Study subjects
The study was approved by the Ethics Committee at the Institute of Medical Biology Chinese Academy of Medical Sciences, and signed informed consent from all study subjects was obtained. The samples were collected from Dai ethnic groups living in Xishuangbanna and Dehong, Yunnan, China during 2015-2018. (Each member was traced backward to the same ethnic group for three generations and is not related to other members.) Since the prevalence of hypertension is related to age, the patients in this study were all over 40 years old (including 40 years old). The inclusion criteria of the hypertensive group were defined by the World Health Organization (1999) (systolic blood pressure (SBP) ≥140 and/or diastolic blood pressure (DBP) ≥90) or if they had previously diagnosed hypertension or were taking antihypertensive medication. The patients with renal and endocrine diseases that can cause secondary hypertension were excluded. The control group was SBP < 140 and DBP < 90, and there was no BP-lowering therapy. Blood pressure was measured using a standard mercury measurement method, three times with a rest for 5 min, and the average was used for analyses. Height, weight, age, gender TC, LDL and HDL were recorded for all subjects. A total of 1221 patients (over 40 years old) were recruited. Considering the possibility of measurement errors, we eliminated the samples with critical values (±5 mmHg). Finally, a total of 1034 patients were included, including 495 cases and 539 controls.
Choosing SNPs and genotyping
Although the association analyses in the Chinese Han population[14, 15] and other countries[16, 17] suggested that the CACNA1A (rs8182538), CACNA1C (rs758116) and the CACNB2 (rs4373814, rs11014166, rs12258967) polymorphisms were associated with blood pressure and hypertension (no reports about CACNA1S polymorphisms), these SNPs were not consistent with our pre-experimental results (200 cases vs 200 controls, unpublished results). Therefore, based on the haplotype analysis results of the Beijing Han (CHB, HapMap)[18], we chose another 17 SNPs in the genes (CACNA1A, CACNA1C, CACNA1S, CACNB2) that encode the proteins of VDCCs to perform genotyping in the Dai population. The locations of these SNPs are shown in Figure 1. There are 4 SNPs in CACNA1A, 5 SNPs in CACNA1C, 2 SNPs in CACNA1S and 6 SNPs in CACNB2. The linkage disequilibrium analysis of these SNPs was performed by Haploview software[19].
Peripheral blood (2 ml) of participants was extracted and placed into the heparin anticoagulation vacuum tube. DNA preparation: DNA extraction was performed using the AxyPrep Blood Genomic DNA Mini Prep Kit (Axygen, Hangzhou City, China) according to the manufacturer’s instructions. PCR primer design: Primer 3 online version 0.4.0 was used to design specific multiple primers, which were supplied by Shanghai Balig Biotechnology Co., Ltd. The primer sequences are shown in Supplementary Table 1. Multiplex PCR amplification was performed to obtain the PCR products (first round reaction mix for PCR contained 3.2 µl of ddH2O, 1 µl of buffer, 2 µl of primer, 0.8 µl of dNTP, 0.1 µl of Taq polymerase, 2 µl of DNA, 1 µl of Mg2+). Reaction system conditions included pre-denaturation 95°C for 15 min, denaturation at 94°C for 30 s, annealing at 60°C for 10 min, extension at 72°C for 30 s for 4 cycles and an extension at 72°C 30 s for 20 cycles. The second round PCR mix included 3.6 µl of ddH2O, 2 µl of buffer, 3.6 µl of barcode, 0.8 µl of dNTP, 0.1 µl of Taq polymerase, 10 µl of DNA, and 1 µl of Mg2+. Reaction conditions included pre-denaturation at 95°C for 15 min, denaturation at 94°C for 30 s, annealing at 60°C for 4 min, extension at 72°C for 30 s for 5 cycles and annealing at 65°C for 1 min and extension at 72°C for 30 s for 20 cycles). The Illumina HiSeq platform was used for sequencing and the sequencings were performed by Novogene Co., Ltd (Beijing, China). The sequencing images were transformed into sequenced reads through base recognition analysis, and final identification of SNPs was conducted by Samtools 0.1.19[20].
Statistical analysis
After the genotypes of the SNPs were identified, we performed statistical analyses between the case and control groups. The quantitative data were described by mean ± standard deviation, and the comparison between the two groups was performed by independent-sample T test. Qualitative data and allele frequencies were compared using the chi-square test. The associations between SNPs and hypertension were further adjusted (adjusted age, gender, BMI, TG, LDL and HDL) by logistic regression analyses in three genetic models (dominant model (AA+AB vs BB, with minor A), recessive model (AA vs AB+BB), and additive model (AA vs AB vs BB)). The T test and chi-square test were performed using SPSS 25.0 software. Logistic regression analyses were performed by plink 1.9 software[21].Relative risk was expressed by odds ratio (OR) and 95% CI. All statistical tests were statistically significant with two-tailed probability (P<0.05).