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. 2024 May 3;103(18):e38057. doi: 10.1097/MD.0000000000038057

Causal relationship between hypertension and risk of constipation: A 2-way 2-sample Mendelian randomization study

Rong Wang a, Huiying Sun a, Ting Yang a, Junfeng Xu b,*
PMCID: PMC11062663  PMID: 38701266

Abstract

Patients with hypertension have a higher risk of having constipation and vice versa. The causal association between these 2 variables is not proven. We performed a retrospective Mendelian randomization analysis to determine the causal association between constipation and hypertension. Two-sample 2-way Mendelian randomization analysis was used. Genetic variants for constipation were derived from genome-wide association study data of European origin (15,902 cases and 395,721 controls). Corresponding genetic associations for hypertension were derived from European ancestry GWAS data (54,358 cases and 408,652 controls). Genetic susceptibility to hypertension was associated with an increased risk of constipation (OR: 3.459, 95% CI: 1.820–6.573, P < .001). In an inverse Mendelian randomization analysis, no causal effect of constipation on hypertension was found (OR: 0.999, 95% CI: 0.987–1.011, P = .834). In sensitivity analyses, these associations persisted and no multiple effects were found. This study suggests that there is a causal relationship between hypertension and constipation and that hypertension may increase the risk of developing constipation.

Keywords: causal relationship, constipation, hypertension, Mendelian randomization

1. Introduction

Hypertension, as 1 of the global public health problems, is characterized by high morbidity, high disability, high mortality, and low awareness, and is an important risk factor for cardiovascular and cerebrovascular diseases, bringing a heavy disease and economic burden to the society.[1,2] Constipation is a common complication in patients with hypertension, and prolonged straining to defecate and repeated defecation will cause a sudden increase in blood pressure, triggering cardiovascular, and cerebrovascular diseases, which is extremely harmful.[3] A large cohort study from Australia found that among hospitalized patients ≥ 60 years of age, patients with constipation had a 96% increased risk of hypertension compared with non-constipated individuals.[4] Moreover, studies have shown that chronic constipation can cause mental stress, which may be associated with increased blood pressure.[5] In addition, constipation is an adverse effect of some antihypertensive drugs (e.g., calcium channel blockers and diuretics),[6,7] so we cannot exclude another possibility that hypertension or its therapeutic management directly or indirectly contributes to constipation. Therefore, it is necessary to clarify whether there is a causal and directional relationship between hypertension and constipation through certain research approaches in the hope of deepening the understanding of the etiologic basis of hypertension and updating the prevention strategies for hypertension.

Recently, Mendelian randomization (MR) has been increasingly used to assess plausible causal relationships between exposures and outcomes. MR is an analysis of genetic variables that follows Mendelian laws of inheritance, i.e. single-nucleotide polymorphisms (SNPs) are used as instrumental variables to assess causal associations between exposure factors and outcome variables.[8] Since genetic variation in MR follows the principle of random assignment of alleles to offspring, it is less susceptible to confounding factors such as environmental or adaptive factors and reverse causation.[9] This process is similar to randomized controlled trials in clinical settings. Therefore, this study analyzed the causal association between hypertension and constipation by a 2-sample bidirectional MR study using a large-scale genome-wide association study (GWAS) dataset.

2. Materials and methods

2.1. Study design

Data on hypertension and constipation in the MR study were obtained from publicly available summary-level data from corresponding consortium (Table 1). The study design strictly followed the 3 assumptions of Mendelian randomization as shown in Figure 1. All included study data were publicly available from GWAS, MRC-IEU, and FinnGen consortium, were approved by the relevant ethical review boards and participants gave informed consent, therefore no further ethical review was required.

Table 1.

Details of traits used in Mendelian randomization analyses.

Trait Consortium Population Number of SNPs Sample size n_cases n_controls PubMed ID
Constipation (exposure) FinnGen European 20,170,236 377,277 36,022 341,255 NA
Constipation (outcome) NA European 24,176,599 411,623 15,902 395,721 3,459,403[10]
Hypertension MRC-IEU European 9,851,867 463,010 54,358 408,652 NA
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MRC-IEU = MRC Integrative Epidemiology Unit, NA = not available.

Figure 1.

Figure 1.

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Assumption 1 indicates that the genetic variants proposed as instrumental variables should be robustly associated with the exposure. Assumption 2 indicates that instrumental variables should not be associated with potential confounders. Assumption 3 indicates that instrumental variables should affect the risk of the outcome merely through the risk factor, not via alternative pathways. IVs = instrumental variables, MR = Mendelian randomization.

2.2. Data resources

GWAS summary statistics for constipation as an exposure variable were obtained from the FinnGen consortium (https://r9.finngen.fi), which included 36,022 cases and 341,255 controls. Data on constipation as an outcome variable used a dataset from the IEU OpenGWAS project (GWAS ID: ebi-a-GCST90018829), which included a total of 15,902 cases and 395,721 controls.[10] In addition, the hypertension data for this study were also obtained from the dataset of the IEU OpenGWAS project (GWAS ID: ukb-b-12493), which included a total of 54,358 cases and 408,652 controls. Details of the data can be found at https://gwas.mrcieu.ac.uk/. All data in this study are from European populations.

2.3. Genetic instrument selection

In this study, when constipation was used as the exposure variable, in order to obtain sufficient candidate SNPs, we set the P value threshold at 5 × 10−6 and used PLINK aggregation to calculate the linkage disequilibrium (LD) between SNPs for each exposure variable,[11] retaining the SNPs with r2 < 0.001 and a physical distance of bases > 10,000 kb. In addition, to further assess the strength of each instrumental variable, we calculated the F statistic of the instrumental variables in the exposure and excluded SNPs with F < 10 to ensure that the instrumental variables had sufficient validity and instrumental strength. The F statistic formula is calculated as follows[11]:

F=( ​​β​​ SE)2

where β is the allele effect value and SE is the standard error. Finally, 16 independent SNPs screened by the above treatments were used as instrumental variables for constipation. Detailed information on the genetic instrumentation is provided in Table 2.

