Antihypertensive drug targets and breast cancer risk: a two-sample Mendelian randomization study

Nearly one in three adults aged 30–79 years were estimated to have hypertension globally in 2019 [1], which led to a high prevalence of antihypertensive medication use. It is the most commonly prescribed medication in Sweden with over 2.1 million patients taking anti-hypertensive drugs in 2020 [2]. The exposure to antihypertensive medication has also been increasing in recent years. In UK, the prevalence of primary care patients with antihypertensive drug prescriptions has increased from 7.8% (1988) to 21.9% (2018) [3]. These drugs are usually prescribed to hypertensive patients as a long-term management [4]. Given the large disease burden and high consumption of the antihypertensive medication, there are concerns surrounding their carcinogenic potential as well as interests regarding their possible anti-cancer effect since the targets of these drugs are widely distributed in normal tissue and may be involved in tumor development. For example, renin-angiotensin system, the target for angiotensin-converting enzyme inhibitors (ACEi) and angiotensin receptor blockers (ARBs), contains components that promote or inhibit cellular proliferation [5]. Many observational studies with cohort or case–control design have evaluated the possible link between antihypertensive medication and risk of breast cancer (BC) [6‐8], the most common type of cancer and the leading cause of cancer death among women worldwide [9]. However, the results are conflicting, as these studies suffer from various biases, including unmeasured confounding, immortal time bias, confounding by indication and surveillance bias, which might result in inconsistent conclusions. Due to such shortcomings of the observational studies, previous results could not draw causative conclusions. In addition, there are ethical constraints for conducting randomized clinical trials (RCTs). Therefore, we opted for an alternative design to investigate the causal effect of anti-hypertensive medications on BC risk.

Mendelian randomization (MR) mimics a natural experiment by using genetic variants as a proxy (instrumental variable) for the modifiable exposure [10]. The principle is that randomization occurs naturally at conception when genetic variants are allocated at random to individuals from their parents. Consequently, the inherited genetic variants are independent of potential confounding environmental exposures. MR can be regarded as analogous to an RCT that uses genetic variation as the method of randomization ultimately providing causal insights. In addition, the risk estimated from MR reflects a lifetime risk, which is longer than the follow-up in a RCT. MR has successfully identified unintended drug effects including adverse drug effects and drug repurposing [11, 12]. As for the association between antihypertensive medication and cancer risk, Yarmolinsky et al. reported long-term ACE inhibition to be associated with an increased risk of colorectal cancer by using a MR analysis [13]. However, the ARB, a common antihypertensive medication [14], was not included in the analysis. Additionally, the instrumental variable for each class of drug was selected based on only one target. However, antihypertensive drugs may act on multiple targets involved in different pathways, thus analyses capturing all the possible targets with corresponding instrumental variables for each drug are needed. Finally, the instruments for the target from Yarmolinsky et al. were derived only from the blood serum, whereas the targeted genes may be differentially expressed in a tissue-specific manner [15].

Here we aimed to investigate the effect of antihypertensive medication use on BC risk using a two-sample MR design with a consideration of all the commonly prescribed medications for hypertension, and exploring the eQTL from both the whole blood and several other tissues. This study will add evidence to the current knowledge derived from observational studies and try to draw causal conclusions regarding the potential association between antihypertensive medication use on BC risk.

This study was based on several publicly available databases, which are summarized in the Supplementary File 1a, where we used the summary statistics without accessing any personal information. The study design is demonstrated in Fig. 1, which is also described below. We used two-sample MR to estimate the association between target gene expression (the exposure, say x) and BC risk (the outcome, say y) with effect size β_xy. The basic principle of MR is that, if a modifiable exposure alters outcome then the instrumental variable (here genetic variants, say g) that modifies the level of that exposure, should also be related to the outcome [16]. Expression quantitative trait loci (eQTL) data were used to assess the association between genetic instruments and level of target gene expressions (β_gx). The associations between genetic instruments and BC risk were estimated with genome wide association study (GWAS) summary statistics (β_gy). In a MR analysis, β_xy (defined as β_xy = β_gy/β_gx) is interpreted as the effect of x on y free of non-genetic confounders. For a genetic instrument to be considered valid three basic assumptions must have held: (1) The genetic variants are associated with the exposure (relevance assumption); (2) There are no unmeasured confounders of the associations between genetic variants and outcome (independence assumption); (3) The genetic variants affect the outcome only through their effect on the exposure (exclusion restriction) [10]. We further performed sensitivity analyses to confirm the discovered MR associations such as assessment of pleiotropy, colocalization, and multiple tissue enrichment analyses.

