CYP11B1 gene polymorphisms and susceptibility to ischemic stroke in a Chinese Han population

• Published in: Frontiers in neuroscience Vol. 16; p. 1030551
• Main Authors: Liu, Gaowen, Duan, Ying
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 01.12.2022
• Subjects: case-control study; CYP11B1; gene polymorphisms; ischemic stroke; Neuroscience; susceptibility; susceptibility; case-control study; CYP11B1; gene polymorphisms; ischemic stroke
• DOI: 10.3389/fnins.2022.1030551
• ISSN: 1662-453X; 1662-4548

Ischemic stroke (IS) is the major cause of death and disability. While previous studies confirmed that is closely associated with IS, the present study aimed to analyze the impact of gene polymorphisms on the IS susceptibility. The present study genotyped six single nucleotide polymorphisms (SNPs) (including rs4736312, rs5017238, rs5301, rs5283, rs6410, and rs4534) of in peripheral blood samples from IS and control populations. Logistic regression analysis was used to analyze the association between the SNPs and IS risk. The multifactor dimensionality reduction (MDR) method was used to determine the roles of SNP-SNP interactions in IS. The present study showed that rs5283 was associated with an increased susceptibility to IS [odds ratio (OR) 1.81, = 0.012]. On the contrary, rs6410 had a protective influence on IS risk (OR 0.56, = 0.020). Stratified analyses indicated that rs5283 could enhance the risk of IS in subjects aged >63 years (OR 2.41, = 0.011), of female gender (OR 3.31, = 0.001), that do not smoke (OR 1.64, = 0.005), and with hypertension (OR 2.07, = 0.003). Whereas, rs6410 was related to a lower susceptibility to IS in subjects aged >63 years (OR 0.43, = 0.032), of female gender (OR 0.30, = 0.006), do not smoke (OR 0.42, = 0.017), and with hypertension (OR 0.52, = 0.022). Besides, rs4736312 reduced the IS susceptibility in non-smokers (OR 0.69, = 0.031). Rs4534 had a risk-decreasing impact on IS in non-drinking (OR 0.54, = 0.016). Moreover, the results of the MDR analysis corroborate that the best prediction model for IS was rs5283. This study revealed that gene polymorphisms strongly correlated with IS in the Chinese Han population.