Table 2.

Single-nucleotide polymorphisms (SNPs) related to constipation at genome-wide significance.

SNP EA OA EAF Beta SE P value Sample size F statistics
rs144347372 T C 0.006715 0.226071 0.048909 3.80E−06 377,277 21.3658
rs35839493 G A 0.127316 −0.0609 0.01222 6.24E−07 377,277 24.83758
rs1595463 C A 0.538093 0.03947 0.008117 1.16E−06 377,277 23.64668
rs1462692 T C 0.684687 0.039683 0.008678 4.81E−06 377,277 20.91228
rs6594752 T C 0.230413 −0.045765 0.009637 2.05E−06 377,277 22.54912
rs75439231 T C 0.014976 0.148908 0.032109 3.52E−06 377,277 21.50767
rs7745923 C T 0.867986 −0.05465 0.011816 3.74E−06 377,277 21.39133
rs1983785 A C 0.793037 0.055606 0.010187 4.79E−08 377,277 29.79864
rs197366 G A 0.3025 0.040886 0.008725 2.79E−06 377,277 21.95894
rs77711275 G T 0.066743 −0.078109 0.016381 1.86E−06 377,277 22.73783
rs7071947 G A 0.639903 0.03868 0.008413 4.28E−06 377,277 21.13614
rs146001354 C T 0.053933 0.082287 0.017639 3.08E−06 377,277 21.76358
rs7989659 A G 0.915722 −0.069064 0.014887 3.50E−06 377,277 21.52316
rs9931348 T C 0.19626 −0.047059 0.010207 4.02E−06 377,277 21.25762
rs4800316 A G 0.028326 0.109101 0.023658 4.00E−06 377,277 21.26604
rs113664674 A G 0.013795 0.152896 0.033355 4.56E−06 377,277 21.01202
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EA = effect allele, EAF = effect allele frequency, OA = other allele, SE = standard error, SNP = single-nucleotide polymorphism.

When hypertension was used as the exposure variable, the P value threshold was set at 5 × 10−8, and the rest of the processing of the instrumental variable for hypertension was the same as for constipation, resulting in 71 independent SNPs as instrumental variables for hypertension. Detailed information about the genetic instrumentation is provided in Table 3.

Table 3.

Single-nucleotide polymorphisms (SNPs) related to hypertension at genome-wide significance

