{"paper_id":"c9678a51-fb9d-4156-9ae4-6176723292d9","body_text":"-\n6\n/\n%\n\u0001\n6\n/\n*\n7\n&\n3\n4\n*\n5\n:\n1\n0\n\u0001\n#\nP\nY\n\u0001\n\u0012\n\u0012\n\u0018\n\u0013\n\u0013\n\u0012\n\u0001\n\u0011\n\u0011\n\u0001\n-\nV\nO\nE\n\f\n\u0015\n\u0017\n\u0001\n\u0015\n\u0017\n\u000e\n\u0013\n\u0013\n\u0013\n\u0001\n\u0011\n\u0011\n\u0001\n\u0011\n\u0011\nBiomarkers and gastrointestinal symptoms in endometriosis\nPetersson, Agnes\n2025\nDocument Version:\nPublisher's PDF, also known as Version of record\nLink to publication\nCitation for published version (APA):\nPetersson, A. (2025). Biomarkers and gastrointestinal symptoms in endometriosis. [Doctoral Thesis\n(compilation), Department of Clinical Sciences, Malmö]. 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May. 2026\n\nBiomarkers and gastrointestinal \nsymptoms in endometriosis\nAGNES PETERSSON  \nDEPARTMENT OF CLINICAL SCIENCES, MALMÖ | FACULTY OF MEDICINE | LUND UNIVERSITY\n\nDepartment of Clinical Sciences, Malmö\nLund University, Faculty of Medicine  \nDoctoral Dissertation Series 2025:50 \nISBN 978-91-8021-703-3\nISSN 1652-8220\n9 789180 217033\n\n1 \nBiomarkers and gastrointestinal symptoms in endometriosis \n  \n\n\n\nBiomarkers and gastrointestinal \nsymptoms in endometriosis  \nAgnes Petersson \nDOCTORAL DISSERTATION \nDoctoral dissertation for the degree of Doctor of Philosophy (PhD) at the Faculty \nof Medicine at Lund University to be publicly defended on 8th of May at 09.00 in \nHoodsalen, Ruth Lundskogs gata 3, Malmö \nFaculty opponent \nProfessor Karin Sundfeldt, University of Gothenburg \n\n\nOrganization: LUND UNIVERSITY  \nDocument name:  DOCTORAL DISSERTATION Date of issue: 2025-05-08 \nAuthor: Agnes Petersson Sponsoring organization: \nTitle: Biomarkers and gastrointestinal symptoms in endometriosis  \nAbstract: \nEndometriosis is a highly prevalent gynecological disease that often causes gastrointestinal symptoms. \nGiven the diagnostic delay of several years, more effective methods for diagnosis are crucial to reduce \nthe disease burden for these women.  \nThis thesis investigated differences between endometriosis and IBS by comparing sociodemographic \nfactors, lifestyle habits, gastrointestinal symptoms and biomarkers. Two cohorts of patients with \nendometriosis were included: 172 women with surgically confirmed diagnoses and 81 diagnosed by \ntransvaginal ultrasound. Women from the general population and healthy controls served as controls, \nand women with IBS were used for comparisons of gastrointestinal symptoms and autoantibodies. \nQuestionnaires regarding sociodemographic factors, lifestyle habits and symptoms were completed. \nBlood and fecal samples were collected. The gut microbiota, polygenic risk scores and autoantibodies \nwere analyzed and evaluated as potential biomarkers for endometriosis.  \nDifferences in sociodemographic and lifestyle factors between endometriosis and IBS were limited. \nGastrointestinal symptoms were more aggravated in IBS and different initial triggering factors were \nidentified. Both alpha- and beta diversity of the gut microbiota were higher in controls than \nendometriosis patients. The abundances of several bacteria differed between the groups. Some \nassociations between PRS and localization of endometriosis and hormone treatment were observed. \nThyroid-stimulating hormone receptor antibodies (TRAb), both IgG and IgM, were increased in \nendometriosis compared with controls, in one study. None of the other analyzed autoantibodies were \nelevated, indicating that the results were not caused by cross-reactivity. However, the results of higher \nTRAb IgG levels could not be confirmed when analyzed using updated clinical methods.  \nThese results show that, compared with controls, women with endometriosis have an aberrant \nmicrobiota. TRAb is a potential biomarker for endometriosis, but current tests in the clinic cannot be \nused to detect elevated levels in endometriosis. In future research, further evaluation of potential \nbiomarkers, including TRAb and the gut microbiota, would be valuable. \nKey words: Endometriosis, gastrointestinal symptoms, gut microbiota, PRS, TRAb, biomarkers \nClassification system and/or index terms (if any) Supplementary bibliographical information \nLanguage: English  ISSN and key title: 1652-8220 \nISBN: 978-91-8021-703-3 \nRecipnt’s notes  Number of pages: 70 \nPrice Security classification\nI, the undersigned, being the copyright owner of the abstract of the above-mentioned dissertation, \nhereby grant to all reference sources permission to publish and disseminate the abstract of the above-\nmentioned dissertation. \nSignature  Date 2025-03-28 \n\nBiomarkers and gastrointestinal \nsymptoms in endometriosis  \nAgnes Petersson \n\n\nCoverphoto by Agnes Petersson \nCopyright pp 1-70 Agnes Petersson \nPaper 1: © The Authors (Manuscript unpublished) \nPaper 2: Open access, © The Authors \nPaper 3: Open access, © The Authors \nPaper 4: Open access,  © The Authors  \nPaper 5: © The Authors (Manuscript unpublished) \nFaculty of Medicine \nDepartment of Clinical Sciences, Malmö \nISBN 978-91-8021-703-3 \nISSN 1652-8220 \nPrinted in Sweden by Media-Tryck, Lund University \nLund 2025 \n\n\nTo my family \n\nTable of Contents\nAbstract ........................................................................................................ \n10 \nPopulärvetenskaplig sammanfattning .......................................................... 11 \nList of Papers ................................................................................................ 13 \nAuthor’s contribution to the papers .............................................................. 14 \nAbbreviations ............................................................................................... 15 \nIntroduction .......................................................................................................... 17 \nEndometriosis ............................................................................................... 17 \nSymptoms and presentation of the disease .......................................... 18 \nDiagnosis ............................................................................................. 18 \nTreatment ............................................................................................. 20 \nPathogenesis and pathophysiology ...................................................... 20 \nThe gut microbiota and endometriosis ................................................ 21 \nPolygenic risk scores ........................................................................... 23 \nThyroid disease and endometriosis...................................................... 24 \nIrritable bowel syndrome ............................................................................. 25 \nDiagnostic criteria for IBS ................................................................... 25 \nExtraintestinal symptoms in IBS ......................................................... 26 \nPathogenesis and pathophysiology ...................................................... 26 \nManagement of IBS ............................................................................. 27 \nOverlaps between endometriosis and irritable bowel syndrome .................. 28 \nSymptomatology.................................................................................. 28 \nPathophysiology .................................................................................. 28 \nHypersensitivity ................................................................................... 29 \nAims ....................................................................................................................... 31 \nMaterials and methods ......................................................................................... 33 \nStudy population .......................................................................................... 33 \nEndometriosis patients ......................................................................... 33 \nIBS patients ......................................................................................... 34 \nControls ............................................................................................... 34 \nStudy design ................................................................................................. 36 \nQuestionnaires .............................................................................................. 37 \n\nClinical data survey \n............................................................................. 37 \nThe Visual Analogue Scale for Irritable Bowel Syndrome ................. 37 \nIrritable bowel syndrome-severity scoring system .............................. 37 \nLaboratory methods ..................................................................................... 38 \nPaper II ................................................................................................ 38 \nPaper III ............................................................................................... 38 \nPapers IV and V................................................................................... 38 \nData Categorization ...................................................................................... 39 \nStatistical methods ....................................................................................... 40 \nGenetic analyses .................................................................................. 40 \nEthical considerations .................................................................................. 41 \nResults .................................................................................................................... 43 \nBaseline characteristics ................................................................................ 43 \nGut microbiota ............................................................................................. 44 \nPolygenic risk score ..................................................................................... 47 \nAntibodies (Papers IV and V) ...................................................................... 48 \nDiscussion .............................................................................................................. 51 \nGeneral discussion ....................................................................................... 51 \nSociodemographic factors, lifestyle and gastrointestinal symptoms ... 51 \nThe gut microbiota .............................................................................. 51 \nTRAb and endometriosis ..................................................................... 53 \nGenetic analyses of endometriosis ...................................................... 54 \nMethodological considerations .................................................................... 54 \nConclusions ........................................................................................................... 57 \nFuture perspectives .............................................................................................. 59 \nAcknowledgements ............................................................................................... 61 \nReferences ............................................................................................................. 63 \n\n10 \nAbstract   \nEndometriosis is a highly prevalen t gynecological disease that often causes \ngastrointestinal symptoms. Given the di agnostic delay of several years, more \neffective methods for diagnosis are cruc ial to reduce the disease burden for these \nwomen.  \nThis thesis investigated differences between endometriosis and IBS by comparing \nsociodemographic factors, lifestyle habits, gastrointestinal symptoms and \nbiomarkers. Two cohorts of patients with endometriosis were included: 172 women \nwith surgically confirmed diagnoses and 81 diagnosed by transvaginal ultrasound. \nWomen from the general population and hea lthy controls served as controls, and \nwomen with IBS were used for comparis ons of gastrointestinal symptoms and \nautoantibodies. Questionnaires regarding sociodemographic factors, lifestyle habits \nand symptoms were completed. Blood a nd fecal samples were collected. The gut \nmicrobiota, polygenic risk scores and autoantibodies were analyzed and evaluated \nas potential biomarkers for endometriosis.  \nDifferences in sociodemographic and lifest yle factors between endometriosis and \nIBS were limited. Gastrointestinal sympto ms were more aggravated in IBS and \ndifferent initial triggering factors were identified. Both alpha- and beta diversity of \nthe gut microbiota were higher in controls than endometriosis patients. The \nabundances of several bacteria differed between the groups. Some associations \nbetween PRS and localization of endomet riosis and hormone treatment were \nobserved. Thyroid-stimulating hormone receptor antibodies (TRAb), both IgG and \nIgM, were increased in endometriosis compared with controls, in one study. None \nof the other analyzed autoantibodies were elevated, indicating that the results were \nnot caused by cross-reactivity. However, the results of higher TRAb IgG levels \ncould not be confirmed when analyzed using updated clinical methods.  \nThese results show that, compared with c ontrols, women with endometriosis have \nan aberrant microbiota. TRAb is a potential biomarker for endometriosis, but current \ntests in the clinic cannot be used to detect elevated levels in endometriosis. In future \nresearch, further evaluation of potential biomarkers, including TRAb and the gut \nmicrobiota, would be valuable.  \n\n11 \nPopulärvetenskaplig sammanfattning \nEndometrios är en gynekologisk sjukdom som orsakas av kronisk inflammation till \nföljd av att livmoderslemhinna växer utanför livmodern. Det kan förekomma i form \nav till exempel cystor på äggstockarna e ller påväxt på bukväggen, urinblåsan eller \ntarmarna. Endometrios är en sjukdom som drabbar upp till var tionde kvinna i fertil \nålder, vilket innebär att cirka 250 000 kvinnor i Sverige är drabbade. Sjukdomen är \ngodartad men kan orsaka besvärliga symptom i form av smärtor, mag-tarmbesvär, \nmenstruationsrubbningar och ofrivillig barnlöshet. Orsaken till uppkomsten och \nutvecklingen av endometrios är inte helt kartlagd.  \nDet finns idag inget godkänt blodprov som kan visa om man har sjukdomen. \nTidigare har en definitiv diagnos kräv t undersökning med titthålskirurgi men idag \nhar riktlinjerna ändrats till att i första ha nd använda ultraljud, och i vissa fall MRI. \nEftersom symptomen för endometrios kan variera mycket mellan olika patienter och \nofta misstas för mensvärk, IBS eller a ndra sjukdomar, är fördröjningen till rätt \ndiagnos vanligtvis lång.  \nSyftet med den här avhandlingen var a tt karakterisera mag-tarmbesvär och \nsociodemografiska drag hos patienter med endometrios samt undersöka potentiella \nbiomarkörer för sjukdomen. Totalt i avhand lingen har 172 kvinnor med kirurgiskt \ndiagnostiserad endometrios och 81 kvinnor med ultraljudsverifierad endometrios \ndeltagit. Samtliga har svarat på frågeformulär och lämnat blodprover, medan en del \näven lämnat avföringsprover. Som jämför else har patienter med IBS, friska \nkontroller och kontroller från den allmänna befolkningen använts.  \nI delarbete 1 har vi jämfört sociodemograf iska faktorer och magtarmsymptom hos \npatienter med endometrios och IBS. Sk illnaderna i sociodemografi och livsstil \nvisade sig vara begränsad mellan de två grupperna. Patienterna med IBS hade mer \nsymptom vad gäller smärta, diarré, fö rstoppning, uppspändhe t, illamående och \ninverkan på det dagliga livet än patienter na med endometrios. Det visade sig även \nfinnas tydliga skillnader i vad som initialt triggat i gång symptomen där \nmenstruationsdebut var vanligast vid endom etrios medan stress, infektion eller \nantibiotikabehandling var vanligare vid IBS.  \nBakteriefloran i tarmen har identifiera ts som en bidragande faktor i många \nsjukdomar och associationer har setts även  till endometrios. Därför tittade vi i \ndelarbete 2 på vilka skillnader i tarmflora som finns mellan patienter med \nendometrios och den allmänna befol kningen. Vi kunde se att mångfalden av \nbakterier var högre i befolkningen än hos de med endometrios. Flera olika bakterier \nvisade olika riklig förekomst mellan grupperna.   \nI delarbete 3 undersökte vi patienter me d endometrios avseende deras genotyp och \ngenetisk riskpoäng, så kallad polygenic riskscore (PRS), beräknades. Vi undersökte \nassociationer mellan PRS och kliniska fynd såsom typ av endometrios, symptom \n\n12 \noch behandling. Det fanns vissa assoc iationer mellan PRS och spridning av \nendometrios, involvering av magtarmkanalen samt hormonbehandling.  \nI tidigare studier har man sett att nivåer na av antikroppar mot sköldkörtelreceptorn \nsom kallas TRAK IgG verkar vara förhöjda i blodet hos patienter med endometrios. \nI delarbete 4 tittade vi på ett större anta l antikroppar inom samma familj för att se \natt de förhöjda nivåerna inte kunde förklaras av en korsreaktion vid analysen, vilket \nvi kunde bekräfta inte var fa llet. I delarbete 5 ville vi bekräfta de tidigare resultat \nsom visat att TRAK IgG är förhöjda vid endometrios, vilket gjordes genom att \nanalysera prover från nya patienter på två olika laboratorier. Jämfört med tidigare \nhade analysmetoderna ändrats och resultaten kunde inte bekräftas. Tolkningen är att \nanalysmetoderna inte är tillräckligt känsliga för att användas i detta syfte.   \nYtterligare forskning behövs för att utreda om fynden i avhandlingen verkligen \nskiljer sig hos patienter med endometrios och kan användas i kliniken. Att hitta en \nkliniskt användbar biomarkör skulle va ra till stor nytta för patienter med \nendometrios då det kan leda till att kvi nnor med hög sannolikhet för endometrios \nsnabbt kan identifieras och remitteras för vidare utredning.    \n\n13 \nList of Papers  \n \nPaper I \nAgnes Petersson, Bodil Roth, Ligita Jokubkiene, Povilas Sladkevicius, Bodil \nOhlsson, Comparison of sociodemographic factors, lifestyle, and gastrointestinal \nsymptoms between patients with endometriosis and IBS. Submitted. \n \nPaper II \nAgnes Svensson, Louise Brunkwall, Bodil Roth, Marju Orho-Melander and Bodil \nOhlsson, Associations Between Endometriosis and Gut Microbiota. Reprod Sci, \n2021. 28(8): p. 2367-2377. \n \nPaper III \nAgnes Svensson*, Koldo Garcia-Etxebarria*, Anna Åkesson, Christer Borgfeldt, \nBodil Roth, Malin Ek, Mauro D’Amato and Bodil Ohlsson, Applicability of \npolygenic risk scores in endometriosis clinical presentation. BMC Womens health, \n2022. 22 (1): p. 208.  \n* Shared first authorship. \n \nPaper IV \nAgnes Svensson, Bodil Roth, Linnea Kronvall and Bodil Ohlsson, TSH receptor \nantibodies (TRAb) - A potential new biomarker for endometriosis. Eur J Obstet \nGynecol Reprod Biol, 2022. 278: p. 115-121. \n \nPaper V \nAgnes Petersson, Bodil Roth, Charlotte Becker and Bodil Ohlsson, Elevated levels \nof TRAb IgG autoantibodies are not recognized in endometriosis by current \nclinical methods. Submitted.  \n \n \nRelated articles by the author \n \nAgnes Petersson, Bodil Roth, Ligita Jokubkiene, Povilas Sladkevicius and Bodil \nOhlsson, Differences in circulating AXIN1 between endometriosis and IBS are \ninfluenced by the tests used. A cross-sectional study. Submitted.  \n \n \n\n14 \nAuthor’s contribution to the papers\nPaper I \nConceptualization of the \nproject. Data processing. Statistics. Interpretation of data. \nWriting, original draft. Reviewing and editing including all communication with \nthe journals.  \nPaper II \nWriting, original draft. Reviewing and editing. \nPaper III \nStatistics. Interpretation of data. Writing, original draft. Reviewing and editing \nincluding all communication with the journals and reviewers.   \nPaper IV \nConceptualization of the project. Data processing. Statistics. Interpretation of data. \nWriting, original draft. Reviewing and editing including all communication with \nthe journals and reviewers.   \nPaper V \nConceptualization of the project. Data processing. Statistics. Interpretation of data. \nWriting, original draft. Reviewing and editing including all communication with \nthe journals.   \n\n15 \nAbbreviations \nAUC Area under the curve \nBD Blood donor \nBMI Body mass index \nBSA Bovine serum albumin \nhCG Human chorionic gonadotropin \nECLI Electro-chemiluminescence immunoassay \nELISA Enzyme-linked immunosorbent assay \nFSH Follicle-stimulating hormone \nFSHR Follicle-stimulating hormone receptor \nGI Gastrointestinal  \nGnRH Gonadotropin-releasing hormone  \nGWAS Genome wide association study \nIBS Irritable bowel syndrome \nIBS-SSS Irritable bowel syndrome severity scoring system \nIQR Interquartile range \nLH Luteinizing hormone \nLHR Luteinizing hormone receptor \nMOS Malmö Offspring Study  \nMRI Magnetic resonance imaging  \nPRS Polygenic risk score \nROC Receiver operating characteristic \nRU  Relative units \nSD Standard deviation  \nTRAb  Thyroid-stimulating hormone receptor antibody  \nTSH Thyroid-stimulating hormone \nVAS-IBS Visual analogue scale for irritable bowel syndrome \n \n  \n\n\n\n17 \nIntroduction  \nEndometriosis \nEndometriosis is a benign gynecological disease characterized by the presence of \nendometrial-like cells and stroma locate d outside the uterus. Lesions are most \ncommonly found on the pelvic peritoneum , the ovaries and in the rectovaginal \nseptum [1]. The prevalence of endometri osis varies across studies and depends on \nthe diagnostic methods. Estimates typically range from 2 to 10% within the female \npopulation. Recently, a systematic review estimated that the overall prevalence was \n18% [2].  \n \n \nFigure 1. Female internal reproductive organs with possible localizations of endometriotic lesions. \nImage source: Adobe Stock.  \n  \n\n\n18 \nSymptoms and presentation of the disease  \nIn general, pain is the most apparent sy mptom of endometriosis. It usually begins \nwith severe menstrual cramps at the beginning of the menstrual phase. For some \npatients, the number of days with pain increases, leading to constant pain and \nchronic pain syndrome due to pain sens itization. Endometriosis can also cause \nsymptoms such as deep dyspareunia, back pain, and symptoms associated with the \nbladder and bowel [3]. GI symptoms have  been reported in 90% of women with \nendometriosis. Since only 7.5% of the women had established endometriosis located \nto the bowel, the GI symptoms seem to be mainly independent of the localization of \nlesions [4]. What causes GI symptoms in patients with endometriosis is not fully \nunderstood. Visceral hypersensitivity has been found to be common in \nendometriosis patients, which could intensify pain and explain why symptoms often \nnot are proportionate to disease extent [5]. Inflammatory activity caused by \nendometriosis lesions, comorbidity with IBS and endometriosis lesions involving \nthe bowel are other explanations presented [6]. This disease is a common cause of \ninfertility, which can be observed in 25% of women with endometriosis [7].        \nDiagnosis \nFor many years, laparoscopic visualization with histopathological confirmation has \nbeen considered the gold standard for th e diagnosis of endometriosis. However, \nrecent guidelines recommend a nonsurgical diagnosis based on anamnesis, physical \nexamination and medical imaging [8]. This recommendation is based on the \nrecognition that surgery not only involves risks but can also lead to long diagnostic \ndelays. Several studies have reported an overall diagnostic delay of 4–10.4 years \nfrom the onset of symptoms to diagnos is [9, 10]. The three subtypes of \nendometriosis include superficial disease, deep infiltrative disease, and \nendometriomas, where the first is difficult to detect with imaging techniques [11]. \nSince 2022, transvaginal ultrasound has been considered gold standard in \ndiagnosing endometriosis [8]. Transvagin al ultrasound can be used to identify \nendometriomas and deep endometriosis involving the bowel, bladder or ureter. MRI \nis not recommended as a primary inves tigation in patients with suspected \nendometriosis. However, it may be useful for assessing the extent of deep \nendometriosis. In patients with norma l findings upon clinical examination, \nultrasound and MRI, the possibility of endom etriosis should not be excluded if a \nclinical suspicion remains [12].  \n\n19 \n \nFigure 2. Imaging and laparoscopic appearance of endometriosis subtypes. Reproduced from Allaire \net al. CMAJ. 2023: E363-E371. \nBiomarkers  \nA biomarker is defined as a specific characteristic, often biological, that is \nmeasured as an indicator of a physiological process or a pathological condition or \nto assess the effects of an intervention or treatment. Several markers, including \nglycoproteins, angiogenetic factors, oxidative stress markers, inflammatory \nproteins, hormone-related factors, miRNA markers, DNA markers and the \nmicrobiota, have been tested as potential biomarkers for endometriosis [13]. A \nCochrane study from 2016, including 54 studies, concluded that currently no \nbiomarker candidates can be considered diagnostic tools for endometriosis in \nclinical practice [14]. Most biomarkers were assessed in only single studies, and a \nmeta-analysis could be performed for only PGP 9.5 and CYP 19. Currently, \nbiomarkers are not recommended for diagnosing endometriosis [15]. \n \n\n\n20 \nTreatment  \nMany different guidelines have been publ ished to help clinicians treat \nendometriosis. The main goal is to improve pain symptoms, limit the growth of the \nlesions and increase fertility. First-line treatments for suspected or verified \nsymptomatic endometriosis include combined oral contraceptives and progesterone. \nSecond-line treatments include gonadotr opin-releasing hormone agonists (GnRH \nagonists) and intrauterine devices (IUDs ) [16]. Hormonal treatment is often \ncombined with analgesics  such as paracetamol, nonsteroidal anti-inflammatory \ndrugs (NSAIDs) and, in some cases, opioids [17]. \nIn patients who do not respond to conservativ e treatment, surgery is an option. If \npossible, laparoscopic surgery is always  preferred before laparotomy [18]. \nConservative surgery, which aims to pr eserve fertility, includes the excision or \nablation of lesions, division of adhesions and pelvic nerve interruption. Definitive \nsurgery, which generally involves hyster ectomy with or without oophorectomy, is \nthought to be more effective over time; however, this procedure is no guarantee of \npain relief [19].  \nComplementary therapies such as acupuncture and transcutaneous electrical nerve \nstimulation (TENS) have both been shown to reduce chronic pelvic pain and deep \ndyspareunia in women with deep endometriosis [20]; however, further studies are \nneeded to elucidate their roles in the clinic.  \nPathogenesis and pathophysiology \nThe etiology and pathology of endometriosis are not fully known. In 1927, Sampson \npresented the theory of retrograde menstrua tion, which is still widely supported \n[21]. He proposed that blood containing e ndometrial cells was passed backward to \nthe pelvic cavity through the fallopian tubes during menstruation. However, 90% of \nwomen with patent tubes have evidence of blood in their peritoneal fluid during \nperimenstrual period, indicating that re trograde menstruation is a very common \nphysiological event [22]. The fact that only a minority of women with retrograde \nmenstruation develop endometriosis suggest s that other mechanisms are involved \nin lesion development, and several different theories have been proposed [23]. The \ncoelomic metaplasia theory states that cells lining the visceral and abdominal \nperitoneum differentiate in situ into e ndometrial tissue. Another theory is the \nMullerian rest theory, which states th at residual cells migrating from the \nembryologic Mullerian duct develop into endometriotic lesions when stimulated by \nestrogen [23]. Additionally, other theories posit that endometrial tissue originates \nfrom the differentiation of stem cells, which are disseminated from the bone marrow \n[24].  \nThe hereditability of endometriosis has b een estimated to be approximately 50% \nbased on twin studies [25, 26]. Genome-wide association studies (GWASs) can be \n\n21 \nused to identify genetic variants underlying a disease. Endometriosis GWASs have \nidentified several genomic regions and vari ants associated with the endometriosis \nrisk [27]. These regions are related to estrogen-induced cell growth, cell \ndifferentiation, intracellular adhesion, hormone receptors, inflammatory cytokines, \nand cell damage. In addition, epigenetic m odifications play a definite role in the \ndevelopment of endometriosis [28].  \nThe gut microbiota and endometriosis  \nThe gastrointestinal (GI) tract is a comp lex system characterized by the symbiosis \nof gut mucosal cells, the immune system, food molecules and microorganisms. It is \na dynamic environment, and the microbiota is constantly changing. The \ndevelopment of 16S ribosomal RNA (rRNA)  sequence identification has provided \ninsights into the diversity of the gut microbiota. An analysis of 16S rRNA sequences \nallows the identification of species a nd determination of operational taxonomic \nunits (OTUs). The 97% sequence identity of 16S rRNA is often considered a good \napproximation to species [29]. Bacteria are classified into groups and subgroups \naccording to kingdom, phylum, class, order,  family, genus and species (Figure 3). \nOver 1500 species of bacteria belonging to over 50 different phyla reside in the \nintestines [30]. A culture-independent analys is revealed that the gut microbiota is \ndominated by Bacteroidetes and Firmicutes, followed by Actinobacteria, \nFusobacteria, Proteobacteria, Tenericutes and Verrucomicrobia [31, 32].  \nSequencing of the 16S rRNA revealed that th e vast majority of bacteria belong to \nthree bacterial groups: Bacteroides, Clostridia cluster IV and Clostridia cluster XIVa \n[33]. Clostridia are gram-positive rods in the phylum Firmicutes [34]. We are \ncolonized with commensal Clostridia from early infancy throughout life, and they \nparticipate in maintaining well-functio ning metabolic, physiologic and immune \nprocesses in our intestines. Clostridia st rongly contribute to maintaining a normal \ngut function but are also involved in the development of dysbiosis. Some Clostridia \nare pathogenic, such as Clostridium perfringens and Clostridium tetani in cluster I \nand Clostridium difficile in cluster XI. However, most of the Clostridia in our GI \ntract are commensals [34]. \nThe gut microbiota plays major roles in  the maintenance of health and the \ndevelopment of disease [35]. The gut micr obiota, through the inflammatory and \nmetabolic changes it induces, has been show n to affect conditions both inside and \noutside the GI tract. Strong evidence is available for an association between an \nimbalance in the microbiota composition, known as dysbiosis, and diseases such as \narthritis, inflammatory bowel disease (IBD) and colon cancer [36,  37]. Previous \nstudies in animal models and patients with  endometriosis have shown dysbiosis in \nthe gut [38]. The gut microbiota has been shown to affect estrogen levels and \nestrogen-dependent diseases [39, 40]. Sy stemic levels of estrogen in \npostmenopausal women are strongly associated with fecal microbiome richness and \n\n22 \nfecal levels of Clostridia [25]. Higher estrogen levels stimulate epithelial \nproliferation in the female reproductive tract and have been shown to drive diseases \nsuch as endometriosis and endometrial cancer [41]. \nThe gut microbiota may also affect other mechanisms involved in the pathogenesis \nof endometriosis. Recent studies have shown that the gut microbiota is a major \nregulator of inflammatory processes outside the GI tract [42]. For example, the gut \nmicrobiota affects the activity level of IL-17 producing CD4+ T lymphocytes [43]. \nThe levels of IL-17 are significantly higher in patients with mild endometriosis than \nin those with moderate/severe endometriosis or healthy women, suggesting that IL-\n17 plays a role in the pathogenesis of endometriosis [44]. Due to the impact of \nimmunological changes in patients with endometriosis and the impact of the gut \nmicrobiota on immune responses, resear chers have hypothesized that the gut \nmicrobiota is involved in the pathogenesis of endometriosis [11]. \nFigure 3. Example of bacterial taxonomic classification.  \n\n\n23 \nPolygenic risk scores  \nThe interest in risk models has increased over the years and genetic risk variants for \nvarious diseases are being discovered through GWASs [45, 46]. GWASs is used in \ngenetics research and test thousands of ge netic variants to identify those who are \nstatistically associated with a disease. Si nce single risk loci usually have a low \nimpact on disease risk, combining the effects of multiple risk variants has become \na way to predict the risk more accurately [47, 48]. One commonly used score is the \npolygenic risk score (PRS), which combines allelic variations of single nucleotide \npolymorphisms (SNPs) derived from  GWASs [49]. In endometriosis, \napproximately 26 % of the polygenic risk is explained by SNPs [50]. There are \nseveral GWASs for endometriosis, reporting genetic variants involved in sex steroid \nhormone pathways and development of the female reproductive tract [51]. PRS \nderived from GWASs has been associated with endometriosis, and the subtypes \novarian, infiltrating and superficial [52].  \nFigure 4. Representative density plot of a population according to the polygenic risk score. The figure \nis labelled according to the lowest (0–20%), population average (40–60%) and highest (80–100%)\nquintiles of genetic risk.  \n\n\n24 \nThyroid disease and endometriosis  \nThyroid disease occurs more frequently in women than in men, which correlates \nwith the autoimmune nature of many t hyroid diseases. Different thyroid disorders \ncan disturb menstruation and ovulation [53]. Hyperthyroidism can cause \noligomenorrhoea, whereas hypothyroidis m can manifest as menorrhagia or \noligomenorrhoea, infertility or miscarri age. Several autoimmune disorders, \nincluding thyroid disorders such as Hashimoto’s thyroi ditis and Graves’ disease, \nhave been reported by some authors to be  associated with endometriosis [54-57]. \nHowever, compared with that in the ge neral population, the prevalence of thyroid \ndisorders in patients with endometriosis is not increased according to one study [58]. \nSince endometriosis is considered a chr onic inflammatory process, the increased \nprevalence of autoimmune thyroid disorders could be linked to the immune \ndysregulation in patients with endometrios is [59]. Moreover, thyroid dysfunction \nmay affect the development of endometri osis. Thyroid hormone action in humans \nis mediated by receptor binding. Binding sites for thyroid hormones have been \nfound in different human tissues, including the brain, heart, liver, lung, kidney and \npancreas [60]. The thyroid-stimulating hormone (TSH) receptor mRNA and protein \nare highly expressed in the ovarian surf ace epithelium in humans. TSH thereby \nstimulates the endometrium to produce thyroid hormones, with function as a site for \nextrathyroidal hormone production [61, 62]. The development of multicystic ovaries \nduring profound hypothyroidism has been reported [63], and a mouse study showed \nthat endometriotic implants grow in the presence of increased thyroid hormone \nlevels [58]. A previous study reported that  the serum levels of thyroid-stimulating \nhormone receptor antibody (TRAb) IgG exceed  the detection limit of 0.3 IU/L in \n93.0% of patients with endometriosis compared with 7.9% in the general population \n[64]. Only TRAb levels under or in grey-zone values were associated with \nendometriosis, not levels above the cut-off value for thyroid disease.  \n\n25 \nIrritable bowel syndrome \nIBS is a disease of the gut‒brain interaction (DGBI), in which recurrent abdominal \npain is associated with defecation or a change in bowel habits [65]. Estimates of the \nglobal prevalence vary from 1% to 25%, with a pooled prevalence of 3.8% [66]. \nPrevalence rates are higher for women than for men, and individuals younger than \n50 years are more commonly affected [67].  \nDiagnostic criteria for IBS \nIBS is clinically diagnosed according to the Rome IV criteria [68]. The prevalence \nis lower according to the updated criteria of Rome IV (3.8%) compared with the \npreviously used Rome III (9.2%). Differences in Rome III and Rome IV criteria are \npresented in Table 1. According to Rome IV , the diagnosis is made if a patient has \nexperienced abdominal pain ≥1 day/week in the last 3 months, related to at least two \nof the following characteristics: related to defecation, associated with a change in \nthe frequency of stool, and associated with a change in the form of stool. The disease \nis divided into four subtypes based on th e predominant pattern of bowel habits: \nconstipation-predominant IBS (IBS-C), di arrhea-predominant (IBS-D), mixed IBS \n(IBS-M) and unspecified IBS (IBS-U). The subtype is determined by the Bristol \nstool form scale [69].  \n \nTable 1. Diagnostic criteria for IBS according to Rome III and Rome IV. \nRome III Rome IV \nRecurrent abdominal pain or discomfort for at \nleast 3 days per month in the last 3 months, \nassociated with 2 or more of the following criteria: \n \n1. Improvement with defecation \n2. Onset associated with a change in frequency \nof stool \n3. Onset associated with a change in form \n(appearance) of stool \n \nCriteria fulfilled for the last 3 months with \nsymptom onset at least 6 months prior to \ndiagnosis \nRecurrent abdominal pain, on average, at least \n1 day per week in the last 3 months, associated \nwith 2 or more of the following criteria: \n \n1. Related to defecation \n2. Associated with a change in frequency of \nstool \n3. Associated with a change in form \n(appearance) of stool \n \nCriteria fulfilled for the last 3 months with \nsymptom onset at least 6 months prior to \ndiagnosis \n \n  \n\n26 \nExtraintestinal symptoms in IBS \nAlthough IBS is characterized by abdomin al pain and altered bowel habits, \nextraintestinal manifestations are common in this group of patients. The prevalence \nof extraintestinal syndromes or symptoms have been shown to be much higher in \nIBS than in healthy controls or in patie nts with organic GI diseases. About 50% of \npatients with IBS have some sort of a dditional somatic or mental symptom [70]. \nThe most reported extraintestinal sympto ms in patients with IBS are back pain, \npelvic pain, fatigue, fibromyalgia, he adache, sleep difficulties and urogenital \nsymptoms [71]. Pelvic pain causes many patients with IBS to seek gynaecological \ncare, without any findings of gynaecol ogical diagnoses, and several studies have \nshown IBS to be associated with gynaecological symptoms such as dyspareunia and \ndysmenorrhea [72]. GI symptoms in IBS vary over the phases of the menstrual \ncycle, with worsening of constipation during the luteal phase and overall increasing \nsymptoms during the menstrual phase [73]. Chronic fatigue is most common in \nfemales and younger patients with IBS, and impacts GI symptoms, psychological \nwell-being and quality of life [74]. The prevalence of IBS is estimated to be 35-92% \nin patients diagnosed with chronic fatigue syndrome [75, 76]. Results show that the \nmore extraintestinal symptoms and psychiatric comorbidity patients with IBS have, \nthe more IBS symptoms they have and the harder it gets to successfully treat their \nGI symptoms. Patients with IBS attend h ealthcare twice as much as controls, and \nmost of their healthcare visits are caused by extraintestinal symptoms [77].  \nPathogenesis and pathophysiology  \nThe pathogenesis and pathophysiology of IBS are complex and still not fully known. \nIt is considered a functional disorder, since no structural or biochemical \nabnormalities have been identified. IBS is a heterogenous disorder, and the \npathogenesis appears to be multifactoria l. Several potential disease-contributing \nfactors have been identified, and research  has focused on gut–b rain signalling, the \ngut microbiota, visceral hypersensitivity, disturbed intestinal motility, \nimmunological factors, psychological factors, and food hypersensitivity [78]. \nDepression and anxiety affect up to one-thi rd of patients with IBS, and results \nindicate that there are bidirectional gut–brain and brain–gut pathways [79, 80] \n(Figure 5). In approximately half of th e patients, IBS seems to be developed \nprimarily, suggesting that disturbance in the gut function is contributing to the \ndevelopment of the mood disorder [81].  \nSeveral environmental factors are associa ted with IBS, such as stress, food \nintolerance, antibiotic treatment and GI infection [82, 83]. Disturbance in intestinal \nmotility, with increased or decreased gut transit time and irregular bowel \ncontractions, is described in some patients with IBS [84]. The role of microbiota in \nIBS is debated, but alterations in the gut microbial composition have been found \n\n27 \ncompared with healthy subjects. Lower microbial diversity in the gut has been found \nin patients with IBS [85]. A reducti on in abundance of Lactobacillus and \nBifidobacterium, and an increase in pot ential pathogenic bacteria such as \nEscherichia coli, have been found in pa tients with IBS compared with healthy \nsubjects [86]. Also, an increased ratio of Firmicutes/Bacteroides has been reported \n[87]. Post-infectious IBS (PI-IBS) is a phenomenon where IBS symptoms arise after \nan acute gastroenteritis, and the risk of  developing IBS after a gastrointestinal \ninfection has been shown to significantly increase [88]. Suggested pathophysiologic \nmechanism for PI-IBS are altered gut mo tility, increased intestinal permeability, \nintestinal inflammation and increased proinflammatory cytokines [89]. \n  \nFigure 5. Bidirectional gut‒brain interaction in IBS. Image created with BioRender.com.  \nManagement of IBS \nLifestyle alterations can alleviate both GI and extraintestinal symptoms in patients \nwith IBS. This motivates first line-treatment, including advice regarding diet, \nincreased physical activity, sleep, stress management and smoking, which has been \nshown to be efficient in up to 50% of patients [90]. The UK National Institute for \nHealth and Care Excellence (NICE) presen t current clinical dietary guidelines for \npatients with IBS. The guidelines recomme nd regular meals, and restriction of \ncaffein, fizzy drinks, alcohol, resistant star ch and high-fiber food [91]. If adequate \nsymptom relief is not achieved by these recommendations, further dietary \nmanagement should be given by healthcar e professionals. Dietary advice includes \nsingle food avoidance and exclusion diet s such as a low FODMAP (fermentable \noligosaccharides, disaccharides, monosaccharides and polyols) diet.  \nFor those with insufficient effects of lifest yle alterations, more advanced treatment \nstrategies, including medical, behavioral and dietary therapies, should be considered \n[91]. Pharmacological treatment of IBS is  focused on identifying the dominant GI \nsymptoms and, accordingly, finding treatment options that improve the symptoms. \nA challenge is that the predominant symp toms can vary over time, and treatment \nmust therefore be personalized. For patients with IBS-C, bulking agents and osmotic \nlaxatives are most often used, whereas IBS-D patients are treated with antidiarrheal \n\n\n28 \ndrugs such as loperamide. Antidepressants , such as selective serotonin reuptake \ninhibitors and tricyclic antidepressants, are believed to decrease the degree of \nabdominal pain associated with IBS vi a centrally mediated antinociceptive \npathways. For more temporary abdominal  pain, antispasmodics can relax smooth \nmuscle and affect GI motility [92]. Othe r medical treatments include antibiotics, \nprobiotics, prosecretory agents and 5-HT3 receptor antagonists [82]. In patients with \nIBS, psychological comorbidities are common and can aggravate GI symptoms \n[93]. For these patients, cognitive behavioral therapy and gut-directed hypnotherapy \nhave been well studied and shown to be effective [94, 95].  \nOverlaps between endometriosis and irritable bowel \nsyndrome  \nSymptomatology  \nEndometriosis and IBS have a significant  overlap in symptom presentation, and \nconsequently the diseases may coexist or be misdiagnosed, leading to diagnostic \ndelays, unnecessary investigations and inadequate treatment. Examples of \nsymptoms which can be found in bot h diseases are abdominal pain, bloating, \ndiarrhea, constipation and dyspareunia. To differentiate between the two diseases in \nclinical practice is a challenge due to th e overlap in symptomatology and lack of \nclinically useful biomarkers.    \nA recent meta-analysis reported that the odds of IBS were three times higher in \npatients with endometriosis compared w ith healthy controls [96]. All studies \nincluded in the analysis showed a positiv e association of IBS and endometriosis. \nThe prevalence rate of IBS in women with endometriosis ranged from 10.6 to 52%. \nAn increased probability of being diagnosed  with IBS is seen in endometriosis \npatients both with and without bowel involvement [97].       \nPathophysiology    \nThe two diseases share several potential pathophysiological mechanisms, and \nmultiple theories have been proposed . An immunological linkage has been \nsuggested, with altered levels of inflammatory cytokines in the peritoneal cavity and \nincreased mast cell activation found in both conditions. In endometriosis, activated \nmast cells have been shown near nerve e ndings in the abdomen and pelvis, and in \nIBS they have been found near the bowel mucosa [98]. Pro-inflammatory cytokines \npromote the chronic low-grade inflammations which can be observed in both \nconditions. Other pathophysiological mechan isms described in both endometriosis \n\n29 \nand IBS are visceral hypersensitivity, dysbi osis of gut microbiota and altered \nintestinal permeability [5, 99, 100]. As previously mentioned, it has been described \nthat both patients with endometriosis and patients with IBS might experience \nvisceral hypersensitivity. Having a diet including FODMAPs cause luminal \ndistension, which can be painful in patients with visceral hypersensitivity. In IBS, a \nlow FODMAP diet is known to decrease GI symptoms and is one of the main \nrecommended dietary managements [91]. Also, a majority of patients with \nendometriosis report improvement in bowel symptoms with a low FODMAP diet \n[101]. \nAnother theory is that endometriosis a nd IBS have an increased association due to \na hormonal connection, involving GnRH -containing neurons, and LH-receptors \nwithin the pelvic organs and the ENS [ 102, 103]. GI symptoms, both in patients \nwith IBS and patients with endometriosis, have been reported to fluctuate over the \nmenstrual cycle with worsening during me nstruation, indicating that female sex \nhormones impact the symptoms [73, 104].  \nHypersensitivity  \nThe experience of pain is a physiologi cal response to activation of nociceptive \npathways. The nociceptive system can be sensitized by functional, inflammatory or \nchemical factors, leading to pain hype rsensitivity. Both peripheral and central \nneurons can be involved in sensitizati on. Central hypersensitivity is normally \nreversible if the stimulus ceases. Howe ver, in some individuals, genetic and \nemotional factors appear to interact with afferent input and lead to irreversible \nincreases central pain sensitivity [105]. Visceral hypersensitivity refers to an \nincreased pain sensation experienced in the visceral organs, which is affected by the \nbidirectional communication between the GI tract and the brain, often referred to as \nthe brain–gut axis. Influences such as psychological traits, genetic predisposition \nand stress response system impact the brain–gut axis and can modulate the \nperception of visceral pain. The organizati on of the enteric nerve system (ENS) is \nin close proximity to the visceral orga ns and there is a neurogenic afferent \nconvergence within the central nervous system. The crosstalk between visceral \norgans is physiological but enables cross organ sensitisation, which means that pain \nin one organ can cause symptoms in othe r organs [106]. Visceral hypersensitivity \nand central sensitisation in IBS have been demonstrated with lower pain thresholds \nfor rectal distension, referred pain, skin hypersensitivity and muscular hyperalgesia \n[107, 108]. In endometriosis, intensity of pain has been reported to be independent \nof disease extent [109], and the patients seem to have lower thresholds for pain \nrelated to central sensitization mechanis ms. Pain provocation by rectal balloon \ndilation, detected lower pain thresholds in patients with endometriosis compared \nwith controls, implying that visceral  pain hypersensitivity is common in \nendometriosis [5].  \n\n\n\n31 \nAims \nThe overall aim of this thesis was to investigate potential biomarkers for \nendometriosis. The specific aims of the included papers are as follows:  \n \nPaper I \nThe primary aim was to compare sociodemographic factors and GI symptoms \nbetween patients with endometriosis and those with IBS. \n \nPaper II \nThe primary aim was to investigate the gut microbiota in patients with endometriosis \ncompared with that in people from the general population. The secondary aim was \nto examine differences in microbiota abundance within the endometriosis cohort, \ndependent on disease localization, GI symptoms, and treatment.  \n \nPaper III \nThe primary aim was to examine whether the PRS for endometriosis and different \nclinical presentations of the disease we re associated. The secondary aim was to \ninvestigate the associations of the PRS for endometriosis with the levels of different \ninflammatory proteins and TRAb. \n \nPaper IV \nThe primary aim was to examine the prev alence of autoantibodies in patients with \nendometriosis with the purpose of evaluating the potential of TRAb IgG as a \ndiagnostic marker for endometriosis.  \n \nPaper V \nThe primary aim was to confirm that the concentrations of TRAb IgG are truly \nelevated in patients with endometriosis co mpared with controls from the general \npopulation and patients with IBS by performing routine clinical analyses.  \n\n\n\n33 \nMaterials and methods \nStudy population  \nEndometriosis patients  \nWomen with endometriosis were identified  at the Department of Gynecology at \nSkåne University Hospital, Malmö, Swed en. The first cohort, which had been \npreviously recruited, was identified by a search of medical records in the County of \nRegion Skåne according to the International Classification of Diseases and Related \nHealth Problems (ICD-10, N80). Recru itment occurred between March 2013 and \nJuly 2014 and between September 2016 and March 2017. The inclusion criteria \nwere a definite diagnosis of endomet riosis, confirmed by laparotomy or \nlaparoscopy, an ability to comprehend the Swedish or English language and an age \nof 18–70 years. The exclusion criteria were an uncertain diagnosis of endometriosis, \nmultiple or severe somatic or psychiatric comorbidities, a diagnosis of inflammatory \nbowel syndrome (IBD) and current pre gnancy. A total of 605 patients were \nidentified between 2013 and 2017. Among those, 307 declined to participate, 72 had \nmoved from the region, 32 had significant comorbidities, 18 had an uncertain \ndiagnosis, and four denied a diagnosis, leaving 172 women included. In Paper I, 32 \nwomen were excluded because of having a diagnosis of IBS, leaving 140 women to \nbe included for clinical analysis.  \nThe second cohort of patients was recru ited between February 2022 and March \n2023. Patients who were diagnosed with e ndometriosis by transvaginal ultrasound \nat the Department of Gynecology at Skån e University Hospital, Malmö, Sweden, \nwere asked to participate in the study. Patients were systematically examined by \nultrasound examiners experienced in iden tifying endometriosis according to the \nInternational Deep Endometriosis Analysis (IDEA) group recommendations [110]. \nThe diagnostic method was changed from the first inclusion period due to updated \nguidelines [8]. The inclusion criteria were a diagnosis of endometriosis, confirmed \nby ultrasonography, and comprehension of the Swedish or English language. The \nexclusion criteria were the same as those in the first cohort. During the inclusion \nperiod, 96 patients fulfilled the inclusion cr iteria and were asked to participate in \nthe study. Of those, 15 declined to participate, leaving 81 women to be included. In \n\n34 \nPaper I, seven women were excluded because of having a diagnosis of IBS, leaving \n74 women to be included for clinical analysis (Table 2).  \nIBS patients  \nPatients with IBS were recruited during two periods to participate in a dietary trial. \nDuring the first inclusion period, which took place from 2018 to 2019, patients were \nrecruited from primary care centers (PCCs) and the Department of Gastroenterology \nat Skåne University Hospital, Malmö. Patients with IBS were identified by a search \nof the medical records in the County of  Region Skåne according to ICD-10, K58.0 \nand K58.9. The inclusion criteria were a symptom score >175 on the IBS-SSS, age \n18–70 years, and ability to understand the Swedish language. The exclusion criteria \nwere alcohol or drug abuse, severe somatic  or psychiatric diseases, a severe food \nallergy, eating disturbances, having a low-FODMAP diet, LCHF, and a gluten-free \nor vegan diet. In total, 697 patients were contacted. Among them, 145 were willing \nto participate. Later, 22 did not meet the inclusion criteria and 18 declined to \nparticipate, leaving 105 included participants. All men (n=23) and one patient with \na diagnosis of endometriosis were excluded from this study, leaving 81 women who \nwere ultimately included.   \nThe second inclusion period took place from 2022 to 2024. Patients were identified \nby a search of the medical records in th e County of Region Skåne according to the \nICD-10, K58.1 (IBS-D), K58.2 (IBS-C), K58.3 (IBS-M), and K58.8 (IBS-U), \ndiagnosed from 2019 to 2022. A total of 744 patients were randomly selected and \ncontacted by letter or phone. Of these, 58 were willing to participate. From social \nmedia, 218 patients with an IBS diagnosis signed up to participate. Later, 6 did not \nmeet the inclusion criteria, and 66 declined  to participate. All men (n=21) and one \npatient with a diagnosis of endometriosis were excluded. Only patients (n=118) who \nhad been included before August 2023 were included in Study I. In total, 199 women \nwith IBS were included in Study I. In Study V, patients were randomly selected \nfrom the second inclusion period for an an alysis of TRAb levels in Gothenburg \n(n=50) or Malmö (n=50), of whom 24 were analyzed in both departments (Table 2). \nCeliac disease was excluded in all IBS patients by analyzing the levels of \ntransglutaminase antibodies.     \nControls \nMalmö Offspring Study \nThe Malmö Diet and Cancer Study (MDCS) consists of 28,098 individuals from the \ngeneral population, enrolled between  1991 and 1996. From the MDCS 6103 \nparticipants were randomly selected and included in the Malmö Diet and Cancer \nCardiovascular Cohort (MDC-CC). Offspring of the subjects in the MDC-CC were \n\n35 \ninvited to participate in the Malmö Of fspring Study (MOS) [111]. In the present \nstudy, controls were randomly recruited from a previously selected cohort from \nMOS to study GI symptoms in the general population [112]. In Study II, each patient \nwas matched with three controls according to sex (female), age (± 730 days), body \nmass index (BMI) (±2 BMI units), and sm oking status. Only participants from the \nMOS who had answered a questionnaire and provided stool samples were included \nin the matching process. Those who were diagnosed with celiac disease, lactose \nintolerance, IBD or IBS were excluded from the matching process. In total, 198 \nwomen served as controls [median age 37 (32–44) years]. In Study IV, the control \ngroup for the analysis of TRAb IgG levels consisted of  100 and 114 MOS \nparticipants, respectively. From the initial selected MOS cohort  [112], women \nunder the age of 60 years who had both answered questionnaires and provided blood \nsamples were recruited as controls for GI symptoms and circulating biomarkers [64, \n113].   \nHealthy controls  \nThe control group for the analysis of antibodies against FSH, FSHR, hCG, LH, \nLHR, TSH and TRAb IgA/IgM in Study IV consisted of 50 healthy, female blood \ndonors from Malmö, who were randomly asked to participate as controls.  \nIn Study V, healthy controls, consisting of  health care workers, relatives of health \ncare workers and medical students practicing at SUS, Malmö, aged 18–70 years, \nwere recruited to participate by personal invitations or advertisement. The exclusion \ncriterion was having an acute or chronic illness or significant GI symptoms. In total, \n74 controls were recruited, of whom 50 women were randomly selected for Study \nV.  \nReference values from the Department of C linical Chemistry in Malmö were used \nfor TRAb IgG, TSH, T3, FT3, T4 and FT4 levels in Study IV. Reference values \nfrom the Division of Clinical Chemistry in Malmö and the Departments of Clinical \nChemistry at Sahlgrenska University Hosp ital for TRAb IgG levels were used in \nStudy V. \n  \n\n36 \nTable 2. Table of patients and controls included in Papers I–V. \nPaper I Paper II Paper III Paper IV Paper V \nEndometriosis 214,\nexcluded all \nwith \nconcomitant \nIBS \n66, \nfirst cohort \n172, \nfirst cohort \n172,  \nfirst cohort \n121, \nfirst and \nsecond \ncohorts \nIBS  199 76 \nMOS, general \npopulation \n198,\nexcluded \nthose with \norganic GI \ndiseases \nand IBS \n100/114\nexcluded \nthose with \norganic GI \ndiseases \nand IBS \nHealthy blood \ndonors \n50 \nHealthy hospital \nstaff/relatives/ \nstudents \n50\nMOS: Malmö Offspring Study \nStudy design \nAll studies included in this thesis were  cross-sectional. Study I compared \nsociodemographic factors between patients with endometriosis and patients with \nIBS. Study II compared the gut microbiota in patients with endometriosis and people \nfrom the MOS. Study III investigated PRS in patients with endometriosis. Study IV \ncompared antibodies in patients with endometriosis with people from the MOS and \nhealthy controls. Study V compared TRAb levels in patients with endometriosis and \npatients with IBS and healthy controls . Study participants answered a study \nquestionnaire regarding sociodemographic factors, lifestyle habits, and medical \nhistory, completed the VAS-IBS and provided blood samples. For Study II, all \nparticipants also provided stool samples.   \n\n37 \nQuestionnaires \nClinical data survey \nAll participants, except healthy blood donor s, answered questions regarding their \neducation, occupation, marital status, smoking habits, alcohol habits, physical \nactivity, medical history, and pharmacological treatments. Healthy blood donors \nanswered only a brief questionnaire in which they stated that they were healthy and \nused no medications. All participants  in the MOS answered the lifestyle \nquestionnaire in a web-based form [111]. All the endometriosis patients answered a \npreviously developed questionnaire a ddressing their endometriosis-associated \nsymptoms and GI symptoms, including th e onset of symptoms, triggering factors \nand treatment. All IBS patients answered a similar questionnaire addressing their \nGI symptoms, including onset, triggering factors and treatment [64].  \nThe Visual Analogue Scale for Irritable Bowel Syndrome \nGI symptoms in patients and controls (except blood donors) were quantified using \nthe VAS-IBS. The VAS-IBS is a questionnaire that was initially developed to \nmeasure GI symptoms in patients with functional bowel disease. It has been \npsychometrically validated for use prospectively [114, 115], and it has been \nvalidated in an Asian cohort [116]. The severity of seven different symptoms over \nthe last two weeks were estimated: abdominal pain, diarrhea, constipation, bloating \nand flatulence, nausea and vomiting, psychological well-being, and the influence of \nintestinal symptoms on daily life. Each  symptom was measured on a continuous \nscale from 0 to 100 mm, where 0 represents no symptoms and 100 represents a lot \nof symptoms. The scales were inverted from  the original version [114]. Reference \nvalues are available for healthy volunteers [117].  \nIrritable bowel syndrome-severity scoring system \nIn Paper I and V, IBS patients and h ealthy controls completed the IBS-SSS \nregarding abdominal pain, abdominal distension, satisfaction with bowel habits, and \nthe impact of bowel habits on daily life. IBS-SSS estimated the symptoms using \nvisual analogue scales (VAS) scores ranging from 0 mm to 100 mm, and the number \nof days with abdominal pain over the prev ious 10 days was reported to ensure that \nthe patient fulfilled the inclusion and excl usion criteria. The maximum achievable \nscore is 500. Scores <75 indicate the absence of disease, scores ranging from 75–\n174 indicate mild disease, scores ranging from 175–299 indicate moderate disease, \nand scores ≥300 indicate severe disease [118]. \n\n38 \nLaboratory methods \nPaper II \nAnalysis of the gut microbiota \nStool samples were collected from all patients and controls in their homes and stored \nfrozen in sterile tubes until analysis. After arrival at the laboratory, the samples were \nstored at –80 °C. Microbial DNA was extracted at GATC Biotech in Germany using \na QIAamp Column Stool Kit. The V1–V3 regions of the 16S ribosomal RNA were \npairwise amplified and sequenced using the HiSeq Illumina platform at GATC \nBiotech, Constance, Germany. The sequences were binned together into operational \ntaxonomic units (OTUs) using QIIME and classified at the genus level by matching \nwith the Greengenes reference database [119] . Bacteria that occurred in only <10 \nsamples were excluded, leaving 58 bact eria included in the comparison between \npatients and controls and 62 bacteria in calculations within the endometriosis cohort. \nPaper III \nDNA sample sequencing  \nDNA samples were genotyped using the Global Screening Assay, on an Illumina \niScan high-throughput screening system at the Institute of Clinical Molecular \nBiology (Christian-Albrechts-University, Kiel, Germany). The GenCell algorithm \nimplemented in Illumina GenomeStudio so ftware was used to obtain the alleles \nfrom the raw intensity data.   \nPapers IV and V \nImmunological analyses \nAntibodies against FSH, FSHR, hCG, LH, LHR, TSH and TRAb IgA/IgM in serum \nwere analyzed using ELISAs. Microtiter plates were coated with FSH, FSHR, hCG, \nLH, TSH, or TRAb IgA/IgM in phosphate -buffered saline (PBS) and LHR in \ncarbonate buffer (pH 9.2) and incubated at 4 °C overnight on a shaker. The plates \nwere washed with PBS containing 0.05% tween (PBST) three times, blocked with \nbovine serum albumin (BSA), and incubate d at room temperature for 1 h on a \nshaker. Mouse anti-FSH, rabbit anti-TS H IgG and mouse anti-TSHR IgG were \nserially diluted with 1% BSA–0.05% PBST. Antibodies were detected by adding \nHRP-conjugated anti-human, rabbit anti-mouse or goat anti-rabbit antibodies. \nWashing and an incubation at room temper ature were repeated between each step. \nThe color reaction was induced by adding a peroxidase substrate system, and the \n\n39 \nabsorbance was directly read at 450 nm . The absorbance was translated to a \nconcentration in relative units (RUs). Seru m from controls was used to construct a \nfrequency table with a 97.5% positive cutoff value.  \nTSH, T3, FT3, T4, FT4 and TRAb IgG levels were analyzed at the Department of \nClinical Chemistry in Malmö, according to standardized methods used in the clinic. \nSerum TSH, T3, FT3, T4 and FT4 levels were analyzed using a competitive \nimmunoassay with direct chemiluminescence technology according to the Atellica-\nIM method. An analysis of serum TR Ab IgG levels was conducted using a \ncompetitive electrochemilumi nescence immunoass ay (ECLI) detection technique \nbased on ruthenium derivate. As stated in the laboratory protocol, TRAb IgG levels \n>1.7 IU/L were considered positive, and levels of 1.2–1.7 IU/L were considered \ngrey zone. Until 2016, the detecti on level in the laboratory was ≥0.3 IU/L, and the \nfunctional level was 0.8 IU/L. In 2017, the laboratory raised the detection level to \n≥1.0 IU/L, due to low sensitivity at low leve ls. In Study V, TRAb IgG levels were \nanalyzed at the Department of Clinical  Chemistry at Sahlgrenska University \nHospital in Gothenburg, which is able to obtain lower values than the Department \nof Clinical Chemistry in Malmö. The detection level in the laboratory was ≥0.26 \nIU/L, and the functional level was 0.8 IU/L, and the intra-assay CV was 12% at low \nconcentrations.  \nData Categorization  \nThe education level was categorized in to graduated primary school, graduated \nsecondary school, or graduated university. In Paper I, graduation from university \nwas replaced by at least one year of university studies. Occupation was divided into \nworking full time, working 51–99% of the time, working 1–50% of the time, sick \nleave, retired, unemployed, or studying. Ma rital status was categorized into living \nalone, married/partners living together, and ot her, e.g., partners not living together \nor living with individuals others than their partner. In Paper I, smoking was divided \ninto never smokers, former smokers, present irregular smokers, and regular \nsmokers. Alcohol intake was divided into <1 standard glass per week, 1–4 standard \nglasses per week, 5–9 standard glasses per week, and >10 standard glasses per week. \nPhysical activity per week was categorized into never, <30 minutes, 30–60 minutes, \n60–90 minutes, 90–120 minutes, and >120 minutes. In Paper I, BMI was \ncategorized as <25, 25–29.9, and ≥30 kg/m 2 according to the World Health \nOrganization (WHO) standard [120]. In Papers II, III, IV and V, smoking was \ndivided into currently smoking or not currently smoking. Alcohol was divided into \n< 1or ≥1 standard glass of alcohol per week. Physical activity was divided into <1 \nhour or ≥1 hour of activity that led to breat hlessness per week. Hormone treatment \nincluded estrogen, progesterone and GnRH agonists, and was divided into current \ntreatment or no current treatment. Previous habits or treatments were not considered. \n\n40 \nThe localization of endometrios was divided into isolated ovarian lesions or spread \nto any other location and involvement of the bowel or not.  \nStatistical methods \nStatistical analyses were performed using the IBM SPSS® statistical computer \npackage versions 26 & 28 for Windows. Variables were tested for a normal \ndistribution via visualization in a histogram and the Kolmogorov‒Smirnov test. \nComparisons between groups were performed using the Mann‒Whitney U test \n(Paper IV and V) or Kruskal‒Wallis (Paper V) when the distribution was skewed. \nFor correlations, Spearman’s rank correlation test was used (Paper IV). Fischer’s \nexact test was used for categorical variables (Papers I, IV and V). Binary logistic \nregression was used in Paper I to estimate odds ratios and 95% confidence \nintervals (CIs). In Paper IV, receiver operating characteristic (ROC) curves, with \nareas under the curves (AUCs) and 95% CIs, were calculated for TRAb IgG and \nIgM levels. The values are presented as medians (interquartile ranges (IQRs)), \nmeans ± standard deviations (SDs) or numbers (percentages (%)). p <0.05 was \nconsidered statistically significant.  \nIn Paper II, alpha diversity was tested to analyze the diversity of genera among \nsamples using the Shannon diversity index. Alpha diversity was calculated using \ndiversity, and an analysis of variance (ANOVA) was performed. Beta diversity \nwas calculated to detect differences in the microbiota composition among the \ngroups using the Bray‒Curtis dissimilarity index. Vegdist was used to calculate \nbeta diversity. Further significant differences in the dissimilarity index were tested \nwith Adonis, within the R package vegan.  \nGenetic analyses \nQuality control  \nIn Paper III, genotyping data were quality controlled (QC) by removing samples \nand markers using the following pipeline: exclusion of samples with ≥15% \nmissing rates; exclusion of markers with noncalled alleles; exclusion of markers \nwith missing call rates >0.05; exclusion of samples with ≥5% missing rates; \nexclusion of related samples (PI-HAT >0.1875); exclusion of samples whose \ngenotyped sex could not be determined; exclusion of samples with high \nheterozygosity rates (more than three times the SD of the mean); only autosomal \nSNPs were retained; removal of markers with Hardy‒Weinberg equilibrium P-\nvalue <1x10\n-5; removal of markers whose P-value for the difference in \nmissingness between cases and controls was <1x10-5; and removal of samples that \n\n41 \nwere outliers, identified using principal component analysis (deviation of more \nthan 6 times the interquartile range). In total, 140 samples passed QC.  \nCalculation of Polygenic risk score \nThe results from a genome-wide association study on endometriosis [51], available \nfrom the GWAS catalog GCTS004549 [46], were used for the calculation of the \nPRS. The 13 SNPs available in our data and with p-value <5 x 10 \n-8 were applied. \nThe weighted and unweighted PRSs were calculated as it is implemented in PLINK \nsoftware (version 1.9) [121]. \nPrincipal component analysis  \nFour principal components were calculated for each patient to control for population \nstratification. The genotyped data were  pruned to obtain SNPs with no linkage \ndisequilibrium using PLINK software [122], and SNPs from high-LD regions were \nexcluded. FlashPCA was subsequently used  to calculate the principal components \nof the SNP data.  \nEthical considerations \nAll studies were conducted according to the guidelines of the Declaration of \nHelsinki and approved by the Ethics Board of Lund University. Approval numbers \nwere as follows: for the MOS population 2012/594; for endometriosis patients \n2012/564, 2016/56 and 2016/375; for IBS patients 2017/171, 2017/810 and \n2021/05407–01; and for healthy controls 2020/02432 and 2021/00049. For Study \nII, III, IV and V, the Swedish Biobank approved the use of fecal and blood samples, \nrespectively, and the Swedish Authority for Privacy Protection approved the genetic \nanalyses (approval number 1565–2012). All the subjects provided written, informed \nconsent before inclusion in the studies and were informed about their right to \nwithdraw their consent at any time after inclusion.  \nNone of the study participants were expo sed to any medical risks associated with \nthe studies in the present thesis. All ex aminations by vaginal ultrasonography or \nlaparoscopy were performed for dia gnostic purposes, and patients with \nendometriosis were asked to participat e in the study after the diagnosis was \nconfirmed. Since personal data regardi ng health and genetic information are \nhandled, a potential integrity risk exists. The data in all the studies were transferred \nto coded datasets to minimize this risk. The potential benefits of these studies \noutweigh the potential risks and are considered justifiable.  \n \n \n\n\n\n43 \nResults \nBaseline characteristics  \nIn Paper I, differences in socioeconomic factors and lifestyle factors between \nwomen with endometriosis and those with IBS were found to be limited. Patients \nwith endometriosis were younger (p<0.001) and more often studying (p=0.006) than \npatients with IBS. No differences were identified in education, marital status, \nsmoking status, alcohol consumption or physical activity. The prevalence of hypo- \nand hyperthyroidism did not differ between endometriosis patients (8.4% and 1.4%) \nand IBS patients (9.0% and 1.0%). Hormonal treatment and analgesic treatment \nsuch as NSAIDs and opioids were more common in patients with endometriosis \n(40.7% vs. 20.6% and 18.7% vs. 9.0%, resp ectively). Patients with IBS used more \nproton pump inhibitors (20.6% vs. 4.2%), laxatives (16.6% vs. 3.3%), and \nantidiarrheic drugs (7.5% vs. 1.4%) (Table 3).  \nPatients with IBS reported more severe GI symptoms on VAS-IBS than did those \nwith endometriosis regarding abdominal pain (p<0.001), diarrhea (p<0.001), \nconstipation (p<0.001), bloating and flat ulence (p<0.001), vomiting and nausea \n(p<0.042), the influence of intestinal symptoms on daily life (p<0.001), and \npsychological well-being (p<0.003), after adjustment for confounders. A total of \n15% of the patients with endometriosis reported no GI symptoms. In endometriosis, \n47.2% of the women said that they were able to differentiate between abdominal \npain from endometriosis or from the GI tract.  \nAn initial triggering factor for GI sy mptoms was reported by 21.5% of the \nendometriosis patients and 27.1% of the IBS patients. A significant difference in \nwhat initially triggered the disease was observed between the groups. Menarche was \nthe most common trigger of endometriosis, and stress, infection or antibiotic \ntreatment were the most common triggers of IBS.  \nThe majority of patients with both endometriosis (51.6%) and IBS (87.9%) had tried \nvarious dietary changes due to GI symptoms. Among those patients, 73.3% with \nendometriosis and 72.0% with IBS experienced an improvement in their symptoms \n(p=1.000). \n \n \n\n44 \nTable 3 . Patient characteristics, pharmacological tr eatment and gastrointestinal symptoms differing \nsignificantly between patients with endometriosis and patients with IBS.  \nEndometriosis IBS P-value\nAge (years) 38 (33–43) 43 (33–55) <0.001 \nAlcohol intake per week, glasses \nn (%) \n<1  134 (62.6) 95 (47.7) \n1–4  66 (30.8) 76 (38.2) 0.022 \n5–9  11 (5.1) 24 (12.1) 0.004 \n≥10  2 (1.0) 4 (2.0) 0.684 \nDrugs n (%) \nNSAIDs 40 (18.7) 18 (9.0) 0.007 \nOpioids 20 (9.3) 0 <0.001 \nLaxatives and bulking agents 7 (3.3) 33 (16.6) <0.001 \nLoperamide 3 (1.4) 15 (7.5) 0.003 \nHormonal treatment  87 (40.7) 41 (20.6) <0.001 \nAbdominal pain 40 (9–72) 50 (34–65) <0.001 \nDiarrhea 11 (0–48) 52 (10–73) <0.001 \nConstipation 28 (0–65) 54 (10–75) <0.001 \nBloating and flatulence 50 (15–76) 76 (62–88) <0.001 \nVomiting and nausea 6 (0–35) 14 (2–40) 0.042 \nIntestinal symptoms’ \ninfluence on daily life \n35 (5–77) 71 (57–83) <0.001 \nPsychological well-being 32 (6–62) 47 (20–64) 0.003 \nIBS, irritable bowel syndrome. Gastrointestinal symptoms during the last 2 weeks were measured by \nthe visual analogue scale for irritable bowel syndrome (VAS-IBS). The values are presented as \nnumbers and percentages or medians and interquartile ranges (IQRs). A p-value <0.05 was considered \nto indicate statistical significance.  \nGut microbiota \nIn Paper II, we investigated the gut mi crobiota in patients with endometriosis \ncompared with that in people from the general population. According to the \nANOVA results, the alpha diversity was significantly higher in the control group \nthan in the endometriosis patient group (p=4.9e\n-0.5). The Adonis test revealed that \nthe beta diversity was also higher in the control group than in the endometriosis \ngroup, however the R2 value was low (0.02) (Table 4).  \nThe abundance of 19 gut bacteria at genus level differed between the endometriosis \npatients and the controls (Table 4). After correction for multiple testing, with a false \ndiscovery rate (FDR) of 0.05, the number was reduced to 12 bacteria belonging to \nthe classes Bacilli (N=1), Bacteroidia (N=4), Clostridia (N=4), Coriobacteriia (N=2) \nand Gammaproteobacteria (N=1). Two bacteria in the Bacteroidia class and two in \nthe Clostridia class were more abundant in patients than in controls, whereas two \ndifferent bacteria in the Bacteroidia and Clostridia classes were more abundant in \n\n45 \ncontrols than in patients. The genera in  the Bacilli and Coriobacteriia classes were \nless abundant, whereas the genus in Gamm aproteobacteria was more abundant in \npatients than in controls.  \nNo significant differences in microbiot a abundance were observed after FDR \nadjustment within the endometriosis cohort when stratified based on disease \nlocation, symptoms or hormone treatment. \nPatients who had received antibiotic treatment in the last six months were excluded, \nand after adjustment for the FDR, only th ree bacteria with a significant difference \nin abundance between patients and controls were detected, namely, Lachnospiria, \nOscillospira and a genus in the order Bacteroidales.  \n \n \nFigure 6. Altered gut microbiota. Image source: Adobe Stock.  \n  \n\n\n46 \nTable 4. Summary of organic findings in Papers II and IV. \nEndometriosis \npatients  \nControls  \nAlpha diversity Lower Higher \nBeta diversity Lower Higher \ng__Paraprevotella; f__Paraprevotellaceae; \no__Bacteroidales; c__Bacteroidia  \nLower Higher\ng__Adlercreutzia; f__Coriobacteriaceae; \no__Coriobacteriales; c__Coriobacteriia  \nLower Higher \ng__f__o__Bacteroidales; c__Bacteroidia Lower Higher\ng__Lachnospira; f__Lachnospiraceae; \no__Clostridiales; c__Clostridia  \nLower Higher \ng__Oscillospira; f__Ruminococcaceae; \no__Clostridiales; c__Clostridia  \nHigher Lower\ng__f__Coriobacteriaceae; o__Coriobacteriales; \nc__Coriobacteriia  \nLower Higher \ng__Bacteroides; f__Bacteroidaceae; o__Bacteroidales; \nc__Bacteroidia  \nHigher Lower\ng__Parabacteroides; f__Porphyromonadaceae; \no__Bacteroidales; c__Bacteroidia  \nHigher Lower \ng__f__o__SHA98; c__Clostridia  Lower Higher\ng__f__Enterobacteriaceae; o__Enterobacteriales; \nc__Gammaproteobacter  \nHigher Lower \ng__Turicibacter; f__Turicibacteraceae; \no__Turicibacterales; c__Bacilli  \nLower Higher\ng__Coprococcus; f__Lachnospiraceae; \no__Clostridiales; c__Clostridia  \nHigher Lower \ng__f__o__YS2; c__4C0d2  Lower Higher\ng__f__o__RF32; c__Alphaproteobacteria  Lower Higher \ng__f__Peptostreptococcaceae; o__Clostridiales; \nc__Clostridia  \nLower Higher\ng__f__Barnesiellaceae; o__Bacteroidales; \nc__Bacteroidia  \nLower Higher \ng__f__Halanaerobiaceae; o__Halanaerobiales; \nc__Clostridia  \nLower Higher\ng__f__o__RF39; c__Mollicutes Lower Higher \ng__f__Lachnospiraceae; o__Clostridiales; \nc__Clostridia  \nHigher Lower\nTRAb IgM levels Higher Lower \nTRAb IgG levels (Study IV) Higher Lower\n\n47 \nPolygenic risk score \nThe primary aim of Paper III was to examine whether the PRS for endometriosis \ndevelopment and different clinical presentations of the disease were associated. \nThe results revealed that in the third quartile of both the weighted PRS and \nunweighted PRS, fewer patients had spread endometriosis than in the lowest \nquartile (OR: 0.252; 95% CI: 0.081–0.782, p=0.017; OR: 0.182; 95% CI: 0.052–\n0.0630, p=0.007) and highest quartile (OR: 0.409; 95% CI: 0.136–1.288, p=0.111; \nOR: 0.245; 95% CI: 0.077–0.781, p=0.017). An inverse association between the \nsecond quartile of the weighted PRS and endometrial involvement of the GI tract \nwas observed (OR: 0.158; 95% CI: 0.026–0.949, p=0.044). The third quartile of \nthe unweighted PRS was associated with lower use of hormone therapy (OR: \n0.250; 95% CI: 0.075–0.829, p=0.023). However, both the sensitivity and \nspecificity for all the clinical outcomes were low. No associations between PRS \nand any of the analyzed circulating inflammatory proteins or TRAb were \nobserved.    \n \n \n \n \n \n \n \n \n \n \n \n  \n\n48 \nAntibodies (Papers IV and V) \nSera from 172 endometriosis patients had previously been analyzed for TRAb IgG \nlevels according to standardized methods at the Department of Clinical Chemistry, \nMalmö, with a detection limit of ≥1.0 IU/L. The results revealed that 29.1% of the \nendometriosis patients had TRAb IgG levels  above the detection limit of 1.0 IU/L, \nwhereas 2.6% of the controls from the general population did (p<0.001).   \nPrior to 2016, the detection limit was ≥0.3 IU/L. Serum samples from 128 of the \n172 endometriosis patients were also analysed for TRAb IgG levels prior to the \nchange in the detection limit. These results showed that 94.5% of the endometriosis \npatients had TRAb levels over ≥0.3 IU/L, whereas 7.9% of the controls had TRAb \nlevels greater than 0.3 IU/L in the MOS (p<0.001). ROC curves revealed an area \nunder the curve (AUC) of 0.940 for TRAb, with a detection limit ≥0.3 IU/L, and an \nAUC of 0.602, with a detection limit of 1. 0 IU/L. The serum levels of TRAb IgM \nwere also increased in patients with e ndometriosis compared with blood donor \ncontrols (p<0.001). \nThe concentrations of TRAb IgG did not  correlate with age, disease duration, \nthyroid hormone levels, TSH levels or GI symptoms. As expected, Graves’ disease \nwas associated with higher levels of TR Ab IgG (p=0.002). No difference in TRAb \nIgG concentrations was observed between endometriosis patients treated with and \nwithout hormonal therapy (p=0.554), those with isolated ovarian endometriosis \n(p=0.394) or those with endometriosis involving the bowel (p=0.123).  A difference \nin TRAb IgG levels was not observed between controls from the MOS who had IBS \n(n=25, 21.9%; p=0.655) or reported GI sy mptoms in the past two weeks (n=30, \n26.3%; p=0.885) and to those without a diagnosis or GI symptoms.  \nThe prevalence of autoantibodies against FSH, FSHR, hCG, LH, LHR or TSH was \nnot increased in patients with endometrios is compared with blood donor controls. \nThe titers of FSHR IgG (p=0.008), FSHR IgM (p<0.001) and TSH IgA (p=0.029) \nwere lower in patients than in blood donor controls.  \nWhen serum TRAb IgG levels were analyzed  in two different clinical laboratories \nin 2023, its levels were not confirmed to be elevated in patients with endometriosis \ncompared with heathy controls and pa tients with IBS. When analyzed in \nGothenburg with a detection limit of 0. 26 IU/L, the number of patients with \ndetectable serum levels of TRAb did no t differ between the endometriosis patients \n(n=10, 8.3%) and the controls (n=2, 4%) (p=0.512) or between the endometriosis \npatients and the IBS patients (n=3, 6%) (p=0 .758). The concentrations of TRAb in \nthe serum did not differ between the e ndometriosis patients and the controls \n(p=0.260) or between the endometriosis patients and the IBS patients (p=0.725).  \nConcordant results were found when the serum was analyzed in Malmö, with a \ndetection limit of 0.8 IU/L. TRAb was not more commonly detected in \nendometriosis patients (n=4, 4.9%) than in  controls (n=4, 8.0%) (p=0.710) or IBS \n\n49 \npatients (n=4, 8.0%), (p=0.710). The concentrations did not differ between the \nendometriosis patients and the controls (p=0.524) or between the endometriosis \npatients and the IBS patients (p=0.585). \n\n\n\n51 \nDiscussion \nGeneral discussion  \nSociodemographic factors, lifestyle and gastrointestinal symptoms \nA main finding from Study I was that women with IBS reported more severe GI \nsymptoms when estimated with a sel f-rating questionnaire than women with \nendometriosis did. Significant differe nces were observed in abdominal pain, \ndiarrhea, constipation, bloating and flat ulence, vomiting and nausea, the influence \nof intestinal symptoms on daily life, and psychological well-being. Similar results \nhave been reported in a previous study [123]. The results indicate that rating of \nsymptoms with a validated questionnai re, in combination with a thorough \nanamnesis, is valuable in clinical practice, to find which patients who should be \nfurther examined for endometriosis. Al though patients with IBS reported higher \nlevels of abdominal pain, patients with endometriosis were more often treated with \nanalgesic drugs. None of the patients with  IBS were treated with opioids, whereas \n9.3% of those with endometriosis were treated with opioids. The difference might \ndepend on fluctuations in pain during the menstrual cycle and on-demand treatment \nwith analgesics. Notably, in this study, we did not know what phase of the menstrual \ncycle the patients were experiencing while  estimating their symptoms using the \nVAS-IBS, which reflects only symptoms over the last two weeks. Additionally, in \nthis study, 37.9% of patients with endom etriosis used hormonal treatment, which \nefficiently relives the symptoms of many patients. Treatment with opioids in \npatients with IBS is not recommended since it aggravates GI dysfunction [124]. The \nopioid prescription in endometriosis should also be questioned, since this group of \npatients have a greater risk for chronic opioid use, and the benefits seems to be \nlimited [125]. \nThe gut microbiota \nWhen this thesis was initiated, only one pr evious study examined the alterations in \nthe gut microbiota in humans with endometriosis [126]. The main finding of that \nstudy was that women with stage 3–4 endom etriosis had an Escherichia/Shigella \ndominant gut microbiome. The hypothesis that endometriosis has an impact on the \n\n52 \ngut microbiota has also been supported by several animal studies. A systematic \nreview from 2020 identified in total six studies on the role of the gut microbiota in \nendometriosis [127]. A study of rhesus monkeys showed that monkeys with \nendometriosis had a significantly altered gut microbiota profile compared with \nhealthy controls [40]. The monkeys with endometriosis had higher concentrations \nof gram-negative bacteria and lower concentrations of lactobacilli.   \nOur study of the gut microbiota in endometriosis patients revealed an overall greater \ndiversity among controls than among patients with endometriosis. Most \nimportantly, the alpha diversity differed, indicating a decreased microbial richness \nin patients with endometriosis. The beta diversity also differed, although it was only \nmarginally higher in controls than in endometriosis patients.  \nSince 2020, the field has expanded rapidly and multiple studies investigating the gut \nmicrobiota in patients with endometriosis have been published [128]. Consistent \nfindings of an endometriosis–microbiome relationship have been reported. In \nagreement with our study, repeated studies have shown a lower diversity of the gut \nmicrobiota in endometriosis patients than in controls [129-131]. Patients with \nendometriosis have an increased abundance of  pathogens in their peritoneal fluid \nand a reduction in the abundance of protec tive microbes in their feces. In contrast, \nin one study, diversity analyses could not identify any differences between \nendometriosis and controls [132]. An elev ated Firmicutes/Bacteroidetes ratio and \nreduced abundances of Gardnerella, Lachnos pira, Paraprevotella and Sneathia are \nreported alterations in the gut microbiota of endometriosis patients [133]. A \ndepletion of Ruminococcus has also been  identified as a potential biomarker for \nendometriosis [131]. Increased abundances of Bifidobacterium, Blautia, Dorea, \nParabacteroides, and Enterobacteriaceae, mainly Escherichia/Shigella, have also \nbeen detected in the gut of patients with endometriosis. A recent study explored the \nrelationships between the gut microbiota and anatomical subtypes of endometriosis \nand recognized several associations. Different bacteria are associated with either an \nincreased or decreased risk of endometriosi s in the ovaries, fallopian tube, pelvic \nperitoneum, vagina, rectovaginal septum or adenomyosis [134].  \nStudies on the role of the gut microbiota in the pathogenesis of endometriosis are \nincreasing, and results indicate that the microbiota is related to estrogen metabolism, \ninflammation, and immunity, contributing to the development of endometriosis \n[38]. It should be considered that the altered composition of gut microbiota also \ncould depend on the GI symptoms in these patients. One example is gut transit time, \nwhich is known to be involved in shaping the microbiota composition [135]. \n\n53 \nTRAb and endometriosis     \nAn increased prevalence of thyroid disord ers in patients with endometriosis has \npreviously been described in several st udies [54-57]. In the total endometriosis \ncohort in this study, the prevalence of hypothyroidism was 8.4%. Among patients \nwith IBS, 9.0% were diagnosed with hypothyroidism.  \nIn 2018, a previous study reported novel findings of significantly elevated levels of \nTRAb IgG in women with endometriosis co mpared with controls from the general \npopulation [64]. In agreement with previous results, Study IV revealed that 94.5% \nof women with endometriosis had TRAb Ig G levels over the detection limit of 0.3 \nIU/L, whereas 7.9% of controls did. The levels of TRAb did not differ between \nendometriosis patients with or without  hypothyroidism, but as expected, patients \nwith Graves’ disease had high levels of TRAb. An in-house analysis of TRAb IgM \nlevels also revealed increased levels in patients with endometriosis compared with \ncontrols. Although the levels of TRAb Ig M also were found to be elevated in \nendometriosis, we only chose to analyze TR Ab IgG further. In our first study of \nTRAb, the ROC curves revealed a larger AUC for IgG than for IgM. Additionally, \nTRAb IgG is analyzed in r outine clinical practice with standardized methods in \ncontrast to TRAb IgM.  \nThe analyses were repeated in a new cohort at two different clinical laboratories to \nfurther evaluate whether TRAb IgG levels  were truly elevated in patients with \nendometriosis. The results showed that current clinical laboratory setups for \nanalyzing TRAbs cannot be used to detect elevated levels, as previously described \nusing other methods. The clinical use of a TRAb analysis is to identify thyroid \ndisorders with high sensitivity and specif icity. In recent years, the methods have \nbeen developed to be more specific for Graves’ disease. One critical concern with \nthe initial findings of elevated TRAb levels  was whether the suggested increase in \nTRAb expression among endometriosis patients was caused by cross-reactivity with \nsome other antibodies. TSH and its cognate  receptor belong to  the glycoprotein \nhormone family, which also includes the closely related glycoproteins FSH, LH and \nhCG. Their structural similarities increase the possibility of cross-reactivity [136]. \nIn our study, no differences in the preval ence or levels of any of the analyzed \nantibodies or their receptors were identified between the endometriosis patients and \nthe controls, indicating that the elevated TRAb levels are not explained by cross-\nreactivity. Even if no cross-reactivity was detected in this study, the question \nremains as to whether the TRAbs detected in previous studies were truly elevated.  \nTSH receptors have been identified in the endometrium and ectopic endometrial \ntissue [61, 62]. Theoretically, different subclasses of TSH receptors may be \nexpressed in different organs, although no proof of this expression pattern has been \npublished. Additionally, heterogeneity ma y exist among TRAbs, and TRAbs with \ndifferent antigenic epitopes have been detected in patients with autoimmune thyroid \n\n54 \ndiseases [137, 138]. Slightly different TR Abs may be detected in patients with \nendometriosis than in those with in thyroid disease. \nGenetic analyses of endometriosis  \nIn our study, the effects of 13 risk va riants were computed into a PRS for \nendometriosis to assess whether an association with the clinical presentations of the \ndisease existed. The results showed an inverse association between the third quartile \nof weighted and unweighted PRS and the spread of endometriosis, between the \nsecond quartile of the weighted PRS and GI involvement, and between the third \nquartile of the unweighted PRS and horm one treatment. However, the genetic \nvariants involved in the development of the disease seemed to be of no clinical use \nfor the prediction of the clinical presenta tion since the sensitiv ity and specificity \nwere low. This is in line with another study, suggesting that PRS for endometriosis \ndoes not capture an increased risk for a specific subtype of endometriosis [52]. \nMethodological considerations \nThe study design of all the papers included in this thesis is cross-sectional; therefore, \ncausality could not be conclusively dete rmined. The patients with endometriosis \nincluded in Paper II, III and IV had received their diagnosis prior to inclusion in the \nstudy, and a majority were already und ergoing treatment. Native blood and fecal \nsamples were therefore not available for analysis.  \nEndometriosis is a heterogenous disease with patients ranging from basically \nasymptomatic to having severe symptoms [139]. There is a possibility that controls \ncould have undiagnosed endometriosis without prominent symptoms. This risk was \nreduced by excluding all controls who re ported GI symptoms. Theoretically, one \nway to minimise this risk could have been  to examine all study participants with \nultrasound, however this was not practically possible in this thesis.  \nGI symptoms are known to be fluctuating over the menstrual cycle, not the least in \npatients with endometriosis [104]. For the st udies in this thesis, we did not obtain \ndata regarding what phase of the menstrual cycle patients or controls were in. Also, \nof the patients with endometriosis 37.9% were currently using hormonal treatment, \nwhich can affect the menstrual cycle and cause amenorrhea.  \nThe clinical methods used to analyze TR Ab IgG are developed to identify thyroid \ndisease. Over the last years, the methods have become more specific for Graves’ \ndisease which is positive for diagnostic pur poses of thyroid disease. However, the \nnew methods seem to be inferior at identifying the variant of antibodies previously \nidentified in endometriosis. To furthe r investigate the slightly elevated \n\n55 \nconcentrations of TRAb that in some st udies have been identified in patients with \nendometriosis, analytical methods th at are more sensitive in the lower \nconcentrations are needed. When TRAb IgG was analyzed in Gothenburg, the \nlowest given concentrations were only available for research and not for clinical use \ndue to low sensitivity.   \nThere are many different questionnaires available for research and clinical practice \nto estimate GI symptoms and quality of life and psychological symptoms. The IBS-\nSSS is one of the most frequently used to measure for IBS severity and was used in \nstudy I and V [140]. However, the IBS-SSS does not measure different bowel \nsymptoms separately. In this thesis, VAS-IBS was also used to estimate GI \nsymptoms, quality of life and psychological  well-being. One of the advantages of \nVAS-IBS is that symptoms are graded on a continuous scale unlike other commonly \nused questionnaires such as the Gastroin testinal Symptom Rating Scale (GSRS), \nwhich VAS-IBS has been validated against [114].  \n \n\n\n\n57 \nConclusions \nThis thesis investigated potential biom arkers for endometriosis. Based on the \nfindings of the included papers, the following conclusions were drawn: \n1. Differences in socioeconomic factors and lifestyle factors are limited \nbetween women with endometriosis and those with IBS. This finding \nhighlights the diagnostic value of potential biomarkers.  \n2. Patients with IBS seem to have more severe GI symptoms than those with \nendometriosis in terms of abdominal pain, diarrhea, constipation, bloating \nand flatulence, vomiting and nausea, the influence of intestinal symptoms \non daily life, and psychological well-being, as evaluated with the VAS-IBS. \n3. Both alpha diversity and beta divers ity are higher in controls from the \ngeneral population than in patients with endometriosis. \n4. Genetic variants involved in the risk of developing endometriosis cannot be \nused to explain the clinical presen tations of endometriosis via the \ncalculation of PRS.  \n5. TRAb IgG levels, which were analyzed with previous clinical methods, and \nTRAb IgM levels, which were analyzed in house, were elevated in patients \nwith endometriosis compared with cont rols. No signs that the results were \ncaused by cross-reactivity with other antibodies were observed.  \n6. With the current routine clinical methods used to analyze TRAb IgG levels, \nelevated TRAb IgG levels could not be detected in patients with \nendometriosis.   \n \n\n\n\n59 \nFuture perspectives  \nSeveral studies have revealed changes in the microbiota of patients with \nendometriosis, and more research is continuously published. However, a consensus \namong the results is lacking, which might  be explained by the large number and \ncomplex composition of bacteria in the gut, methods of microbiota detection, \ninconsistency in diagnostic criteria and confounders for the microbiota composition. \nA challenge for further studies is to standardize sample collection and analysis to \nenable comparisons between studies. A deeper understanding of the gut microbiota \nand microbiome-derived metabolites would provide a basis for the development of \nnew diagnostic and treatment methods fo r endometriosis. The side effects of \nmedical and surgical treatments used today could be reduced if interventions that \ntarget the microbiota are developed.    \nThe genetic information identified from GWASs of endometriosis is not able to \nexplain the clinical presentation of the disease. For this task, an analysis of genetic \nvariants involved in disease presentation is needed to develop useful PRSs.  \nThe present thesis evaluated TRAb as a potential biomarker for endometriosis. An \nin-house analysis of TRAb IgM levels and previous methods for clinical analyses \nof TRAb IgG levels indicated elevated levels in patients with endometriosis. The \nlevels were moderate and required methodological sensitivity at low levels, which \ncurrent methods cannot provide. The results of elevated levels of TRAb IgG in \nendometriosis patients could not be reproduced with the current clinical methods. \nFurther research on TRAb and an evaluation of the previous positive findings may \nbe performed in laboratory experimental settings. The roles of TSH receptors and \nautoantibodies against TSH receptors in the pathophysiology of endometriosis \ndeserve further research. \n \n\n\n\n61 \nAcknowledgements \nProfessor Bodil Ohlsson, my main supervisor, thank you for inviting me to join you \nin your research and taking me on as a PhD student. Thank you for your endless \ncreativity, encouragement and support. You are a true inspiration. \nBodil Roth, my cosupervisor, thank you for sharing your great knowledge in the \nlaboratory with me and for the collaboration in recruiting patients.  \nSimon Timpka and Olle Melander, my half-time opponents, thank you for your \nfeedback, encouragement and inspiring comments.  \nI thank my coauthors, Louise Brunkwall, Marju Orho-Melander, Koldo-Garcia-\nEtxebarria, Mauro D´Amato , Anna Åkesson , Christer Borgfeldt , Malin Ek , \nLinnea Kronvall , Povilas Sladkevicius , Ligita Jokubkiene  and Charlotte \nBecker, for their valuable contributions. \nTo my colleagues at the Department of Transplantation in Malmö, thank you for \nsupporting me and giving me time to work on my thesis. \nMy parents,  Mats and Pernilla , thank you for all the love, encouragement, and \npossibilities you have given me throughout the years.   \nTo my sister Edith, thank you for inspiring me and showing me that everything is \npossible.  \nMy husband, Simon, I thank you for always standing by my side and making me \nthe best version of myself. Experiencing life with you is more than I could have ever \nwished for. I love you.   \n\n\n\n63 \nReferences \n1. Giudice, L.C. and L.C. Kao, Endometriosis. Lancet, 2004. 364(9447): p. 1789-99. \n2. Moradi, Y., et al., A systematic review on the prevalence of endometriosis in \nwomen. Indian J Med Res, 2021. 154(3): p. 446-454. \n3. Sinaii, N., et al., Differences in characteristics among 1,000 women with \nendometriosis based on extent of disease. Fertil Steril, 2008. 89(3): p. 538-45. \n4. Maroun, P., et al., Relevance of gastrointestinal symptoms in endometriosis. Aust \nN Z J Obstet Gynaecol, 2009. 49(4): p. 411-4. \n5. Issa, B., et al., Visceral hypersensitivity in endometriosis: a new target for \ntreatment? Gut, 2012. 61(3): p. 367-72. \n6. Roman, H., et al., Are digestive symptoms in women presenting with pelvic \nendometriosis specific to lesion localizations? A preliminary prospective study. \nHum Reprod, 2012. 27(12): p. 3440-9. \n7. Orlov, S. and L. Jokubkiene, Prevalence of endometriosis and adenomyosis at \ntransvaginal ultrasound examination in symptomatic women. Acta Obstet \nGynecol Scand, 2022. 101(5): p. 524-531. \n8. ESHRE. Guideline Endometriosis 2022. Available from: \nhttps://www.eshre.eu/Guidelines-and-Legal/Guidelines/Endometriosis-\nguideline.aspx. \n9. Hudelist, G., et al., Diagnostic delay for endometriosis in Austria and Germany: \ncauses and possible consequences. Hum Reprod, 2012. 27(12): p. 3412-6. \n10. De Corte, P., et al., Time to Diagnose Endometriosis: Current Status, Challenges \nand Regional Characteristics-A Systematic Literature Review. Bjog, 2025. \n132(2): p. 118-130. \n11. Consul, N., et al., Continued improvement to imaging diagnosis and treatment \ntriage of endometriosis: The role of the multi-disciplinary conference. Curr Probl \nDiagn Radiol, 2024. 53(6): p. 663-669. \n12. Endometriosis: diagnosis and management. London: National Institute for Health \nand Care Excellence (NICE) 2024 Apr 16; (NICE Guideline, No. 73.) [Available \nfrom: https://www.ncbi.nlm.nih.gov/books/NBK604070/. \n13. Kovács, Z., et al., Novel diagnostic options for endometriosis - Based on the \nglycome and microbiome. J Adv Res, 2021. 33: p. 167-181. \n14. Gupta, D., et al., Endometrial biomarkers for the non-invasive diagnosis of \nendometriosis. Cochrane Database Syst Rev, 2016. 4(4): p. Cd012165. \n15. Kimber-Trojnar, Ż., et al., The Potential of Non-Invasive Biomarkers for Early \nDiagnosis of Asymptomatic Patients with Endometriosis. J Clin Med, 2021. \n10(13). \n\n64 \n16. Kalaitzopoulos, D.R., et al., Treatment of endometriosis: a review with \ncomparison of 8 guidelines. BMC Womens Health, 2021. 21(1): p. 397. \n17. Hickey, M., K. Ballard, and C. Farquhar, Endometriosis. Bmj, 2014. 348: p. \ng1752. \n18. Johnson, N.P. and L. Hummelshoj, Consensus on current management of \nendometriosis. Hum Reprod, 2013. 28(6): p. 1552-68. \n19. Martin, D.C., Hysterectomy for treatment of pain associated with endometriosis. J \nMinim Invasive Gynecol, 2006. 13(6): p. 566-72. \n20. Mira, T.A.A., et al., Systematic review and meta-analysis of complementary \ntreatments for women with symptomatic endometriosis. Int J Gynaecol Obstet, \n2018. 143(1): p. 2-9. \n21. Sampson, J.A., Metastatic or Embolic Endometriosis, due to the Menstrual \nDissemination of Endometrial Tissue into the Venous Circulation. Am J Pathol, \n1927. 3(2): p. 93-110.43. \n22. Halme, J., et al., Retrograde menstruation in healthy women and in patients with \nendometriosis. Obstet Gynecol, 1984. 64(2): p. 151-4. \n23. Burney, R.O. and L.C. Giudice, Pathogenesis and pathophysiology of \nendometriosis. Fertil Steril, 2012. 98(3): p. 511-9. \n24. Sasson, I.E. and H.S. Taylor, Stem cells and the pathogenesis of endometriosis. \nAnn N Y Acad Sci, 2008. 1127: p. 106-15. \n25. Treloar, S.A., et al., Genetic influences on endometriosis in an Australian twin \nsample. sueT@qimr.edu.au. Fertil Steril, 1999. 71(4): p. 701-10. \n26. Saha, R., et al., Heritability of endometriosis. Fertil Steril, 2015. 104(4): p. 947-\n952. \n27. Borghese, B., et al., Recent insights on the genetics and epigenetics of \nendometriosis. Clin Genet, 2017. 91(2): p. 254-264. \n28. Guo, S.W., Epigenetics of endometriosis. Mol Hum Reprod, 2009. 15(10): p. 587-\n607. \n29. Edgar, R.C., Updating the 97% identity threshold for 16S ribosomal RNA OTUs. \nBioinformatics, 2018. 34(14): p. 2371-2375. \n30. Robles-Alonso, V. and F. Guarner, [Progress in the knowledge of the intestinal \nhuman microbiota]. Nutr Hosp, 2013. 28(3): p. 553-7. \n31. Poonam Jethwani, K.G., Gut Microbiota in Health and Diseases – A Review. \nInt.J.Curr.Microbiol.App.Sci, 2019. 8(8): p. 1586-1599. \n32. Seong, C.N., et al., Taxonomic hierarchy of the phylum Firmicutes and novel \nFirmicutes species originated from various environments in Korea. J Microbiol, \n2018. 56(1): p. 1-10. \n33. Nagano, Y., K. Itoh, and K. Honda, The induction of Treg cells by gut-indigenous \nClostridium. Curr Opin Immunol, 2012. 24(4): p. 392-7. \n34. Lopetuso, L.R., et al., Commensal Clostridia: leading players in the maintenance \nof gut homeostasis. Gut Pathog, 2013. 5(1): p. 23. \n35. Zhang, Y.J., et al., Impacts of gut bacteria on human health and diseases. Int J \nMol Sci, 2015. 16(4): p. 7493-519. \n36. Arvonen, M., et al., Gut microbiota-host interactions and juvenile idiopathic \narthritis. Pediatr Rheumatol Online J, 2016. 14(1): p. 44. \n\n65 \n37. Huipeng, W., et al., The differences in colonic mucosal microbiota between \nnormal individual and colon cancer patients by polymerase chain reaction-\ndenaturing gradient gel electrophoresis. J Clin Gastroenterol, 2014. 48(2): p. \n138-44. \n38. Guo, C. and C. Zhang, Role of the gut microbiota in the pathogenesis of \nendometriosis: a review. Front Microbiol, 2024. 15: p. 1363455. \n39. Baker, J.M., L. Al-Nakkash, and M.M. Herbst-Kralovetz, Estrogen-gut \nmicrobiome axis: Physiological and clinical implications. Maturitas, 2017. 103: \np. 45-53. \n40. Flores, R., et al., Fecal microbial determinants of fecal and systemic estrogens \nand estrogen metabolites: a cross-sectional study. J Transl Med, 2012. 10: p. 253. \n41. Zhang, Q., et al., Enhanced estrogen-induced proliferation in obese rat \nendometrium. Am J Obstet Gynecol, 2009. 200(2): p. 186.e1-8. \n42. Karmarkar, D. and K.L. Rock, Microbiota signalling through MyD88 is necessary \nfor a systemic neutrophilic inflammatory response. Immunology, 2013. 140(4): p. \n483-92. \n43. Ivanov, II, et al., Induction of intestinal Th17 cells by segmented filamentous \nbacteria. Cell, 2009. 139(3): p. 485-98. \n44. Zhang, X., et al., Peritoneal fluid concentrations of interleukin-17 correlate with \nthe severity of endometriosis and infertility of this disorder. Bjog, 2005. 112(8): p. \n1153-5. \n45. Visscher, P.M., et al., 10 Years of GWAS Discovery: Biology, Function, and \nTranslation. Am J Hum Genet, 2017. 101(1): p. 5-22. \n46. Buniello, A., et al., The NHGRI-EBI GWAS Catalog of published genome-wide \nassociation studies, targeted arrays and summary statistics 2019. Nucleic Acids \nRes, 2019. 47(D1): p. D1005-d1012. \n47. Dudbridge, F., Power and predictive accuracy of polygenic risk scores. PLoS \nGenet, 2013. 9(3): p. e1003348. \n48. Lambert, S.A., G. Abraham, and M. Inouye, Towards clinical utility of polygenic \nrisk scores. Hum Mol Genet, 2019. 28(R2): p. R133-r142. \n49. Lewis, C.M. and E. Vassos, Polygenic risk scores: from research tools to clinical \ninstruments. Genome Med, 2020. 12(1): p. 44. \n50. Lee, S.H., et al., Estimation and partitioning of polygenic variation captured by \ncommon SNPs for Alzheimer's disease, multiple sclerosis and endometriosis. Hum \nMol Genet, 2013. 22(4): p. 832-41. \n51. Sapkota, Y., et al., Meta-analysis identifies five novel loci associated with \nendometriosis highlighting key genes involved in hormone metabolism. Nat \nCommun, 2017. 8: p. 15539. \n52. Kloeve-Mogensen, K., et al., Polygenic Risk Score Prediction for Endometriosis.