Genetic etiology of schizophrenia: possible role of immunoglobulin γ genes

Rapid detection of alteration of serum IgG in patients with schizophrenia after risperidone treatment by matrix-assisted laser desorption ionization/time-of-flight mass spectrometry

RATIONALE

The aim of the study was to use a technique that combines acid hydrolysis and matrix-assisted laser desorption ionization/time-of-flight mass spectrometry (MALDI-TOF MS) in order to detect the serum biomarkers of patients diagnosed with schizophrenia both before and after four-week antipsychotic treatment with risperidone.

METHODS

During this study's two-year period, inpatients were diagnosed with schizophrenia using the Structured Clinical Interview for DSM-IV Axis I Disorders. Severity was then evaluated using the Positive and Negative Syndrome Scale both at baseline and at endpoint following four-week treatment with risperidone. The patients' serum biomarkers were quickly measured using acid hydrolysis and MALDI-TOF MS. The resulting peptides were then analyzed using MALDI-TOF MS. We constructed a receiver operating characteristic (ROC) curve for the evaluated biomarkers.

RESULTS

We recruited 20 pairs of participants for this study. The experimental group was treated with serum protein with HCl for 10 minutes to effectively hydrolyze abundant proteins. The target peptide, the immunoglobulin gamma chain (IgG), was then rapidly detected using this manner. A significant difference was found in the IgG levels of patients with schizophrenia before and after antipsychotic treatment. We constructed a ROC curve based on the IgG, and the area under said curve was 0.969. In comparison to conventional detection protocols, this method takes only minutes to complete and is also less costly.

CONCLUSIONS

This study found that applying acid hydrolysis with MALDI-TOF MS technology could rapidly differentiate serum IgG levels in patients with schizophrenia before and after being treated with risperidone. This IgG difference may enhance the understanding of mechanism of antipsychotic treatment of schizophrenia. Copyright © 2016 John Wiley & Sons, Ltd.

Immunoglobulin G genotypes and the risk of schizophrenia

Genes of the immune system are relevant to the etiology of schizophrenia. However, to our knowledge, no large-scale studies, using molecular methods, have been undertaken to investigate the role of highly polymorphic immunoglobulin GM (γ marker) genes in this disorder. In this investigation, we aimed to determine whether particular GM genotypes were associated with susceptibility to schizophrenia. Using a matched case-control study design, we analyzed DNA samples from 798 subjects-398 patients with schizophrenia and 400 controls-obtained from the U.S. National Institute of Mental Health Repository. GM alleles were determined by the TaqMan(®) genotyping assay. The GM 3/3; 23-/23- genotype was highly significantly associated with susceptibility to schizophrenia (p = 0.0002). Subjects with this genotype were over three times (OR 3.4; 95 % CI 1.7-6.7) as likely to develop schizophrenia as those without this genotype. Our results show that immunoglobulin GM genes are risk factors for the development of schizophrenia. Since GM alleles have been implicated in gluten sensitivity and in immunity to neurotropic viruses associated with cognitive impairment, the results presented here may help unify these two disparate areas of pathology affected in this disorder.

A pilot study on commonality and specificity of copy number variants in schizophrenia and bipolar disorder

Schizophrenia (SZ) and bipolar disorder (BD) are known to share genetic risks. In this work, we conducted whole-genome scanning to identify cross-disorder and disorder-specific copy number variants (CNVs) for these two disorders. The Database of Genotypes and Phenotypes (dbGaP) data were used for discovery, deriving from 2416 SZ patients, 592 BD patients and 2393 controls of European Ancestry, as well as 998 SZ patients, 121 BD patients and 822 controls of African Ancestry. PennCNV and Birdsuite detected high-confidence CNVs that were aggregated into CNV regions (CNVRs) and compared with the database of genomic variants for confirmation. Then, large (size⩾500 kb) and small common CNVRs (size <500 kb, frequency⩾1%) were examined for their associations with SZ and BD. Particularly for the European Ancestry samples, the dbGaP findings were further evaluated in the Wellcome Trust Case Control Consortium (WTCCC) data set for replication. Previously implicated variants (1q21.1, 15q13.3, 16p11.2 and 22q11.21) were replicated. Some cross-disorder variants were noted to differentially affect SZ and BD, including CNVRs in chromosomal regions encoding immunoglobulins and T-cell receptors that were associated more with SZ, and the 10q11.21 small CNVR (GPRIN2) associated more with BD. Disorder-specific CNVRs were also found. The 22q11.21 CNVR (COMT) and small CNVRs in 11p15.4 (TRIM5) and 15q13.2 (ARHGAP11B and FAN1) appeared to be SZ-specific. CNVRs in 17q21.2, 9p21.3 and 9q21.13 might be BD-specific. Overall, our primary findings in individual disorders largely echo previous reports. In addition, the comparison between SZ and BD reveals both specific and common risk CNVs. Particularly for the latter, differential involvement is noted, motivating further comparative studies and quantitative models.