SNP EA OA EAF Beta SE P value Sample size F statistics
rs3790604 A C 0.073159 0.009082 0.001282 1.40E−12 463,010 50.20001
rs17558745 T C 0.311877 0.003993 0.000722 3.20E−08 463,010 30.61245
rs11801879 C T 0.088418 −0.007605 0.001178 1.10E−10 463,010 41.6546
rs17035646 A G 0.337161 0.00607 0.000708 1.00E−17 463,010 73.42863
rs7528118 A G 0.240027 0.004379 0.000783 2.30E−08 463,010 31.25824
rs1275985 T C 0.617253 −0.006219 0.000686 1.20E−19 463,010 82.20507
rs1918898 T C 0.356125 −0.003967 0.000697 1.30E−08 463,010 32.38242
rs10804330 C T 0.431675 −0.004051 0.000678 2.30E−09 463,010 35.72904
rs346078 C G 0.378129 0.003872 0.000688 1.80E−08 463,010 31.69383
rs3821843 A G 0.678977 0.004645 0.000725 1.50E−10 463,010 41.08456
rs6766859 T C 0.626849 −0.004041 0.000692 5.20E−09 463,010 34.10532
rs2643826 T C 0.45231 0.004939 0.000671 1.80E−13 463,010 54.21038
rs7685862 A C 0.795291 −0.004766 0.000826 7.80E−09 463,010 33.32354
rs9330353 A T 0.417876 0.004606 0.000677 1.00E−11 463,010 46.32003
rs6822044 G C 0.347199 −0.00421 0.000701 1.90E−09 463,010 36.07488
rs13125101 A G 0.29184 0.009552 0.000734 9.70E−39 463,010 169.4527
rs3796581 G A 0.183958 −0.005747 0.00086 2.30E−11 463,010 44.68469
rs12656497 C T 0.596328 0.005379 0.000679 2.30E−15 463,010 62.82704
rs6866614 G A 0.576646 0.003921 0.000679 7.80E−09 463,010 33.32702
rs56273825 C T 0.021882 −0.013479 0.002404 2.10E−08 463,010 31.42504
rs7700842 C T 0.371105 −0.006924 0.000689 8.80E−24 463,010 101.0806
rs4412193 G A 0.366882 −0.00472 0.000692 9.30E−12 463,010 46.48017
rs7763350 C A 0.322191 0.004488 0.000712 2.90E−10 463,010 39.7497
rs57139556 G A 0.071572 −0.007728 0.001291 2.10E−09 463,010 35.84075
rs1077394 T C 0.672304 0.004163 0.000709 4.40E−09 463,010 34.44313
rs9375459 T C 0.437127 0.006208 0.00067 2.00E−20 463,010 85.76024
rs6918911 T A 0.079876 −0.008244 0.001277 1.10E−10 463,010 41.71047
rs55730499 T C 0.079714 0.007794 0.00123 2.40E−10 463,010 40.11921
rs6961048 G C 0.101304 0.006425 0.001104 5.80E−09 463,010 33.88867
rs1870735 G C 0.548152 −0.00368 0.000675 4.90E−08 463,010 29.748
rs10245376 T G 0.155336 0.005806 0.00092 2.70E−10 463,010 39.85409
rs3735533 C T 0.926702 0.00878 0.001276 6.00E−12 463,010 47.33895
rs3918226 T C 0.081012 0.010156 0.001238 2.40E−16 463,010 67.26885
rs6991641 C G 0.598329 −0.004681 0.000686 9.20E−12 463,010 46.50111
rs76452347 T C 0.204442 −0.005136 0.000857 2.10E−09 463,010 35.91914
rs35587371 A T 0.303398 0.00481 0.000725 3.20E−11 463,010 44.0443
rs72831345 A G 0.145089 −0.009581 0.000944 3.50E−24 463,010 102.912
rs11191559 T C 0.07762 −0.007719 0.001242 5.20E−10 463,010 38.61673
rs12263737 A G 0.271095 −0.00441 0.000749 3.80E−09 463,010 34.70252
rs10749409 G C 0.684325 −0.004731 0.000717 4.20E−11 463,010 43.50544
rs12762222 C T 0.01942 0.013488 0.002442 3.30E−08 463,010 30.50045
rs740746 A G 0.73319 0.00558 0.000755 1.40E−13 463,010 54.64505
rs12258967 G C 0.299316 −0.005039 0.000728 4.40E−12 463,010 47.91774
rs55670730 T A 0.110744 0.006003 0.001072 2.10E−08 463,010 31.35829
rs568546 T C 0.521082 −0.005226 0.000669 5.60E−15 463,010 61.03386
rs11604462 A G 0.343347 0.004418 0.0007 2.80E−10 463,010 39.81921
rs12360772 A G 0.186914 0.0058 0.000859 1.50E−11 463,010 45.59209
rs633185 C G 0.715077 0.006529 0.000741 1.30E−18 463,010 77.5508
rs3184504 C T 0.517267 −0.006092 0.000665 5.30E−20 463,010 83.84619
rs35443 C G 0.381805 −0.004953 0.000685 4.60E−13 463,010 52.35391
rs7297416 C A 0.297749 −0.004012 0.000728 3.60E−08 463,010 30.34072
rs2728624 A G 0.226934 −0.004587 0.000797 8.50E−09 463,010 33.15894
rs8042127 T C 0.479558 0.003919 0.00067 4.80E−09 463,010 34.25564
rs7497304 T G 0.325747 0.005862 0.00071 1.50E−16 463,010 68.21065
rs2759315 A C 0.44312 0.004714 0.000671 2.10E−12 463,010 49.36755
rs12932686 C T 0.413548 0.003897 0.000677 8.60E−09 463,010 33.12414
rs77924615 A G 0.196675 −0.005163 0.000846 1.00E−09 463,010 37.27977
rs56094641 G A 0.404625 0.004028 0.000678 2.90E−09 463,010 35.26321
rs16948048 G A 0.366921 0.004295 0.000691 5.10E−10 463,010 38.62933
rs35184780 G C 0.438777 0.003897 0.00068 1.00E−08 463,010 32.80805
rs4291 A T 0.623299 −0.003921 0.000691 1.40E−08 463,010 32.20751
rs62089932 T C 0.859954 −0.005799 0.001027 1.60E−08 463,010 31.8931
rs68096471 A G 0.269191 −0.004449 0.000752 3.30E−09 463,010 35.02357
rs2003476 C T 0.405754 −0.003995 0.000682 4.70E−09 463,010 34.30433
rs167479 T G 0.472463 −0.005817 0.000667 2.60E−18 463,010 76.15264
rs6031435 G A 0.459301 0.004188 0.000672 4.50E−10 463,010 38.86797
rs1327235 G A 0.476253 0.004291 0.000667 1.30E−10 463,010 41.3465
rs8118848 A G 0.237633 −0.004893 0.000783 4.10E−10 463,010 39.05232
rs6108171 T A 0.247296 −0.007493 0.000775 4.20E−22 463,010 93.41106
rs6026744 T A 0.119013 0.008356 0.001032 5.70E−16 463,010 65.53713
rs162395 C T 0.571316 0.003877 0.000673 8.10E−09 463,010 33.23985
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EA = effect allele, EAF = effect allele frequency, OA = other allele, SE = standard error, SNP = single-nucleotide polymorphism.

Processed SNPs were subsequently matched to GWAS data for outcome variables based on chromosome and location. Finally, we harmonized the exposure and outcome datasets to ensure that the effects of SNPs on exposure and outcome corresponded to the same alleles and to remove palindromic SNPs with intermediate allele frequencies. Detailed information is provided in Tables 4 and 5.

Table 4.

Details of the IVs used for MR analysis [causal effect of constipation on hypertension].

SNP EA OA Exposure Outcome F_statistics
Beta SE P value EAF Beta SE P value EAF
rs113664674 A G 0.152896 0.033355 4.56E−06 0.013795 −0.011716 0.004216 0.0055 0.006714 21.01201748
rs144347372 T C 0.226071 0.048909 3.80E−06 0.006715 −0.005271 0.002969 0.075999 0.016178 21.36580439
rs1462692 T C 0.039683 0.008678 4.81E−06 0.684687 0.00017 0.000716 0.81 0.681154 20.91227551
rs1595463 C A 0.03947 0.008117 1.16E−06 0.538093 −0.000191 0.000673 0.780001 0.467621 23.64667895
rs197366 G A 0.040886 0.008725 2.79E−06 0.3025 7.40E−05 0.00078 0.92 0.244588 21.95894185
rs1983785 A C 0.055606 0.010187 4.79E−08 0.793037 0.000376 0.000866 0.66 0.819485 29.79864084
rs35839493 G A −0.0609 0.01222 6.24E−07 0.127316 0.000425 0.001465 0.77 0.055361 24.83757788
rs4800316 A G 0.109101 0.023658 4.00E−06 0.028326 0.001281 0.001652 0.44 0.042257 21.26604468
rs6594752 T C −0.045765 0.009637 2.05E−06 0.230413 0.000643 0.000863 0.46 0.182176 22.54911818
rs7071947 G A 0.03868 0.008413 4.28E−06 0.639903 −0.000801 0.00068 0.24 0.595008 21.13614244
rs75439231 T C 0.148908 0.032109 3.52E−06 0.014976 −0.003098 0.002041 0.13 0.027732 21.50766788
rs7745923 C T −0.05465 0.011816 3.74E−06 0.867986 −0.001624 0.000935 0.081999 0.847644 21.39132956
rs77711275 G T −0.078109 0.016381 1.86E−06 0.066743 −0.000618 0.001301 0.64 0.071921 22.73782708
rs7989659 A G −0.069064 0.014887 3.50E−06 0.915722 −0.003122 0.001425 0.029 0.942123 21.52316471
rs9931348 T C −0.047059 0.010207 4.02E−06 0.19626 −0.001243 0.000835 0.14 0.205889 21.2576224
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EA = effect allele, EAF = effect allele frequency, OA = other allele, SE = standard error, SNP = single-nucleotide polymorphism.

