Schizophrenia symptom subtypes reveal distinct genetic risk profiles

Schizophrenia patients with different symptom profiles carry measurably different genetic liabilities, according to a study published in BMC Medicine that stratified patients into clinically defined subtypes and searched for genetic risk factors specific to each group.

The research team, led by Meng Zhou, Yamin Zhang and Tao Li, worked with a Chinese Han cohort of 2,416 people with schizophrenia. They applied K-means cluster analysis to the patients’ symptom profiles to identify clinical subtypes, and then tested whether the resulting classification held up in an independent cohort of 480 patients.

Three stable subtypes emerged: Cluster-L, characterized by low severity; Cluster-S, characterized by severe symptoms; and Cluster-N, defined by predominant negative symptoms. The classification was reproduced in the independent cohort, and the three subtypes also showed significantly different symptom network structures, supporting the idea that these groups represent distinct clinical presentations rather than arbitrary statistical divisions.

When the researchers conducted subtype-specific genome-wide association studies, they detected three independent genome-wide significant loci. One locus within the CNTN2 gene showed significance specifically in Cluster-N, with lead SNP rs3767295 (P = 6.40 × 10−10, OR = 0.62). Gene-based analyses identified eight significant risk genes, seven of which were significant only in Cluster-N, suggesting that much of the subtype-specific genetic signal concentrated in the negative-symptom group.

Distinct patterns also appeared in pathway-specific polygenic risk scores and cell type-specific polygenic risk scores. GABA-PRS (OR = 1.19 [1.06–1.34], Padjusted = 0.040) and oligodendrocyte progenitor cells-PRS (OR = 1.25 [1.11–1.41], Padjusted = 0.004) were significantly elevated in Cluster-N. Astrocyte-PRS was elevated only in Cluster-S (OR = 1.30 [1.10–1.53], Padjusted = 0.033), while oligodendrocyte-PRS was elevated in both Cluster-S (OR = 1.28 [1.10–1.50], Padjusted = 0.036) and Cluster-N (OR = 1.19 [1.06–1.34], Padjusted = 0.047).

The authors conclude that reducing clinical heterogeneity improves statistical power to detect genetic risk loci, and that patients with distinct symptom profiles harbor differential genetic liabilities, with certain genetic effects appearing more pronounced in specific symptom-defined subtypes. The study was published open access on 28 October 2026.

Subject of Research: Genetic architecture of symptom-defined schizophrenia subtypes

Article Title: Genetic architecture of schizophrenia clinical subtype

Article References: Zhou, M., Zhang, Y., Zhao, Y., Fu, Z., Wang, X., Dang, X., Wang, H., Wei, W., Ren, H., Li, M., Wang, Q., Deng, W., Guo, W., Luo, X.-J., & Li, T. (2026). Genetic architecture of schizophrenia clinical subtype. BMC Medicine. https://doi.org/10.1186/s12916-026-05357-y

Image Credits: AI Generated

DOI: 10.1186/s12916-026-05357-y

Keywords: schizophrenia, clinical subtypes, GWAS, polygenic risk scores, negative symptoms, CNTN2, genetic architecture, cluster analysis, BMC Medicine, psychiatric genetics, Genetic, architecture