The phenotypic and genetic association between endometriosis and immunological diseases

Is there an increased risk of immunological diseases among endometriosis patients, and does a shared genetic basis contribute to this risk?

Endometriosis patients show a significantly increased risk of autoimmune, autoinflammatory, and mixed-pattern diseases, including rheumatoid arthritis, multiple sclerosis, coeliac disease, osteoarthritis, and psoriasis, with genetic correlations between endometriosis and osteoarthritis, rheumatoid arthritis, and multiple sclerosis, and a potential causal link to rheumatoid arthritis.

The epidemiological evidence for an increased risk of immunological diseases among women with endometriosis is limited in scope and has varied in robustness due to the opportunity for biases. The presence of a biological basis for increased comorbidity across immunological conditions has not been investigated. Here we investigate the phenotypic and genetic association between endometriosis and 31 immune conditions in the UK Biobank.

Phenotypic analyses between endometriosis and immune conditions (17 classical autoimmune, 10 autoinflammatory, and 4 mixed-pattern diseases) were conducted using two approaches (8223 endometriosis, 64 620 immunological disease cases): (i) retrospective cohort study design to incorporate temporality between diagnoses and (ii) cross-sectional analysis for simple association. Genome-wide association studies (GWAS) and meta-analyses for those immune conditions that showed phenotypic association with endometriosis (1493-77 052 cases) were conducted.

Comprehensive phenotypic association analyses were conducted in females in the UK Biobank. GWAS for immunological conditions were conducted in females-only and sex-combined study populations in UK Biobank and meta-analysed with existing largest available GWAS results. Genetic correlation and Mendelian randomization (MR) analyses were conducted to investigate potential causal relationships. Those immune conditions with significant genetic correlation with endometriosis were included in multi-trait analysis of GWAS to boost discovery of novel and shared genetic variants. These shared variants were functionally annotated to identify affected genes utilizing expression quantitative trait loci (eQTL) data from GTEx and eQTLGen databases. Biological pathway enrichment analysis was conducted to identify shared underlying biological pathways.

In both retrospective cohort and cross-sectional analyses, endometriosis patients were at significantly increased (30-80%) risk of classical autoimmune (rheumatoid arthritis, multiple sclerosis, coeliac disease), autoinflammatory (osteoarthritis), and mixed-pattern (psoriasis) diseases. Osteoarthritis (genetic correlation (rg) = 0.28, P = 3.25 × 10-15), rheumatoid arthritis (rg = 0.27, P = 1.5 × 10-5) and multiple sclerosis (rg = 0.09, P = 4.00 × 10-3) were significantly genetically correlated with endometriosis. MR analysis suggested a causal association between endometriosis and rheumatoid arthritis (OR = 1.16, 95% CI = 1.02-1.33). eQTL analyses highlighted genes affected by shared risk variants, enriched for seven pathways across all four conditions, with three genetic loci shared between endometriosis and osteoarthritis (BMPR2/2q33.1, BSN/3p21.31, MLLT10/10p12.31) and one with rheumatoid arthritis (XKR6/8p23.1).

We conducted the first female-specific GWAS analyses for immune conditions. Given the novelty of these analyses, the sample sizes from which results were derived were limited compared to sex-combined GWAS meta-analyses, which limited the power to use female-specific summary statistics to uncover the shared genetic basis with endometriosis in follow-up analyses. Secondly, the 39 genome-wide significant endometriosis-associated variants used as instrumental variables in the MR analysis explained approximately 5% of disease variation, which may account for the nominal or non-significant MR results.

Endometriosis patients have a moderately increased risk for osteoarthritis, rheumatoid arthritis, and to a lesser extent, multiple sclerosis, due to underlying shared biological mechanisms. Clinical implications primarily involve the need for increased awareness and vigilance. The shared genetic basis opens up opportunities for developing new treatments or repurposing therapies across these conditions.

We thank all the UK Biobank and 23andMe participants. Part of this research was conducted using the UK Biobank Resource under Application Number 9637. N.R. was supported by a grant from the Wellbeing of Women UK (RG2031) and the EU Horizon 2020 funded project FEMaLe (101017562). A.P.M. was supported in part by Versus Arthritis (grant 21754). H.F. was supported by the National Natural Science Foundation of China (grant 32170663). N.R., S.A.M., and K.T.Z. were supported in part by a grant from CDMRP DoD PRMRP (W81XWH-20-PRMRP-IIRA). K.T.Z. and C.M.B. reported grants in 3 years prior, outside the submitted work, from Bayer AG, AbbVie Inc., Volition Rx, MDNA Life Sciences, PrecisionLife Ltd., and Roche Diagnostics Inc. S.A.M. reports grants in the 3 years prior, outside this submitted work, from AbbVie Inc. N.R. is a consultant for Endogene.bio, outside this submitted work. The other authors have no conflicts of interest to declare.

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