Table 5.

Details of the IVs used for MR analysis [causal effect of hypertension on constipation].

SNP EA OA Exposure Outcome F_statistics P value
Beta SE P value EAF Beta SE Beta SE
rs10245376 T G 0.005806 0.00092 2.70E−10 rs10245376 T G 0.005806 0.00092 2.70E−10
rs10749409 G C −0.004731 0.000717 4.20E−11 rs10749409 G C −0.004731 0.000717 4.20E−11
rs1077394 T C 0.004163 0.000709 4.40E−09 rs1077394 T C 0.004163 0.000709 4.40E−09
rs10804330 C T −0.004051 0.000678 2.30E−09 rs10804330 C T −0.004051 0.000678 2.30E−09
rs11191559 T C −0.007719 0.001242 5.20E−10 rs11191559 T C −0.007719 0.001242 5.20E−10
rs11604462 A G 0.004418 0.0007 2.80E−10 rs11604462 A G 0.004418 0.0007 2.80E−10
rs11801879 C T −0.007605 0.001178 1.10E−10 rs11801879 C T −0.007605 0.001178 1.10E−10
rs12258967 G C −0.005039 0.000728 4.40E−12 rs12258967 G C −0.005039 0.000728 4.40E−12
rs12263737 A G −0.00441 0.000749 3.80E−09 rs12263737 A G −0.00441 0.000749 3.80E−09
rs12360772 A G 0.0058 0.000859 1.50E−11 rs12360772 A G 0.0058 0.000859 1.50E−11
rs12656497 C T 0.005379 0.000679 2.30E−15 rs12656497 C T 0.005379 0.000679 2.30E−15
rs1275985 T C −0.006219 0.000686 1.20E−19 rs1275985 T C −0.006219 0.000686 1.20E−19
rs12762222 C T 0.013488 0.002442 3.30E−08 rs12762222 C T 0.013488 0.002442 3.30E−08
rs12932686 C T 0.003897 0.000677 8.60E−09 rs12932686 C T 0.003897 0.000677 8.60E−09
rs13125101 A G 0.009552 0.000734 9.70E−39 rs13125101 A G 0.009552 0.000734 9.70E−39
rs1327235 G A 0.004291 0.000667 1.30E−10 rs1327235 G A 0.004291 0.000667 1.30E−10
rs167479 T G −0.005817 0.000667 2.60E−18 rs167479 T G −0.005817 0.000667 2.60E−18
rs16948048 G A 0.004295 0.000691 5.10E−10 rs16948048 G A 0.004295 0.000691 5.10E−10
rs17035646 A G 0.00607 0.000708 1.00E−17 rs17035646 A G 0.00607 0.000708 1.00E−17
rs17558745 T C 0.003993 0.000722 3.20E−08 rs17558745 T C 0.003993 0.000722 3.20E−08
rs1870735 G C −0.00368 0.000675 4.90E−08 rs1870735 G C −0.00368 0.000675 4.90E−08
rs1918898 T C −0.003967 0.000697 1.30E−08 rs1918898 T C −0.003967 0.000697 1.30E−08
rs2003476 C T −0.003995 0.000682 4.70E−09 rs2003476 C T −0.003995 0.000682 4.70E−09
rs2643826 T C 0.004939 0.000671 1.80E−13 rs2643826 T C 0.004939 0.000671 1.80E−13
rs2728624 A G −0.004587 0.000797 8.50E−09 rs2728624 A G −0.004587 0.000797 8.50E−09
rs2759315 A C 0.004714 0.000671 2.10E−12 rs2759315 A C 0.004714 0.000671 2.10E−12
rs3184504 C T −0.006092 0.000665 5.30E−20 rs3184504 C T −0.006092 0.000665 5.30E−20
rs346078 C G 0.003872 0.000688 1.80E−08 rs346078 C G 0.003872 0.000688 1.80E−08
rs35184780 G C 0.003897 0.00068 1.00E−08 rs35184780 G C 0.003897 0.00068 1.00E−08
rs35443 C G −0.004953 0.000685 4.60E−13 rs35443 C G −0.004953 0.000685 4.60E−13
rs35587371 A T 0.00481 0.000725 3.20E−11 rs35587371 A T 0.00481 0.000725 3.20E−11
rs3735533 C T 0.00878 0.001276 6.00E−12 rs3735533 C T 0.00878 0.001276 6.00E−12
rs3790604 A C 0.009082 0.001282 1.40E−12 rs3790604 A C 0.009082 0.001282 1.40E−12
rs3796581 G A −0.005747 0.00086 2.30E−11 rs3796581 G A −0.005747 0.00086 2.30E−11
rs3821843 A G 0.004645 0.000725 1.50E−10 rs3821843 A G 0.004645 0.000725 1.50E−10
rs3918226 T C 0.010156 0.001238 2.40E−16 rs3918226 T C 0.010156 0.001238 2.40E−16
rs4291 A T −0.003921 0.000691 1.40E−08 rs4291 A T −0.003921 0.000691 1.40E−08
rs4412193 G A −0.00472 0.000692 9.30E−12 rs4412193 G A −0.00472 0.000692 9.30E−12
rs55670730 T A 0.006003 0.001072 2.10E−08 rs55670730 T A 0.006003 0.001072 2.10E−08
rs55730499 T C 0.007794 0.00123 2.40E−10 rs55730499 T C 0.007794 0.00123 2.40E−10
rs56094641 G A 0.004028 0.000678 2.90E−09 rs56094641 G A 0.004028 0.000678 2.90E−09
rs56273825 C T −0.013479 0.002404 2.10E−08 rs56273825 C T −0.013479 0.002404 2.10E−08
rs568546 T C −0.005226 0.000669 5.60E−15 rs568546 T C −0.005226 0.000669 5.60E−15
rs57139556 G A −0.007728 0.001291 2.10E−09 rs57139556 G A −0.007728 0.001291 2.10E−09
rs6026744 T A 0.008356 0.001032 5.70E−16 rs6026744 T A 0.008356 0.001032 5.70E−16
rs6031435 G A 0.004188 0.000672 4.50E−10 rs6031435 G A 0.004188 0.000672 4.50E−10
rs6108171 T A −0.007493 0.000775 4.20E−22 rs6108171 T A −0.007493 0.000775 4.20E−22
rs633185 C G 0.006529 0.000741 1.30E−18 rs633185 C G 0.006529 0.000741 1.30E−18
rs6766859 T C −0.004041 0.000692 5.20E−09 rs6766859 T C −0.004041 0.000692 5.20E−09
rs68096471 A G −0.004449 0.000752 3.30E−09 rs68096471 A G −0.004449 0.000752 3.30E−09
rs6822044 G C −0.00421 0.000701 1.90E−09 rs6822044 G C −0.00421 0.000701 1.90E−09
rs6866614 G A 0.003921 0.000679 7.80E−09 rs6866614 G A 0.003921 0.000679 7.80E−09
rs6961048 G C 0.006425 0.001104 5.80E−09 rs6961048 G C 0.006425 0.001104 5.80E−09
rs6991641 C G −0.004681 0.000686 9.20E−12 rs6991641 C G −0.004681 0.000686 9.20E−12
rs72831345 A G −0.009581 0.000944 3.50E−24 rs72831345 A G −0.009581 0.000944 3.50E−24
rs7297416 C A −0.004012 0.000728 3.60E−08 rs7297416 C A −0.004012 0.000728 3.60E−08
rs740746 A G 0.00558 0.000755 1.40E−13 rs740746 A G 0.00558 0.000755 1.40E−13
rs7497304 T G 0.005862 0.00071 1.50E−16 rs7497304 T G 0.005862 0.00071 1.50E−16
rs76452347 T C −0.005136 0.000857 2.10E−09 rs76452347 T C −0.005136 0.000857 2.10E−09
rs7685862 A C −0.004766 0.000826 7.80E−09 rs7685862 A C −0.004766 0.000826 7.80E−09
rs7700842 C T −0.006924 0.000689 8.80E−24 rs7700842 C T −0.006924 0.000689 8.80E−24
rs7763350 C A 0.004488 0.000712 2.90E−10 rs7763350 C A 0.004488 0.000712 2.90E−10
rs77924615 A G −0.005163 0.000846 1.00E−09 rs77924615 A G −0.005163 0.000846 1.00E−09
rs8042127 T C 0.003919 0.00067 4.80E−09 rs8042127 T C 0.003919 0.00067 4.80E−09
rs8118848 A G −0.004893 0.000783 4.10E−10 rs8118848 A G −0.004893 0.000783 4.10E−10
rs9330353 A T 0.004606 0.000677 1.00E−11 rs9330353 A T 0.004606 0.000677 1.00E−11
rs9375459 T C 006208 0.00067 2.00E−20 rs9375459 T C 006208 0.00067 2.00E−20
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EA = effect allele, EAF = effect allele frequency, OA = other allele, SE = standard error, SNP = single-nucleotide polymorphism.

