Large-scale genome-wide association study to determine the genetic underpinnings of female genital tract polyps

18 STUDY QUESTION 19 Can a large-scale genome-wide association study (GWAS) meta-analysis identify the genomic 20 risk loci and associated candidate genes for female genital tract (FGT) polyps, provide insights 21 into the mechanism underlying their development , and inform potential overlap with other 22 traits, including endometrial cancer? 23 SUMMARY ANSWER 24 GWAS meta-analysis of FGT polyps highlighted the potentially shared mechanisms between 25 polyp development and cancerous processes. 26 WHAT IS KNOWN ALREADY 27 Small-scale candidate gene studies have focused on biological processes such as estrogen 28 stimulation and inflammation to clarify the biology behind FGT polyps. However, the exact 29 mechanism for the development of polyps is still elusive. At the same time, a genome -wide 30 approach, which has become the gold standard in complex disease genetics, has never been 31 used to uncover the genetics of the FGT polyps. 32 STUDY DESIGN, SIZE, DURATION 33 We performed a genome wide association study (GWAS) meta -analysis including a total of 34 25,100 women with FGT polyps (International Classification of Disease, ICD -10 diagnosis 35 code N84) and 207,193 female controls (without N84 code) of European ancestry from the 36 FinnGen study (11,092 cases and 94,394 controls) and the Estonian Biobank (EstBB, 14,008 37 cases and 112,799 controls). 38 . CC-BY-NC-ND 4.0 International licenseIt is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint The copyright holder for thisthis version posted January 30, 2024. ; https://doi.org/10.1101/2024.01.29.24301773doi: medRxiv preprint 3 PARTICIPANTS/MATERIALS, SETTING, METHODS 39 A meta-analysis and functional annotation of GWAS signals were performed to identify and 40 prioritise genes in associated loci. To determine associations with other phenotypes, we 41 performed a look-up of associated variants across multiple traits and health conditions, a genetic 42 correlation analysis, and a phenome -wide association study (PheWAS) with ICD10 diagnosis 43 codes. 44 MAIN RESULTS AND THE ROLE OF CHANCE 45 Our GWAS meta-analysis revealed ten significant (P < 5 x 10-8) genomic risk loci. Two signals, 46 rs2277339 (P = 7.6 x 10-10) and rs1265005 (P = 1.1 x 10-9) (in linkage disequilibrium (LD) with 47 rs805698 r2 = 0.75), are exonic missense variants in PRIM1, and COL17A1 genes, respectively. 48 Based on the literature, these genes may play a role in cellular proliferation. Several of the 49 identified genomic loci had previously been linked to endometrial cancer and/or uterine 50 fibroids. Thus, highlighting the potentially shared mechanisms underlying tissue overgrowth 51 and cancerous processes, which may be relevant to the development of polyps. Genetic 52 correlation analysis revealed a negative correlation between sex hormone -binding globulin 53 (SHBG) and the risk of FGT polyps (rg = -0,21, se = 0.04, P = 2.9 x 10-6), and on the phenotypic 54 level (PheWAS), the strongest associations were observed with endometriosis, leiomyoma of 55 the uterus and excessive, frequent and irregular menstruation. 56 LARGE SCALE DATA 57 The complete GWAS summary statistics will be made available after publication through the 58 GWAS Catalogue (https://www.ebi.ac.uk/gwas/). 59 LIMITATIONS, REASONS FOR CAUTION 60 . CC-BY-NC-ND 4.0 International licenseIt is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint The copyright holder for thisthis version posted January 30, 2024. ; https://doi.org/10.1101/2024.01.29.24301773doi: medRxiv preprint 4 In this study, we focused broadly on polyps of FGT and did not differentiate between the polyp 61 subtypes. The prevalence of FGT polyps led us to assume that most women included in the 62 study had endometrial polyps. Further study on the expression profile of FGT polyps could 63 complement the GWAS study to substantiate the functional importance of the identified 64 variants. 65 WIDER IMPLICATIONS OF THE FINDINGS 66 The study findings have the potential to significantly enhance our understanding of the genetic 67 mechanisms involved, paving the way for future functional follow -up, which in turn could 68 improve the diagnosis, risk assessment, and targeted treatment options, since surgery is the only 69 line of treatment available for diagnosed polyps. 70 TRIAL REGISTRATION NUMBER: 71 Not applicable 72 Key words: Genome-wide association study, Female genital tract polyps, Endometrial polyps, 73 Benign disorders, cell proliferation, PRIM1, COL17A1. 74

