Genetic Variation in SLC8A1 Gene Involved in Blood Pressure Responses to Acute Salt Loading

Genetic Variation in SLC8A1 Gene Involved in Blood Pressure Responses to Acute Salt Loading Abstract BACKGROUND Salt sensitivity of blood pressure (SSBP) increases the risk of cardiovascular complications, and the heritability of SSBP is about 50% in Chinese population. However, studies identifying genes involved in BP responses to acute sodium loading and diuresis shrinkage are still limited. METHOD A total of 342 essential hypertensives from Beijing were recruited in our study. A modified Sullivan’s acute oral saline load and diuresis shrinkage test was conducted to each individual. Medical history and lifestyle risk factors were obtained by questionnaire. Generalized linear model was used to examine the associations of 29 single-nucleotide polymorphisms (SNPs) with SSBP and false discovery rate (FDR) was used to correct P values for multiple testing. RESULTS In the process of acute sodium loading, after adjusting for age and 24-hour urinary sodium concentration, SNPs in CYP11B2, PRKG1, SLC8A1 genes were significantly associated with systolic BP (SBP) rising in the additive and recessive model; SNPs in CYP4A11, PRKG1, SLC8A1, and ADRB2 genes were significantly associated with diastolic BP (DBP) rising. In the process of diuresis shrinkage, SNPs of CLCNKA, eNOS, PRKG1 gene were associated with SBP and DBP decreasing. After FDR correction, rs434082 in SLC8A1 gene was still significantly associated with blood pressure rising during salt load. In the additive model, A allele increased DBP of 2.8 mm Hg (FDR_q = 0.029) and MAP of 3.1 mm Hg (FDR_q = 0.029) after adjusting for age and 24-hour urinary sodium concentration. CONCLUSION SLC8A1 gene may contribute to BP change in the process of acute sodium loading in a Han Chinese population. acute salt loading, blood pressure, hypertension, salt sensitivity, single-nucleotide polymorphisms Blood pressure (BP) responses to the changes of salt intake. Definition of salt sensitivity of blood pressure (SSBP) is that BP of some members of the population exhibits changes parallel to changes in salt intake.1 About half of the hypertensions and 26% of the normotensives are salt sensitivity.2–4 SSBP and high salt intake will increase the risk of cardiovascular complications5,6 and may lead to left ventricular hypertrophy, microalbuminuria, and endothelial dysfunction.7 BP responses to sodium intake are partially under genetic control. The heritability of SSBP is about 50% in Chinese subjects, which is higher than that of hypertension.8 Genes can influence SSBP through different pathways. Renin–angiotensin system involves in regulating renal sodium transportation, especially under the condition of sodium deficit,9 and it is the most important regulator of BP. It has been demonstrated that AGT,10AGTR1,11CHP11B2,12 and STRN13 genes in renin–angiotensin system pathway are associated with salt-sensitive hypertension (SSH). Additionally, genes that regulate vascular smooth muscle tone, like SLC24A3 and SLC8A11, can influence SSH through modifying the concentration of Ca2+. Moreover, GRK4 gene variants can also affect hypertension and salt sensitivity through impaired natriuretic response.14–16 Recent genome-wide association study (GWAS) also demonstrated several novel genes associated with SSH. PRKG1 gene was found to be associated with variation in diastolic BP (DBP) after acute salt load on 329 subjects.1 The Genetic Epidemiology Network of Salt Sensitivity (GenSalt) study17 demonstrated that MKNK1, C2orf80, EPHA6, SCOC-AS1, SCOC, CLGN, MGAT4D, ARHGAP42, CASP4, and LINC01478 genes interacted with sodium to influence BP among 1,876 Chinese participants. Salt sensitivity can be assessed by different protocols.18 A 4-hour intravenous infusion of 2 l saline and a 10 mmol sodium diet plus 40 mg furosemide orally were used to identify salt sensitivity in 1977. Either mean arterial pressure (MAP) raises more than 5 mm Hg after salt loading or MAP reduces more than 10 mm Hg after diuresis shrinkage were defined as salt sensitivity. SSH patients have irregular vascular response to angiotensin-II infusion.19 High salt load may cause abnormal BP elevation in SSH patients by activates tissue renin–angiotensin system. Abnormally renal tubular reclamation of Na+ and Cl− may contribute to the anomalous BP change in diuresis shrinkage.20 Different underlying pathophysiological mechanism may indicate different genetic mechanism involved in the process of acute salt loading and diuresis shrinkage. GenSalt study recently found that genes in natriuretic peptide system21 and SGK1 gene22 were associated with BP response to 7-day low-sodium or high-sodium dietary intervention. Snyder et al.23 found that Arg16Gly polymorphism in ADRB2 gene affected natriuretic response to acute saline infusion, which may impact BP regulation. However, GenSalt study focuses on genetic determinants which may affect BP change during chronic sodium loading. Although the study conducted by Snyder et al. focuses on acute salt loading, the sample size is relatively small (n = 31). Studies identifying specific genes involved in BP changes parallel to acute salt loading and diuresis shrinkage of a considerable sample size are still limited. In the present study, we aimed at identifying single-nucleotide polymorphism (SNPs) associated with BP changes during the process of acute oral saline load and diuresis shrinkage. A review as preformed to select candidate genes, and a modified Sullivan’s acute oral saline load and diuresis shrinkage test (MSAOSL-DST) was used to identify salt sensitivity hypertension. METHODS Study population and data collection The study was conducted in 4 communities in a district of Beijing in 2011. Inclusion criteria was as follows: (i) Chinese Han unrelated residents who had been living in Beijing for more than 5 years; (ii) Essential hypertension diagnosed by secondary hospital or tertiary hospital, or on antihypertension medications; (iii) Stage 1 hypertension (140 mm Hg ≤ systolic BP (SBP) ≤ 159 mm Hg and/or 90 mm Hg ≤ DBP ≤ 99 mm Hg). All the participants were asked to stop taking antihypertensive medicine for at least 12 hours. Participants with cardiac insufficiency, cardiomyopathy, valvulopathy, congenital heart disease, myocardial infarction, stroke, type 2 diabetes mellitus, hepatopathy, nephropathy, cancer, and secondary hypertension were excluded. Our protocol was approved by Ethics Committee of Capital Medical University. All participants provided their informed consent prior participating in this study. In the end, 342 unrelated hypertension patients were recruited. Demographic characters, lifestyle risk factors, and medical history of chronic diseases and medication history were collected through a face-to-face interview by trained interviewers using uniform questionnaires. Smoking was defined as at least 1 cigarette per day, lasting for more than 1 year. Those who have not smoked for at least 3 months were defined as smoking cessation. Mercury column type sphygmomanometer was used to measure BP. People who had smoked, exercised, had caffeinated products, or other stimulants will be asked to delay obtaining BP measurements for at least 30 minutes. Two staffs were adequately trained in BP techniques follow the recommendations of the American Heart Association,24 and they measured the BP of all the participants in this study. BP measurement was taken 3 times at the right brachial artery after the participant has rested in a seated position for 5 minutes. MAP was computed according to the standard formula MAP = (SBP + 2 × DBP)/3. MAP was used to represent BP. Each patient was asked to provide a collection of 24-hour urine, and after abandon the first urine at 6:00 am, participants collected all urine from then on to the next 6:00 am. One-milliliter urine was derived from the mixed 24-hour urine to measure the concentrate of Na+. Assessment of salt sensitivity The assessment of salt sensitivity was achieved by a modified Sullivan’s method (MSAOSL-DST) which has been described in detail in our previously published paper.25,26 Each fasting participant orally took 1,000 ml 0.9% NaCl on 8:00 am within 30 minutes. BP was measured before salt intake and 2 hours after salt loading. Then participants took 40-mg furosemide orally, and were measured for BP 2 hours later again. MAP raising more than 5 mm Hg after acute salt loading and (or) MAP reducing more than 10 mm Hg after diuresis shrinkage test was defined as SSH. MAP raising less than 5 mm Hg after acute salt loading and (or) MAP reducing less than 10 mm Hg after diuresis shrinkage was defined as salt-resistant hypertension. Candidate