2.4. Mendelian randomization analysis

In this study, inverse variance weighting (IVW), MR-Egger regression, and weighted median method were used as MR analysis methods to assess the causal relationship between constipation and hypertension. The IVW method is the main analytical approach because it assumes that all genetic variation satisfies the 3 assumptions of IV, uses the inverse of the ending variance as weights to fit the model, and provides the most accurate estimates in the absence of horizontal pleiotropy and heterogeneity.[12] Second, we complemented the IVW approach with MR-Egger regression and weighted median methods, both to estimate causal effects based on regression effect coefficients on exposure effect coefficients and to take into account the potential bias of polytomous effects at the IV level, in order to confirm the robustness and reliability of the study results in a wider range of contexts.[13] MR-Egger regression is essentially similar to the IVW method, except that its regression model includes an intercept that reflects horizontal pleiotropy,[14] and therefore has a higher ability to detect pleiotropy and heterogeneity. Compared to IVW and MR-Egger regressions, weighted medians, which are methods for calculating median causal estimates, are more robust to null IVs.[15] The combination of these methods provides a comprehensive view of exposure and outcome causality, enhancing the robustness of the results. In this study, statistical significance was set at P < .05. All Mendelian randomization analyses were performed using RStudio software (version: 2023.09.1 Build 494) and R software (version: 4.3.2).

