Abstract
In clinical practice, the co-existence of endometriosis and gastrointestinal symptoms is often
observed; however, the factors driving this link remain largely unknown. Here, using large-
scale multifaceted data including observational, genetic, and pharmaceutical datasets, we
report a positive phenotypic and genetic association of endometriosis with peptic ulcer
disease (PUD), gastro-oesophageal reflux disease (GORD), a combined GORD/PUD
Medicated (GPM) phenotype and irritable bowel syndrome (IBS), but not with inflammatory
bowel disease (IBD). Mendelian randomization analysis identified a causal effect of the GPM
phenotype on endometriosis and a bidirectional causal association between endometriosis and
IBS. Cross-trait meta-analysis and colocalization along with comprehensive functional
annotation confirmed two shared genetic loci ( FN1,
TACSTD2) for endometriosis with IBS
and twelve loci (ETAA1, HOXC4, RERG, SEMA3F, SPAG16, HIST1H2BC, RAB5B, CCKBR
and PDE4B ) with GORD and PUD. Shared genetic loci may contribute to risk of both
endometriosis and digestive disorders through the involvement of DNA damage, estrogen
regulated cell-proliferation and inflammation, and barrier dysfunction. Analyses of
medication usage identified a higher use of drugs for IBS, GORD and PUD in women
diagnosed with endometriosis as well as a higher use of hormone therapies in women
diagnosed with IBS, GORD and PUD but not for IBD, which strongly supports the co-
occurrence of these conditions and highlights the potential for drug repositioning and caution
around drug contraindications in clinical practice. Taken together, the combined evidence
robustly suggests a shared disease aetiology and provides important clinical implications for
diagnostic and treatment decisions for endometriosis and digestive disorders.
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WHAT IS ALREADY KNOWN ON THIS TOPIC?
• Both endometriosis and gastrointestinal disorders affect a large proportion of people
worldwide and the co-existence of endometriosis and gastrointestinal symptoms (eg,
abnormal pain, bloating, constipation) is often observed in clinical practice.
• The association of these two diseases was supported but also limited to previous
observational evidence which highlights a three-fold increase in the prevalence of
irritable bowel syndrome (IBS) in women with endometriosis.
• Observational study is easily subject to measurement error, confounding and reverse
causation. Therefore, it is important to assess the association using multidimensional
datasets and more accurate approaches, such as the use of genetic data in a mendelian
randomisation framework as well as the analysis from a perspective of medication usage.
WHAT THIS STUDY ADDS
• Genetic risk factors for endometriosis and gastrointestinal disorders, two leading causes
of discomfort and chronic pelvic pain, are correlated.
• Mendelian randomisation analyses supported a causal relationship between genetic
predisposition to gastrointestinal disorders (gastro-oesophageal reflux disease (GORD)
and peptic ulcer diseases (PUD)) and endometriosis risk, and evidence for a bidirectional
causal relationship between endometriosis and IBS, which might explain in part the co-
occurrence of these diseases.
• The identification of shared risk loci highlighted biological pathways that may contribute
to the pathogenesis of both diseases, including estrogen regulation and inflammation, as
well as potential therapeutic drug targets such as CCKBR and PDE4B.
• The higher use of drugs for IBS, GORD and PUD in women diagnosed with
endometriosis as well as the higher use of hormone therapies in women diagnosed with
IBS, GORD and PUD, support the co-occurrence of these conditions and shared disease
aetiology but also highlights the potential for drug repositioning and caution around drug
contraindications.
Introduction
Endometriosis is a common gynaecological disease affecting around 11% of reproductive
aged women, significantly impacting quality of life and work productivity 1 2 . The clinical
manifestations of endometriosis are diverse. Many of the symptoms are non-specific, which
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preclude timely diagnosis and further prognosis 1 3 . It has often been observed that many
women diagnosed with endometriosis also experience symptoms associated with
gastrointestinal disorders (GI) including abdominal pain, bloating, constipation, heartburn,
dyspepsia, vomiting, painful bowel movements, diarrhea, and nausea
4-6. Studies have shown
that whilst these symptoms do not necessarily involve bowel lesions associated with
endometriosis, symptoms such as cyclic-related bloating, constipation and diarrhea can get
worse during menstruation
5-8. Inevitably, this presents challenges for clinicians to accurately
diagnosis both diseases among women. Understanding shared disease aetiology critically
impacts both disease diagnosis and management.
Previous observational studies have provided some evidence for the associations between
endometriosis and digestive disorders. Meta-analyses have reported a three-fold increase in
the prevalence of IBS in women with endometriosis compared to women without
endometriosis
9 10. This was supported by a recent retrospective study using a large nationwide
biobank-based cohort, the Estonian Biobank (EstBB), that reported a notable proportion of
women diagnosed with endometriosis or IBS also suffered from IBS (13.6%) or
endometriosis (9.0%), respectively
11. A nationwide Danish cohort study found a significantly
increased risk of inflammatory bowel disease (IBD) in endometriosis patients with a
standardised incidence ratio (SIR) of 1.5 (95% confidence interval 1.4 to 1.7), and the
relationship became stronger when restricted to surgically confirmed endometriosis
12.
Currently, very few observational studies have investigated the association between
endometriosis and other gastrointestinal disorders. However, endometriosis symptoms
overlap with other common gastrointestinal disorders, including peptic ulcer disease (PUD)
and gastro-oesophageal reflux disease (GORD)
13.
Despite studies showing endometriosis patients are more likely than people without
endometriosis to present gastrointestinal symptoms or have a diagnosis of gastrointestinal
disorders, it is uncertain whether this is due to 1) a direct effect of endometriosis itself; 2)
shared aetiological factors between endometriosis and gastrointestinal diseases; 3) side
effects of medical treatments; or 4) the inevitable association bias in observational studies,
such as the measurement error, reverse causation, residual or unmeasured confounding
14. For
example, therapeutic use of gonadotropin-releasing hormone (GnRH) analogues and
nonsteroidal anti-inflammatory drugs (NSAIDs), to manage symptoms of endometriosis, has
been widely reported to aggravate the severity of gastrointestinal symptoms and contribute to
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gastrointestinal disorders including PUD 6 15-18 . Therefore, using a more accurate approach
and multidimensional dataset to validate the relationship between endometriosis and
gastrointestinal disorders has important implications, not only for understanding shared
disease mechanisms but also for informing therapeutic strategies in clinical practice.
Endometriosis and gastrointestinal diseases mentioned above are common multifactorial
diseases with environmental and genetic risk factors both playing roles in the development of
these diseases
19 20 . Twin and family studies have shown a heritable component of
endometriosis, IBS, PUD, IBD and GORD 21-26. Genome-wide association study (GWAS),
which have been widely used to identify disease associated genetic risk variants 27, also
enable the use of mendelian randomisation (MR) approaches to assess the causal effect of
cumulative genetic predisposition to one disease on other disease risk. Given the advantage
that genetic alleles are randomly determined at conception and free from potential
environmental confounders (eg. medication usage) and measurement error due to self-report,
MR analysis can minimize the biases that frequently weaken results obtained from
observational approachs
14 28. Therefore, application of GWAS data and an MR framework is
of great value in understanding shared aetiology.
One study recently implicated causal links between endometriosis and depression with gastric
mucosa abnormalities using genetic data29. However, the relationship between endometriosis
and other common GI disorders, like IBS and IBD and PUD, were not investigated. GWAS
studies have identified risk variants for endometriosis and gastrointestinal disorders
independently30-32, including one female-specific IBS risk locus at 9q31.2, which was also
previously reported as more strongly associated with early age at menarche32, a risk factor for
endometriosis. This study presents a comprehensive evaluation of the relationship between
endometriosis and gastrointestinal disorders through analysis of large-scale genetic datasets,
and epidemiological and pharmaceutical data in the UK Biobank (UKB) and Australian
Longitudinal Study on Women’s Health (ALSWH)
33 34.
Method
Data resources
The large-scale GWAS summary statistics for endometriosis and five gastrointestinal
disorder phenotypes, utilized in this study, have been well described in previous studies 30 31.
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Summary data for endometriosis were restricted to eight European ancestry cohorts 31 35 for
the purpose of this analysis. A total number of 14,926 cases and 189,715 controls genotyped
across 7,899,415 SNPs were included in the endometriosis meta-analysis. GWAS summary
statistics for four gastrointestinal disorders, gastro-oesophageal reflux disease (GORD) (n
case
= 39,851, ncontrol = 416,563), peptic ulcer disease (PUD) (n case = 12,226, ncontrol = 444,188),
irritable bowel syndrome (IBS) (n case = 14994, n control = 441420) and inflammatory bowel
disease (IBD) (n case = 6,115, n control = 450,299), were previously generated using genetic
data from individuals in the UK Biobank (UKB), using the health-related outcomes data from
combing self-reported, primary care, death register and hospital reported diagnoses. As
medications used for PUD also have a therapeutic effect on GORD, a fifth phenotype for
gastrointestinal disorders is the combined GORD and PUD and individuals taking
medications for GORD/PUD making a total of 75,192 cases and 381,222 controls in the
GORD/PUD Medicated (GPM) phenotype
30. Sex stratified GWAS summary statistics for
IBS were also generated in this study for the purpose of exploring potential sex bias in the
relationship between endometriosis and IBS.