With this two-sample MR study, we observed that the overall BC risk was increased 16% along with one SD decrease of SLC12A2 gene expression and shared a similar effect with its divergent transcript CTC-228N24.3. SLC12A2 encodes Na(+)-K(+)-2Cl(–) co-transporter isoform 1 (NKCC1), which can be targeted by loop diuretics including torasemide, bumetanide and quinethazone. Thus, long-term use of these drugs may potentially increase overall BC risk. The significant association with the expression of SLC12A2 was further observed with ER+BC. In addition, a SD decrease in expression of PDE1B, which can be targeted by three CCBs: nicardipine, felodipine and bepridil, was associated with 7% decreased risk of ER+BC. We did not observe any significant association between other target gene expressions and BC risk.

A recent meta-analysis evaluated the association between antihypertensive medication use and BC according to 57 conventional observational studies and also reported that use of diuretics was associated with increased BC risk [28]. However, this study also found an increased BC risk among users of BBs, or CCBs [28], which is inconsistent with our result. Another meta-analysis based on four studies found that the relative risk of BC among users of loop diuretics was 0.91 (0.77–1.06) compared to nonusers, in possible disagreement with our findings [29]. A RCT-based meta-analysis concluded no consistent evidence that antihypertensive medication use had any effect on cancer risk [3]. The inconsistent findings may be due to the difference in study population, exposure assessment and the control of confounding effects. The observational studies are subjected to selection bias, information bias, and confounding by indication. Our results are in agreement with the findings from Yarmolinsky et al. who investigated antihypertensive drug use and risk of common cancers by evaluating SNPs in ACE, ADRB1, and SLC12A3 in GWAS of SBP to proxy genetic inhibition of the angiotensin-converting enzyme (ACE), β-1 adrenergic receptor (ADRB1), and sodium-chloride symporter (NCC) [13]. None of the inhibited targets were associated with the risk of BC [13]. Unlike this MR study which only considered one target for each type of antihypertensive drug, we included all the potential targets.

The mechanisms that links SLC12A2 gene expression and BC risk are unclear. The GSMR analysis for the association between SBP and BC risk indicates that the effect of the drugs on BC risk was not through blood pressure, which is consistent with the finding that there is no evidence of genetic correlation between blood pressure and BC risk [30]. The SLC12A2-coded protein, NKCC1 has been reported to be involved in mammary gland development and regulate breast morphogenesis [31]. So far, very few studies have investigated the association of BC risk and use of loop diuretics, although among which furosemide targets also NKCC2, a homogeneous protein of NKCC1. Elsewhere an in vitro study reported expression of SLC12A2 in BC cells to be downregulated by the treatment with estrogen [32], which is a well-known risk factor for BC. Our identification of phenotypes related to the top SNP of SLC12A2 indicates obesity may contribute to the increased BC risk linked to SLC12A2 gene expression. Interestingly, loss of SLC12A2 in pancreatic β-cells was associated with weight gain in mice [33]. Obesity was recognized as a risk factor for particularly ER+BC [34]. This is in accordance with our current study where SLC12A2 expression was found protective against BC risk and this association was only significant for ER+BC. It is incumbent on further studies to investigate if SLC12A2 gene expression affects BC risk through obesity/estrogen-related pathways. It should be noted that the case number of ER-BC GWAS was much less than ER+BC GWAS which might detail the loss of signal. Four out of five datasets from Expression Atlas also indicated lower expression of SLC12A2 in BC tissue (or tissue from BC patients) than the normal tissue (or tissue from controls). On contrary, several in vitro studies reported that inhibition of NKCC1 could reduce cell proliferation, invasion and/or migration in glioblastoma, glioma, esophageal squamous cell carcinoma, hepatocellular carcinoma and gastric cancer cells which may indicate a global underlying tumor-inhibiting mechanism [35‐41]. Sun et al. also found that increased expression of NKCC1 was associated with poor prognosis in lung adenocarcinoma and EGFR-mutated adenocarcinoma [42]. More studies are required to investigate the role of NKCC1 in BC etiology.