2.5. Heterogeneity and sensitivity analysis

Considering the possible problems of pleiotropy and heterogeneity of SNPs, we performed a series of sensitivity analyses, including Cochran Q test, MR-Egger intercept test, MR-PRESSO test, leave-one-out analysis. Among these, Cochran Q test was used to assess the heterogeneity between SNP estimates and when P > .05 was considered to indicate low heterogeneity, i.e., it indicated random variation in the estimates between the working variables and a lack of horizontal multivariate validity.[13] The MR-Egger intercept is an indicator of directional pleiotropy (P < .05 is considered to be the presence of directional pleiotropy).[16] MR-PRESSO was applied to detect potential peripheral SNPs and provide adjusted results after excluding outliers, thus correcting for horizontal pleiotropy.[17] The leave-one-out method focuses on exploring whether the effects of individual SNPs disproportionately affect causality.[18] All statistical tests were 2-sided and were performed using the TwoSampleMR[19] and Mendelian Randomization[20] packages in the R software (version 4.3.2).

3. Results

3.1. MR analysis and sensitivity analysis of constipation on hypertension

In MR analysis, a total of 15 SNPs were obtained as IVs from the constipation dataset in order to validate the causal effect of constipation on hypertension. No significant evidence of a causal effect of constipation on hypertension was found by the main MR analysis method, IVW analysis (OR: 1.00, 95% CI: 0.99–1.01, P = .833). Meanwhile, similar risk estimates were obtained using MR-Egger regression (OR = 1.00, 95% CI = 0.99–1.02, P = .743) and weighted median approach (OR = 0.98, 95% CI = 0.96–1.01, P = .257). Detailed information is provided in Tables 6 and 7 and Figures 2 and 3.

Table 6.

MR results for positive control outcomes.

Exposure Outcome Method OR 95% CI P value
Hypertension Constipation IVW 3.459 0.599–1.883 <.001
Weighted median 3.332 0.334–2.073 .007
MR-Egger 3.405 −1.158 to 3.608 .317
Constipation Hypertension IVW 0.999 0.987–1.011 .834
Weighted median 1.002 0.989–1.016 .743
MR-Egger 0.984 0.957–1.011 .257
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CI = confidence interval, IVW = inverse variance weighted, OR = odds ratio.

Table 7.

Information on forest mapping.

Outcome Method N-SNP P or or_lci95 or_uci95 Heterogeneity MR-Egger_intercept MR-PRESSO_Global_Test_P
Hypertension IVW 15 .833 0.999 0.987 1.011 0.024 0.248 0.038 (raw, 0 outlier)
Weighted median 15 .743 1.002 0.989 1.016
MR-Egger 15 .257 0.984 0.957 1.011
Constipation IVW 67 <.001 3.459 1.820 6.573 0.140 0.989 0.145 (raw, 0 outlier)
Weighted median 67 .007 3.332 1.328 8.360
MR-Egger 67 .317 3.405 0.314 36.888
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CI = confidence interval, IVW = Inverse variance weighted, OR = odds ratio, SNP = single-nucleotide polymorphism.

Figure 2.

Figure 2.

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(A) Effect of Constipation on hypertension. (B) Effect of hypertension on Constipation.

Figure 3.

Figure 3.

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The slopes of each line represent the causal association for each method. The light blue line represents the inverse-variance weighted estimate, the green line represents the weighted median estimate, the dark blue line represents the Mendelian randomization-Egger estimate. (A) Effect of Constipation on hypertension; (B) effect of hypertension on constipation.

The Cochrane Q test analysis showed a large heterogeneity in both the IVW method (Q = 26.306, P = .024) and the MR-Egger method (Q = 23.640, P = .035), but it did not affect the results of the IVW, and the MR-PRESSO gave similar results (Global_teas_P value = .038). The MR-Egger intercept test showed no evidence of potential horizontal pleiotropy (intercept of <0.001, P = .248). The MR-PRESSO test did not identify outliers among the SNPs, and the leave-one-out analysis did not identify SNPs that had a large effect on the causal association estimates. Detailed information is provided in Tables 8–11 and Figure 4.

Table 8.

Results of heterogeneity by the Cochran Q test.

Exposure Outcome Method Q Q_df Q_pval
Hypertension Constipation MR-Egger 78.483 65 0.122
Inverse variance weighted 78.483 66 0.14
Constipation Hypertension MR-Egger 23.64 13 0.035
Inverse variance weighted 26.306 14 0.024
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Table 11.

Results of the leave-one-out analysis.