Comorbidity analysis
As a cross-sectional analysis, the comorbid relationship between endometriosis and each
gastrointestinal disorder (IBS, IBD, GORD and PUD) described above were investigated
among unrelated European female individuals in the UKB, with ancestry definition described
previously36. Phenotypes were defined using self-reported, hospital admission, death register
or primary care record data. Endometriosis cases were defined using date and source of
endometriosis reported (UKB data fields:132122 & 132123), ICD10 diagnosis (UKB data
field:41270), ICD9 diagnosis (UKB data field: 41271) and self-report (UKB data field:
20002), totalling 5,392 cases (excluding endometriosis of the uterus/adenomyosis).
Gastrointestinal disorders definitions were similar as previously described by Wu et al. 30
however, these were also restricted to females. A total of 16,330 IBS cases were included
(UKB data field: 131639) alongside 22,383 GORD cases (UKB data field: 131585). IBD and
PUD were defined using a combination of disease codes, IBD cases were a combination of
Crohn’s diseases (UKB data field: 131627) and ulcerative colitis (UKB data field: 131629)
diagnoses totalling 2,708 cases and PUD cases were a combination of gastric ulcer cases
(UKB data field : 131591), duodenal ulcer cases (UKB data field: 131593), other site peptic
ulcer cases (UKB data field: 131595) and gastro-jejunal ulcer cases (UKB data field :
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131597) totalling 5,208. We firstly measured whether individuals diagnosed with
endometriosis were more likely to have a diagnosis of IBS, IBD, GORD and/or PUD using
Fisher’s exact test. Next, we conducted a competitive comorbidity analysis to test which
digestive disorder is more prone to be comorbid with endometriosis among these four
disorders. Briefly, the proportion of endometriosis cases in each of the four digestive diseases
were calculated and then compared in pairs using a two-proportion Z-test. To meet the
prerequisite of this analysis that samples in each pair are independent, we removed
overlapping samples when calculating the proportion.
Genetic correlation
Genetic correlation attributable to the genome-wide common SNPs between endometriosis
and each of the other five gastrointestinal disorder phenotypes (IBS, IBD, GORD, PUD,
GPM) was estimated using bivariate linkage disequilibrium score regression (LDSC)
37 and
their respective GWAS summary statistics. GWAS summary data was formatted using the
function ‘munge_sumstats.py’ outlined in the LDSC manual and the genetic correlation for
each pair was estimated. The European 1000 genome reference data was adopted in the
calculation of linkage disequilibrium (LD) scores. A sex-stratified analysis was conducted to
further investigate whether the genetic correlation between endometriosis and IBS is sex
dependent. Given that there was no sample overlap in GWAS studies of endometriosis and
gastrointestinal disorders and all participants are of European ancestry, we also reduced
standard error of genetic correlations by constraining the intercept, which was used to protect
bias from population stratification and sample overlap in different GWAS studies.
Assessing potential causal relationships
Mendelian randomisation (MR) uses genetic variants that are robustly associated with
exposure of interest to test whether those genetic variants also increase the risk of another
trait
14. MR has emerged as a valuable tool to assess the causal effect of one trait on another.
The genetic variants selected are robust and are not associated with other confounders and
will only influence the outcome trait through the trait of interest if there is a causal
association, thus less susceptible to confounding, measurement error, and reverse causation
when compared with conventional observation studies
14 38 39 . In this study, the causal
relationships between endometriosis and gastrointestinal disorder phenotypes (IBS, GORD,
PUD, GPM) was investigated using one wildly-accepted MR method called Generalised
Summary-data-based Mendelian randomization (GSMR)
40. The combined phenotype of
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GPM was used in place of individual GWAS for PUD and GORD to increase study power.
GSMR uses all significantly associated SNPs as SNP instruments to test for causality. To
reduce the influence of horizontal pleiotropy (a single locus directly affecting multiple
phenotypes), one potential confounding factor for Mendelian randomization analysis, we also
applied the HEIDI-outlier analysis to detect SNPs having obvious pleotropic effect on both
risk factor and diseases. To remove potential confounding from the correlation between the
GI traits, we applied mtCOJO
40 on both the exposure and outcome trait. We further used the
adjusted GWAS summary statistics to repeat the GSMR analysis again. A P-value of < 0.05
was considered significant. In some cases there was an insufficient number of SNPs to use as
instruments and so the GWAS threshold was relaxed to allow at least ten SNPs for each
phenotype, following the author’s recommendation to include at least 10 SNP instruments
during GSMR analysis to achieve robust results.
Cross-trait meta-analysis of endometriosis and gastrointestinal diseases
We next adopted two complementary cross-trait meta-analysis methods, MetABF
41 and Eskin
random-effects model (RE2C) 42, to identify whether there are shared risk loci between
endometriosis and the digestive disorders (IBS, GPM), as well as potential novel risk loci for
each disease. MetABF performs the multi-trait meta-analysis based on the Bayesian
framework. Effect alleles were harmonised across all three GWAS. Both fixed and
independent effect models were used when performing this meta-analysis. The prior
parameter accounting for effects of heterogeneity in two diseases was set as 0.1, which is
typically used in complex diseases. As a result, SNPs with a logABF > 4 and at least a
normally significant P-value < 0.05 in each individual disease GWAS analysis were defined
as significant in the MetABF analysis.
To validate the MetABF results, we used a complementary cross-trait meta-analysis
approach, RE2C, which dramatically increases power when statistics among different studies
are correlated compared with other methods. RE2C also accounts for the heterogeneous
effects within studies using a novel statistic model. Similar to MetABF, effect alleles were
harmonised across the GWAS prior to being used as input for the RE2C analysis. As a result,
a SNP meeting the P -value threshold of < 5e-8 in either fixed (Lin-Sullivan method) or
random (RE2C) effects model and having at least a normally significant P-value < 0.05 in the
individual disease GWAS, were deemed as significant in the meta-analysis. SNPs meeting
both thresholds of MetABF and RE2C were selected for the further fine mapping analysis in
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Functional Mapping and Annotation (FUMA) 43 to identify independent risk loci using a
threshold of r2/i1 </i1 0.6 and then the lead SNPs at a threshold of r2/i1 </i1 0.1. The maximum
distance between LD blocks to merge into a locus were set as 250kb.
Colocalization analysis
To identify specific genomic regions that have the same causal variant for each disease we
conducted a pairwise GWAS (GWAS-PW) 44 analysis. Again, this analysis was restricted to
comparisons with IBS and GPM. The input to GWAS-PW is a set of estimated effect sizes
and standard error for each SNP on each of the paired diseases. The whole genome was split
into 1,703 LD independent blocks, and the probability is estimated for four models extended
from Giambartolomei et al
45, that a given region (a) contains a genetic variant that impacts
first disease (PPA1); (b) contains a genetic variant that impacts the second disease (PPA2);
(c) contains a genetic variant that affects both diseases; (PPA3) or (d) contains two distinct
variants that influences each disease separately (PPA4). Paired summary statistics for
endometriosis with IBS or GPM were analysed. Any regions that were identified with a
PPA3/PPA4 >0.5 were considered to show evidence of a shared causal variant and two
distinct causal variants respectively.
Functional annotation and gene mapping
In order to identify potential target genes associated with both endometriosis and IBS or
GPM, we used FUMA to perform Multi-marker Analysis of GenoMic Annotation
(MAGMA) gene-set analysis and two additional annotation approaches, positional mapping
with combined annotation-dependent depletion (CADD) score and cis-expression
quantitative trait loci (eQTL) mapping for independent SNPs and SNPs in LD identified in
the above cross-trait meta-analysis. Gene sets were adopted from Genotype-Tissue
Expression (GTEx) project which collects 54 non-diseased tissue sites across nearly 1000
individuals
46. Cis-eQTL information of 12 digestive and reproductive tissues (Supplementary
Table 1) in the GTEx Project 46, endometrium eQTLs 47 and a large blood eQTL dataset,
eQTLGen48 were used for the eQTL mapping analysis. Variants with a CADD score of more
than 12.7 were defined as potentially pathogenic.
SMR analysis is a powerful approach to identify likely causal relationship between the trait-
associated SNPs and gene expression. SMR analysis was performed on endometriosis, IBS
and GPM respectively using eQTL data from 12 digestive and reproductive tissues in the
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GTEx project46 and endometrium 47. Associations were defined as significant if PSMR 0.05. We determined if any SMR significant genes were shared between the
diseases. Shared causal associations indicated that SNPs may be associated with both
diseases through the regulation of expression of the same gene.