gene selection Candidate genes were select based on the following inclusion criteria. Candidate genes have been reported to be associated with SSH (or SSBP) in Chinese population, or associated with SSH in GWAS, or associated with SSH (or SSBP) in meta-analysis or systematic review. Genetic data were downloaded from database of the international HapMap Project (HapMap Data Rel 24/phase IINov08, on NVBI B36 assembly, dbSNP b126), and SNPs with the minor allele frequency in Han Chinese population more than 0.10 were selected by the Haploview 4.0 software (version 4.0; Mark Daly’s Laboratory, Broad Institute; http://sourceforge.net/projects/haploview/). DNA extraction and genotyping We selected 29 SNPs to test their association with SSBP. Genomic DNA was extracted from the peripheral blood with a QIAamp DNA Blood Mini Kit (Tiangen, Hilden, Germany). Sequenom Mass ARRAY Platform was used to do genotyping (San Diego, CA). All SNPs in this report had a genotyping success rate of >90%. The value of OD260/OD280 was calculated in order to evaluate the concentration of DNA. Result showed that the DNA concentration was >10 ng/µl if OD260/OD280 was between 1.7 and 2.0. Statistical analysis If all continuous variables were with normal distribution, then means ± SDs were reported, otherwise, medians ± quintiles were reported. Number (percentages) was reported for categorical variables. Student’s t-test was used to examine the difference between 2 groups of continuous variables with normal distribution. Wilcoxon rank–sum nonparametric test was used to explore the disparity of continuous variables with nonnormal distribution. Chi-squared test was used to test for the difference of categorical variables. Chi-squared test was conducted to each SNP in control group to detect for deviation from Hardy–Weinberg equilibrium. Generalized linear model was used to examine the associations of the SNPs with SSBP. False discovery rate (FDR) was calculated to account for multiple testing. All analysis was conducted in IBM SPSS Statistics 19.0 software (SPSS, Chicago, IL). RESULTS General information of SNPs and characteristics of participants The minor allele frequency of 29 selected SNPs ranged from 10.8% to 46.0%. All SNPs were in Hardy–Weinberg equilibrium in control group (P > 0.05). Details were show in Table 1. Table 1. Information of SNPs included in the study SNPs  Genes  Chromosome  Position (bp)  Alleles (minor/major)  MAF (%)  HWE  P  rs4961  ADD1  4  2906707  G/T  46.0  0.884  rs699  AGT  1  230845794  T/C  20.8  0.521  rs2681472  ATP2B1  12  90008959  C/T  34.0  0.859  rs7961152  BCAT1  12  24981611  A/C  10.8  0.054  rs848307  CLCNKA  1  16319232  T/C  29.8  0.541  rs1739843  CLCNKA  1  16343254  T/C  29.8  0.544  rs1010069  CLCNKA  1  16352937  C/T  31.1  0.592  rs1799998  CYP11B2  8  143999600  C/T  28.1  0.348  rs1126742  CYP4A11  6  47398496  C/T  19.9  0.459  rs1799983  eNOS  7  150696111  T/G  10.9  0.566  rs5351  ETBR  13  78475313  G/A  38.1  0.866  rs16998073  FGF5  4  81184341  T/A  45.7  0.301  rs1129649  GNB3  12  6948468  C/T  28.9  0.813  rs1024323  GRK4  4  3006043  A/G  18.7  0.630  rs1801058  GRK4  4  3039150  C/T  43.0  0.259  rs2398162  NR2F2-AS1  15  96830550  A/G  38.4  0.945  rs2288774  NEDD4L  18  55983330  C/T  35.4  0.449  rs4149601  NEDD4L  18  55816791  A/G  16.2  0.835  rs7897633  PRKG1  10  52957721  A/C  49.7  0.973  rs1904694  PRKG1  10  52905494  G/A  38.2  0.478  rs5735  SCNN1G  16  23200848  T/C  17.6  0.676  rs3790261  SLC24A3  20  19560664  G/A  35.7  0.554  rs434082  SLC8A1  2  40485074  A/G  15.9  0.727  rs11893826  SLC8A1  2  40564647  A/G  30.5  0.093  rs1937506  -a  13  68035371  A/G  12.8  0.235  rs3754777  STK39  2  169015914  A/G  24.5  0.874  rs6749447  STK39  2  169041386  T/G  35.6  0.464  rs1042714  β2AR  5  148206473  G/C  10.9  0.367  rs1042713  β2AR  5  148206440  G/A  41.6  0.884  SNPs  Genes  Chromosome  Position (bp)  Alleles (minor/major)  MAF (%)  HWE  P  rs4961  ADD1  4  2906707  G/T  46.0  0.884  rs699  AGT  1  230845794  T/C  20.8  0.521  rs2681472  ATP2B1  12  90008959  C/T  34.0  0.859  rs7961152  BCAT1  12  24981611  A/C  10.8  0.054  rs848307  CLCNKA  1  16319232  T/C  29.8  0.541  rs1739843  CLCNKA  1  16343254  T/C  29.8  0.544  rs1010069  CLCNKA  1  16352937  C/T  31.1  0.592  rs1799998  CYP11B2  8  143999600  C/T  28.1  0.348  rs1126742  CYP4A11  6  47398496  C/T  19.9  0.459  rs1799983  eNOS  7  150696111  T/G  10.9  0.566  rs5351  ETBR  13  78475313  G/A  38.1  0.866  rs16998073  FGF5  4  81184341  T/A  45.7  0.301  rs1129649  GNB3  12  6948468  C/T  28.9  0.813  rs1024323  GRK4  4  3006043  A/G  18.7  0.630  rs1801058  GRK4  4  3039150  C/T  43.0  0.259  rs2398162  NR2F2-AS1  15  96830550  A/G  38.4  0.945  rs2288774  NEDD4L  18  55983330  C/T  35.4  0.449  rs4149601  NEDD4L  18  55816791  A/G  16.2  0.835  rs7897633  PRKG1  10  52957721  A/C  49.7  0.973  rs1904694  PRKG1  10  52905494  G/A  38.2  0.478  rs5735  SCNN1G  16  23200848  T/C  17.6  0.676  rs3790261  SLC24A3  20  19560664  G/A  35.7  0.554  rs434082  SLC8A1  2  40485074  A/G  15.9  0.727  rs11893826  SLC8A1  2  40564647  A/G  30.5  0.093  rs1937506  -a  13  68035371  A/G  12.8  0.235  rs3754777  STK39  2  169015914  A/G  24.5  0.874  rs6749447  STK39  2  169041386  T/G  35.6  0.464  rs1042714  β2AR  5  148206473  G/C  10.9  0.367  rs1042713  β2AR  5  148206440  G/A  41.6  0.884  Abbreviations: MAF, minor allele frequency; HWE, Hardy–Weinberg equilibrium; SNP, single-nucleotide polymorphism. ars1937506 locates in intergenic region. View Large Characteristics of the 342 subjects were shown in Table 2. The average age was significantly lower in salt-resistant hypertension group than in SSH group (57.16 ± 8.35 vs. 59.62 ± 8.95 years, P = 0.038). Twenty-four hour urinary sodium concentration of SSH group (118 ± 49.59 mmol/l) was significantly higher than that in salt-resistant hypertension group (104.03 ± 45.95 mmol/l). No significant differences were found in gender, smoking, drinking, exercise, body mass index, blood lipid, and 24-hour urine sodium content between salt-resistant hypertension and SSH groups. Table 2. General characteristics of participants   SRH  SSH  P  Age (year)  57.16 ± 8.35  59.62 ± 8.95  0.038*  Sex      0.286   Male  86 (31.0)  15 (24.2)     Female  191 (69.0)  47 (75.8)    Smoking      0.656   Current  51 (19.0)  13 (22.0)     Seldom/never  196 (72.9)  43 (72.9)     Past smoker  22 (8.2)  3 (5.1)    Drinking      0.918   ≥3 times/week  39 (14.8)  8 (13.6)     ≤2 times/week  27 (10.3)  7 (11.9)     <1 time/week  197 (74.9)  44 (74.6)    Exercise      0.871   5–7 h/week  87 (40.8)  11 (33.3)     3–4 h/week  21 (9.9)  3 (9.1)     1–2 h/week  27 (12.7)  4 (12.1)     <1 h/week  78 (36.7)  15 (45.5)    BMI (kg/m2)  27.52 ± 3.62  27.47 ± 3.61  0.916  TC (mmol/l)  4.99 ± 1.02  5.16 ± 0.88  0.239  HDLC (mmol/l)  1.42 ± 0.35  1.43 ± 0.31  0.851  LDLC (mmol/l)  3.37 ± 1.05  3.76 ± 1.05  0.118  NaConc24h (mmol/l)  104.03 ± 45.95  118 ± 49.59  0.045*  Na24h (mmol)  196.84 ± 91.53  179.47 ± 87.59  0.182    SRH  SSH  P  Age (year)  57.16 ± 8.35  59.62 ± 8.95  0.038*  Sex      0.286   Male  86 (31.0)  15 (24.2)     Female  191 (69.0)  47 (75.8)    Smoking      0.656   Current  51 (19.0)  13 (22.0)     Seldom/never  196 (72.9)  43 (72.9)     Past smoker  22 (8.2)  3 (5.1)    Drinking      0.918   ≥3 times/week  39 (14.8)  8 (13.6)     ≤2 times/week  27 (10.3)  7 (11.9)     <1 time/week  197 (74.9)  44 (74.6)    Exercise      0.871   5–7 h/week  87 (40.8)  11 (33.3)     3–4 h/week  21 (9.9)  3 (9.1)     1–2 h/week  27 (12.7)  4 (12.1)     <1 h/week  78 (36.7)  15 (45.5)    BMI (kg/m2)  27.52 ± 3.62  27.47 ± 3.61  0.916  TC (mmol/l)  4.99 ± 1.02  5.16 ± 0.88  0.239  HDLC (mmol/l)  1.42 ± 0.35  1.43 ± 0.31  0.851  LDLC (mmol/l)  3.37 ± 1.05  3.76 ± 1.05  0.118  NaConc24h (mmol/l)  104.03 ± 45.95  118 ± 49.59  0.045*  Na24h (mmol)  196.84 ± 91.53  179.47 ± 87.59  0.182  *P < 0.05. Abbreviations: BMI, body mass index; HDLC, high-density lipoprotein cholesterol; LDLC, low-density lipoprotein cholesterol; SRH, salt-resistant hypertension; SSH, salt-sensitive hypertension; TC, total cholesterol. View Large Association between SNPs and SSBP Each SNP was tested for the association with BP change in both process of acute salt loading and diuresis shrinkage test. In the process of acute salt loading, P values of those SNPs significantly associated with BP change before FDR correction and FDR_q values were shown in Table 3. SNPs in CYP11B2, PRKG1, SLC8A1 genes showed significant association with SBP rising in additive and recessive model after adjusting for age and 24-hour urinary sodium concentration. SNPs in CYP4A11, PRKG1, SLC8A1, and ADRB2 genes showed significant