Exposure Outcome SNP Beta SE P
Hypertension Constipation rs10245376 1.271669 0.3307084 1.20E−04
rs10749409 1.239748 0.3322945 1.91E−04
rs1077394 1.236625 0.3317484 1.93E−04
rs10804330 1.1647 0.3194117 2.66E−04
rs11191559 1.23612 0.3321397 1.98E−04
rs11604462 1.216981 0.3310703 2.37E−04
rs11801879 1.257099 0.3314859 1.49E−04
rs12258967 1.259405 0.3317959 1.47E−04
rs12263737 1.207413 0.3292077 2.45E−04
rs12360772 1.274058 0.3307225 1.17E−04
rs12656497 1.329976 0.3239857 4.04E−05
rs1275985 1.206556 0.3332904 2.94E−04
rs12762222 1.228464 0.3314138 2.10E−04
rs12932686 1.191441 0.3261296 2.59E−04
rs13125101 1.308172 0.3375506 1.06E−04
rs1327235 1.246483 0.3321472 1.75E−04
rs162395 1.205266 0.327384 2.32E−04
rs167479 1.157919 0.3271877 4.02E−04
rs16948048 1.216269 0.3308783 2.37E−04
rs17035646 1.256552 0.3337779 1.67E−04
rs17558745 1.210571 0.3293909 2.38E−04
rs1918898 1.296944 0.3244128 6.39E−05
rs2003476 1.272538 0.3296868 1.13E−04
rs2643826 1.301043 0.3278047 7.22E−05
rs2728624 1.199204 0.3275619 2.51E−04
rs2759315 1.284748 0.3278411 8.90E−05
rs3184504 1.282283 0.3326757 1.16E−04
rs346078 1.297242 0.3240427 6.25E−05
rs35443 1.195669 0.3298254 2.89E−04
rs35587371 1.233379 0.3320901 2.04E−04
rs3735533 1.286971 0.3298704 9.56E−05
rs3790604 1.233327 0.333539 2.18E−04
rs3796581 1.26293 0.3317375 1.41E−04
rs3821843 1.256028 0.331808 1.53E−04
rs3918226 1.270239 0.3324216 1.33E−04
rs4291 1.276652 0.3288311 1.03E−04
rs4412193 1.217256 0.3315777 2.42E−04
rs55670730 1.210058 0.3293087 2.38E−04
rs55730499 1.197609 0.3279274 2.60E−04
rs56094641 1.314967 0.3200041 3.97E−05
rs56273825 1.253614 0.3312646 1.54E−04
rs568546 1.253493 0.3330551 1.67E−04
rs57139556 1.301021 0.3253742 6.37E−05
rs6026744 1.201956 0.3321154 2.96E−04
rs6031435 1.22095 0.3313366 2.29E−04
rs6108171 1.156645 0.3293124 4.44E−04
rs62089932 1.203706 0.3266601 2.29E−04
rs633185 1.235661 0.3341178 2.17E−04
rs6766859 1.242073 0.3318297 1.82E−04
rs68096471 1.231968 0.3317448 2.04E−04
rs6822044 1.183174 0.3244225 2.65E−04
rs6866614 1.27697 0.3286192 1.02E−04
rs6918911 1.228264 0.331196 2.08E−04
rs6961048 1.219221 0.3309353 2.29E−04
rs72831345 1.172988 0.3312837 3.99E−04
rs7297416 1.260904 0.330792 1.38E−04
rs740746 1.18803 0.3289311 3.04E−04
rs7497304 1.214906 0.3326723 2.60E−04
rs7528118 1.223596 0.3302353 2.11E−04
rs76452347 1.257801 0.3312431 1.46E−04
rs7685862 1.25054 0.3316082 1.63E−04
rs7700842 1.278257 0.3341859 1.31E−04
rs7763350 1.217754 0.3310812 2.35E−04
rs77924615 1.230236 0.3318344 2.09E−04
rs8042127 1.23477 0.3316978 1.97E−04
rs8118848 1.291897 0.326938 7.77E−05
rs9375459 1.306539 0.3308646 7.85E−05
All 1.240975 0.3275617 1.52E−04
Constipation Hypertension rs113664674 7.35E−04 0.00539936 0.8917805
rs144347372 1.58E−03 0.00630837 0.8025851
rs1462692 −1.64E−03 0.00651935 0.8012599
rs1595463 −1.02E−03 0.00655162 0.8763158
rs197366 −1.46E−03 0.00650648 0.822681
rs1983785 −1.99E−03 0.00656897 0.761375
rs35839493 −1.08E−03 0.00643419 0.866954
rs4800316 −2.51E−03 0.00651979 0.7002307
rs6594752 −5.27E−04 0.00645382 0.9348955
rs7071947 4.82E−05 0.006379 0.9939738
rs75439231 1.02E−03 0.00639755 0.8732742
rs7745923 −3.53E−03 0.00610132 0.5628001
rs77711275 −1.99E−03 0.00652775 0.7609626
rs7989659 −3.55E−03 0.00579018 0.5402259
rs9931348 −3.14E−03 0.00620795 0.613399
All −1.28E−03 0.00609985 0.8337776
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SE = standard error, SNP = single-nucleotide polymorphism.

Figure 4.

Figure 4.

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Each black point represents result of the IVW MR method applied to estimate the causal effect between constipation and hypertension excluding particular SNP. (A) Effect of constipation on hypertension; (B) effect of hypertension on constipation.

Table 10.

Results of horizontal pleiotropy by the MR-Egger intercept test.

Exposure Outcome Intercept SE P value
Hypertension Constipation 8.95E−05 0.007 .989
Constipation Hypertension <0.001 <0.001 .248
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SE: standard error.

Table 9.

Results of heterogeneity by the MR-PRESSO global test.

Exposure Outcome Method Causal estimate SD T statistics P value
Hypertension Constipation Raw 1.241 0.328 3.789 <.001
Outlier-corrected NA NA NA NA
Constipation Hypertension Raw −0.001 0.006 −0.210 .837
Outlier-corrected NA NA NA NA
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NA = not applicable.

3.2. MR analysis and sensitivity analysis of hypertension on constipation

To test whether this association was bidirectional, reverse MR analysis was performed. A total of 67 SNPs were obtained as IVs from the hypertension dataset. A causal effect of hypertension on constipation was demonstrated using IVW analysis (OR = 3.459, 95% CI = 1.820–6.573, P < .001), while this association persisted in weighted median analysis (OR = 3.332, 95% CI = 1.328–8.360, P = .007). Detailed information is provided in Table 6 and Figures 2 and 3.

The results of the heterogeneity test showed that the Cochrane Q test for both IVW (Q = 78.483, P = .122) and MR-Egger (Q = 78.483, P = .140) indicated the absence of heterogeneity, and the MR-PRESSO gave a similar result (Global_teas_P value = .145). The test for multinomiality showed that the MR-Egger regression had an intercept < 0.001, P = .989 > 0.05, indicating that there was no potential for horizontal multinomiality. Leave-one-out analysis did not identify SNPs with biased causality, and the MR-PRESSO test did not identify outliers. Detailed information is provided in Tables 8–11 and Figure 4.

4. Discussion

We investigated the causal relationship between constipation and hypertension using large-scale genome-wide association pooled data with 2-way, 2-sample MR analysis. We found that hypertension may be a risk factor for constipation, but there was insufficient evidence to suggest that constipation was associated with the subrisk of developing hypertension. These results suggest a close association between constipation and hypertension, and have a role in the prevention and treatment of constipation. According to us, this is the first MR study to examine the interaction between constipation and hypertension.