Additional epigenomic functional annotation was performed with EpiMap
49 using epigenome
maps from relevant tissues (uterus, ovary, gastroesophageal sphincter, Peyer’s patch,
oesophagus, stomach, colon, intestine, rectum) to define chromatin states, enhancers,
upstream regulators and downstream target genes.
Pathway-based enrichment analysis
To identify which biological pathways are associated with both endometriosis and IBS or
GPM, we firstly performed a gene-set enrichment analysis using MAGMA implemented in
FUMA. Significant SNPs from the cross-trait meta-analysis were used as input for MAGMA
and a window of 0kb outside of a gene was adopted in the gene-set analysis. In addition,
genes annotated to significant loci from the cross-trait meta-analysis were included in a
GENE2FUNCTION analysis in FUMA to identify whether these genes were enriched in any
curated gene sets.
Phenome-wide association
In order to investigate whether the correlation between endometriosis and each of IBS and
GPM can be explained by the genetic susceptibility to any other traits or diseases, we
searched traits that were associated with genome-wide significant independent SNPs and
SNPs in LD (r
2 > 0.8) from the cross-trait meta-analysis. We used information from GWAS
catalogue and PhenoScanner 50.
Drug target analysis
Using the online Open-targets drug database (www.targetvalidation.org
), we investigated if
any known drug targets are common across endometriosis and gastrointestinal disorders
(GORD, PUD, IBS) and if any genes functionally annotated to shared risk loci are potential
drug targets for either endometriosis and/or digestive disorders.
Medication usage
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To investigate the implications of medication use on the relationship between endometriosis
and gastrointestinal disorders we analysed Pharmaceutical Benefits Scheme (PBS) data by
endometriosis status from the 1973-78 and 1989-95 cohorts in the Australian Longitudinal
Study on Women’s Health (ALSWH)
33 34 . The frequency of medications used in these
women was calculated. In addition, we characterized the medication use (UKB data field:
20003) in unrelated women in the UK Biobank, including 5,392 women diagnosed with
endometriosis, 15,881 women with IBS, 22,383 women with GORD, 5,208 women with
PUD and 2,708 women with IBD. We randomly selected age-matched controls to avoid the
potential bias caused by differences in age distribution between cases and controls.
Differences in the proportion of women, with and without an above diagnosis, using reported
medications was tested using fisher test. After correcting for multiple testing using
Bonferroni analysis, a P-value of < 0.05 was considered significant.
Results
Significant comorbid relationship between endometriosis and GI disorders
Using data from 188,461 unrelated females in UKB, we found a bidirectional
epidemiological relationship between endometriosis and each of the four GI disorders (IBS,
IBD, GORD, PUD). GORD and IBS remained significant after accounting for multiple tests.
Of those associations (Table 1), women with endometriosis were two times more likely to
have an IBS diagnosis (OR = 2.01, 95% CI 1.86 to 2.16; P-value = 3.90e-68), and 1.4 times
more likely to have a GORD diagnosis (OR = 1.40, 95% CI 1.30 to 1.50; p = 3.54e-18), than
those free of endometriosis. The competitive comorbidity analyses confirmed that women
with endometriosis are more prone to be comorbid with IBS, followed by GORD, when
compared with PUD (OR = 1.22, 95% CI 1.05 to 1.42; p = 0.01) and IBD (OR = 1.25, 95%
CI 1.01 to 1.53; p = 0.04) (Figure 1).
Genetic correlation between endometriosis and GI disorders
Compared with comorbidity relationship identified above, the LDSC analysis only provided
evidence of a significant positive genetic correlation (rg) between endometriosis and IBS (rg
= 0.22, p = 0.005), GORD (rg = 0.16, p = 0.004), PUD (rg = 0.23, p = 0.003) and GPM (rg =
0.22, p =
2.17e-06) (Figure 2A). There was no evidence of significant correlation between
endometriosis and IBD. Constraining the intercept due to no sample overlap, resulted in a
smaller standard error whereas there was little change in the genetic correlation (Figure 2A).
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Although endometriosis is rarely observed in males, males do carry endometriosis risk
alleles, as such we also conducted the genetic correlation analysis separately for females and
males. The results remained significant between endometriosis and both the separate female
(rg = 0.28, p = 0.003) and male (rg = 0.21, p = 0.014) IBS GWAS cohorts (Figure 2B).
Complex causal relationship between endometriosis and GI disorders
Following the identification of shared genetic correlation, we applied an MR method 40 to
estimate the causal relationship between GPM, IBS, and endometriosis (Figure 3). We
identified evidence of a significant association between GPM and endometriosis whereby
genetic variants contributing to the risk of GPM (genetic predisposition to GPM) also
increased risk of endometriosis (odds ratio = 1.56 (95% CI 1.35 to 1.76), p = 2.47e-5) (Table
2). The reverse MR analysis (the genetic effect of endometriosis on GPM) was not
statistically significant (odds ratio = 0.98 (95% CI 0.94 to 1.02), p = 0.32). Due to the limited
number of SNP instruments available for IBS when using a genome-wide significant level (P
< 5e-8), we were unable to estimate the effect of IBS on endometriosis risk. However, using
endometriosis as the exposure we identified that genetic variants contributing to the risk of
endometriosis had a small effect on risk to IBS (odds ratio=1.07 (95% CI 1.01 to 1.13), p =
0.042). This effect was no longer significant following stringent Bonferroni correction for
multiple testing.
To increase the number of SNP instruments in the analysis we relaxed the SNP inclusion
threshold to P < 5e-6 and repeated the GSMR analysis. The relationship between GPM and
endometriosis, and endometriosis and IBS, was consistent, although attenuated, compared
with that estimated using the genome-wide significant level ( P < 5e-8) (Table 2).
Interestingly, we also found evidence of bi-directional relationship between IBS and
endometriosis. Genetic variants that increased risk of IBS had a significant risk effect on
endometriosis (odds ratio=1.15 (95% CI 1.03 to 1.28), p = 0.028) however, this effect was no
longer significant following stringent Bonferroni correction for multiple testing.
A genetic correlation and strong bi-directional association between IBS and GPM has been
previously reported
30 , with genetic predisposition to IBS having a causal effect on GPM
(odds ratio = 1.20 (95% CI 1.15 to 1.24), p = 1.93e-14) and genetic predisposition to GPM
having a causal effect on IBS (odds ratio = 1.34 (95% CI 1.28 to 1.40), p = 7.29e-23). The
complex causal relationship among the three diseases is illustrated in Figure 3. The
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relationship between GI disorders may act as a confounder impacting the results of each pair
of MR analyses. To avoid the potential effect of GPM on the relationship between
endometriosis and IBS, we adjusted the GWAS data of both endometriosis and IBS for the
effects of GPM using mtCOJO to identify disease specific variant associations independent
of GPM. Following this conditional analysis, evidence for the bi-directional causal
relationship between IBS and endometriosis remained (Table 2, Figure 4). The causal
relationship between GPM and endometriosis, following adjustment for the genetic effects of
IBS, was only significant when the less stringent SNP inclusion p-value threshold was used
but did not pass correction for multiple testing (odds ratio = 1.16 (95% CI 1.05 to 1.27), p =
0.008) (Table 2, Figure 4).
MR was run separately for GORD and PUD to test if the relationship between GPM and
endometriosis was driven by one particular phenotype. There was evidence of a significant
relationship between GORD and endometriosis which remained when conditioning both
traits on PUD (OR=1.15 (95% CI 1.10 to 1.21), p=1.69e-6) however, there was no evidence
of a causal relationship between PUD and endometriosis (Supplementary Table 2). More
powerful GWAS studies may be required to validate these causal relationships.
Genomic loci associated with both endometriosis and GI disorders
To identify if there are any risk loci associated with both endometriosis and IBS or GPM, we
carried out a cross-trait meta-analysis using two different methods, MetABF and RE2C.
SNPs were considered associated with both diseases at a genome-wide significant level if
they had a logABF > 4 in MetABF and a P -value < 5e-8 in RE2C models and a P-value <
0.05 in each individual GWAS analysis. As a result, a total number of 477 SNPs met criteria
for endometriosis and GPM while only 32 SNPs were significant for endometriosis and IBS.
Using FUMA, 12 genomic risk loci (21 independent signals) were identified as significantly
associated with both endometriosis and GPM and three with endometriosis and IBS (Table
3). Among those loci identified by the cross-trait meta-analysis, the SNP on chr2:67845739
(rs2861694) within ETAA1 was previously reported as associated with both endometriosis
and GPM, another five SNPs were significantly associated with either endometriosis or
GPM. The remaining nine risk loci were identified for the first time at a genome-wide level
of significance for endometriosis and GPM and IBS (Table 3).
Evidence of shared causal variants between endometriosis and GI disorders
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GWAS-PW was used to perform a colocalization analysis to assess if any of the genomic
regions jointly affected endometriosis and IBS. Results (Table 4) showed that there were
three regions with PPA3 > 0.5 and three regions with PPA4 > 0.5, suggesting that 3 regions
contain the same causal variant for both endometriosis and IBS whereas another three regions
contain distinct and independent causal variants for endometriosis and IBS respectively.