75 Polyps of the female genital tract (FGT) are generally benign tissue overgrowths found 76 in both reproductive-aged and postmenopausal women. While the prevalence of polyps can be 77 as high as 50%, most women are asymptomatic. Hence, polyps are usually detected incidentally 78 during routine ultrasound examinations, diagnostic hysteroscopy for other gynaecological 79 disorders, or infertility treatment among women of reproductive age (Hinckley and Milki, 2004; 80 Fatemi et al., 2010; Karayalcin et al., 2010; Bettocchi et al., 2011). However, the occurrence 81 of polyps is age-dependent, with a higher prevalence among postmenopausal women compared 82 . CC-BY-NC-ND 4.0 International licenseIt is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint The copyright holder for thisthis version posted January 30, 2024. ; https://doi.org/10.1101/2024.01.29.24301773doi: medRxiv preprint 5 to premenopausal women (Dreisler et al., 2009). Despite the asymptomatic and benign nature 83 of FGT polyps, for some women, they can negatively impact the daily quality of life by causing 84 abnormal vaginal bleeding and infertility. 85 Endometrial polyps (EPs) are the most common type of FGT polyps, with a prevalence 86 ranging from 7.8% to 50% (Dreisler et al., 2009; de Azevedo et al., 2016; Tanos et al., 2017). 87 In contrast, endocervical polyps occur only in 2% to 5% of cases , whereas vaginal polyps are 88 rarer (Tanos et al. , 2017) ; therefore, limited evidence is available about their biology and 89 clinical implications. Some known risk factors for the development of EPs are advanced age, 90 hypertension, diabetes, obesity, hyper oestrogenism, administration of hormone replacement 91 therapy (HRT), and tamoxifen (Vitale et al., 2021; Vieira et al., 2022). Nevertheless, the exact 92 pathogenesis of FGT polyps remains unclear. Histologically, EPs are characterised by large, 93 thickened blood vessels with fibrous stroma and irregularly shaped glandular spaces (Tanos et 94 al., 2017). Moreover, EPs can be associated with concomitant intrauterine pathologies like 95 endometrial hyperplasia, adenomyosis, endometriosis and chronic endometritis (Annan et al., 96 2012; Raz et al., 2021). Despite the benign nature of EPs, around 3.5% of cases progress into 97 carcinoma (Lee et al., 2010; Sasaki et al., 2018; Uglietti et al., 2019). At the same time, the 98 extent of biological mechanisms and pathways shared between EPs and carcinoma, as well as 99 unique molecular characteristics of each condition remain unclear. 100 Very little is known about the heritability and genetic background of FGT polyps. 101 Genetic factors, including chromosomal translocations in 6p21-22, 12q13-15, or 7q22 regions, 102 may contribute to polypoid morphology (Dal Cin et al., 1995; Nijkang et al., 2019; Vieira et 103 al., 2022), and genetic disorders like Lynch or Cowden syndrome have been reported to be 104 accountable for the development of EPs (Vieira et al., 2022). However, a recent study by Sahoo 105 et al. did not confirm the presence of chromosomal rearrangements in endometrial polyps 106 (Sahoo et al., 2022). 107 . CC-BY-NC-ND 4.0 International licenseIt is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint The copyright holder for thisthis version posted January 30, 2024. ; https://doi.org/10.1101/2024.01.29.24301773doi: medRxiv preprint 6 Thus, the confirmed pathophysiology for the development of FGT polyps is still 108 unknown. However, it can be assumed that the development and mechanism of polyps are 109 multifactorial and can also depend on genetic predisposition. Thus far, t he proposed genetic 110 mechanisms are primarily based on small candidate gene studies and are inconclusive (Altaner 111 et al., 2006; Pal et al., 2008; Banas et al., 2018; Doria et al., 2018; Takeda et al., 2019). Studies 112 in other complex diseases have shown that genome-wide association studies (GWAS) can 113 provide valuable insight into disease biology (Claussnitzer et al., 2016), but as far as we are 114 aware, no large-scale GWAS have been published for FGT polyps. Therefore, we performed a 115 GWAS meta-analysis to identify the genetic variants associated with FGT polyps, followed by 116 numerous post-GWAS analyses to understand the shared and unique genetic underpinnings of 117 FGT polyps and endometrial cancer. Ultimately, this knowledge can highlight potential clinical 118 avenues for appropriate diagnosis and management of FGT polyps. 119