\n \nFront Reprod Health, 2021. 3: p. 793226. \n53. Doufas, A.G. and G. Mastorakos, The hypothalamic-pituitary-thyroid axis and the \nfemale reproductive system. Ann N Y Acad Sci, 2000. 900: p. 65-76. \n54. Korošec, S., et al., Coexistence of Endometriosis and Thyroid Autoimmunity in \nInfertile Women: Impact on in vitro Fertilization and Reproductive Outcomes. \nGynecol Obstet Invest, 2024. 89(5): p. 413-423. \n\n66 \n55. Yuk, J.S., et al., Graves Disease Is Associated With Endometriosis: A 3-Year \nPopulation-Based Cross-Sectional Study. Medicine (Baltimore), 2016. 95(10): p. \ne2975. \n56. Sinaii, N., et al., High rates of autoimmune and endocrine disorders, \nfibromyalgia, chronic fatigue syndrome and atopic diseases among women with \nendometriosis: a survey analysis. Hum Reprod, 2002. 17(10): p. 2715-24. \n57. Poppe, K., et al., Thyroid dysfunction and autoimmunity in infertile women. \nThyroid, 2002. 12(11): p. 997-1001. \n58. Peyneau, M., et al., Role of thyroid dysimmunity and thyroid hormones in \nendometriosis. Proc Natl Acad Sci U S A, 2019. 116(24): p. 11894-11899. \n59. Ahn, S.H., et al., Pathophysiology and Immune Dysfunction in Endometriosis. \nBiomed Res Int, 2015. 2015: p. 795976. \n60. Shahrara, S., V. Drvota, and C. Sylvén, Organ specific expression of thyroid \nhormone receptor mRNA and protein in different human tissues. Biol Pharm Bull, \n1999. 22(10): p. 1027-33. \n61. Aghajanova, L., et al., Receptors for thyroid-stimulating hormone and thyroid \nhormones in human ovarian tissue. Reprod Biomed Online, 2009. 18(3): p. 337-\n47. \n62. Aghajanova, L., et al., Thyroid-stimulating hormone receptor and thyroid \nhormone receptors are involved in human endometrial physiology. Fertil Steril, \n2011. 95(1): p. 230-7, 237.e1-2. \n63. Van Voorhis, B.J., et al., Primary hypothyroidism associated with multicystic \novaries and ovarian torsion in an adult. Obstet Gynecol, 1994. 83(5 Pt 2): p. 885-\n7. \n64. Ek, M., et al., Characteristics of endometriosis: A case-cohort study showing \nelevated IgG titers against the TSH receptor (TRAb) and mental comorbidity. Eur \nJ Obstet Gynecol Reprod Biol, 2018. 231: p. 8-14. \n65. Mearin, F., et al., Bowel Disorders. Gastroenterology, 2016. \n66. Oka, P., et al., Global prevalence of irritable bowel syndrome according to Rome \nIII or IV criteria: a systematic review and meta-analysis. Lancet Gastroenterol \nHepatol, 2020. 5(10): p. 908-917. \n67. Lovell, R.M. and A.C. Ford, Global prevalence of and risk factors for irritable \nbowel syndrome: a meta-analysis. Clin Gastroenterol Hepatol, 2012. 10(7): p. \n712-721.e4. \n68. Hellström, P.M. and P. Benno, The Rome IV: Irritable bowel syndrome - A \nfunctional disorder. Best Pract Res Clin Gastroenterol, 2019. 40-41: p. 101634. \n69. Vasant, D.H., et al., British Society of Gastroenterology guidelines on the \nmanagement of irritable bowel syndrome. Gut, 2021. 70(7): p. 1214-1240. \n70. Whitehead, W.E., O. Palsson, and K.R. Jones, Systematic review of the \ncomorbidity of irritable bowel syndrome with other disorders: what are the \ncauses and implications? Gastroenterology, 2002. 122(4): p. 1140-56. \n71. Riedl, A., et al., Somatic comorbidities of irritable bowel syndrome: a systematic \nanalysis. J Psychosom Res, 2008. 64(6): p. 573-82. \n72. Choung, R.S., et al., Irritable bowel syndrome and chronic pelvic pain: a \npopulation-based study. J Clin Gastroenterol, 2010. 44(10): p. 696-701. \n\n67 \n73. Pati, G.K., et al., Irritable Bowel Syndrome and the Menstrual Cycle. Cureus, \n2021. 13(1): p. e12692. \n74. Han, C.J. and G.S. Yang, Fatigue in Irritable Bowel Syndrome: A Systematic \nReview and Meta-analysis of Pooled Frequency and Severity of Fatigue. Asian \nNurs Res (Korean Soc Nurs Sci), 2016. 10(1): p. 1-10. \n75. Sperber, A.D. and R. Dekel, Irritable Bowel Syndrome and Co-morbid \nGastrointestinal and Extra-gastrointestinal Functional Syndromes. J \nNeurogastroenterol Motil, 2010. 16(2): p. 113-9. \n76. Hausteiner-Wiehle, C. and P. Henningsen, Irritable bowel syndrome: relations \nwith functional, mental, and somatoform disorders. World J Gastroenterol, 2014. \n20(20): p. 6024-30. \n77. Ohlsson, B., Extraintestinal manifestations in irritable bowel syndrome: A \nsystematic review. Therap Adv Gastroenterol, 2022. 15: p. 17562848221114558. \n78. Chong, P.P., et al., The Microbiome and Irritable Bowel Syndrome - A Review on \nthe Pathophysiology, Current Research and Future Therapy. Front Microbiol, \n2019. 10: p. 1136. \n79. Koloski, N.A., M. Jo nes, and N.J. Talley, Evidence that independent gut-to-brain \nand brain-to-gut pathways operate in the irritable bowel syndrome and functional \ndyspepsia: a 1-year population-based prospective study. Aliment Pharmacol \nTher, 2016. 44(6): p. 592-600. \n80. Staudacher, H.M., et al., Irritable bowel syndrome and mental health comorbidity \n- approach to multidisciplinary management. Nat Rev Gastroenterol Hepatol, \n2023. 20(9): p. 582-596. \n81. Akbari, R., et al., Attention in irritable bowel syndrome: A systematic review of \naffected domains and brain-gut axis interactions. J Psychosom Res, 2025. 191: p. \n112067. \n82. Chey, W.D., J. Kurlander, and S. Eswaran, Irritable bowel syndrome: a clinical \nreview. Jama, 2015. 313(9): p. 949-58. \n83. Dai, C. and M. Jiang, The incidence and risk factors of post-infectious irritable \nbowel syndrome: a meta-analysis. Hepatogastroenterology, 2012. 59(113): p. 67-\n72. \n84. Törnblom, H., et al., Colonic transit time and IBS symptoms: what's the link? Am \nJ Gastroenterol, 2012. 107(5): p. 754-60. \n85. Pittayanon, R., et al., Gut Microbiota in Patients With Irritable Bowel Syndrome-\nA Systematic Review. Gastroenterology, 2019. 157(1): p. 97-108. \n86. Wang, L., et al., Gut Microbial Dysbiosis in the Irritable Bowel Syndrome: A \nSystematic Review and Meta-Analysis of Case-Control Studies. J Acad Nutr Diet, \n2020. 120(4): p. 565-586. \n87. Duan, R., et al., Alterations of Gut Microbiota in Patients With Irritable Bowel \nSyndrome Based on 16S rRNA-Targeted Sequencing: A Systematic Review. Clin \nTransl Gastroenterol, 2019. 10\n(2): p. e00012. \n88. Thabane, M., D.T. Kottachchi, and J.K. Marshall, Systematic review and meta-\nanalysis: The incidence and prognosis of post-infectious irritable bowel \nsyndrome. Aliment Pharmacol Ther, 2007. 26(4): p. 535-44. \n\n68 \n89. Thabane, M. and J.K. Marshall, Po st-infectious irritable bowel syndrome. World\nJ Gastroenterol, 2009. 15(29): p. 3591-6.\n90.\nBöhn, L., et al., Diet low in FODMAPs reduces symptoms of irritable bowel\nsyn\ndrome as well as traditional dietary advice: a randomized controlled trial.\nGastroenterology, 2015. 149(6): p. 1399-1407.e2.\n91.\nHookway, C., et al., Irritable bowel syndrome in adults in primary care: summary\nof\n updated NICE guidance. Bmj, 2015. 350: p. h701.\n9\n2.\nWall, G.C., et al., Irritable bowel syndrome: a concise review of current\ntreatment concepts. World J Gastroenterol, 2014. 20(27): p. 8796-806.\n9\n3. M\nai, F., Somatization disorder: a practical review. Can J Psychiatry, 2004.\n49(1\n0): p. 652-62.\n94.\nRadu, M., et al., Predictors of outcome in cognitive and behavioural interventions\nfor irritable bowel syndrome. \nA meta-analysis. J Gastrointestin Liver Dis, 2018.\n27(3\n): p. 257-263.\n95.\nLövdahl, J., et al., Nurse-Administered, Gut-Directed Hypnotherapy in IBS:\nEfficacy and Factors Predicting a Positive Response. Am J Clin Hypn, 2015.\n58(1\n): p. 100-14.\n9\n6.\nNabi, M.Y., et al., Endometriosis and irritable bowel syndrome: A systematic\nreview and \nmeta-analyses. Front Med (Lausanne), 2022. 9: p. 914356.\n97.\nSchomacker, M.L., et al., Is endometriosis associated with irritable bowel\nsyn\ndrome? A cross-sectional study. Eur J Obstet Gynecol Reprod Biol, 2018. 231:\np. 6\n5-69.\n98. Viganò, D., F. Zara, and P. Usai, Irritable bowel syndrome and endometriosis:\nNew insights for old diseases. Dig Liver Dis, 2018. 50(3): p. 213-219.\n99. Kennedy, P.J., et al., Irritable bowel syndrome: a microbiome-gut-brain axis\ndisorder? World J Gastroenterol, 2014. 20(39): p. 14105-25.\n100. Tang, H.Y., et al., Uncovering the pathophysiology of irritable bowel syndrome\nby ex\nploring the gut-brain axis: a narrative review. Ann Transl Med, 2021. 9(14):\np\n. 11\n87.\n101.\nMoore, J.S., et al., Endometriosis in patients with irritable bowel syndrome:\nS\npecific symptomatic and demographic profile, and response to the low\nFODMAP diet. A\nust N Z J Obstet Gynaecol, 2017. 57(2): p. 201-205.\n102. Hammar, O., et al., Depletion of enteric gonadotropin-releasing hormone is found\nin a few patients suffering from severe gastrointestinal dysmotility. Scand J\nGastro\nenterol, 2012. 47(10): p. 1165-73.\n103.\nYung, Y., et al., Localization of luteinizing hormone receptor protein in the\nhu\nman ovary. Mol Hum Reprod, 2014. 20(9): p. 844-9.\n104.\nBernstein, M.T., et al., Gastrointestinal symptoms before and during menses in\nhealthy women. BMC Womens Health, 2014. 14: p. 14.\n1\n05. Denk, F., S.B. McMahon, and I. Tracey, Pain vulnerability: a neurobiological\npers\npective. Nat Neurosci, 2014. 17(2): p. 192-200.\n106. Mal\nykhina, A.P., Neural mechanisms of pelvic organ cross-sensitization.\nNeuroscience, 2007. 149(3): p. 660-72.\n107.\nCoffin, B., et al., Alteration of the spinal modulation of nociceptive processing in\npatients with irritable bowel syndrome. Gut, 2004. 53(10): p. 1465-70.\n\n69 \n108. Stabell, N., et al., Widespread hyperalgesia in adolescents with symptoms of \nirritable bowel syndrome: results from a large population-based study. J Pain, \n2014. 15(9): p. 898-906. \n109. Stratton, P. and K.J. Berkley, Chronic pelvic pain and endometriosis: \ntranslational evidence of the relationship and implications. Hum Reprod Update, \n2011. 17(3): p. 327-46. \n110. Guerriero, S., et al., Systematic approach to sonographic evaluation of the pelvis \nin women with suspected endometriosis, including terms, definitions and \nmeasurements: a consensus opinion from the International Deep Endometriosis \nAnalysis (IDEA) group. Ultrasound Obstet Gynecol, 2016. 48(3): p. 318-32. \n111. Brunkwall, L., et al., The Malmö Offspring Study (MOS): design, methods and \nfirst results. Eur J Epidemiol, 2021. 36(1): p. 103-116. \n112. Ohlsson, B., M. Orho-Melander, and P.M. Nilsson, Higher Levels of Serum \nZonulin May Rather Be Associated with Increased Risk of Obesity and \nHyperlipidemia, Than with Gastrointestinal Symptoms or Disease Manifestations. \nInt J Mol Sci, 2017. 18(3). \n113. Ek, M., et al., AXIN1 in Plasma or Serum Is a Potential New Biomarker for \nEndometriosis. Int J Mol Sci, 2019. 20(1). \n114. Bengtsson, M., B. Ohlsson, and K. Ulander, Development and psychometric \ntesting of the Visual Analogue Scale for Irritable Bowel Syndrome (VAS-IBS). \nBMC Gastroenterol, 2007. 7: p. 16. \n115. Bengtsson, M., et al., Further validation of the visual analogue scale for irritable \nbowel syndrome after use in clinical practice. Gastroenterol Nurs, 2013. 36(3): p. \n188-98. \n116. Yoo, H.Y., et al., Validation of the Korean version of visual analogue scale for \nirritable bowel syndrome questionnaire for assessment of defecation pattern \nchanges. Ann Surg Treat Res, 2018. 94(5): p. 254-261. \n117. Bengtsson, M., et al., Evaluation of gastrointestinal symptoms in different patient \ngroups using the visual analogue scale for irritable bowel syndrome (VAS-IBS). \nBMC Gastroenterol, 2011. 11: p. 122. \n118. Francis, C.Y., J. Mo rris, and P.J. Whorwell, The irritable bowel severity scoring \nsystem: a simple method of monitoring irritable bowel syndrome and its progress. \nAliment Pharmacol Ther, 1997. 11(2): p. 395-402. \n119. Caporaso, J.G., et al., QIIME allows analysis of high-throughput community \nsequencing data. Nat Methods, 2010. 7(5): p. 335-6. \n120. Obesity: preventing and managing the global epidemic. Report of a WHO \nconsultation. World Health Organ Tech Rep Ser, 2000. 894: p. i-xii, 1-253. \n121. Li, S.X., et al., Prospective Evaluation of the Addition of Polygenic Risk Scores to \nBreast Cancer Risk Models. JNCI Cancer Spectr, 2021. 5(3). \n122. Chang, C.C., et al., Second-generation PLINK: rising to the challenge of larger \nand richer datasets. Gigascience, 2015. 4: p. 7. \n123. Saidi, K., S. Sharma, and B. Ohlsson, A systematic review and meta-analysis of \nthe associations between endometriosis and irritable bowel syndrome. Eur J \nObstet Gynecol Reprod Biol, 2020. 246: p. 99-105. \n\n70 \n124. Szigethy, E., M. Knisely, and D. Drossman, Opioid misuse in gastroenterology\na\nnd non-opioid management of abdominal pain. Nat Rev Gastroenterol Hepatol,\n2\n018. 15(3): p. 168-180.\n125. Lamvu, G., et al., Patterns of Prescription Opioid Use in Women With\nEndometriosis: Evaluating Prolonged Use, Daily Dose, and Concomitant Use\nWith\n Benzodiazepines. Obstet Gynecol, 2019. 133(6): p. 1120-1130.\n12\n6. At\na, B., et al., The Endobiota Study: Comparison of Vaginal, Cervical and Gut\nMicrobiota Between Women with Stage 3/4 Endometriosis and Healthy Controls.\nSci Rep, 2019. 9(1): p. 2204.\n127.\nLeonardi, M., et al., Endometriosis and the microbiome: a systematic review.\nBjog, 2020. 127(2): p. 239-249.\n12\n8. Talwar, C., V. Singh, and R. Kommagani, The gut microbiota: a double-edged\nswo\nrd in endometriosis†. Biol Reprod, 2022. 107(4): p. 881-901.\n129.\nShan, J., et al., Gut microbiota imbalance and its correlations with hormone and\ninflammatory factors in patients with stage 3/4 endometriosis. Arch Gynecol\nO\nbstet, 2021. 304(5): p. 1363-1373.\n130.\nLe, N., et al., Association of microbial dynamics with urinary estrogens and\nestro\ngen metabolites in patients with endometriosis. PLoS One, 2021. 16(12): p.\ne0261362.\n13\n1. Huang, L., et al., Gut Microbiota Exceeds Cervical Microbiota for Ea rly\nD\niagnosis of Endometriosis. Front Cell Infect Microbiol, 2021. 11: p. 788836.\n132.\nPérez-Prieto, I., et al., Gut microbiome in endometriosis: a cohort study on 1000\nindividuals. BMC Med, 2024. 22(1): p. 294.\n133. Shelekhova M.S., M.A.N., Fil'cha kova A.N., Grudkova Y.V., Rayevskiy K.P.,\nC\nurrent understanding of the connection between endometriosis and intestinal\nmicrobiocenosis: a literature review. Russian Medicine 2024. 30(2): p. 181-190.\n134. Tang, Y., et al., Unraveling the relationship between gut microbiota and site-\nspecific endometriosis: a Mendelian randomization analysis. Front Microbiol,\n2\n024. 15: p. 1363080.\n13\n5. Procházková, N., et al., Advancing human gut microbiota research by considering\ngut transit time. Gut, 2023. 72(1): p. 180-191.\n13\n6. Schlaff, S., S.W. Rosen, and J. Roth, Antibody to human follicle-stimulating\nhor\nmone: cross-reactivity with three other hormones. J Clin Invest, 1968. 47(7):\np. 17\n22-9.\n13\n7. Zheng, J., et al., Identification and functionalization of thyrotropin receptor\na\nntibodies with different antigenic epitopes. Am J Physiol Endocrinol Metab,\n2024. 327(3): p. E328-e343.\n138. Cai, Y., et al., Identification of novel HLA-A0201-restricted T-cell epitopes\nag\nainst thyroid antigens in autoimmune thyroid diseases. Endocrine, 2020. 69(3):\np. 5\n62-570.\n139.\nDiVasta, A.D., et al., Spectrum of symptoms in women diagnosed\nw\nith endometriosis during adolescence vs adulthood. Am J Obstet Gynecol, 2018.\n21\n8(3): p. 324.e1-324.e11.\n140. R\nome_Foundation. Questionnaires. 2025; Available from:\nh\nttps://theromefoundation.org/questionnaires/.","source_license":"CC0","license_restricted":false}