Analysing endometriosis and GPM, we identified six regions with PPA3 > 0.5 and 60 regions
with PPA4 > 0.5. None of the regions with PPA3 > 0.5 in endometriosis and GPM
overlapped with the three regions identified between endometriosis and IBS. Regions with
evidence of a single casual variant (PPA3 > 0.5) for both endometriosis and either IBS or
GPM are shown in Table 4. Among these identified regions, the two loci ( TACSTD2 and
FN1) with the highest probability of a shared causal variant for endometriosis and IBS and
the three loci (ETAA1 , HOXC4 and RERG) with the highest probability of a shared causal
variant for endometriosis and GPM were also identified by the cross-trait meta-analysis
described above. Specifically, the region with the strongest pleiotropic effect on
endometriosis and GPM is located near ETAA1/LINCO1812 on chromosome 2 (Figure 5) ,
SNPs in this region are significantly associated with these two diseases and the index SNPs in
the individual GWAS studies are in strong LD (r
2 = 0.88). Other regions identified by both
cross-trait meta-analysis and GWAS-PW are shown in Supplementary Figure 1A-G.
Gene mapping and functional annotation of shared risk loci
We performed a gene-based analysis using MAGMA to identify potential genes associated
with both endometriosis and IBS or GPM. A total of 19 protein coding genes mapped to
SNPs from the endometriosis and GPM cross-trait meta-analysis reached genome-wide
significance (Supplementary Table 3). Only FN1 passed the MAGMA analysis for SNPs
from endometriosis and IBS meta-analysis.
To better understand the potential regulatory function of identified risk loci associated with
both diseases, we mapped risk SNPs to cis-eQTLs in different tissues for genes up to 1MB on
either side of the variant using FUMA. Lead SNPs in three loci ( RAB5B, ETAA1 and HOXC)
from the cross-trait meta-analysis were found to impact gene expression in either blood or
both digestive and reproductive tissues. In detail, we identified eQTLs for four genes in
digestive tissues that contained SNPs associated with risk of endometriosis and IBS from the
GWAS meta-analysis (Supplementary Table 4). Similarly, we identified eQTLs for 37 genes
that contained SNPs associated with risk of endometriosis and GPM from the GWAS meta-
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15
analysis (Supplementary Table 4). Seven are expressed both in digestive and reproductive
tissues. Using a more powerful blood eQTL dataset from the eQTLGen project we identified
a total of 8 and 162 genes with eQTLs containing SNPs associated with risk of endometriosis
and IBS, and GPM, respectively (Supplementary Table 4). Whilst 70% of genes with eQTLs
in digestive and reproductive tissues were also in blood, indicating genetic regulation of gene
expression can be shared across tissues, 12 were not identified in blood and may represent
tissue specific effects. For example, the lead SNP, rs773111, in RAB5B locus shared by
endometriosis and GPM is an eQTL for RAB5B expression in blood and for nearby SUOX
gene expressed in blood, digestive, and reproductive tissues.
Combined annotation-dependent depletion (CADD) scores, which inform the deleterious
effect of a SNP on protein function, were used to further understand the function of shared
SNPs using FUMA. Our results showed that risk variants shared between endometriosis and
IBS located in WNT4 on chromosome 1 and FN1 on chromosome 2 had at least one SNP
with CADD score greater than 12.7 using positional gene mapping (Supplementary Table 5).
Risk variants shared between endometriosis and GPM located in 33 different genes had at
least one SNP with CADD score greater than 12.7 (Supplementary Table 5).
To investigate the shared functional mechanism of SNPs associated with both endometriosis
and digestive disorders, we applied the Summary data-based Mendelian randomization
(SMR) method. SMR integrates the GWAS summary statistics of disease with SNP-gene
associations (eQTL), and the significant SMR association indicates that the SNP is causal for
the disease as mediated through gene expression or has a pleiotropic effect on both disease
and gene expression. We aimed to identify common associations between individual
endometriosis and IBS and GPM SMR analyses. eQTL information in digestive and
reproductive tissues in the GTEx project and in endometrium were used in this study. Our
Results
identified 155 genes with normally significant SMR associations ( P-SMR 0.05) for which variants were associated with risk of endometriosis and GPM and
expression in digestive and reproductive tissues simultaneously (Supplementary Table 6). Of
the 155 significant SMR associations, one variant (rs2344609), significantly associated with
CNGA4 expression, was significant in the cross-trait meta-analysis and another (rs9873183),
associated with expression of RNF123, was in LD (r
2 > 0.5) with significant SNPs in the
cross-trait meta-analysis. When applied to endometriosis and IBS, we identified 91 genes
with nominally significant SMR associations for variants associated with both diseases and
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16
expression in digestive and reproductive tissues (Supplementary Table 6). Of the 91
significant SMR associations, one variant (rs232877) associated with expression of MYSM1
was in LD (r 2 > 0.65) with the lead SNP of TACSTD2 loci identified in the cross-trait meta-
analysis, demonstrating that it may contribute to the risk of both endometriosis and IBS
mediated through MYSM1 expression.
Risk SNPs from the cross-trait metanalyses were also mapped to regulatory regions in
reproductive and gastrointestinal tissues using EpiMap
49. Of 477 SNPs significant in the
endometriosis and GPM meta-analysis, 35 were located in predicted enhancers and nine of
these enhancers were predicted in both reproductive and gastrointestinal tissues
(Supplementary Table 7). Gene targets of these enhancers included 10 genes on chromosome
3 (CYB561D2, GNAI2, HYAL3, NAT6, NPRL2, RBM5, RBM6, SEMA3F, SLC38A3, TUSC2)
and nine genes on chromosome 12 ( RERG, HOXC4, HOXC5, HOXC6, HOXC8, HOXC9,
HOXC10, HOXC11, HOXC13) including a cluster of HOXC genes (Supplementary Table 8).
Five SNPs were located in predicter promoter regions for RBM5 and RBM6 on chromosome
3 and HOXC-AS1, RERG and SUOX on chromosome 12. Only one SNP significant in the
endometriosis and IBS meta-analysis was located in a regulatory region, a predicted enhancer
and promoter region in FN1 on chromosome 2 in colon and esophagus (Supplementary Table
7).
In total, 218 genes were mapped to 24 shared risk loci using at least one annotation method
above (Supplementary Table 9) and 37 genes had evidence from at least two methods (Table
5).
Pathways enriched for genes in shared risk loci
The MAGMA gene-set analysis, which uses the full distribution of input SNP p-values to
identify whether curated gene sets and GO terms from MsigDB were significantly associated
with both diseases, found no gene set remained significant after multiple testing. We instead
used another pathway enrichment approach, GENE2FUNC, to test whether 204 prioritized
genes (eQTL, CADD, MAGMA, SMR) linked to endometriosis and GPM were enriched in
pre-defined pathways based on their gene expression. As a result, a total number of five
KEGG gene sets passed adjusted p-value threshold of P < 0.05, including “leukocyte
transendothelial migration”, “oxidative phosphorylation”, “epithelial cell signalling in
helicobacter pylori infection”, and “chemokine_signaling pathway” (Supplementary Table
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17
10). Genes were also enriched in 40 GWAS Catalog reported gene sets, including fat
distribution, BMI, intelligence, and depression (Supplementary Table 10). The 14 genes
linked to endometriosis and IBS were enriched in two KEGG pathways including “pathway
in cancer” and “ECM receptor interaction” and 17 GWAS Catalog gene sets (Supplementary
Table 11).
Additional phenotypes associated with shared risk loci
Given the nature of SNP pleiotropy, we further investigated whether there were previously
reported trait associations with SNPs related to risk of both endometriosis and gastrointestinal
diseases through PhenoScanner and GWAS Catalog. Interestingly, as shown from the results
in Supplementary Table 12, our results identified that fat and estrogen related traits (BMI,
body fat percentage, waist circumference, hip circumference, WHR, weight, age at first birth
and age at menarche) are associated with six (WNT4, SEMA3F, HIST1H2BC, RERG, RAB5B,
HOXC4/5/6) of twelve regions shared between endometriosis and GPM, which consistently
supported that those identified regions might contribute to the risk of both endometriosis and
GPM through the dysregulation of estrogen and inflammation. The precise interaction
mechanism of estrogen and fat related traits with endometriosis and GPM is unknown and
requires further investigation.