120 Ethical approval 121 All Estonian Biobank (EstBB) participants have signed a broad informed consent form, 122 and analyses were carried out under ethical approvals 1.1 -12/624 and 1.1 -12/2733 from the 123 Estonian Committee on Bioethics and Human Research (Estonian Ministry of Social Affairs) 124 and data release application 6-7/GI/630 from the EstBB. For the FinnGen study, we used only 125 publicly available GWAS summary statistics without individual-level data and thus, a separate 126 ethics approval was not needed. 127 Study cohorts 128 Our analyses included a total of 25,100 women with polyps of the FGT (International 129 Classification of Disease, ICD -10 diagnosis code N84) and 207,193 female controls (without 130 . CC-BY-NC-ND 4.0 International licenseIt is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint The copyright holder for thisthis version posted January 30, 2024. ; https://doi.org/10.1101/2024.01.29.24301773doi: medRxiv preprint 7 the N84 code) of European ancestry from two studies: summary level statistics from the 131 FinnGen R7 data release (11,092 cases and 94,394 controls) and individual-level data from the 132 EstBB (14,008 cases and 112,799 controls). In FinnGen, cases were defined using the ICD -10 133 code N84 or corresponding ICD-9 (6210, 6227, 6237, 6246) and ICD-8 (62520) codes. Similar 134 to EstBB, controls were defined as women who did not have the abovementioned disease codes. 135 To increase study power, we did not distinguish between different types of FGT polyp 136 location in our phenotype definition. However, according to the FinnGen Risteys browser 137 (https://r7.risteys.finngen.fi/phenocode/N14_POLYPFEMGEN), 20% of FGT polyp cases 138 were also cases for phenotype “Uterine polyps”, while in the EstBB data, 70.5 % of N84 cases 139 had a diagnosis for uterine polyps (as defined by the presence of the ICD-10 code N84.0). This 140 most likely reflects differences in the source of phenotype information - FinnGen phenotype 141 definitions mostly use hospital records and thus involve more severe cases, while the EstBB 142 also uses primary care records. 143 Cohort-level analyses 144 The EstBB is a population -based biobank including more than 200,000 individuals 145 (approximately 135,000 of them women) representing 20% of the Estonian adult population. 146 Information on ICD codes is obtained via regular linking with the National Health Insurance 147 Fund and other relevant databases. Individuals with ICD-10 code N84 (mean age at recruitment 148 49.2 years, standard deviation 12.1) were categorised as cases having been diagnosed with 149 polyps of the genital tract, and all female biobank participants without the diagnosis were 150 considered as controls (mean age at recruitment 44.3 years, sd 16.6). The genotyping procedure 151 for EstBB has been described previously (Koel et al., 2023; Laisk et al., 2021; Pujol-Gualdo et 152 al., 2022). Briefly, Illumina GSAv1.0, GSAv2.0, and GSAv2.0_EST arrays were used for the 153 genotyping of biobank participants at the Core Genotyping Lab of the Institute of Genomics, 154 . CC-BY-NC-ND 4.0 International licenseIt is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint The copyright holder for thisthis version posted January 30, 2024. ; https://doi.org/10.1101/2024.01.29.24301773doi: medRxiv preprint 8 University of Tartu. Individuals with a call -rate less than 95% and sex mismatch between 155 phenotypic and chromosomal data were excluded from the analysis. Before imputation, 156 genotyped variants were filtered by applying criteria of call rate < 95%, Hardy -Weinberg 157 equilibrium P < 10 −4 (for autosomal variants only), and minor allele frequency < 1%. Eagle 158 v2.3 software was used for pre-phasing, and Beagle was used for imputation. The population -159 specific imputation reference of 2297 whole genome sequencing samples was used. Association 160 analysis was performed using REGENIE v2.2.4 with year of birth and 10 principal components 161 as covariates in step I, and variants with a minor allele count < 5 were excluded by default. In 162 downstream association analysis, poorly imputed variants with an INFO score < 0.4 were 163 excluded. 