association with DBP rising in recessive model after adjusting for potential confounders. After FDR correction, only rs434082 in SLC8A1 gene was significantly associated with DBP and MAP rising after acute sodium loading. Table 3. P values (before/after FDR correction) for association between SNPs and BP change after acute salt loading and diuresis shrinkage   Crude  Adjusteda  Gene  Additive  Dominant  Recessive  Additive  Dominant  Recessive  Acute salt loading   ΔSBP1b  PRKG1  rs7897633  0.073/0.265  0.025/0.242  0.491/0.838  0.046/0.334  0.019/0.276  0.357/0.609      rs1904694  0.050/0.290  0.169/0.446  0.056/0.541  0.047/0.273  0.168/0.487  0.050/0.483    SLC8A1  rs434082  0.007/0.203  0.024/0.348  0.016/0.232  0.012/0.348  0.044/0.319  0.017/0.247   ΔDBP1b  CYP4A11  rs1126742  0.119/0.575  0.321/0.716  0.024/0.232  0.095/0.459  0.273/0.660  0.018/0.261    PRKG1  rs7897633  0.006/0.087  0.044/0.319  0.012/0.348  0.010/0.145  0.049/0.284  0.023/0.222    SLC8A1  rs434082  0.001/0.029c  0.001/0.029c  0.060/0.365  0.001/0.029c  0.002/0.049c  0.063/0.365    ADRB2  rs1042714  0.230/0.834  0.482/0.874  0.013/0.189  0.221/0.712  0.480/0.773  0.011/0.319    ADRB2  rs1042713  0.234/0.754  0.046/0.267  0.755/0.952  0.148/0.613  0.029/0.280  0.937/0.937   ΔMAP1b  PRKG1  rs7897633  0.008/0.116  0.015/0.109  0.056/0.406  0.008/0.116  0.014/0.135  0.059/0.428      rs1904694  0.048/0.348  0.232/0.612  0.028/0.271  0.053/0.384  0.276/0.616  0.024/0.232    SLC8A1  rs434082  3.50 × 10–4/0.010c  0.001/0.029c  0.015/0.435  0.001/0.029c  0.003/0.044c  0.016/0.464    ADRB2  rs1042714  0.303/0.628  0.576/0.879  0.019/0.276  0.304/0.588  0.590/0.901  0.019/0.276    ADRB2  rs1042713  0.160/0.464  0.048/0.232  0.915/0.915  0.116/0.481  0.037/0.179  0.787/0.992  Diuresis shrinkage   ΔSBP2b  BCAT1  rs7961152  0.090/0.653  0.802/0.969  2.77 × 10–5/0.001c  0.291/0.767  0.225/0.725  3.85 × 10–5/0.001c    CLCNKA  rs848307  0.590/0.856  0.517/0.789  0.022/0.160  0.631/0.963  0.463/0.671  0.021/0.152      rs1739843  0.950/0.950  0.251/0.728  0.036/0.209  0.959/0.959  0.232/0.612  0.032/0.186      rs1010069  0.492/0.892  0.539/0.782  0.011/0.106  0.594/0.957  0.418/0.671  0.012/0.174    eNOS  rs1799983  0.572/0.873  0.397/0.647  0.044/0.604  0.720/0.994  0.570/0.787  0.049/0.237    PRKG1  rs1904694  0.003/0.087  0.026/0.754  0.008/0.116  0.005/0.145  0.030/0.870  0.012/0.116   ΔDBP2b  PRKG1  rs1904694  0.015/0.218  0.026/0.377  0.105/0.945  0.027/0.783  0.045/0.435  0.126/0.680   ΔMAP2b  BCAT1  rs7961152  0.236/0.856  0.498/0.903  0.003/0.087  0.239/0.990  0.503/0.858  0.003/0.087    eNOS  rs1799983  0.485/0.879  0.862/0.961  0.028/0.271  0.500/0.906  0.881/0.912  0.031/0.300    PRKG1  rs1904694  0.002/0.058  0.009/0.261  0.015/0.218  0.004/0.116  0.015/0.435  0.021/0.305    Crude  Adjusteda  Gene  Additive  Dominant  Recessive  Additive  Dominant  Recessive  Acute salt loading   ΔSBP1b  PRKG1  rs7897633  0.073/0.265  0.025/0.242  0.491/0.838  0.046/0.334  0.019/0.276  0.357/0.609      rs1904694  0.050/0.290  0.169/0.446  0.056/0.541  0.047/0.273  0.168/0.487  0.050/0.483    SLC8A1  rs434082  0.007/0.203  0.024/0.348  0.016/0.232  0.012/0.348  0.044/0.319  0.017/0.247   ΔDBP1b  CYP4A11  rs1126742  0.119/0.575  0.321/0.716  0.024/0.232  0.095/0.459  0.273/0.660  0.018/0.261    PRKG1  rs7897633  0.006/0.087  0.044/0.319  0.012/0.348  0.010/0.145  0.049/0.284  0.023/0.222    SLC8A1  rs434082  0.001/0.029c  0.001/0.029c  0.060/0.365  0.001/0.029c  0.002/0.049c  0.063/0.365    ADRB2  rs1042714  0.230/0.834  0.482/0.874  0.013/0.189  0.221/0.712  0.480/0.773  0.011/0.319    ADRB2  rs1042713  0.234/0.754  0.046/0.267  0.755/0.952  0.148/0.613  0.029/0.280  0.937/0.937   ΔMAP1b  PRKG1  rs7897633  0.008/0.116  0.015/0.109  0.056/0.406  0.008/0.116  0.014/0.135  0.059/0.428      rs1904694  0.048/0.348  0.232/0.612  0.028/0.271  0.053/0.384  0.276/0.616  0.024/0.232    SLC8A1  rs434082  3.50 × 10–4/0.010c  0.001/0.029c  0.015/0.435  0.001/0.029c  0.003/0.044c  0.016/0.464    ADRB2  rs1042714  0.303/0.628  0.576/0.879  0.019/0.276  0.304/0.588  0.590/0.901  0.019/0.276    ADRB2  rs1042713  0.160/0.464  0.048/0.232  0.915/0.915  0.116/0.481  0.037/0.179  0.787/0.992  Diuresis shrinkage   ΔSBP2b  BCAT1  rs7961152  0.090/0.653  0.802/0.969  2.77 × 10–5/0.001c  0.291/0.767  0.225/0.725  3.85 × 10–5/0.001c    CLCNKA  rs848307  0.590/0.856  0.517/0.789  0.022/0.160  0.631/0.963  0.463/0.671  0.021/0.152      rs1739843  0.950/0.950  0.251/0.728  0.036/0.209  0.959/0.959  0.232/0.612  0.032/0.186      rs1010069  0.492/0.892  0.539/0.782  0.011/0.106  0.594/0.957  0.418/0.671  0.012/0.174    eNOS  rs1799983  0.572/0.873  0.397/0.647  0.044/0.604  0.720/0.994  0.570/0.787  0.049/0.237    PRKG1  rs1904694  0.003/0.087  0.026/0.754  0.008/0.116  0.005/0.145  0.030/0.870  0.012/0.116   ΔDBP2b  PRKG1  rs1904694  0.015/0.218  0.026/0.377  0.105/0.945  0.027/0.783  0.045/0.435  0.126/0.680   ΔMAP2b  BCAT1  rs7961152  0.236/0.856  0.498/0.903  0.003/0.087  0.239/0.990  0.503/0.858  0.003/0.087    eNOS  rs1799983  0.485/0.879  0.862/0.961  0.028/0.271  0.500/0.906  0.881/0.912  0.031/0.300    PRKG1  rs1904694  0.002/0.058  0.009/0.261  0.015/0.218  0.004/0.116  0.015/0.435  0.021/0.305  Abbreviations: BP, blood pressure; DBP, diastolic blood pressure; FDR, false discovery rate; MAP, mean arterial pressure; SNP, single-nucleotide polymorphism. aAdjusted for age and 24-hour urinary sodium concentration. bΔSBP1, ΔDBP1, and ΔMAP1 were defined as the BP after acute salt loading for 2 hours minus BP before acute salt loading. cFDR_q < 0.05. View Large In the process of oral taking furosemide, SNPs in CLCNKA, eNOS, PRKG1 gene were associated with SBP decreasing, and SNPs in PRKG1 gene was associated with DBP decreasing. After FDR correction, rs7961152 in BCAT1 was significantly associated with SBP reduction in recessive model with and without adjusting for potential confounders. Details of the results were shown in Table 3. Association between rs434082 in SLC8A1 gene and SSBP Rs434082 in SLC8A1 gene was found to be significantly associated with BP change in the process of acute salt loading after FDR correction. The effect size (β) and 95% confidence interval for association between rs434082 in SLC8A1 gene and SSBP were shown in Table 4. In additive model, A allele increased DBP for 2.8 mm Hg (FDR_q = 0.029), and increased MAP for 3.1 mm Hg (FDR_q = 0.029) after adjusting for age and 24-hour urinary sodium concentration. In recessive model, A allele increased DBP for 3.0 mm Hg (FDR_q = 0.029), and increased MAP for 3.1 mm Hg (FDR_q = 0.044) after adjusting for age and 24-hour urinary sodium concentration. Table 4. Effect size (β) and 95% CI for association between rs434082 in SLC8A1 gene and blood pressure change after acute sodium loading BP  Genetic models  Crude, β (95% CI)  P  FDR_q  Adjustedaβ (95% CI)  P  FDR_q  ΔSBP1b  Additive  3.804 (1.052, 6.556)  0.007  0.203  3.665 (0.789, 6.540)  0.012  0.348    AA vs. GG + GA  11.986 (2.221, 21.751)  0.016  0.232  12.101 (2.205, 21.996)  0.017  0.247    GA + AA vs. GG  3.537 (0.460, 6.614)  0.024  0.348  3.337 (0.095, 6.579)  0.044  0.319  ΔDBP1b  Additive  2.828 (1.216, 4.440)  0.001  0.029c  2.850 (1.179, 4.522)  0.001  0.029c    AA vs. GG + GA  5.539 (−0.237, 11.316)  0.060  0.348  5.509 (−0.309, 11.326)  0.063  0.365    GA + AA vs. GG  2.963 (1.163, 4.763)  0.001  0.029c  3.012 (1.130, 4.895)  0.002  0.049c  ΔMAP1b  Additive  3.153 (1.424, 4.882)  <0.001  0.012c  3.122 (1.321, 4.923)  0.001  0.029c    AA vs. GG + GA  7.688 (1.506, 13.870)  0.015  0.435  7.706 (1.457, 13.954)  0.016  0.464    GA + AA vs. GG  3.154 (1.221, 5.088)  0.001  0.029c  3.121 (1.089, 5.153)  0.003  0.044c  BP  Genetic models  Crude, β (95% CI)  P  FDR_q  Adjustedaβ (95% CI)  P  FDR_q  ΔSBP1b  Additive  3.804 (1.052, 6.556)  0.007  0.203  3.665 (0.789, 6.540)  0.012  0.348    AA vs. GG + GA  11.986 (2.221, 21.751)  0.016  0.232  12.101 (2.205, 21.996)  0.017  0.247    GA + AA vs. GG  3.537 (0.460, 6.614)  0.024  0.348  3.337 (0.095, 6.579)  0.044  0.319  ΔDBP1b  Additive  2.828 (1.216, 4.440)  0.001  0.029c  2.850 (1.179, 4.522)  0.001  0.029c    AA vs. GG + GA  5.539 (−0.237, 11.316)  0.060  0.348  5.509 (−0.309, 11.326)  0.063  0.365    GA + AA vs. GG  2.963 (1.163, 4.763)  0.001  0.029c  3.012 (1.130, 4.895)  0.002  0.049c  ΔMAP1b  Additive  3.153 (1.424, 4.882)  <0.001  0.012c  3.122 (1.321, 4.923)  0.001  0.029c    AA vs. GG + GA  7.688 (1.506, 13.870)  0.015  0.435  7.706 (1.457, 13.954)  0.016  0.464    GA + AA vs. GG  3.154 (1.221, 5.088)  0.001  0.029c  3.121 (1.089, 5.153)  0.003  0.044c  Abbreviations: BP, blood pressure; CI, confidence interval; DBP, diastolic blood pressure; FDR, false discovery rate; MAP, mean