Potential for drug repositioning
The online Open-target drug platform was used to assess if any of the genes linked to both
endometriosis and the GI disorders were potential drug targets
(https://www.targetvalidation.org). A total of 218 unique genes with evidence from gene
mapping and functional annotation (Supplementary Table 9) were used to search for known
endometriosis and gastrointestinal disorder (GORD, PUD, IBS) drug targets. One gene,
CCKBR encoded a protein that was targeted by two drugs Proglumide (ATC code:
A02BX06) and Netzepide (NCT01298999 and NCT02597712) for the clinical treatment of
GORD and PUD. In addition, PDE4B with its encoded protein cAMP-specific 3',5'-cyclic
phosphodiesterase 4B being targeted by Pentoxifylline, acts as an inhibitor targeting the
immune system and has been clinically trialled for the treatment of both endometriosis (phase
III) and IBS (Phase IV) separately (Table 6). Compared with IBS which has multiple sources
of evidence to support the promising treatment effect of Pentoxifylline
51 52, there is limited
evidence on whether Pentoxifylline impacts endometriosis related pain reduction 53. Notably,
when not restricted to the aforementioned gene set, 34 genes with encoded proteins were
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18
targets of both endometriosis and IBS/GORD/PUD drugs (Supplementary Table 13). This
study may provide novel insights and evidence for the further investigation of therapeutic
targets for both endometriosis and GI traits.
Insights from medication use in both diseases
Identified comorbid relationships between endometriosis and gastrointestinal disorders and
shared symptomology as well as shared genetic components also raise questions around the
potential effects of medication use on disease aetiology and management. We investigated
prescription medication use in women by endometriosis status using data from the PBS
records for both the 1973-78 and the 1989-95 ALSWH cohorts. Interestingly, drugs for peptic
ulcer and gastro-oesophageal reflux were within the top 10 most frequently used drugs in
both cohorts and such drug usage rate was significantly higher in women with endometriosis
than those without in 1989-95 ALSWH cohort after multiple testing (Supplementary Table
14), further evidence of the likely co-occurrence of the diseases and disease symptoms.
Consistently, using age-matched medication data of unrelated European women within the
UK biobank revealed that in addition to the expected hormonal therapies and NSAIDs, up to
seven medications for treatments of GORD, PUD and IBS were also significantly higher in
women with endometriosis compared with women without (Table 7 & Supplementary Table
15). More interestingly, when comparing medication usage between women with and without
gastrointestinal disorders in the UK biobank, we also found a significantly higher use of
hormone therapies among IBS, GORD, and PUD, but not for IBD (Table 7 & Supplementary
Table 16), which is consistent with genetic results in this study. We next searched for the
target genes of those drugs used for GI disorders identified above, and found that SLC22A1,
one of their transporters, has also been identified by our cross-trait meta-analysis and
subsequent functional mapping (Supplementary Table 4 & Supplementary Table 9).
Discussion
Summary findings of this study
This is the first study to comprehensively illustrate the link between endometriosis and
gastrointestinal disorders which both affect a large proportion of people worldwide, using
large-scale multi-dimensional data including clinical, genetic, and pharmaceutical datasets.
We confirmed both a bidirectional epidemiological association and a shared genetic basis of
endometriosis with each of the three GI traits (IBS, GORD, and PUD). Evidence of
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19
medication use further supported the co-occurrence and shared disease aetiology of these
conditions but also highlights the potential for drug repositioning and caution around drug
contraindications in clinical practice.
Evidence for comorbid relationships
Endometriosis and IBS, two of the leading causes of chronic pelvic pain, are often
misdiagnosed in clinics due to non-specific symptoms
54. Several epidemiological studies
indicated women with endometriosis have an increased risk of a diagnosis of IBS 55 56. For
example, one nationwide UK case-control study demonstrated women diagnosed with
endometriosis were two and half times more likely to receive a new diagnosis of IBS when
compared with controls (OR = 2.5, 95% CI 2.2 to 2.8)
54. Few studies have investigated if
women with IBS are more likely to be diagnosed with endometriosis. Our analysis using
diagnoses reported in UKB supported the epidemiological association between endometriosis
and IBS. We identified a bidirectional association between endometriosis and all four
gastrointestinal disorders. Of those associations, endometriosis showed a stronger
relationship with IBS and GORD when compared with PUD and IBD. Therefore, in addition
to the clinically reported shared symptomology, this study provides further evidence of a
complex phenotypic association between endometriosis and gastrointestinal disorders.
Evidence of shared genetic aetiology and potential drug candidates
A previous study investigating the shared genetic basis between endometriosis and
depression has implicated gastric mucosa abnormalities in this casual pathway
29. Adewuyi et
al. reported a strong genetic correlation between endometriosis and GORD using two early
published GWAS summary datasets in the UKB29 however, other common GI disorders such
as IBS were not measured. Consistent with previous reports, our study, which included one
third more individuals from the UKB, also identified a significant genetic correlation between
endometriosis and GORD. In addition, our study identified novel genetic correlations
between endometriosis and IBS and PUD, but not for IBD. This is in line with known genetic
differences between IBD and the other three GI disorders identified using both partitioned
SNP-based heritability analysis and bivariate LDSC analysis
30. When using a more powerful
phenotype GPM, a combination of diagnosis of PUD and/or GORD as two acid-related
diseases that share treatment therapy in clinical practice, we found a stronger genetic
correlation with endometriosis. Many observational studies are subject to the confounding
effects of environment and lifestyle factors. In contrast, our analysis based on genotype-level
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data are unlikely to suffer from such methodological bias. Therefore, the estimated one-fifth
of the genetic contribution to endometriosis, which is shared with the genetic contribution to
IBS or GPM, may partly explain the significant comorbid relationship between the diseases.
In addition to a genetic correlation between endometriosis and IBS and GPM we identified a
bidirectional causal relationship between genetic risk of IBS and endometriosis and a
unidirectional causal relationship between GPM and endometriosis. The MR framework is a
powerful and cost-effective method for inferring causality due to its advantage that genetic
alleles are determined at conception, so that MR results are free from potential environmental
confounders (eg. medication usage) and bias which are often found in observational studies
57.
In this study, the identification of bidirectional causality (vertical pleiotropy) between
endometriosis and IBS suggests that the increased risks of endometriosis in IBS patients and
vice versa are, in part, mediated by the genetic liability to the other disease. The estimated
causal relationship between traits can also be affected by violations of MR assumptions
which occur when genetic variants are also associated with confounding factors or influence
the outcome through a confounding factor. A strength of our study is that we conducted the
mtCOJO conditional analysis which takes into account the correlation between traits given
the previously reported complexity among GI disorders
30, and the significant bidirectional
relationship between IBS and GPM in this study using both standard and reverse MR analysis
(Figure 3). The MR results remained similar after conditioning on GPM, indicating that the
bidirectional causal relationship between endometriosis and IBS at the genetic level were not
driven by their relationship with GPM.
Moreover, the subsequent identification of shared genomic loci using cross-trait meta-
analysis and colocalization approaches further provides clues as to the possible biological
mechanisms and specific pathways driving the causal relationships between the different
gastrointestinal disorders and endometriosis. For example, both TACSTD2 on chromosome 1
and FN1 on chromosome 2 shared by endometriosis and IBS are involved in various cellular
processes including cell proliferation, motility, invasion and migration
58,59. TACSTD2 is a
novel region that has not been implicated in IBS or endometriosis GWAS analyses
previously. The intracellular calcium signal transducer TACSTD2 was reported to be
overexpressed in endometrioid-type endometrial carcinoma and gastrointestinal cancers
60 61.
Another shared locus FN1 has been previously linked to the risk of endometriosis at a
genome-wide significance threshold of P < 5e-8 in both the latest GWAS study62 and a recent
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Greek population-based GWAS study 63. Despite FN1 not having been identified in IBS
GWAS meta-analyses, there are studies demonstrating a significant down-regulation of
expression of FN1 in IBS patients compared with controls, which may be responsible for the
increased mucosal permeability and visceral hypersensitivity of IBS through its mediation in
barrier dysfunction
64 65 . Functional annotations in this study also suggest a possible
pathogenic effect of these two regions, providing evidence that the lead SNP (rs6661808) at
the TASCTD2 locus is an eQTL in both blood and digestive tissues, while the lead SNP in the
FN1 region was within a predicted enhancer or promoter in digestive tissues and had a
CADD score over 12.7.
Three genomic loci shared by endometriosis and GPM were identified in this study using
both cross-trait meta-analysis and GWAS-PW, including ETAA1 on chromosome 2, HOXC
and RERG on chromosome 12. ETAA1 is an activator of ATR kinase which plays a key role
in protecting the genome against both intrinsic replication problems and substantial extrinsic
DNA damage
66, while the other two regions are closely associated with receptor signalling
and estrogen metabolism 67-70. The ETAA1 locus has been previously reported to be
associated with risk of both traits at genome-wide significance level 30 62 . Functional
annotation of independent SNPs in the HOXC region suggest that these variants impact
regulatory elements in both digestive and reproductive tissues and regulate expression of
several HOXC genes (HOXC4, HOXC5, HOXC6, HOXC8, HOXC9, HOXC10, HOXC-AS1) .