In our sensitivity analysis, we found that the expression of the divergent transcript of SCL12A2, CTC-228N24.3 was also associated with BC risk. It is non-trivial to decouple the two genes merely based on the summary statistics as they largely belong to the same haplogroup. In previous GWAS both genes have been implicated for BC (study ID in GWAS Catalog: GCST004988) and for blood pressure (GCST90132903-05 and GCST90020232-37), respectively, often via rs17764730 or other SNPs in LD such as rs1112956 and rs36715. As the eQTL results point out, the rs17764730 SNP has tangible cis-effects on both of them and our analyses do not discount one over the other, rather speculate on possible mechanisms between the protein coding gene of the two having a causal effect on BC risk. CTC-228N24.3, a lincRNA encoder (RNA1184), also known as ENSG00000245937 is a divergent transcript to SLC12A2 and mutually share enhancer/promoters GH05J128081 and GH05J128534 (GeneHancer data) where the rs17764730 resides. Previous studies showed mutation in this region regulate expression modulation of both genes [43]. Our observations may only provide a plausible biological basis for the conclusions drawn, which remain yet to be confirmed with further functional investigations.

PDE1B was the only other gene that showed the association with ER+BC risk. The function of protein PDE1B includes dopaminergic signaling, immune cell activation, and cell survival. It is one of the family members of phosphodiesterases (PDEs) that hydrolyze cyclic adenosine monophosphate (cAMP) and cyclic guanosine monophosphate (cGMP); the latter two participate in many physiological processes such as visual transduction, cell proliferation and differentiation, and cell-cycle regulation [44]. Some tumor cells overexpress PDEs and as a consequence, the level of cAMP/cGMP in tumor cells is lower than the normal cells [45]. PDEs have become the potential therapeutic target to increase intracellular cAMP/cGMP and thus inhibit tumor growth [46, 47]. PDE1B can be targeted by miR-5701 to inhibit proliferation and promote apoptosis of clear cell renal cell carcinoma cells [48]. Wittliff et al. used gene expression of PDE1B and several other genes to predict the overall survival of breast carcinoma [49]. However, in the tissue-specific MR, the results for the mammary gland contradicted the current evidence.

We need to emphasize the strengths and weaknesses of this study. Use of GWAS summary statistics with two sample MR increased statistical power. The application of genetic variants to proxy the use of antihypertensive medication reduced the chance of confounding, misclassification and immortal time bias that are common caveats in a conventional observational study [50]. The inherited variants were present since conception affecting the target gene expression, which provided the opportunity to observe the effect of antihypertensive medication on BC risk in the long term. Compared to RCT, our study design is more efficient as cancer is a late-onset disorder and needs long-term follow-up. Using a plethora of publicly available summary statistics data from GWAS, MR was performed without recruiting new patients or designing additional studies like RCT. We conducted multiple sensitivity analyses such as colocalization analysis and pleiotropy test to evaluate the viability of the assumptions of the instrument variables and to reduce chance findings. As for limitations, the exploration of the molecular subtype of BC was underpowered due to small sample size. Larger BC subtype-specific GWAS data from the consortium are needed to remedy such issue. Low statistical power was also a limitation for the localization analyses. In addition, the coloc package assumes a single causal variant for both traits in the genomic region examined, but multiple conditionally independent variants may exist in regions while ‘coloc.SuSiE’ was unable to provide credible set for BC GWAS. We were unable to exclusively identify the causal effect from SLC12A2 and SLC12A2-DT. Horizontal pleiotropy was assessed via differential expression of other genes, but it is uncertain if there were possible horizontal pleiotropic effects through other related traits. The instrumental variants for the exposure were based on eQTL data derived from both genders and the BC GWAS data were only based on females. Therefore, future studies need to investigate whether the actions of antihypertensive target genes on BC risk are gender specific. The effect of differed gene expression on BC risk due to polymorphism may not be the same as that due to the use of antihypertensive medication, as the former exposure is from early lifetime and the latter mostly from adulthood. Therefore, our results provide a strong signal to select existing drugs (NKCC1-targeted antihypertensive medication) to be validated with RCT. Additionally, our results suggest future studies could focus on the association between expression level of NKCC1 protein and BC risk, which may provide evidence on risk reduction.

By using two-sample MR, we found BC risk was negatively associated with expression of SLC12A2, and ER+BC risk was positively associated with expression of PDE1B. Therefore, expression modulation of SLC12A2 and PDE1B via antihypertensive drug usage (in addition to possible impacts through SLC12A2-DT) was associated respectively with increased and decreased risk of BC. The observed effect on the BC risk was independent of systolic blood pressure.