arterial pressure. aAdjusted for age and 24-hour urinary sodium concentration. bΔSBP1, ΔDBP1, and ΔMAP1 were defined as the BP after acute salt loading for 2 hours minus BP before acute salt loading. cFDR_q < 0.05. View Large DISCUSSION Our study demonstrated that SNPs in CYP11B2, ADRB2, SLC8A1, CYP4A11 genes were nominally associated with BP rising after acute salt loading, while SNPs in BCAT1, CLCNKA, and eNOS gene nominally associated with BP reduction during diuresis shrinkage. Rs1904694 in PRKG1 gene involved in BP changes during both processes. After adjusted for multiple testing, rs434082 in SLC8A1 gene was significantly associated with BP rising after acute salt loading. Luft et al.18 demonstrated firstly in 1977 that a 4-hour intravenous infusion of 2 l saline and a 10 mmol sodium diet plus 40 mg furosemide orally could identify salt sensitivity. Various methods have been modified to identify salt sensitivity after that. Sullivan et al. provided evidence that daily 150 mmol sodium intake can distinguish sodium sensitivity efficiently.25 However, there is not a standard protocol to identify salt sensitivity. In the present study, acute oral salt loading and oral furosemide were used together to identify salt sensitivity. This method is modified from Sullivan’s salt sensitivity test, and has been used in Chinese population previously.27 GenSalt study focus on response to 7-day low-sodium or high-sodium dietary intervention,21,22 while our current study focus on BP changes in the process of acute salt loading and diuresis shrinkage. Because salt sensitivity tests are usually in poor compliance, it is especially hard to distinguish salt sensitivity people in the community-based study. As an important strength, participants were recruited from community in this study, which can avoid selection bias. Current study recruited 342 hypertension individuals to define their salt sensitivity status. To our knowledge, among the studies use acute sodium loading and diuresis shrinkage to distinguish salt sensitivity, this study is the largest community-based study in China. What is more, it is the first study to explore SNPs involved in BP response in both process of acute salt loading and diuresis shrinkage in a Han Chinese population. In the current study, polymorphisms in CYP11B2, ADRB2, and SLC8A1 gene were associated with ascending BP during acute salt loading before FDR correction. CYP11B2 gene is in renin–angiotensin system pathway. ADRB2 gene is involved in the synthesis of catecholamine’s receptor and in the pathway associated with sympathetic nervous system. SLC8A1 gene regulates vascular smooth muscle tone through an increase in the concentration of cytoplasmic calcium (Ca2+). All the above genes are involved in the process of increasing vascular reactivity. On the contrary, most genes associated with BP reduction after diuresis shrinkage were involved in decreasing vascular reactivity or renal sodium transport. For example, eNOS gene related to nitric oxide (NO) synthesis was associated with BP reduction after diuresis shrinkage. Increasing NO production can lead to endothelial vasodilatation and decrease sodium transport. Regulation of SSBP is a complex and systematic biological process. Our results suggested genes related to increasing vascular reactivity and renal sodium transport were associated with BP rising after acute salt loading, while genes related to decreasing vascular reactivity and renal sodium transport were associated with BP reducing after diuresis shrinkage. SNPs in PRKG1 gene were nominally associated with SSBP in both process of acute salt loading and diuresis shrinkage. PRKG1 gene locates on chromosome 10, and encodes the soluble guanosine 3′,5′-cyclic phosphate-dependent protein kinase type. PRKG1 proteins can not only cause vascular smooth muscle contraction by reducing the activity of NO, but also raise BP by increase Ca2+ concentration in cells. It has been demonstrated that salt sensitivity is triggered by Ca2+ entry through in arterial smooth muscle.28 A GWAS conducted by Citterio et al. showed that rs7897633, which locates in the first introns of PRKG1 gene, might be associated with variation in DBP after acute salt loading (P  =  2.34 × 10–5).1 Our study showed rs7897633 in PRKG1 associated with SBP and DBP after acute salt loading before FDR correction, which was consistent with this GWAS. We also found rs1799983 in eNOS gene was associated with BP reduction after diuresis shrinkage before FDR correction. PRKG1 involved in NO signaling, while eNOS is also related to NO synthesis. These 2 genes have been shown to be associated with vascular smooth muscle (VSM) dysfunction and essential hypertension in previous studies.1 In the current study, SNPs within these 2 genes contribute to the process of both BP rising after acute oral salt loading and BP reduction after diuresis shrinkage, which indicated the important role of VSMs function in regulating BP. After FDR correction, rs434082 in SLC8A1 gene was significantly associated with BP rising after acute salt loading. SLC8A1 codes for Na+/Ca2+ exchanger type 1, which plays an important role in the biochemical control of peripheral vascular resistance, and is involved in the pathogenesis of hypertension and salt sensitivity.29,30SLC8A1 gene was previously found to be associated with SBP and hypertension in KoraS3 cohort (P < 10–3).31 Another recent study of candidate genes for SSH demonstrated a significant interaction between SLC8A1 gene and renal pressure-natriuresis in response to acute salt loading, supporting the pathophysiological mechanisms of the effect of SLC8A1 gene on SSH. This study also revealed that SLC8A1 gene rs434082 had an effect size of 3.16 mm Hg on SBP response to salt loading,1 which was consistent with our results. In the current study, rs7961152 in BCAT1 gene was found to be associated with SBP in recessive model after FDR correction. The Wellcome Trust Case Control Consortium (WTCCC) conducted a GWAS and highlighted rs7961152 in BCAT1 gene might be associated with essential hypertension (P = 3.03 × 10–5).32 Two years later, Hong et al. found rs7961152 was associated with hypertension risk in Korean population (odds ratio = 1.286, P = 0.040).33 Another study conducted in 101 Korean participants also found rs7961152 to be significantly associated with salt sensitivity after adjusting for potential confounders.34 Our result was consistent with the above studies. Branched chain aminotransferase 1 (BCAT1) are essential for cell growth and apoptosis, and it had been reported to be associated with different types of cancer.35,36 The mechanisms of its effect to salt sensitivity are still unclear. As a limitation of the current study, because only 2 participants had AA genotype in rs7961152, the statistical power in recessive model is relatively low. Larger sample size is still needed to confirm our positive results. However, the statistical power of our main results, the association between rs434082 in SLC8A1 gene and BP change after acute sodium loading in additive and recessive model, was above 90%. Thus, although the sample size is relatively small to explore the effect of every candidate SNP on BP change, it is large enough to detect the effect of rs434082 in SLC8A1 on SBP after acute salt load. This result may indicate a potential pathogenesis of salt sensitivity hypertension. In conclusion, we found SLC8A1 gene rs434082 contributes to BP change in the process of acute salt loading in Han Chinese population. DISCLOSURE The authors declared no conflict of interest. ACKNOWLEDGMENTS This study received financial support from the Natural Science Foundation of China (81373076, 81602908), the National key research and development program of China (2016YFC0900603), and the Importation and Development of High-Caliber Talents Project of Beijing Municipal Institutions (CIT&TCD201504088).We thank associated professor Tao Wang in Genetic and Genomics Data Analysis Unit, Division of Biostatistics, Albert Einstein College. He provided valuable suggestions on statistical methods and help us to revise the manuscript in writing. REFERENCES 1. Elijovich F, Weinberger MH, Anderson CA, Appel LJ, Bursztyn M, Cook NR, Dart RA, Newton-Cheh CH, Sacks FM, Laffer CL; American Heart Association Professional and Public Education Committee of the Council on Hypertension; Council on Functional Genomics and Translational Biology; and Stroke Council. Salt sensitivity of blood pressure: a scientific statement from the American Heart Association. 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Genetic Variation in SLC8A1 Gene Involved in Blood Pressure Responses to Acute Salt Loading