Altered expression of the HOXC cluster has been found in ectopic and eutopic tissues from
endometriosis patients vs. control
71-73, as well as in gastrointestinal disorders such as
ulcerative colitis, colorectal cancer and gastric cancer 74-77 . Even though RERG, and nearby
PTPRO, were not implicated in any GWAS studies of the separate traits, P-values for the lead
SNP were close to genome-wide significance ( PEndometriosis = 9.24E-06, PGPM = 8.80E-07)
suggesting the increased power from combining the traits was able to identify a novel risk
locus for both diseases. Moreover, experiments have shown that the upregulated ER β
expression and attenuated ERα expression in endometriosis lesions indicated that insufficient
expression of PTPRO may be involved in the progression of endometriosis 78. Research
findings on the association between estrogen and GORD and PUD have been contradictory79-
84, evidenced by some studies reporting a higher prevalence rate of GORD and PUD in men
compared with women before the age of menopause 81 85 and others reporting a positive
correlation between GORD symptoms and postmenopausal hormone therapy 86. In this study,
we provided additional evidence that this estrogen related loci on chromosome 12 may be
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involved in the progression of both endometriosis and GORD and PUD however, the
underlying molecular mechanism remains unclear.
In addition to the five highlighted regions shared by endometriosis and IBS/GPM, another six
regions (SEMA3F, SPAG16, HIST1H2BC, RAB5B, CCKBR and PDE4B) identified by cross-
trait meta-analysis and at least two functional annotation analyses also implicate potential
pathways that are associated with the two traits. With the exception of HIST1H2BC and
SPAG16 loci, the remaining four loci have been implicated in previous GORD or PUD
GWAS studies
30 87 . The lead SNPs in these six regions are all nominally significantly
associated with endometriosis and have not been linked to endometriosis in previous GWAS
studies. They may represent novel target genes or pathways involved in endometriosis
progression. For example, HIST1H2BC, SPAG16, SEMA3F and RAB5B themselves or genes
nearby those regions may be associated with endometriosis by either being the estradiol
responsive gene, or related to steroid hormone treatment and metabolism, and further regulate
the proliferation of endometrial stromal cells
88-95.
Evidence for the potential of drug repositioning in clinics
To verify whether the 218 candidate genes identified have any implications in the clinic, we
searched the online drug target databases and identified CCKBR and PDE4B with their
encoded proteins as drug targets. While the former is currently used for treatment of PUD
and GORD, the latter has been clinically trialled for both IBS and endometriosis. PDE4B is
mainly present in immune and epithelial cells and has a role modulating inflammation and
epithelial integrity
96 while CCKBR encodes a G-protein coupled receptor for gastrin and
cholecystokinin. Even though CCKBR has not been targeted for treatment of endometriosis,
a recent study has demonstrated that reduction of gastrin is associated with inactivation of
CCKBR/ERK/P65 signalling in estrogen receptor positive breast cancer cells, and lower
expression of gastrin and CCKBR was correlated to worse prognosis in breast cancer
97.
Therefore, the involvement of gastrin and CCKBR in estrogen metabolism may implicate this
gene as a potential drug target for endometriosis. Moreover, considering the low quality of
current evidence for Pentoxifylline which was used to treat endometriosis by targeting
PDE4B encoded protein
53, this study provides more evidence and novel insight for the further
investigation of PDE4B for the purpose of treating both endometriosis and GI disorders.
Evidence for associations with medication usage
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In the present study, our ability to link diagnoses with drug usage further revealed overlap in
medication use between endometriosis and GI disorders, providing novel insights for disease
aetiology and management in clinics. The identification of a higher use of drugs for IBS,
GORD and PUD in women diagnosed with endometriosis as well as the higher use of
hormone therapies in women diagnosed with IBS, GORD and PUD but not for IBD, strongly
supports the coexistence and potential manifestations of underlying pathophysiological and
genetic correlations between the diseases. Whilst not unexpected, the frequent use of
NSAIDs by women with endometriosis highlights potential confounding from
contraindicated therapies as the frequent use of NSAIDs during endometriosis treatment is a
well-known risk factor for PUD by destroying the mucus layer in the digestive tract
15.
However, the genetic correlation between the diseases suggests the relationship is not driven
by a consequence of medical therapies alone. Additionally, we also identified that the
frequency of other treatments for gastrointestinal disorders such as omeprazole and laxatives
was also significantly higher in women with endometriosis than women without. One of the
gene targets of omeprazole, ATP4A, is a member of the ATPase family responsible for
oxidative phosphorylation. Evidence from the cross-trait meta-analysis and functional
annotation methods highlighted ATP6V0E1 and ATP6V0E2 as potential target genes involved
in both endometriosis and GPM. ATP6V0E1 and ATP6V0E2 also belong to ATPase family
suggesting targeting this pathway may have effects on both GI disorders and endometriosis.
Other evidence towards the potential of drug repositioning includes that visceral sensitivity
and chronic low-grade inflammatory state have been key characteristics in both IBS and
endometriosis
98 and therapies targeted at relieving pain in IBS can also relieve pain during
menstruation99. Similarly, a New Zealand based study reported that women with IBS and
concurrent endometriosis had a significantly higher response rate to a low FODMAP diet,
one therapy for IBS, than those IBS patients with no known endometriosis100.
Clinical implications
At least three types of clinical implication can be drawn from this study. First, regarding
diagnosis for both endometriosis and GI disorders, shared aetiology suggests joint or
alternative diagnoses should considered for patients presenting symptoms related to either
disease. Second, evidence from medication use suggest caution around contraindications for
some drugs, as NASIDs, often used for endometriosis, are a well-known risk factor for PUD.
Therefore, it may be worthwhile for clinicians to consider potential contraindications when
prescribing NASIDs for female patients presenting with symptoms shared between the
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24
diseases such as abnormal pain, bloating or constipation, etc. Third, support for PDE4B as a
shared drug target for the treatment of both IBS and endometriosis, suggest comorbidity of
endometriosis and IBS should be considered in the design and recruitment for clinical trials.
Strengths and limitations
One major strength of the current study is the use of large-scale population data, genetic and
medication usage data for both gastrointestinal disorders and endometriosis, to
comprehensively illustrate the association between these two disorders. Integrating these
datasets provides more convincing evidence for the association of diseases, as well as
important clinical implications. Despite these interesting findings, we acknowledge serval
limitations. First, endometriosis is a highly heterogeneous condition with variation in lesion
location and grade
101. Similarly, the four GI phenotypes derived from UKB may also
introduce further heterogeneity 30. It is not clear if certain subtypes of endometriosis share
more genetic risk factors with digestive disorders. Therefore, the associations identified in
this study should be validated in larger endometriosis datasets with more detailed phenotype
information when these are available. Second, as mentioned in Wu et al.
30, the existence of
co-reporting of some diagnoses, including two gastrointestinal disorders, may bias the
association with specific digestive disorders. However, the sensitivity tests carried out in the
study, which excluded those individuals with more than one diagnosis, demonstrated that the
co-existence did not impact conclusions. We concluded that GWAS summary statistics for
IBS and GPM phenotypes are robust, and identified different genetic risk factors shared
between endometriosis and IBS and GPM. Third, compared with the other four phenotypes,
there are fewer IBD cases available in UKB, which may limit the power for both genetic and
epidemiological analyses. Results for the IBD GWAS were highly consistent with previously
published GWAS
30 suggesting results in this study are robust.
Conclusions
This study comprehensively assesses the observational, genetic, and pharmaceutical usage
associations between endometriosis and gastrointestinal disorders using various statistical
approaches and multidimensional large-scale datasets. We provide strong evidence for the
shared aetiology of endometriosis and digestive disorders and highlight target genes and
pathways contributing to the shared aetiology. The results suggest potential targets for
treatment, considerations for disease management and caution around contraindications for
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25
some drugs. The clinical implications could facilitate better clinical outcomes for women
with both endometriosis and gastrointestinal diseases.
Data Availability
This study includes no data deposited in external repositories.
Author Contributions
F.Y, S.M and G.W.M designed the study with input from the other authors. G.W.M, S.M,
Y.W, R.H and G.D.M coordinated data collection, quality control of data, data management
and analysis of the original datasets. F.Y, S.M, R.H and Y.W ran additional quality control
and filtering of datasets. Data analysis was performed by F.Y which was interpreted by all
authors. F.Y, S.M, and G.W.M drafted the report with input from all other authors. The final
manuscript has been critically revised and approved by all authors.
Funding
This work was supported by the National Health and Medical Research Council of Australia
[Project Grants GNT1147846, GNT1105321 and GNT1049472, Investigator Grant 1177194
to G.W.M and Medical Research Future Fund Research Grant MRF1199785 to G.D.M and
S.M]. For funding details of the endometriosis meta-analysis please see Sapkota et al.,
(2017).
Acknowledgements
This research has been conducted using the UK Biobank Resource under Application
Number 54861 and 12505. Summary statistics from the endometriosis GWAS used in this
study contain data from 23andMe. We would like to thank the research participants and
employees of 23andMe, Inc. for making this work possible.
