Meta-analysis of GABRB2 polymorphisms and the risk of schizophrenia combined with GWAS data of the Han Chinese population and psychiatric genomics consortium.
Tian ZhangJun LiHao YuYongyong ShiZhiqiang LiLinyan WangZiqi WangTianlan LuLifang WangWeihua YueDai ZhangPublished in: PloS one (2018)
Schizophrenia (SCZ) is a severe psychiatric disorder with evidence of a strong genetic component in the complex etiologies. Some studies indicated that gamma-aminobutyric acid (GABA)A receptor β2 subunit gene (GABRB2) was associated with SCZ. Other studies reported a negative association. Moreover, the results of two previous meta-analyses of GABRB2 with SCZ were inconsistent and the sample sizes were limited. Therefore, an updated meta-analysis combined with genome-wide association study (GWAS) data of the Han Chinese population and Psychiatric Genomics Consortium (PGC) was performed. Available case-control and family-based genetic data were extracted from association studies, and the GWAS data were included. The findings showed no association between six single-nucleotide polymorphisms of GABRB2 (rs6556547, rs1816071, rs1816072, rs194072, rs252944, and rs187269) and SCZ in a total of 51,491 patients and 74,667 controls. The ethnic subgroup analysis revealed no significant association in Asian populations. Since the PGC data of SCZ (SCZ-PGC, 2014) contained 3 studies of Asian populations (1866 patients and 3418 controls), only the data of European samples in SCZ-PGC were used for the meta-analysis of the Caucasian population in the present study. The result still showed no association in the Caucasian population. In conclusion, the present meta-analysis on combined data from GWASs of the Han Chinese population and PGC suggested that GABRB2 polymorphisms might not be associated with SCZ.
Keyphrases
- case control
- systematic review
- electronic health record
- meta analyses
- skeletal muscle
- big data
- end stage renal disease
- mental health
- genome wide association study
- newly diagnosed
- randomized controlled trial
- bipolar disorder
- ejection fraction
- single cell
- data analysis
- clinical trial
- peritoneal dialysis
- prognostic factors
- dna methylation
- gene expression
- machine learning
- deep learning
- patient reported outcomes
- african american
- study protocol
- binding protein