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© American Journal of Hypertension, Ltd 2017. All rights reserved. For Permissions, please email: journals.permissions@oup.com
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Abstract

Abstract BACKGROUND Salt sensitivity of blood pressure (SSBP) increases the risk of cardiovascular complications, and the heritability of SSBP is about 50% in Chinese population. However, studies identifying genes involved in BP responses to acute sodium loading and diuresis shrinkage are still limited. METHOD A total of 342 essential hypertensives from Beijing were recruited in our study. A modified Sullivan’s acute oral saline load and diuresis shrinkage test was conducted to each individual. Medical history and lifestyle risk factors were obtained by questionnaire. Generalized linear model was used to examine the associations of 29 single-nucleotide polymorphisms (SNPs) with SSBP and false discovery rate (FDR) was used to correct P values for multiple testing. RESULTS In the process of acute sodium loading, after adjusting for age and 24-hour urinary sodium concentration, SNPs in CYP11B2, PRKG1, SLC8A1 genes were significantly associated with systolic BP (SBP) rising in the additive and recessive model; SNPs in CYP4A11, PRKG1, SLC8A1, and ADRB2 genes were significantly associated with diastolic BP (DBP) rising. In the process of diuresis shrinkage, SNPs of CLCNKA, eNOS, PRKG1 gene were associated with SBP and DBP decreasing. After FDR correction, rs434082 in SLC8A1 gene was still significantly associated with blood pressure rising during salt load. In the additive model, A allele increased DBP of 2.8 mm Hg (FDR_q = 0.029) and MAP of 3.1 mm Hg (FDR_q = 0.029) after adjusting for age and 24-hour urinary sodium concentration. CONCLUSION SLC8A1 gene may contribute to BP change in the process of acute sodium loading in a Han Chinese population. acute salt loading, blood pressure, hypertension, salt sensitivity, single-nucleotide polymorphisms Blood pressure (BP) responses to the changes of salt intake. Definition of salt sensitivity of blood pressure (SSBP) is that BP of some members of the population exhibits changes parallel to changes in salt intake.1 About half of the hypertensions and 26% of the normotensives are salt sensitivity.2–4 SSBP and high salt intake will increase the risk of cardiovascular complications5,6 and may lead to left ventricular hypertrophy, microalbuminuria, and endothelial dysfunction.7 BP responses to sodium intake are partially under genetic control. The heritability of SSBP is about 50% in Chinese subjects, which is higher than that of hypertension.8 Genes can influence SSBP through different pathways. Renin–angiotensin system involves in regulating renal sodium transportation, especially under the condition of sodium deficit,9 and it is the most important regulator of BP. It has been demonstrated that AGT,10AGTR1,11CHP11B2,12 and STRN13 genes in renin–angiotensin system pathway are associated with salt-sensitive hypertension (SSH). Additionally, genes that regulate vascular smooth muscle tone, like SLC24A3 and SLC8A11, can influence SSH through modifying the concentration of Ca2+. Moreover, GRK4 gene variants can also affect hypertension and salt sensitivity through impaired natriuretic response.14–16 Recent genome-wide association study (GWAS) also demonstrated several novel genes associated with SSH. PRKG1 gene was found to be associated with variation in diastolic BP (DBP) after acute salt load on 329 subjects.1 The Genetic Epidemiology Network of Salt Sensitivity (GenSalt) study17 demonstrated that MKNK1, C2orf80, EPHA6, SCOC-AS1, SCOC, CLGN, MGAT4D, ARHGAP42, CASP4, and LINC01478 genes interacted with sodium to influence BP among 1,876 Chinese participants. Salt sensitivity can be assessed by different protocols.18 A 4-hour intravenous infusion of 2 l saline and a 10 mmol sodium diet plus 40 mg furosemide orally were used to identify salt sensitivity in 1977. Either mean arterial pressure (MAP) raises more than 5 mm Hg after salt loading or MAP reduces more than 10 mm Hg after diuresis shrinkage were defined as salt sensitivity. SSH patients have irregular vascular response to angiotensin-II infusion.19 High salt load may cause abnormal BP elevation in SSH patients by activates tissue renin–angiotensin system. Abnormally renal tubular reclamation of Na+ and Cl− may contribute to the anomalous BP change in diuresis shrinkage.20 Different underlying pathophysiological mechanism may indicate different genetic mechanism involved in the process of acute salt loading and diuresis shrinkage. GenSalt study recently found that genes in natriuretic peptide system21 and SGK1 gene22 were associated with BP response to 7-day low-sodium or high-sodium dietary intervention. Snyder et al.23 found that Arg16Gly polymorphism in ADRB2 gene affected natriuretic response to acute saline infusion, which may impact BP regulation. However, GenSalt study focuses on genetic determinants which may affect BP change during chronic sodium loading. Although the study conducted by Snyder et al. focuses on acute salt loading, the sample size is relatively small (n = 31). Studies identifying specific genes involved in BP changes parallel to acute salt loading and diuresis shrinkage of a considerable sample size are still limited. In the present study, we aimed at identifying single-nucleotide polymorphism (SNPs) associated with BP changes during the process of acute oral saline load and diuresis shrinkage. A review as preformed to select candidate genes, and a modified Sullivan’s acute oral saline load and diuresis shrinkage test (MSAOSL-DST) was used to identify salt sensitivity hypertension. METHODS Study population and data collection The study was conducted in 4 communities in a district of Beijing in 2011. Inclusion criteria was as follows: (i) Chinese Han unrelated residents who had been living in Beijing for more than 5 years; (ii) Essential hypertension diagnosed by secondary hospital or tertiary hospital, or on antihypertension medications; (iii) Stage 1 hypertension (140 mm Hg ≤ systolic BP (SBP) ≤ 159 mm Hg and/or 90 mm Hg ≤ DBP ≤ 99 mm Hg). All the participants were asked to stop taking antihypertensive medicine for at least 12 hours. Participants with cardiac insufficiency, cardiomyopathy, valvulopathy, congenital heart disease, myocardial infarction, stroke, type 2 diabetes mellitus, hepatopathy, nephropathy, cancer, and secondary hypertension were excluded. Our protocol was approved by Ethics Committee of Capital Medical University. All participants provided their informed consent prior participating in this study. In the end, 342 unrelated hypertension patients were recruited. Demographic characters, lifestyle risk factors, and medical history of chronic diseases and medication history were collected through a face-to-face interview by trained interviewers using uniform questionnaires. Smoking was defined as at least 1 cigarette per day, lasting for more than 1 year. Those who have not smoked for at least 3 months were defined as smoking cessation. Mercury column type sphygmomanometer was used to measure BP. People who had smoked, exercised, had caffeinated products, or other stimulants will be asked to delay obtaining BP measurements for at least 30 minutes. Two staffs were adequately trained in BP techniques follow the recommendations of the American Heart Association,24 and they measured the BP of all the participants in this study. BP measurement was taken 3 times at the right brachial artery after the participant has rested in a seated position for 5 minutes. MAP was computed according to the standard formula MAP = (SBP + 2 × DBP)/3. MAP was used to represent BP. Each patient was asked to provide a collection of 24-hour urine, and after abandon the first urine at 6:00 am, participants collected all urine from then on to the next 6:00 am. One-milliliter urine was derived from the mixed 24-hour urine to measure the concentrate of Na+. Assessment of salt sensitivity The assessment of salt sensitivity was achieved by a modified Sullivan’s method (MSAOSL-DST) which has been described in detail in our previously published paper.25,26 Each fasting participant orally took 1,000 ml 0.9% NaCl on 8:00 am within 30 minutes. BP was measured before salt intake and 2 hours after salt loading. Then participants took 40-mg furosemide orally, and were measured for BP 2 hours later again. MAP raising more than 5 mm Hg after acute salt loading and (or) MAP reducing more than 10 mm Hg after diuresis shrinkage test was defined as SSH. MAP raising less than 5 mm Hg after acute salt loading and (or) MAP reducing less than 10 mm Hg after diuresis shrinkage was defined