The research on which this paper is partly based was conducted as part of the Australian
Longitudinal Study on Women’s Health by the University of Queensland and The University
of Newcastle. We are grateful to the Australian Government Department of Health and Aged
Care for funding and to the women who provided the survey data.
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26
We acknowledge the Department of Health and Medicare Australia for providing MBS and
PBS data and the Australian Institute of Health and Welfare (AIHW) as the integrating
authority. We also acknowledge the following:
• Centre for Health Record Linkage (CHeReL), NSW Ministry of Health and ACT
Health, for the NSW Admitted Patients Data Collection, and the ACT Admitted
Patient Care Data Collections.
• Queensland Health, including the Statistical Services Branch, for the Qld Hospital
Admitted Patient Data Collection.
• Department of Health Western Australia, including the Data Linkage Branch, and the
WA Hospital Morbidity Data Collection.
• SA NT Datalink, and SA Department for Health and Wellbeing and Northern
Territory Department of Health, for the SA Public Hospital Separations and NT
Public Hospital Inpatient Activity Data Collections.
• Tasmanian Data Linkage Unit, and the Department of Health, Tasmania, for the
Public Hospital Admitted Patient Episodes Data Collection.
• Victorian Department of Health as the source of the Victorian Admitted Episodes
Dataset, and the Centre for Victorian Data Linkage (Victorian Department of Health)
for the provision of data linkage.
The International Endometriosis Genetics Consortium (IEGC)
The following are members of the International Endogene Consortium (IEC): Yadav Sapkota,
Valgerdur Steinthorsdottir, Andrew P. Morris, Amelie Fassbender, Nilufer Rahmioglu,
Immaculata De Vivo, Julie E. Buring, Futao Zhang, Todd L. Edwards, Sarah Jones, Dorien O,
Daniëlle Peterse, Kathryn M. Rexrode, Paul M. Ridker, Andrew J. Schork, Stuart MacGregor,
Nicholas G. Martin, Christian M. Becker, Sosuke Adachi, Kosuke Yoshihara, Takayuki
Enomoto, Atsushi Takahashi, Yoichiro Kamatani, Koichi Matsuda, Michiaki Kubo, Gudmar
Thorleifsson, Reynir T. Geirsson, Unnur Thorsteinsdottir, Leanne M. Wallace, iPSYCH-SSI-
Broad Groupw, Jian Yang, Digna R. Velez Edwards, Mette Nyegaard, Siew-Kee Low, Krina
T. Zondervan, Stacey A. Missmer, Thomas D’Hooghe, Grant W. Montgomery, Daniel I.
Chasman, Kari Stefansson, Joyce Y. Tung, and Dale R. Nyholt
Conflict of interest
The authors declare that they have no conflict of interest.
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Figure 1. Competitive comorbidity analysis for endometriosis and four gastrointestinal
disorders in unrelated female European individuals. The Venn diagram shows the number of
individuals with diagnosis of gastrointestinal disorders. At the bottom of Venn diagram is the
proportion of endometriosis cases (n=5,392) in each of the digestive diseases after removing
the overlapped individuals for these four diseases, ranking from highest proportion to the
least. Paired comparison was conducted using a two-proportion Z test, with the
corresponding P-value under each comparison.
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Figure 2. Results of genetic correlation between endometriosis and a) gastrointestinal
disorders (irritable bowel syndrome (IBS), peptic ulcer disease (PUD), gastro-oesophageal
reflux disease (GORD), GORD/PUD Medicated (GPM) inflammatory bowel disease (IBD))
and b) separate male and female IBS GWAS datasets. The x-axis indicates the value of
genetic correlation, and the error bar indicates its 95% confidence interval. All red lines
represent the results after constraining the heritability intercept to one considering no sample
overlap for each comparison.
Figure 3. Simplified causal relationship identified by GSMR (Generalised Summary-data-
based Mendelian Randomisation). Different arrow colour represents the specific direction of
causal relationship.
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Figure 4. GSMR results for gastrointestinal disorders and endometriosis. The first row
represents results using original GWAS data while the second row used the GWAS data
conditioned on GPM or IBS. GWAS threshold for SNP instrument was set as P < 5e-6. bxy
is the effect of exposure on outcome free of confounding from non-genetic factors and can be
approximately interpreted as log(odds ratio).
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30
Figure 5 . Mirror plot of first two GWAS-PW regions containing same causal variants for
endometriosis and GPM. The left is the genomic locus near ETAA1 on chromosome 2, while
the right is the locus around HOXC4 on chromosome 12.
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31
Table 1. Comorbid relationship between endometriosis and gastrointestinal disorders (GI) in
unrelated European women in the UK Biobank. Association between diseases was tested
using the fisher’s exact test.
GORD
(n=22,383)
IBS
(n=16,330)
PUD
(n=5,208)
IBD
(n=2,708)
Endo vs GI 1.40 (1.30-1.50)
P=3.54e-18
2.01 (1.86-2.15)
P=3.90e-68
1.22 (1.05-1.42)
P=0.01
1.25 (1.01-1.53)
P=0.04
GI vs Endo 1.45 (1.35-1.57)
P=5.94e-22
2.13 (1.98-2.30)
P=7.14e-79
1.22 (1.05-1.42)
P=0.01
1.24 (1.0-1.53)
P=0.04
Note: GORD (Gastro-oesophageal Reflux Disease), IBS (Irritable Bowel Disease), PUD (Peptic Ulcer
Disease) and IBD (Inflammatory bowel disease), Endo (Endometriosis). The number in the bracket below
each disease represent the number of women diagnosed with this disease. There are a total number of 5,392
women diagnosed with endometriosis. Fisher’s exact results are represented by OR, 95% CI values within
brackets and P-value.
Table 2. Summary of GSMR results for endometriosis (Endo), irritable bowel syndrome
(IBS) and GORD/PUD Medicated (GPM) using different SNP instrument GWAS p-value
thresholds.
Exposure Outcome Odds Ratio
(95% CI) SE P-value No. SNP
Instruments
SNP instrument GWAS p-value<5e-8
GPM Endo 1.56 (1.35, 1.76) 0.104 2.47e-05 20
GPM_IBS Endo_IBS 1.22 (1.00, 1.44) 0.112 0.073 17
Endo IBS 1.07 (1.01, 1.13) 0.031 0.042 10
Endo_GPM IBS_GPM 1.09 (1.03, 1.14) 0.028 0.003 12
SNP instrument GWAS p-value<5e-6
GPM Endo 1.18 (1.08, 1.27) 0.049 0.001 132
GPM_IBS Endo _IBS 1.16 (1.05, 1.27) 0.055 0.008 103
Endo IBS 1.04 (1.01, 1.07) 0.016 0.012 54
Endo_GPM IBS _GPM 1.03 (1.00, 1.06) 0.016 0.050 48
IBS Endo 1.15 (1.03, 1.28) 0.066 0.028 30
IBS_GPM Endo _GPM 1.23 (1.09, 1.38) 0.074 0.004 25
_IBS = primary trait conditioned on IBS using mtCOJO
_GPM = primary trait conditioned on GPM using mtCOJO
95% CI = 95% confidence interval
Table 3. Significant SNP loci identified by endometriosis (Endo), irritable bowel syndrome
(IBS) and GORD/PUD Medicated (GPM) cross-trait meta-analysis.
Beta P.value
rsID Nearest gene Chr BP Endo GI Endo GI Meta
Endometriosis & IBS
rs12407439 LINCO1635 1 22347396 -0.14 -0.03 6.57E-08 0.025 3.98E-08
rs6661808 TACSTD2 1 59089534 -0.08 -0.07 0.002 1.20E-06 7.67E-09
rs1250244 FN1 2 216297796 0.10 0.03 8.73E-08 0.001 9.09E-10
Endometriosis & GPM
rs7515106 WNT4 1 22473410 -0.10 0.01 1.89E-09 0.045 5.93E-09
rs7547294 PDE4B 1 66351735 -0.03 -0.03 0.035 2.40E-07 2.53E-08
rs11675830 ETAA1 2 67776860 0.07 0.02 2.57E-06 9.60E-06 5.41E-10
rs4260227 ETAA1 2 67843537 0.07 0.04 2.21E-05 2.10E-09 1.20E-12
rs2861694 ETAA1 2 67845739 0.07 0.04 7.77E-07 1.00E-10 1.05E-15
rs13031614 SPAG16 2 215068514 0.03 0.03 0.022 4.20E-07 3.06E-08
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rs7613360 CAMKV 3 49916710 -0.05 -0.03 0.001 7.40E-07 7.61E-09
rs2008877 SEMA3F-AS1 3 50162291 0.04 0.03 0.002 6.50E-08 8.00E-10
rs2526388 SEMA3F-AS1 3 50174886 0.03 0.03 0.046 1.70E-07 2.20E-08
rs1046953 SEMA3F 3 50197097 0.04 0.03 0.003 3.00E-08 5.15E-10
rs12631337 SEMA3F 3 50198537 0.05 0.03 0.001 1.50E-10 7.38E-13
rs71557318 HIST1H2BC 6 26118570 0.05 -0.03 0.024 1.30E-09 1.03E-09
rs10811669 CDKN2B-
AS1
9 22172893 -0.08 -0.01 1.68E-08 0.03 2.04E-08
rs10500661 CCKBR 11 6273744 0.05 -0.04 0.006 9.70E-12 2.63E-12
rs1479406 RERG 12 15387543 -0.06 -0.03 9.24E-06 8.80E-07 1.06E-10
rs11056461 PTPRO 12 15558466 -0.08 -0.02 2.12E-06 0.00048 2.66E-08
rs3803042 MIR196A2 12 54387947 -0.06 -0.02 4.54E-06 0.0001 1.65E-08
rs11170785 HOXC8 12 54407290 -0.06 -0.02 3.46E-05 8.20E-06 3.25E-09
rs736825 HOXC4/5/6 12 54417576 -0.08 -0.03 1.98E-05 3.00E-06 1.53E-09
rs773111 RAB5B 12 56375740 0.03 0.03 0.028 8.10E-08 6.80E-09
rs9807058 LINC01982 17 50338523 -0.04 -0.03 0.04997 1.50E-07 2.18E-08
Table 4. Genomic regions that contain a same causal variant jointly influencing
endometriosis with irritable bowel syndrome (IBS) and GORD/PUD Medicated (GPM)
respectively.