Available studies have demonstrated a significantly higher prevalence of constipation among hypertensive patients. A cohort study based on 541,172 hospitalized patients aged 60 years showed that the proportion of hypertensive patients with constipation was higher than that of non-hypertensive patients (OR: 1.96; 95% CI: 1.94–1.99; P < .001).[4] Similarly, an observational study based on 2194 older adults (>60 years of age) also found hypertension to be a high-risk factor for the development of chronic constipation in older adults (OR: 1.872; 95% CI: 1.276–2.747; P = .001).[21] Constipation is a common complication in patients with hypertension, and prolonged straining to defecate and repeated defecation in patients can cause a sudden increase in their blood pressure, and it has been reported that fecal pressure can lead to a significant increase in systolic blood pressure of about 70 mm Hg.[22]

The results of the MR study illustrate that constipation has no effect on the prevalence of hypertension, but some studies have shown an increased likelihood of hypertension in constipated patients. A cohort study based on 541,172 patients hospitalized at the age of 60 years showed an increased risk of hypertension in patients with constipation compared to those without constipation.[4] Hypertension being a common clinical cardiovascular disease, a prospective cohort study based on 93,676 menopausal women showed that postmenopausal women with constipation had a 23% higher risk of cardiovascular events than those without constipation at 6.9 years of follow-up.[23] Similarly, an observational study that included 45,122 cases in the Japanese general population found that low bowel frequency (1 time/2–3 days) was associated with a higher fractional risk of cardiovascular death than normal bowel frequency (≥1 time/day).[24] An observational study of the association between daily blood pressure variability and defecation status in 184 subjects found that constipation was independently associated with elevated daily blood pressure variability.[25] This is not exactly the same as our MR findings, and a large number of studies are still needed to confirm the relationship between the 2.

The exact pathogenesis between constipation and hypertension is not clear, but several potential mechanisms exist to explain the association. Autonomic nerves control heart rate and vasoconstriction, which regulate changes in blood pressure,[26] and they similarly influence defecation; therefore, both blood pressure changes and defecation status are indicators of autonomic function, and they may influence each other or occur simultaneously.[27] Studies have shown that hypertension often leads to sympathetic hyperactivity, and this may decrease colonic motility, which in turn leads to constipation.[28] In addition, some studies have shown a link between constipation and the treatment of hypertension, i.e., some antihypertensive medications taken by hypertensive patients, such as calcium channel blockers and diuretics, can promote constipation.[29,30] However, in the present study, non-differential measurement errors and confounding biases such as potential drug effects could be avoided because all genetic variants were innate. Therefore, the results of the present study shed some light on the effect of hypertension on the incidence of constipation.

The present study has several strengths. The main strength is that we designed MR to strengthen the causal inference of a bidirectional association between constipation and hypertension. We used large samples of GWAS data from 2-independent sources for the 2-way association and performed multiple sensitivity analyses, which makes our findings robust.

The present study also has some limitations. First, the GWAS data in this study were all from European populations, and although it reduces bias due to population stratification, its findings may not be directly extendable to other ethnicities. Second, we are still unable to eliminate potential pleiotropic effects that may be obscured by a small number of genetic instruments or a small sample size, although there is little horizontal pleiotropy with the MR-Egger intercept. Third, there was heterogeneity in the studies of constipation on hypertension, and leave-one-out analyses showed instability in the observed associations. Also, SNPs used as genetic tools were weakly associated with constipation (P < 5 × 10−6) and limited in number, which may explain only a small fraction of the variation in exposure and affect the statistical efficacy of the causal estimates. In conclusion, the results of this MR study are not identical to previous cohort studies, and more studies may be needed to confirm this in the future.

5. Conclusion

Our bidirectional MR study showed a causal effect of hypertension on constipation and did not observe a causal effect of constipation on hypertension, and these have implications for clinical practice in terms of developing more targeted preventive interventions or models of care for hypertensive patients to prevent them from developing constipation, but it may not be useful to screen constipated patients for hypertension.

Acknowledgments

Summary-level data were obtained from available GWAS, MRC-IEU, and FinnGen consortium. The authors acknowledge the participants and investigators of these consortia.

Author contributions

Conceptualization: Junfeng Xu, Ting Yang.

Data curation: Rong Wang, Junfeng Xu, Huiying Sun, Ting Yang.

Funding acquisition: Junfeng Xu.

Investigation: Rong Wang, Huiying Sun.

Methodology: Rong Wang.

Resources: Junfeng Xu.

Software: Junfeng Xu, Huiying Sun, Ting Yang.

Supervision: Junfeng Xu.

Validation: Rong Wang.

Visualization: Huiying Sun.

Writing – original draft: Rong Wang.

Writing – review & editing: Rong Wang, Junfeng Xu, Ting Yang.

Abbreviations:

CI
confidence interval
GWAS
genome-wide association study
IV
instrumental variable
IVW
inverse variance weighting
MR
Mendelian randomization
OR
odds ratio
SNPs
single-nucleotide polymorphisms.

This study was funded by the Research Program Project of Tianjin Municipal Education Commission (Approval No. 2022ZD045).

The authors have no conflicts of interest to disclose.

All data generated or analyzed during this study are included in this published article [and its supplementary information files].

How to cite this article: Wang R, Sun H, Yang T, Xu J. Causal relationship between hypertension and risk of constipation: A 2-way 2-sample Mendelian randomization study. Medicine 2024;103:18(e38057).

Contributor Information

Rong Wang, Email: 1283350495@qq.com.

Huiying Sun, Email: 1545345623@qq.com.

Ting Yang, Email: 1063200918@qq.com.

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