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Record W4409656470 · doi:10.1093/humrep/deaf062

The phenotypic and genetic association between endometriosis and immunological diseases

2025· article· en· W4409656470 on OpenAlexaff
Nina Shigesi, Holly R. Harris, Hai Fang, Anne Ndungu, Matthew R. Lincoln, Chris Cotsapas, Julian C. Knight, Stacey A. Missmer, Andrew P. Morris, Christian M. Becker, Nilüfer Rahmioğlu, Krina T. Zondervan

Bibliographic record

VenueHuman Reproduction · 2025
Typearticle
Languageen
FieldMedicine
TopicEndometriosis Research and Treatment
Canadian institutionsUniversity of Toronto
FundersVersus ArthritisNational Natural Science Foundation of China
KeywordsEndometriosisBiobankMedicineRheumatoid arthritisGenome-wide association studyDiseaseImmunologyInternal medicineGenotypeBiologyBioinformaticsGeneticsSingle-nucleotide polymorphism

Abstract

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STUDY QUESTION: Is there an increased risk of immunological diseases among endometriosis patients, and does a shared genetic basis contribute to this risk? SUMMARY ANSWER: 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. WHAT IS KNOWN ALREADY: 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. STUDY DESIGN, SIZE, DURATION: 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. PARTICIPANTS/MATERIALS, SETTING, METHODS: 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. MAIN RESULTS AND THE ROLE OF CHANCE: 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). LIMITATIONS, REASONS FOR CAUTION: 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. WIDER IMPLICATIONS OF THE FINDINGS: 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. STUDY FUNDING/COMPETING INTEREST(S): 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. TRIAL REGISTRATION NUMBER: N/A.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.317
Threshold uncertainty score0.779

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.315
Teacher spread0.293 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations17
Published2025
Admission routes1
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