164 For FinnGen, GWAS summary statistics from the R7 data release were used, and 165 therefore, individual-level data was not available. The summary statistics were obtained from 166 https://www.finngen.fi/en/access_results, whereas the FinnGen cohort and the genotyping/data 167 analysis details have been previously described in Kurki et al. (Kurki et al. , 2023) . To 168 summarise, age, 10 principal components, and genotyping batch were used in REGENIE v2.0.2 169 analysis as covariates, and for FinnGen summary statistics, variants with a minor allele count 170 > 5 and imputation INFO score > 0.6 were included. 171 GWAS meta-analysis 172 A meta-analysis using fixed -effects inverse variance weighting with genomic control 173 was performed with the GWAMA v2.1 tool. The genome -wide significance level was set to 174 P < 5 × 10-8. The genomic inflation factors (lambda) for the individual study summary statistics 175 were 1.046 (EstBB) and 1.045 (FinnGen). Variants present in both cohorts (n = 12,363,169) 176 were included in downstream analyses. 177 Annotation of GWAS signals 178 . CC-BY-NC-ND 4.0 International licenseIt is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint The copyright holder for thisthis version posted January 30, 2024. ; https://doi.org/10.1101/2024.01.29.24301773doi: medRxiv preprint 9 To annotate the GWAS signals and prioritise potential biologically relevant genes at 179 associated loci, we adopted the following approach. 180 First, we used the Functional Mapping and Annotation of Genome -Wide Association 181 Studies (FUMA GWAS) platform v1.5.2 to identify genetic association loci. FUMA is an online 182 platform designed for the annotation , prioritisation, and interpretation of GWAS results that 183 uses data from multiple databases to annotate GWAS signals (Watanabe et al., 2017). In the 184 first step of this analysis, independent significant variants, lead signals and genomic risk loci 185 were defined. Independent significant variants (IndSigSNPs) were defined as variants that were 186 genome-wide significant (P < 5 x 10-8) and had a pairwise LD r2 < 0.6, according to the 1000G 187 EUR reference panel. From this subset, lead variants were derived. Finally, risk loci were 188 defined from independent significant SNPs by merging LD blocks if they are less apart than r2 189 < 0.6. Thus, a genomic risk locus can contain several lead SNPs and/or independent significant 190 SNPs, depending on the size of the locus and the LD structure. Thereafter, potential significant 191 candidate SNPs (GWAS meta-analysis P > 0.05) were determined to be in LD with any of the 192 IndSigSNPs (r2 ≥ 0.6) within a 1Mb window and had a MAF of ≥ 1%. These candidate SNPs 193 were subjected to further annotation using multiple databases such as Annotate Variation 194 (ANNOVAR) (Wang et al. , 2010), RegulomeDB scores (ranging from 1 to 7, where lower 195 score indicates greater evidence for having regulatory function) (Boyle et al. , 2012) , and 196 Combined Annotation -Dependent Depletion ( CADD) (a continuous score showing how 197 deleterious the SNP is to protein structure/function; scores >12.37 indicate potential 198 pathogenicity) (Kircher et al. , 2014) , 15 chromatin states from the Roadmap Epigenomics 199 Project (ENCODE Project Consortium, 2012; Roadmap Epigenomics Consortium et al., 2015), 200 expression quantitative trait loci (eQTL) data (genotype -tissue expression (GTEx) v6 and v7) 201 (GTEx Consortium, 2013) and 3D chromatin interactions from HI -C experiments of 21 202 tissues/cell types (Schmitt et al. , 2016) . This process provides information on the location, 203 . CC-BY-NC-ND 4.0 International licenseIt is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint The copyright holder for thisthis version posted January 30, 2024. ; https://doi.org/10.1101/2024.01.29.24301773doi: medRxiv preprint 10 functional impact, and potential regulatory effects of detected SNPs. For eQTL annotations, we 204 focused on tissues similar to uterine/vaginal tissue (GTEx Consortium, 2020). 