as salt-resistant hypertension. Candidate gene selection Candidate genes were select based on the following inclusion criteria. Candidate genes have been reported to be associated with SSH (or SSBP) in Chinese population, or associated with SSH in GWAS, or associated with SSH (or SSBP) in meta-analysis or systematic review. Genetic data were downloaded from database of the international HapMap Project (HapMap Data Rel 24/phase IINov08, on NVBI B36 assembly, dbSNP b126), and SNPs with the minor allele frequency in Han Chinese population more than 0.10 were selected by the Haploview 4.0 software (version 4.0; Mark Daly’s Laboratory, Broad Institute; http://sourceforge.net/projects/haploview/). DNA extraction and genotyping We selected 29 SNPs to test their association with SSBP. Genomic DNA was extracted from the peripheral blood with a QIAamp DNA Blood Mini Kit (Tiangen, Hilden, Germany). Sequenom Mass ARRAY Platform was used to do genotyping (San Diego, CA). All SNPs in this report had a genotyping success rate of >90%. The value of OD260/OD280 was calculated in order to evaluate the concentration of DNA. Result showed that the DNA concentration was >10 ng/µl if OD260/OD280 was between 1.7 and 2.0. Statistical analysis If all continuous variables were with normal distribution, then means ± SDs were reported, otherwise, medians ± quintiles were reported. Number (percentages) was reported for categorical variables. Student’s t-test was used to examine the difference between 2 groups of continuous variables with normal distribution. Wilcoxon rank–sum nonparametric test was used to explore the disparity of continuous variables with nonnormal distribution. Chi-squared test was used to test for the difference of categorical variables. Chi-squared test was conducted to each SNP in control group to detect for deviation from Hardy–Weinberg equilibrium. Generalized linear model was used to examine the associations of the SNPs with SSBP. False discovery rate (FDR) was calculated to account for multiple testing. All analysis was conducted in IBM SPSS Statistics 19.0 software (SPSS, Chicago, IL). RESULTS General information of SNPs and characteristics of participants The minor allele frequency of 29 selected SNPs ranged from 10.8% to 46.0%. All SNPs were in Hardy–Weinberg equilibrium in control group (P > 0.05). Details were show in Table 1. Table 1. Information of SNPs included in the study SNPs  Genes  Chromosome  Position (bp)  Alleles (minor/major)  MAF (%)  HWE  P  rs4961  ADD1  4  2906707  G/T  46.0  0.884  rs699  AGT  1  230845794  T/C  20.8  0.521  rs2681472  ATP2B1  12  90008959  C/T  34.0  0.859  rs7961152  BCAT1  12  24981611  A/C  10.8  0.054  rs848307  CLCNKA  1  16319232  T/C  29.8  0.541  rs1739843  CLCNKA  1  16343254  T/C  29.8  0.544  rs1010069  CLCNKA  1  16352937  C/T  31.1  0.592  rs1799998  CYP11B2  8  143999600  C/T  28.1  0.348  rs1126742  CYP4A11  6  47398496  C/T  19.9  0.459  rs1799983  eNOS  7  150696111  T/G  10.9  0.566  rs5351  ETBR  13  78475313  G/A  38.1  0.866  rs16998073  FGF5  4  81184341  T/A  45.7  0.301  rs1129649  GNB3  12  6948468  C/T  28.9  0.813  rs1024323  GRK4  4  3006043  A/G  18.7  0.630  rs1801058  GRK4  4  3039150  C/T  43.0  0.259  rs2398162  NR2F2-AS1  15  96830550  A/G  38.4  0.945  rs2288774  NEDD4L  18  55983330  C/T  35.4  0.449  rs4149601  NEDD4L  18  55816791  A/G  16.2  0.835  rs7897633  PRKG1  10  52957721  A/C  49.7  0.973  rs1904694  PRKG1  10  52905494  G/A  38.2  0.478  rs5735  SCNN1G  16  23200848  T/C  17.6  0.676  rs3790261  SLC24A3  20  19560664  G/A  35.7  0.554  rs434082  SLC8A1  2  40485074  A/G  15.9  0.727  rs11893826  SLC8A1  2  40564647  A/G  30.5  0.093  rs1937506  -a  13  68035371  A/G  12.8  0.235  rs3754777  STK39  2  169015914  A/G  24.5  0.874  rs6749447  STK39  2  169041386  T/G  35.6  0.464  rs1042714  β2AR  5  148206473  G/C  10.9  0.367  rs1042713  β2AR  5  148206440  G/A  41.6  0.884  SNPs  Genes  Chromosome  Position (bp)  Alleles (minor/major)  MAF (%)  HWE  P  rs4961  ADD1  4  2906707  G/T  46.0  0.884  rs699  AGT  1  230845794  T/C  20.8  0.521  rs2681472  ATP2B1  12  90008959  C/T  34.0  0.859  rs7961152  BCAT1  12  24981611  A/C  10.8  0.054  rs848307  CLCNKA  1  16319232  T/C  29.8  0.541  rs1739843  CLCNKA  1  16343254  T/C  29.8  0.544  rs1010069  CLCNKA  1  16352937  C/T  31.1  0.592  rs1799998  CYP11B2  8  143999600  C/T  28.1  0.348  rs1126742  CYP4A11  6  47398496  C/T  19.9  0.459  rs1799983  eNOS  7  150696111  T/G  10.9  0.566  rs5351  ETBR  13  78475313  G/A  38.1  0.866  rs16998073  FGF5  4  81184341  T/A  45.7  0.301  rs1129649  GNB3  12  6948468  C/T  28.9  0.813  rs1024323  GRK4  4  3006043  A/G  18.7  0.630  rs1801058  GRK4  4  3039150  C/T  43.0  0.259  rs2398162  NR2F2-AS1  15  96830550  A/G  38.4  0.945  rs2288774  NEDD4L  18  55983330  C/T  35.4  0.449  rs4149601  NEDD4L  18  55816791  A/G  16.2  0.835  rs7897633  PRKG1  10  52957721  A/C  49.7  0.973  rs1904694  PRKG1  10  52905494  G/A  38.2  0.478  rs5735  SCNN1G  16  23200848  T/C  17.6  0.676  rs3790261  SLC24A3  20  19560664  G/A  35.7  0.554  rs434082  SLC8A1  2  40485074  A/G  15.9  0.727  rs11893826  SLC8A1  2  40564647  A/G  30.5  0.093  rs1937506  -a  13  68035371  A/G  12.8  0.235  rs3754777  STK39  2  169015914  A/G  24.5  0.874  rs6749447  STK39  2  169041386  T/G  35.6  0.464  rs1042714  β2AR  5  148206473  G/C  10.9  0.367  rs1042713  β2AR  5  148206440  G/A  41.6  0.884  Abbreviations: MAF, minor allele frequency; HWE, Hardy–Weinberg equilibrium; SNP, single-nucleotide polymorphism. ars1937506 locates in intergenic region. View Large Characteristics of the 342 subjects were shown in Table 2. The average age was significantly lower in salt-resistant hypertension group than in SSH group (57.16 ± 8.35 vs. 59.62 ± 8.95 years, P = 0.038). Twenty-four hour urinary sodium concentration of SSH group (118 ± 49.59 mmol/l) was significantly higher than that in salt-resistant hypertension group (104.03 ± 45.95 mmol/l). No significant differences were found in gender, smoking, drinking, exercise, body mass index, blood lipid, and 24-hour urine sodium content between salt-resistant hypertension and SSH groups. Table 2. General characteristics of participants   SRH  SSH  P  Age (year)  57.16 ± 8.35  59.62 ± 8.95  0.038*  Sex      0.286   Male  86 (31.0)  15 (24.2)     Female  191 (69.0)  47 (75.8)    Smoking      0.656   Current  51 (19.0)  13 (22.0)     Seldom/never  196 (72.9)  43 (72.9)     Past smoker  22 (8.2)  3 (5.1)    Drinking      0.918   ≥3 times/week  39 (14.8)  8 (13.6)     ≤2 times/week  27 (10.3)  7 (11.9)     <1 time/week  197 (74.9)  44 (74.6)    Exercise      0.871   5–7 h/week  87 (40.8)  11 (33.3)     3–4 h/week  21 (9.9)  3 (9.1)     1–2 h/week  27 (12.7)  4 (12.1)     <1 h/week  78 (36.7)  15 (45.5)    BMI (kg/m2)  27.52 ± 3.62  27.47 ± 3.61  0.916  TC (mmol/l)  4.99 ± 1.02  5.16 ± 0.88  0.239  HDLC (mmol/l)  1.42 ± 0.35  1.43 ± 0.31  0.851  LDLC (mmol/l)  3.37 ± 1.05  3.76 ± 1.05  0.118  NaConc24h (mmol/l)  104.03 ± 45.95  118 ± 49.59  0.045*  Na24h (mmol)  196.84 ± 91.53  179.47 ± 87.59  0.182    SRH  SSH  P  Age (year)  57.16 ± 8.35  59.62 ± 8.95  0.038*  Sex      0.286   Male  86 (31.0)  15 (24.2)     Female  191 (69.0)  47 (75.8)    Smoking      0.656   Current  51 (19.0)  13 (22.0)     Seldom/never  196 (72.9)  43 (72.9)     Past smoker  22 (8.2)  3 (5.1)    Drinking      0.918   ≥3 times/week  39 (14.8)  8 (13.6)     ≤2 times/week  27 (10.3)  7 (11.9)     <1 time/week  197 (74.9)  44 (74.6)    Exercise      0.871   5–7 h/week  87 (40.8)  11 (33.3)     3–4 h/week  21 (9.9)  3 (9.1)     1–2 h/week  27 (12.7)  4 (12.1)     <1 h/week  78 (36.7)  15 (45.5)    BMI (kg/m2)  27.52 ± 3.62  27.47 ± 3.61  0.916  TC (mmol/l)  4.99 ± 1.02  5.16 ± 0.88  0.239  HDLC (mmol/l)  1.42 ± 0.35  1.43 ± 0.31  0.851  LDLC (mmol/l)  3.37 ± 1.05  3.76 ± 1.05  0.118  NaConc24h (mmol/l)  104.03 ± 45.95  118 ± 49.59  0.045*  Na24h (mmol)  196.84 ± 91.53  179.47 ± 87.59  0.182  *P < 0.05. Abbreviations: BMI, body mass index; HDLC, high-density lipoprotein cholesterol; LDLC, low-density lipoprotein cholesterol; SRH, salt-resistant hypertension; SSH, salt-sensitive hypertension; TC, total cholesterol. View Large Association between SNPs and SSBP Each SNP was tested for the association with BP change in both process of acute salt loading and diuresis shrinkage test. In the process of acute salt loading, P values of those SNPs significantly associated with BP change before FDR correction and FDR_q values were shown in Table 3. SNPs in CYP11B2, PRKG1, SLC8A1 genes showed significant association with SBP rising in additive and recessive model after adjusting for age and 24-hour urinary sodium concentration. SNPs in CYP4A11, PRKG1, SLC8A1, and