Kohara Katsuhiko, Tabara Yasuharu, Nakura Jun, Imai Yutaka, Ohkubo Takayoshi, Hata Akira, Soma Masayoshi, Nakayama Tomohiro, Umemura Satoshi, Hirawa Nobuhito, Ueshima Hirotsugu, Kita Yoshikuni, Ogihara Toshio, Katsuya Tomohiro, Takahashi Norio, Tokunaga Katsushi, Miki Tetsuro
Department of Geriatric Medicine, Ehime University Graduate School of Medicine, Toon, Japan.
Hypertens Res. 2008 Feb;31(2):203-12. doi: 10.1291/hypres.31.203.
A multiple candidate-gene approach was used to investigate not only candidate genes, but also candidate pathways involved in the regulation of blood pressure. We evaluated 307 single nucleotide polymorphisms (SNPs) in 307 genes and performed an association study between 758 cases and 726 controls. Genes were selected from among those encoding components of signal transduction pathways, including receptors, soluble carrier proteins, binding proteins, channels, enzymes, and G-proteins, that are potentially related to blood pressure regulation. In total, 38 SNPs were positively (p<0.05) associated with hypertension. Replication of the findings and possible polygenic interaction was evaluated in five G-protein-related positive genes (GNI2, GNA14, RGS2, RGS19, RGS20) in a large cohort population (total n=9,700, 3,305 hypertensives and 3,827 normotensive controls). In RGS20 and GNA14, dominant models for the minor allele were significantly associated with hypertension. Multiple dimension reduction (MDR) analysis revealed the presence of gene-gene interaction between GNA14 and RGS20. The MDR-proved combination of two genotypes showed a significant association with hypertension (chi2=9.93, p=0.0016) with an odds ratio of the high-risk genotype of 1.168 (95% confidence interval [CI] [1.061-1.287]). After correction for all possible confounding parameters, the MDR-proved high-risk genotype was still a risk for hypertension (p=0.0052). Furthermore, the high-risk genotype was associated with a significantly higher systolic blood pressure (133.08+/-19.46 vs. 132.25+/-19.19 mmHg, p=0.04) and diastolic blood pressure (79.65+/-11.49 vs. 79.01+/-11.32 mmHg, p=0.019) in the total population. In conclusion, a systemic multiple candidate gene approach can be used to identify not only hypertension-susceptibility genes but also hypertension-susceptibility pathways in which related genes may synergistically collaborate through gene-gene interactions to predispose to hypertension.
采用多候选基因方法不仅研究了候选基因，还研究了参与血压调节的候选通路。我们评估了307个基因中的307个单核苷酸多态性（SNP），并在758例病例和726例对照之间进行了关联研究。基因选自编码信号转导通路成分的基因，包括受体、可溶性载体蛋白、结合蛋白、通道、酶和G蛋白，这些成分可能与血压调节有关。总共38个SNP与高血压呈正相关（p<0.05）。在一个大型队列人群（总共n=9700，3305例高血压患者和3827例血压正常对照）中，对五个与G蛋白相关的阳性基因（GNI2、GNA14、RGS2、RGS19、RGS20）的研究结果进行了重复验证，并评估了可能的多基因相互作用。在RGS20和GNA14中，次要等位基因的显性模型与高血压显著相关。多维度约简（MDR）分析显示GNA14和RGS20之间存在基因-基因相互作用。MDR验证的两种基因型组合与高血压显著相关（χ2=9.93，p=0.0016），高危基因型的比值比为1.168（95%置信区间[CI][1.061-1.287]）。在对所有可能的混杂参数进行校正后，MDR验证的高危基因型仍然是高血压的危险因素（p=0.0052）。此外，在总人群中，高危基因型与显著更高的收缩压（133.08±19.46 vs.132.25±19.19 mmHg，p=0.04）和舒张压（79.65±11.49 vs.79.01±11.32 mmHg，p=0.019）相关。总之，系统性多候选基因方法不仅可用于识别高血压易感基因，还可用于识别高血压易感通路，其中相关基因可能通过基因-基因相互作用协同协作，导致易患高血压。
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