205 Using the lead signal identified by FUMA, we performed a look-up in the Open Targets 206 genetics database (Ghoussaini et al., 2021). This database combines several layers of evidence 207 across a wide range of cell types and tissues to generate an aggregate ‘variant to gene’ (V2G) 208 score. The V2G score provides identification and correlation of likely causal variants and genes 209 to prioritise the potential functional genes associated with the identified variants. V2G score 210 aggregates several parameters like distance from the canonical transcript start site, eQTLs and 211 protein QTLs (pQTLs) datasets, datasets for chromatin interactions and conformation, 212 molecular phenotypes, and in silico functional predictions (using the Variant Effect Predictor 213 or VEP score). 214 Briefly, we prioritised genes in the identified loci by selecting three genes having the 215 highest V2G score. Then we additionally identified those loci where the GWAS signal includes 216 a missense variant using annotation data from FUMA. To provide additional support for 217 prioritisation and further explore regulatory effects, we looked at eQTL associations according 218 to FUMA annotations, and if none were reported, we looked at potential chromatin interactions 219 as these may also indicate regulatory effects. To gain insight into endometrial-specific eQTLs, 220 we queried the candidate SNPs defined by FUMA in the endometrial eQTL database (Fung et 221 al., 2018). 222 Gene-based testing 223 Analysis by Multi-marker Analysis of GenoMic Annotation (MAGMA) v1.6 (de Leeuw 224 et al., 2015), with the default settings in FUMA (Watanabe et al., 2017), was used to perform 225 gene-based association analysis to complement the single variant analyses. Gene-based analysis 226 enables to detect the joint effect of multiple genetic variants and can thus increase the power to 227 detect associations. Briefly, variants located in the gene body were assigned to protein -coding 228 . CC-BY-NC-ND 4.0 International licenseIt is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint The copyright holder for thisthis version posted January 30, 2024. ; https://doi.org/10.1101/2024.01.29.24301773doi: medRxiv preprint 11 genes (n = 18,895; Ensembl build 85), and the SNP P -values were merged into a gene test 229 statistic using the SNP -wise mean model (de Leeuw et al., 2015). The level of genome -wide 230 significance was set at 0.05/18,895 = 2.6 x 10-6, taking into account the number of tested genes. 231 Genetic associations with other traits: 232 During the FUMA functional mapping, candidate SNPs were linked with the GWAS 233 catalogue (https://www.ebi.ac.uk/gwas/, GWAS Catalogue e0_r2022-11-29, FUMA v1.5.1) to 234 explore the association of genetic variants with previously published GWAS of different 235 phenotypic traits. 236 Genetic correlation analysis 237 To estimate the genetic correlations between our FGT polyps meta -analysis and 1,335 238 other traits, we utilised the LD Score Regression method implemented in the Complex Traits 239 Genetics Virtual Lab (CTG-VL) (https://genoma.io/) and 3 additional endometrial cancer traits 240 available in the GWAS catalog ue (accession codes GCST006464, GCST006465 and 241 GCST006466) (Bulik-Sullivan et al. , 2015) . Statistical significance was determined by 242 applying a multiple testing correction (FDR < 5%) using the p.adjust function in R v3.6.3. 243 Associations with other phenotypic traits 244 To determine the associations between ICD -10 diagnosis main codes and the N84 245 diagnosis of polyps in the FGT, we conducted an analysis using individual level data from the 246 EstBB. Logistic regression was used to test the associations between N84 and other ICD -10 247 codes while controlling for age at recruitment and 10 genetic principal components to account 248 for population stratification and avoid false associations due to ancestry/regional differences 249 between cases and controls. Age was included as a covariate to account for incomplete 250 electronic diagnosis data for older participants in the biobank. Our analysis was limited to the 251 diagnosis main codes along with all the subcodes to increase the power of the data. Statistically 252 . CC-BY-NC-ND 4.0 International licenseIt is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint The copyright holder for thisthis version