ADRB2 genes showed significant association with DBP rising in recessive model after adjusting for potential confounders. After FDR correction, only rs434082 in SLC8A1 gene was significantly associated with DBP and MAP rising after acute sodium loading. Table 3. P values (before/after FDR correction) for association between SNPs and BP change after acute salt loading and diuresis shrinkage   Crude  Adjusteda  Gene  Additive  Dominant  Recessive  Additive  Dominant  Recessive  Acute salt loading   ΔSBP1b  PRKG1  rs7897633  0.073/0.265  0.025/0.242  0.491/0.838  0.046/0.334  0.019/0.276  0.357/0.609      rs1904694  0.050/0.290  0.169/0.446  0.056/0.541  0.047/0.273  0.168/0.487  0.050/0.483    SLC8A1  rs434082  0.007/0.203  0.024/0.348  0.016/0.232  0.012/0.348  0.044/0.319  0.017/0.247   ΔDBP1b  CYP4A11  rs1126742  0.119/0.575  0.321/0.716  0.024/0.232  0.095/0.459  0.273/0.660  0.018/0.261    PRKG1  rs7897633  0.006/0.087  0.044/0.319  0.012/0.348  0.010/0.145  0.049/0.284  0.023/0.222    SLC8A1  rs434082  0.001/0.029c  0.001/0.029c  0.060/0.365  0.001/0.029c  0.002/0.049c  0.063/0.365    ADRB2  rs1042714  0.230/0.834  0.482/0.874  0.013/0.189  0.221/0.712  0.480/0.773  0.011/0.319    ADRB2  rs1042713  0.234/0.754  0.046/0.267  0.755/0.952  0.148/0.613  0.029/0.280  0.937/0.937   ΔMAP1b  PRKG1  rs7897633  0.008/0.116  0.015/0.109  0.056/0.406  0.008/0.116  0.014/0.135  0.059/0.428      rs1904694  0.048/0.348  0.232/0.612  0.028/0.271  0.053/0.384  0.276/0.616  0.024/0.232    SLC8A1  rs434082  3.50 × 10–4/0.010c  0.001/0.029c  0.015/0.435  0.001/0.029c  0.003/0.044c  0.016/0.464    ADRB2  rs1042714  0.303/0.628  0.576/0.879  0.019/0.276  0.304/0.588  0.590/0.901  0.019/0.276    ADRB2  rs1042713  0.160/0.464  0.048/0.232  0.915/0.915  0.116/0.481  0.037/0.179  0.787/0.992  Diuresis shrinkage   ΔSBP2b  BCAT1  rs7961152  0.090/0.653  0.802/0.969  2.77 × 10–5/0.001c  0.291/0.767  0.225/0.725  3.85 × 10–5/0.001c    CLCNKA  rs848307  0.590/0.856  0.517/0.789  0.022/0.160  0.631/0.963  0.463/0.671  0.021/0.152      rs1739843  0.950/0.950  0.251/0.728  0.036/0.209  0.959/0.959  0.232/0.612  0.032/0.186      rs1010069  0.492/0.892  0.539/0.782  0.011/0.106  0.594/0.957  0.418/0.671  0.012/0.174    eNOS  rs1799983  0.572/0.873  0.397/0.647  0.044/0.604  0.720/0.994  0.570/0.787  0.049/0.237    PRKG1  rs1904694  0.003/0.087  0.026/0.754  0.008/0.116  0.005/0.145  0.030/0.870  0.012/0.116   ΔDBP2b  PRKG1  rs1904694  0.015/0.218  0.026/0.377  0.105/0.945  0.027/0.783  0.045/0.435  0.126/0.680   ΔMAP2b  BCAT1  rs7961152  0.236/0.856  0.498/0.903  0.003/0.087  0.239/0.990  0.503/0.858  0.003/0.087    eNOS  rs1799983  0.485/0.879  0.862/0.961  0.028/0.271  0.500/0.906  0.881/0.912  0.031/0.300    PRKG1  rs1904694  0.002/0.058  0.009/0.261  0.015/0.218  0.004/0.116  0.015/0.435  0.021/0.305    Crude  Adjusteda  Gene  Additive  Dominant  Recessive  Additive  Dominant  Recessive  Acute salt loading   ΔSBP1b  PRKG1  rs7897633  0.073/0.265  0.025/0.242  0.491/0.838  0.046/0.334  0.019/0.276  0.357/0.609      rs1904694  0.050/0.290  0.169/0.446  0.056/0.541  0.047/0.273  0.168/0.487  0.050/0.483    SLC8A1  rs434082  0.007/0.203  0.024/0.348  0.016/0.232  0.012/0.348  0.044/0.319  0.017/0.247   ΔDBP1b  CYP4A11  rs1126742  0.119/0.575  0.321/0.716  0.024/0.232  0.095/0.459  0.273/0.660  0.018/0.261    PRKG1  rs7897633  0.006/0.087  0.044/0.319  0.012/0.348  0.010/0.145  0.049/0.284  0.023/0.222    SLC8A1  rs434082  0.001/0.029c  0.001/0.029c  0.060/0.365  0.001/0.029c  0.002/0.049c  0.063/0.365    ADRB2  rs1042714  0.230/0.834  0.482/0.874  0.013/0.189  0.221/0.712  0.480/0.773  0.011/0.319    ADRB2  rs1042713  0.234/0.754  0.046/0.267  0.755/0.952  0.148/0.613  0.029/0.280  0.937/0.937   ΔMAP1b  PRKG1  rs7897633  0.008/0.116  0.015/0.109  0.056/0.406  0.008/0.116  0.014/0.135  0.059/0.428      rs1904694  0.048/0.348  0.232/0.612  0.028/0.271  0.053/0.384  0.276/0.616  0.024/0.232    SLC8A1  rs434082  3.50 × 10–4/0.010c  0.001/0.029c  0.015/0.435  0.001/0.029c  0.003/0.044c  0.016/0.464    ADRB2  rs1042714  0.303/0.628  0.576/0.879  0.019/0.276  0.304/0.588  0.590/0.901  0.019/0.276    ADRB2  rs1042713  0.160/0.464  0.048/0.232  0.915/0.915  0.116/0.481  0.037/0.179  0.787/0.992  Diuresis shrinkage   ΔSBP2b  BCAT1  rs7961152  0.090/0.653  0.802/0.969  2.77 × 10–5/0.001c  0.291/0.767  0.225/0.725  3.85 × 10–5/0.001c    CLCNKA  rs848307  0.590/0.856  0.517/0.789  0.022/0.160  0.631/0.963  0.463/0.671  0.021/0.152      rs1739843  0.950/0.950  0.251/0.728  0.036/0.209  0.959/0.959  0.232/0.612  0.032/0.186      rs1010069  0.492/0.892  0.539/0.782  0.011/0.106  0.594/0.957  0.418/0.671  0.012/0.174    eNOS  rs1799983  0.572/0.873  0.397/0.647  0.044/0.604  0.720/0.994  0.570/0.787  0.049/0.237    PRKG1  rs1904694  0.003/0.087  0.026/0.754  0.008/0.116  0.005/0.145  0.030/0.870  0.012/0.116   ΔDBP2b  PRKG1  rs1904694  0.015/0.218  0.026/0.377  0.105/0.945  0.027/0.783  0.045/0.435  0.126/0.680   ΔMAP2b  BCAT1  rs7961152  0.236/0.856  0.498/0.903  0.003/0.087  0.239/0.990  0.503/0.858  0.003/0.087    eNOS  rs1799983  0.485/0.879  0.862/0.961  0.028/0.271  0.500/0.906  0.881/0.912  0.031/0.300    PRKG1  rs1904694  0.002/0.058  0.009/0.261  0.015/0.218  0.004/0.116  0.015/0.435  0.021/0.305  Abbreviations: BP, blood pressure; DBP, diastolic blood pressure; FDR, false discovery rate; MAP, mean arterial pressure; SNP, single-nucleotide polymorphism. aAdjusted for age and 24-hour urinary sodium concentration. bΔSBP1, ΔDBP1, and ΔMAP1 were defined as the BP after acute salt loading for 2 hours minus BP before acute salt loading. cFDR_q < 0.05. View Large In the process of oral taking furosemide, SNPs in CLCNKA, eNOS, PRKG1 gene were associated with SBP decreasing, and SNPs in PRKG1 gene was associated with DBP decreasing. After FDR correction, rs7961152 in BCAT1 was significantly associated with SBP reduction in recessive model with and without adjusting for potential confounders. Details of the results were shown in Table 3. Association between rs434082 in SLC8A1 gene and SSBP Rs434082 in SLC8A1 gene was found to be significantly associated with BP change in the process of acute salt loading after FDR correction. The effect size (β) and 95% confidence interval for association between rs434082 in SLC8A1 gene and SSBP were shown in Table 4. In additive model, A allele increased DBP for 2.8 mm Hg (FDR_q = 0.029), and increased MAP for 3.1 mm Hg (FDR_q = 0.029) after adjusting for age and 24-hour urinary sodium concentration. In recessive model, A allele increased DBP for 3.0 mm Hg (FDR_q = 0.029), and increased MAP for 3.1 mm Hg (FDR_q = 0.044) after adjusting for age and 24-hour urinary sodium concentration. Table 4. Effect size (β) and 95% CI for association between rs434082 in SLC8A1 gene and blood pressure change after acute sodium loading BP  Genetic models  Crude, β (95% CI)  P  FDR_q  Adjustedaβ (95% CI)  P  FDR_q  ΔSBP1b  Additive  3.804 (1.052, 6.556)  0.007  0.203  3.665 (0.789, 6.540)  0.012  0.348    AA vs. GG + GA  11.986 (2.221, 21.751)  0.016  0.232  12.101 (2.205, 21.996)  0.017  0.247    GA + AA vs. GG  3.537 (0.460, 6.614)  0.024  0.348  3.337 (0.095, 6.579)  0.044  0.319  ΔDBP1b  Additive  2.828 (1.216, 4.440)  0.001  0.029c  2.850 (1.179, 4.522)  0.001  0.029c    AA vs. GG + GA  5.539 (−0.237, 11.316)  0.060  0.348  5.509 (−0.309, 11.326)  0.063  0.365    GA + AA vs. GG  2.963 (1.163, 4.763)  0.001  0.029c  3.012 (1.130, 4.895)  0.002  0.049c  ΔMAP1b  Additive  3.153 (1.424, 4.882)  <0.001  0.012c  3.122 (1.321, 4.923)  0.001  0.029c    AA vs. GG + GA  7.688 (1.506, 13.870)  0.015  0.435  7.706 (1.457, 13.954)  0.016  0.464    GA + AA vs. GG  3.154 (1.221, 5.088)  0.001  0.029c  3.121 (1.089, 5.153)  0.003  0.044c  BP  Genetic models  Crude, β (95% CI)  P  FDR_q  Adjustedaβ (95% CI)  P  FDR_q  ΔSBP1b  Additive  3.804 (1.052, 6.556)  0.007  0.203  3.665 (0.789, 6.540)  0.012  0.348    AA vs. GG + GA  11.986 (2.221, 21.751)  0.016  0.232  12.101 (2.205, 21.996)  0.017  0.247    GA + AA vs. GG  3.537 (0.460, 6.614)  0.024  0.348  3.337 (0.095, 6.579)  0.044  0.319  ΔDBP1b  Additive  2.828 (1.216, 4.440)  0.001  0.029c  2.850 (1.179, 4.522)  0.001  0.029c    AA vs. GG + GA  5.539 (−0.237, 11.316)  0.060  0.348  5.509 (−0.309, 11.326)  0.063  0.365    GA + AA vs. GG  2.963 (1.163, 4.763)  0.001  0.029c  3.012 (1.130, 4.895)  0.002  0.049c  ΔMAP1b  Additive  3.153 (1.424, 4.882)  <0.001  0.012c  3.122 (1.321, 4.923)  0.001  0.029c    AA vs. GG + GA  7.688 (1.506, 13.870)  0.015  0.435  7.706 (1.457, 13.954)  0.016  0.464    GA + AA vs. GG  3.154 (1.221, 5.088)  0.001  0.029c  3.121 (1.089, 5.153)  0.003  0.044c  Abbreviations: BP, blood pressure; CI, confidence interval; DBP, diastolic blood