Risk loci (P < 5e-8)
Chr Start End PPA-3 Nearest gene Endo GI Meta
Endometriosis & IBS
2 215573795 217715180 0.818 FN1 Yes No Yes
1 58865399 59889341 0.766 OMA1/ TACSTD2/MYSM1 No No Yes
6 30798252 31565648 0.532 HLA-C No No No
Endometriosis & GPM
2 67227143 68009259 0.983 ETAA1/ LINCO1812 Yes Yes Yes
12 53039757 54777633 0.932 HOXC4/ HOXC-AS1 No No Yes
12 15248516 16309290 0.755 RERG/PTPRO No No Yes
3 47729665 49314960 0.628 DALRD3/KLHDC8B/P4HTM/RBM6 No No No
1 76729016 79660928 0.618 FUBP1/ADGRL4 No No No
10 19717815 22772115 0.551 CASC10 No No No
Table 5. Functionally mapped genes for significant risk loci identified in the cross-trait meta-
analysis of endometriosis and gastrointestinal disorders.
Chr Gene Closest gene
to lead SNP
posMap
MaxCADD
eQTL MAGMA SMR EpiMap
Endometriosis & IBS
1 MYSM1 12.9 Yes Yes
1 OMA1 Yes
1 TACSTD2 Yes Yes
2 FN1 Yes 22 Yes Yes
Endometriosis & GPM
1 PDE4B Yes Yes
2 SPAG16 Yes 17.74 Yes
2 ETAA1 Yes Yes
3 CAMKV Yes 18.51 Yes Yes
3 MST1R 18.51 Yes Yes
3 CTD-2330K9.3 13.15 Yes Yes
3 MON1A 13.15 Yes Yes
3 RBM6 17.77 Yes Yes Yes
3 RBM5 18.47 Yes Yes Yes
3 SEMA3F Yes 19.09 Yes Yes Yes
3 CYB561D2 Yes Yes
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3 RNF123 Yes Yes
3 HYAL3 Yes Yes
3 NAT6 Yes Yes
6 HIST1H3B 13.84 Yes
6 HFE 14.95 Yes
6 HIST1H2BC 14.07 Yes Yes
6 HIST1H1T Yes 14.95
11 FAM160A2 12.74 Yes
11 CNGA4 11.83 Yes Yes
11 C11orf42 12.74 Yes
12 RERG Yes 17.74 Yes Yes Yes
12 PTPRO Yes 17.74 Yes Yes
12 HOXC6 Yes 21.7 Yes Yes Yes
12 HOXC9 21.7 Yes Yes Yes
12 HOXC8 Yes 19.36 Yes Yes Yes
12 HOXC4 Yes 22 Yes Yes Yes
12 HOXC5 Yes 17.09 Yes Yes
12 RAB5B Yes 21.2 Yes Yes
12 SUOX 21.2 Yes Yes
12 RP11-834C11.12 21.7 Yes
12 HOXC10 21.7 Yes
Table 6. Existing drug targets for endometriosis and gastrointestinal disorders.
Human
Target
Drug Phase Type Mechanism
of Action
Indication Source
CCKBR PROGLUMIDE Phase IV Small
molecule
Cholecystokin
in receptor
GORD ATC:A02BX06
CCKBR NETAZEPIDE Phase I Protein Cholecystokin
in receptor
PUD NCT01298999
NCT02597712
PDE4B PENTOXIFYLLINE Phase
III/IV
Small
molecule
3',5'-cyclic
phosphodieste
rase inhibitor
Endo/ IBS NCT00632697
NCT01542268
Note: GORD (Gastro-oesophageal Reflux Disease); IBS (Irritable Bowel Disease); PUD
(Peptic Ulcer Disease); Endo (Endometriosis)
Table 7. Comparison of medication usage in UKB unrelated European women with and
without a diagnosis of endometriosis or gastrointestinal disorders.
Medication Diagnoses Controls P.Value BF.P.value Description
Med No Med No
Endometriosis
Omeprazole 540 4852 5521 86823 1.49E-28 1.73E-25 GORD/PUD Treatment
Laxatives 353 5039 3749 88595 1.52E-16 1.76E-13 Constipation Treatment
Lansoprazole 266 5126 2881 89463 6.96E-12 8.05E-09 GORD/PUD treatment
Mebeverine 73 5319 558 91786 3.84E-09 4.45E-06 IBS Treatment
Ranitidine 163 5229 1765 90579 1.06E-07 0.0001 GORD/PUD treatment
Senna 30 5362 176 92168 1.25E-06 0.0015 Constipation Treatment
Esomeprazole 33 5359 242 92102 2.88E-05 0.0334 GORD/PUD treatment
Paracetamol 1914 3478 25462 66882 8.16E-35 9.45E-32 Painkiller
Premarin 132 5260 595 91749 1.49E-33 1.73E-30 Hormone Therapy
Irritable Bowel Disease
Vagifem 200 15679 758 126274 2.29E-18 2.91E-15 Hormone Therapy
Premarin 185 15694 891 126141 2.31E-09 2.94E-06 Hormone Therapy
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Estraderm 80 15799 291 126741 6.54E-09 8.31E-06 Hormone Therapy
Ovestin 51 15828 151 126881 1.59E-08 2.03E-05 Hormone Therapy
Estradiol product 99 15780 430 126602 2.33E-07 0.0003 Hormone Therapy
Evorel 25 patch 82 15797 346 126686 9.59E-07 0.0012 Hormone Therapy
Conjugated oestrogens 18 15861 29 127003 1.22E-06 0.0016 Hormone Therapy
Climaval 1mg tablet 65 15814 258 126774 2.08E-06 0.0026 Hormone Therapy
Estriol product 37 15842 114 126918 3.17E-06 0.0040 Hormone Therapy
Omeprazole 2242 13637 4209 122823 0 0 GI disorder treatment
Gastro-oesophageal Reflux Disease
Estradiol product 134 22248 317 89211 8.50E-07 0.0010 Hormone Therapy
Estraderm 94 22288 217 89311 1.81E-05 0.0207 Hormone Therapy
Premarin 233 22149 672 88856 2.44E-05 0.0279 Hormone Therapy
Lansoprazole 3705 18677 1640 87888 0 0 GI disorder treatment
Omeprazole 6948 15434 3335 86193 0 0 GI disorder treatment
Ranitidine 1596 20786 1081 88447 0 0 GI disorder treatment
Gaviscon liquid 714 21668 237 89291 1.01E-295 1.15E-292 GI disorder treatment
Paracetamol 7900 14482 21440 68088 1.92E-249 2.20E-246 Painkiller
Esomeprazole 434 21948 99 89429 3.35E-205 3.83E-202 GI disorder treatment
Peptic Ulcer Disease
Estraderm 35 5173 205 72707 1.26E-05 0.0135 Hormone Therapy
Omeprazole 1375 3833 2821 70091 0 0 GI disorder treatment
Lansoprazole 711 4497 1426 71486 2.34E-306 2.49E-303 GI disorder treatment
Ranitidine 351 4857 942 71970 3.67E-118 3.91E-115 GI disorder treatment
Paracetamol 1963 3245 17305 55607 1.74E-103 1.86E-100 Painkiller
Esomeprazole 107 5101 88 72824 1.62E-72 1.73E-69 GI disorder treatment
Tramadol 217 4991 665 72247 1.10E-64 1.17E-61 Opioid
Co-codamol 348 4860 1608 71304 4.27E-64 4.55E-61 Opioid
Amitriptyline 326 4882 1477 71435 1.03E-61 1.10E-58 Antidepressants
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