It is known that genomic abnormalities including single nucleotide polymorphisms (SNPs) and copy number variations (CNVs) appear during chromosomal DNA replication in cell cycle, and, based on previous findings, it is likely that schizophrenia is associated with perturbation of cell cycle.

The mRNA expression levels of 3 different cell cycle-related genes (CD4, MCM7, and POLD4) were significantly decreased in peripheral blood of patients with acute schizophrenia compared with those of control participants, and a combination of these 3 genes could serve as a potential biomarker for schizophrenia. These findings were recently published in Progress in Neuro-Psychopharmacology & Biological Psychiatry journal by investigators affiliated with Kobe University and Hyogo College of Medicine in Japan.

Genome-wide association studies (GWAS) are used to identify multiple common genetic variants, or SNPs, that influence the risk for various disorders and conditions, including neuropsychiatric illness. This established method relies on a sufficiently large sample size and has previously been successful in research on schizophrenia. It is assumed that multiple SNPs work together to influence risk of schizophrenia, as individual SNPs exert a relatively small effect on overall disease risk. However, the contribution of rare genetic variants (ie, those variants that are observed in less than 1% of the population), such as CNVs, appears to be much larger.

In the current study, researchers first examined mRNA expression of 43 cell cycle-related genes in the peripheral blood samples collected from 40 patients (20 females) admitted into the hospital with acute psychosis who were diagnosed with schizophrenia, and from 20 typical, healthy control participants (10 females). Then, they replicated this experiment by examining the top 13 genes from another 82 patients diagnosed with schizophrenia (44 females) and from 74 controls (30 females). Finally, they analyzed mRNA expression of 3 selected genes (CD4, MCM7, and POLD4) in blood samples collected from 22 patients with schizophrenia and 18 controls.

Out of 13 genes identified in the discovery stage, 11 were significantly different between controls and patients with schizophrenia (CDK10, CDK4, MCM3, MCM4, MCM5, MCM6, MCM7, POLD2, and POLD4). Spearman’s correlation analyses revealed that, in the group of patients with schizophrenia patients, CDK10 and MCM3 were negatively correlated with age, MCM3 was negatively correlated with illness duration, MCM4 and MCM5 were positively correlated with antipsychotic dose, and MCM3 and POLD2 were positively correlated with the number of white blood cells.

By using multivariate logistic regression and the likelihood ratio method, investigators determined that a combination of CD4, MCM7, and POLD4 could serve as a potential biomarker for schizophrenia. Whereas the expression levels of CDK4 and MCM7 were significantly decreased only in the acute state, POLD4 was significantly decreased in the acute and remission states in the patients diagnosed with schizophrenia.

Elevated rates of new mutations such as CNVs have previously been reported, and the data collected in the current study are in line with these findings. More specifically, 12 676 potential CNVs were increased and 3 239 potential CNVs were decreased in patients with schizophrenia compared with controls.

Although “the alteration of expression levels of CDK4, MCM7, and POLD4 [in peripheral blood] should be evaluated carefully…. this biomarker [may be] useful for a clinical application and [may] contribute to further elucidation of the pathophysiology of schizophrenia,” the authors concluded in their publication.