pressure; FDR, false discovery rate; MAP, mean arterial pressure. aAdjusted for age and 24-hour urinary sodium concentration. bΔSBP1, ΔDBP1, and ΔMAP1 were defined as the BP after acute salt loading for 2 hours minus BP before acute salt loading. cFDR_q < 0.05. View Large DISCUSSION Our study demonstrated that SNPs in CYP11B2, ADRB2, SLC8A1, CYP4A11 genes were nominally associated with BP rising after acute salt loading, while SNPs in BCAT1, CLCNKA, and eNOS gene nominally associated with BP reduction during diuresis shrinkage. Rs1904694 in PRKG1 gene involved in BP changes during both processes. After adjusted for multiple testing, rs434082 in SLC8A1 gene was significantly associated with BP rising after acute salt loading. Luft et al.18 demonstrated firstly in 1977 that a 4-hour intravenous infusion of 2 l saline and a 10 mmol sodium diet plus 40 mg furosemide orally could identify salt sensitivity. Various methods have been modified to identify salt sensitivity after that. Sullivan et al. provided evidence that daily 150 mmol sodium intake can distinguish sodium sensitivity efficiently.25 However, there is not a standard protocol to identify salt sensitivity. In the present study, acute oral salt loading and oral furosemide were used together to identify salt sensitivity. This method is modified from Sullivan’s salt sensitivity test, and has been used in Chinese population previously.27 GenSalt study focus on response to 7-day low-sodium or high-sodium dietary intervention,21,22 while our current study focus on BP changes in the process of acute salt loading and diuresis shrinkage. Because salt sensitivity tests are usually in poor compliance, it is especially hard to distinguish salt sensitivity people in the community-based study. As an important strength, participants were recruited from community in this study, which can avoid selection bias. Current study recruited 342 hypertension individuals to define their salt sensitivity status. To our knowledge, among the studies use acute sodium loading and diuresis shrinkage to distinguish salt sensitivity, this study is the largest community-based study in China. What is more, it is the first study to explore SNPs involved in BP response in both process of acute salt loading and diuresis shrinkage in a Han Chinese population. In the current study, polymorphisms in CYP11B2, ADRB2, and SLC8A1 gene were associated with ascending BP during acute salt loading before FDR correction. CYP11B2 gene is in renin–angiotensin system pathway. ADRB2 gene is involved in the synthesis of catecholamine’s receptor and in the pathway associated with sympathetic nervous system. SLC8A1 gene regulates vascular smooth muscle tone through an increase in the concentration of cytoplasmic calcium (Ca2+). All the above genes are involved in the process of increasing vascular reactivity. On the contrary, most genes associated with BP reduction after diuresis shrinkage were involved in decreasing vascular reactivity or renal sodium transport. For example, eNOS gene related to nitric oxide (NO) synthesis was associated with BP reduction after diuresis shrinkage. Increasing NO production can lead to endothelial vasodilatation and decrease sodium transport. Regulation of SSBP is a complex and systematic biological process. Our results suggested genes related to increasing vascular reactivity and renal sodium transport were associated with BP rising after acute salt loading, while genes related to decreasing vascular reactivity and renal sodium transport were associated with BP reducing after diuresis shrinkage. SNPs in PRKG1 gene were nominally associated with SSBP in both process of acute salt loading and diuresis shrinkage. PRKG1 gene locates on chromosome 10, and encodes the soluble guanosine 3′,5′-cyclic phosphate-dependent protein kinase type. PRKG1 proteins can not only cause vascular smooth muscle contraction by reducing the activity of NO, but also raise BP by increase Ca2+ concentration in cells. It has been demonstrated that salt sensitivity is triggered by Ca2+ entry through in arterial smooth muscle.28 A GWAS conducted by Citterio et al. showed that rs7897633, which locates in the first introns of PRKG1 gene, might be associated with variation in DBP after acute salt loading (P  =  2.34 × 10–5).1 Our study showed rs7897633 in PRKG1 associated with SBP and DBP after acute salt loading before FDR correction, which was consistent with this GWAS. We also found rs1799983 in eNOS gene was associated with BP reduction after diuresis shrinkage before FDR correction. PRKG1 involved in NO signaling, while eNOS is also related to NO synthesis. These 2 genes have been shown to be associated with vascular smooth muscle (VSM) dysfunction and essential hypertension in previous studies.1 In the current study, SNPs within these 2 genes contribute to the process of both BP rising after acute oral salt loading and BP reduction after diuresis shrinkage, which indicated the important role of VSMs function in regulating BP. After FDR correction, rs434082 in SLC8A1 gene was significantly associated with BP rising after acute salt loading. SLC8A1 codes for Na+/Ca2+ exchanger type 1, which plays an important role in the biochemical control of peripheral vascular resistance, and is involved in the pathogenesis of hypertension and salt sensitivity.29,30SLC8A1 gene was previously found to be associated with SBP and hypertension in KoraS3 cohort (P < 10–3).31 Another recent study of candidate genes for SSH demonstrated a significant interaction between SLC8A1 gene and renal pressure-natriuresis in response to acute salt loading, supporting the pathophysiological mechanisms of the effect of SLC8A1 gene on SSH. This study also revealed that SLC8A1 gene rs434082 had an effect size of 3.16 mm Hg on SBP response to salt loading,1 which was consistent with our results. In the current study, rs7961152 in BCAT1 gene was found to be associated with SBP in recessive model after FDR correction. The Wellcome Trust Case Control Consortium (WTCCC) conducted a GWAS and highlighted rs7961152 in BCAT1 gene might be associated with essential hypertension (P = 3.03 × 10–5).32 Two years later, Hong et al. found rs7961152 was associated with hypertension risk in Korean population (odds ratio = 1.286, P = 0.040).33 Another study conducted in 101 Korean participants also found rs7961152 to be significantly associated with salt sensitivity after adjusting for potential confounders.34 Our result was consistent with the above studies. Branched chain aminotransferase 1 (BCAT1) are essential for cell growth and apoptosis, and it had been reported to be associated with different types of cancer.35,36 The mechanisms of its effect to salt sensitivity are still unclear. As a limitation of the current study, because only 2 participants had AA genotype in rs7961152, the statistical power in recessive model is relatively low. Larger sample size is still needed to confirm our positive results. However, the statistical power of our main results, the association between rs434082 in SLC8A1 gene and BP change after acute sodium loading in additive and recessive model, was above 90%. Thus, although the sample size is relatively small to explore the effect of every candidate SNP on BP change, it is large enough to detect the effect of rs434082 in SLC8A1 on SBP after acute salt load. This result may indicate a potential pathogenesis of salt sensitivity hypertension. In conclusion, we found SLC8A1 gene rs434082 contributes to BP change in the process of acute salt loading in Han Chinese population. DISCLOSURE The authors declared no conflict of interest. ACKNOWLEDGMENTS This study received financial support from the Natural Science Foundation of China (81373076, 81602908), the National key research and development program of China (2016YFC0900603), and the Importation and Development of High-Caliber Talents Project of Beijing Municipal Institutions (CIT&TCD201504088).We thank associated professor Tao Wang in Genetic and Genomics Data Analysis Unit, Division of Biostatistics, Albert Einstein College. He provided valuable suggestions on statistical methods and help us to revise the manuscript in writing. REFERENCES 1. Elijovich F, Weinberger MH, Anderson CA, Appel LJ, Bursztyn M, Cook NR, Dart RA, Newton-Cheh CH, Sacks FM, Laffer CL; American Heart Association Professional and Public Education Committee of the Council on Hypertension; Council on Functional Genomics and Translational Biology; and Stroke Council. Salt sensitivity of blood pressure: a scientific statement from the American Heart Association. 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Published: Apr 1, 2018

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