posted January 30, 2024. ; https://doi.org/10.1101/2024.01.29.24301773doi: medRxiv preprint 12 significant associations were determined by applying Bonferroni correction (2000 tested ICD 253 main codes, corrected P threshold of 2.5 x 10 -5). Odds ratios (ORs) were calculated by the 254 logistic regression method and represented as adjusted ORs. The resulted associations were 255 filtered to remove the diagnoses related to exogenous factors (such as injuries, poisoning, 256 accidents, assaults, etc. in the S, T, U, V, W, X, and Y subchapters) and the PheWAS library 257 (https://github.com/PheWAS/PheWAS) was used to visualise the results. All analyses were 258 performed using R v4.1.3 259 In the FinnGen data, we did not have access to the individual level data, but using the 260 Risteys portal ( https://r7.risteys.finngen.fi/phenocode/N14_POLYPFEMGEN), we explored 261 the results of the survival analysis evaluating associations between FGT polyps and other 262 selected phenotypes. A detailed description of the survival analysis can be found in the Risteys 263 documentation (https://r7.risteys.finngen.fi/documentation), but briefly, this type of analysis 264 tests the association between an exposure endpoint and an outcome endpoint. For example, in 265 the context of FGT polyps, what is the association between a diagnosis of FGT polyp (exposure 266 endpoint) and endometrial carcinoma (outcome endpoint). 267

268 Summary of GWAS 269 GWAS of a total of 25,100 women with polyps of the FGT and 207,193 female controls 270 revealed ten significant (P < 5 x 10 -8) genomic risk loci and 23 independent signals (Fig. 1, 271 Table 1). The strongest signal, rs1702136 (P = 2.17 x 10 -19), was observed on chromosome 3, 272 which is an intronic variant of the EEFSEC gene. The majority of the significant signals 273 (91.3%) were either intronic or intergenic variants, whereas two signals, rs2277339 (P = 7.57 x 274 10-10) and rs1265005 (P = 1.09 x 10-9, in LD with rs805698, r2 = 0.75) on chromosomes 12 and 275 10, respectively, were exonic missense variants. 276 . CC-BY-NC-ND 4.0 International licenseIt is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint The copyright holder for thisthis version posted January 30, 2024. ; https://doi.org/10.1101/2024.01.29.24301773doi: medRxiv preprint 13 277 Table 1 . Summary statistics of significant genomic risk loci with lead SNP and 278 independent significant SNP. 279 chr:pos:A1:A2 rsID of Lead SNP (effect allele) P-value OR (95% CI) IndSigSNP s Effect Allele frequency (Est/Fin) Heter ogene ity p - value 3:128118711:A: G rs1702136 (G) 2.17 x 10 - 19 0.90 (0.88- 0.92) rs1702136 rs3732402 rs4857866 rs7650365 rs2999051 rs13095166 rs74924715 rs1735527 0.75/0.75 0.99 8:116869477:C: T rs800578 (T) 4.91 x 10 - 11 1.08 (1.05- 1.10) rs800578 rs2736213 0.24/0.26 0.90 4:95731394:A:G rs2865375 (A) 4.36 x 10 - 10 0.93 (0.92- 0.95) rs2865375 rs10033997 0.54/0.52 0.45 12:57146069:G: T rs2277339( T) 7.57 x 10 - 10 1.10 (1.06- 1.13) rs2277339 0.87/0.86 0.37 10:105585753:C :T rs19309775 3 (C) 7.59 x 10 - 10 0.83 (0.78- 0.88) rs19309775 3 rs17116149 rs7911816 rs11360949 6 rs1265005 0.97/0.95 0.92 1:61592380:A:G rs12751005 (A) 1.09 x 10-9 1.06 (1.04- 1.09) rs12751005 0.68/0.67 0.90 13:41869725:A: G rs77478686 (G) 8.21 x 10-9 1.18 (1.12- 1.26) rs77478686 0.97/0.95 0.67 . CC-BY-NC-ND 4.0 International licenseIt is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint The copyright holder for thisthis version posted January 30, 2024. ; https://doi.org/10.1101/2024.01.29.24301773doi: medRxiv preprint 14 5:142162633:A: G rs7728894 (G) 1.84 x 10-8 0.93 (0.91- 0.96) rs7728894 0.73/0.75 0.60 5:1285974:A:C rs7705526 (C) 2.33 x 10-8 0.94 (0.92- 0.96) rs7705526 0.68/0.68 0.45 19:8786624:A:G rs2967684 (G) 2.72 x 10-8 0.93 (0.90- 0.95) rs2967684 0.81/0.76 0.40 *Alleles presented in alphabetical order 280 IndSigSNPs: Independent significant SNP 281 282 283 284 285 286 287 288 289 Figure. 