Open AccessImpact of CHRNA5 polymorphisms on the risk of schizophrenia in the Chinese Han population
Author(s) -
Zhan Dafei,
Yao Qiankun,
Fu Shaojian,
Liu Xianglai,
Zhou Jun,
Chen Daqiang,
Yu Chuanlong
Publication year - 2019
Publication title -
molecular genetics and genomic medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.765
H-Index - 29
ISSN - 2324-9269
DOI - 10.1002/mgg3.869
Subject(s) - schizophrenia (object oriented programming) , single nucleotide polymorphism , haplotype , genetic association , psychosis , medicine , population , genetics , biology , psychiatry , allele , genotype , gene , environmental health
Background Schizophrenia is a complex mental disease whose cause is still unknown. Neuronal nicotinic acetylcholine receptors (nAChRs) have been implicated in various neurological disorders, including schizophrenia. The previous reports have shown that CHRNA polymorphisms were involved in schizophrenia. This study is to explore the potential association between CHRNA5 (OMIM#118505) polymorphisms and schizophrenia susceptibility in a Chinese population. Methods and Results A case–control study was conducted with 384 schizophrenia patients and 687 controls. We genotyped eight single nucleotide polymorphisms (SNPs) distributed in CHRNA5 . Regulome DB, HaploReg, and GTEx databases were used to calculate possible functional effects of the polymorphisms. The χ 2 test, genetic model analysis, and haplotype analysis were involved in assessing genetic association between variants and schizophrenia risk. The results exhibited that rs17486278 (NC_000015.10:g.78575140A>C) was associated with a decreased risk of schizophrenia on the basis of the recessive model (adjusted OR = 0.37, 95%CI: 0.15–0.93) in females. Moreover, we found that the four variants rs588765, rs6495306, rs680244, rs692780 were extremely significant after being stratified by ≥45 years. Conclusions Overall, our findings supported that the potential association existed between CHRNA5 polymorphisms and schizophrenia susceptibility in a Chinese population. But, large sample validation is needed to enhance the accuracy of our results.