation in the risk of developing psychiatric disorders are helping realize this potential, but the relevance of these findings to patient outcomes and response to treatment is unclear.”

The study, “Interaction Testing and Polygenic Risk Scoring to Estimate the Association of Common Genetic Variants With Treatment Resistance in Schizophrenia,” was published online in JAMA Psychiatry.