1. Manhattan plot for significant genomic risk loci identified for polyps of female 290 genital tract. On the Manhattan plot, the x -axis represents chromosomes, while the y -axis 291 represents −log10(P-values) for the association of variants identified in polyps of the female 292 genital tract. The horizontal red dashed line represents the genome-wide significance threshold 293 (P < 5 × 10−8). The prioritised genes for each locus are labelled on the top, and genes associated 294 with exonic missense variants are coloured red. 295 Functional annotation of associated variants and gene prioritisation 296 We performed a look -up in the Open Targets Genetics database to evaluate the 297 functional association of identified genomic loci and potentially mapped genes reflected by the 298 . CC-BY-NC-ND 4.0 International licenseIt is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint The copyright holder for thisthis version posted January 30, 2024. ; https://doi.org/10.1101/2024.01.29.24301773doi: medRxiv preprint 15 V2G score. We additionally highlighted those loci where the GWAS signal includes a missense 299 variant using annotation data from FUMA (Table 2). Full details of gene prioritisation together 300 with supporting evidence from FUMA eQTL and chromatin interaction mapping, can be found 301 in Supplementary Table 1. 302 Table 2. Summary of gene prioritisation results 303 Locus Lead variant Highest V2G score Exonic variants Biological evidence 3:128118711: A:G rs1702136 EEFSEC RPN1 DNAJB8 NA EEFSEC potential endometrial cancer susceptibility gene (Kho et al., 2021) 8:116869477: C:T rs800578 TRPS1 NA Potential tumour suppressor candidate in endometrial cancer (Liang et al., 2012) 4:95731394:A: G rs2865375 BMPR1B PDLIM5 HPGDS NA BMPR1B is associated with female infertility. BMPR1B-AS1 facilitates endometrial cancer cell proliferation (Lai et al., 2022). BmprIB mutant mice exhibit a failure in endometrial gland formation (Yi et al., 2001) 12:57146069: G:T rs2277339 PRIM1 STAT6 HSD17B6 PRIM1 Cell proliferation, DNA replication 10:105585753: C:T rs193097753 STN1 SH3PXD2A SLK COL17A1 Cellular migration, cellular differentiation, extracellular matrix organisation . CC-BY-NC-ND 4.0 International licenseIt is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint The copyright holder for thisthis version posted January 30, 2024. ; https://doi.org/10.1101/2024.01.29.24301773doi: medRxiv preprint 16 1:61592380:A: G rs12751005 NFIA NA NFIA is involved in cellular growth and proliferation, tumour morphology. The gene is expressed in endometrial tissue (Humaidan et al., 2012) 13:41869725: A:G rs77478686 NAA16 MTRF1 KBTBD7 NA Differential expression of NAA16 is associated with the pathogenesis of endometriosis (She et al., 2022) 5:142162633: A:G rs7728894 ARHGAP26 FGF1 SPRY4 NA ARHGAP26 promotes ovarian cancer cell invasion and migration (Chen et al., 2019) 5:1285974:A: C rs7705526 TERT CLPTM1L SLC6A18 NA TERT-CLPTM1L locus is a known susceptibility region for cancerous processes 19:8786624:A: G rs2967684 ACTL9 NFILZ ADAMTS10 NA ACTL9 locus associated with endometriosis (Rahmioglu et al., 2023) 304 Based on coding variants in our GWAS signals, we were able to prioritise PRIM1 and COL17A1 305 in loci on chromosomes 12 and 10, respectively. PRIM1 is a DNA primase involved in the 306 initiation of DNA replication by synthesising RNA primers for Okazaki fragments during 307 discontinuous DNA replication (Shiratori et al., 1995). rs2277339 is also a cis-eQTL for PRIM1 308 in endometrial tissue, which further supports PRIM1 as a candidate gene in this locus. 309 . CC-BY-NC-ND 4.0 International licenseIt is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint The copyright holder for thisthis version posted January 30, 2024. ; https://doi.org/10.1101/2024.01.29.24301773doi: medRxiv preprint 17 COL17A1, on the other hand, is primarily involved in cellular migration, cellular differentiation, 310 and extracellular matrix organisation (Jones et al., 2020). While these genes have not yet been 311 directly associated with FGT polyps, their biological functions, particularly those related to 312 cellular proliferation, highlight their potential involvement in the development of polyps. 313 Several of the prioritised candidate genes had previously been associated with 314 (endometrial) cancer - EEFSEC, TRPS1, TERT/CLPTM1L, one could be directly linked with 315 endometrial biology ( BMPR1B), and for the remaining, their biological significance in FGT 316 polyps remains unclear. 317 Gene-based associations of female genital tract polyps: 318 To combine the joint effect of multiple genetic variants and increase the power to detect 319 associations, we performed a MAGMA gene -based test implemented in FUMA. Eight genes 320 were identified which passed the recommended threshold for significance (P = 2.6 × 10 -6, 321 Bonferroni correction for association testing of 18,895 protein-coding genes): EEFSEC, TERT, 322 RUVBL1, BMPR1B, TRPS1, COL17A1, BET1L, WBP4 (Supplementary Figure 1, 323 Supplementary Table 2). Majority of these associations mirror the genes prioritised in the single 324 variant analysis, while the BET1L locus was not genome-wide significant in the single variant 325 analysis and is thus novel. Previously, BET1L has been associated with endometrial cancer 326 (Bateman et al., 2017) and uterine fibroids (Cha et al., 2011; Edwards et al., 2013; Liu et al., 327 2018). 328 GWAS catalogue look-up 329 We searched the GWAS catalogue for associations between previously published 330 phenotypic traits and candidate SNPs identified by the FUMA tool to gain additional insight 331 into their potential biological roles (Fig. 2, Supplementary Table 3). Based on the GWAS 332 catalogue look-up, the TERT-CLPTM1L (rs7705526) locus was clearly associated with cancers, 333 . CC-BY-NC-ND 4.0 International licenseIt is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint The copyright holder for thisthis version posted January 30, 2024. ; https://doi.org/10.1101/2024.01.29.24301773doi: medRxiv preprint 18 including the development of reproductive cancers such as ovarian cancer and prostate cancer. 334 Potential involvement in cancerous processes was also observed for the EEFSEC locus 335 (rs4857866), which was associated with prostate cancer and also nominally with endometrial 336 cancer (P < 1 x 10 -6). Several identified signals were related to reproductive traits, including 337 menarche (rs2277339-PRIM1), menopause (rs2277339 -PRIM1), gestational age (rs4857866 -338 EEFSEC) and uterine fibroids (rs2277339 -PRIM1, rs193097753 -COL17A1, rs17116149 -339 COL17A1). The rs193097753 signal was additionally associated with the known risk factors 340 for the development of FGT polyps, such as type 2 diabetes (P < 5 x 10-8) and waist-to-hip ratio 341 (P < 2 x 10-11), further substantiating its functional significance. 342 343 344 . CC-BY-NC-ND 4.0 International licenseIt is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint The copyright holder for thisthis version posted January 30, 2024. ; https://doi.org/10.1101/2024.01.29.24301773doi: medRxiv preprint 19 345 Figure. 2: GWAS catalogue look -up showing associations between genetic variants 346 associated with female genital tract polyps and other phenotypes. The figure highlights the 347 genome-wide significant (P < 5 x 10 -8) association between FGT polyps genetic risk factors 348 (individual significant SNPs) and previously published phenotypic traits and disorders. 349 Look-up of variants associated with endometrial cancer 350 Since there is some overlap between FGT polyp genetic risk loci and those known to be 351 associated with (endometrial) cancer , we conducted a look -up of variants associated with 352 endometrial cancer (O’Mara et al., 2018) in our GWAS data. Of the 19 SNPs queried, seven 353 . CC-BY-NC-ND 4.0 International licenseIt is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint The copyright holder for thisthis version posted January 30, 2024. ; https://doi.org/10.1101/2024.01.29.24301773doi: medRxiv preprint 20 were nominally significant ( P < 0.05) (rs9668337 -SSPN, rs1740828 -SOX4, rs17601876 -354 CYP19A1, rs882380 -SNX11, rs3184504 -SH2B3, rs1129506 -EVI2A, rs11263761 -HNF1B) in 355 the FGT polyp analysis as well (Supplementary Table 4). When querying the 10 lead variants 356 associated with FGT polyp in the endometrial cancer summary statistics, we observed that three 357 were nominally significant ( P < 0.05) in the endometrial cancer and also in the endometrial 358 cancer with endometrioid histology studies (rs1702136 -EEFSEC, rs2865375 -BMPR1B, 359 rs7705526-TERT). 360 Genetic correlation between FGT polyps and other traits 361 We conducted pairwise genetic correlation (rg) analyses to examine the relationship 362 between polyps of the FGT and 1 ,335 different traits obtained from the Complex Traits 363 Genetics Virtual Lab (CTG-VL, https://genoma.io/) and 3 additional endometrial cancer traits 364 available in the GWAS catalogue (accession codes GCST006464, GCST006465 and 365 GCST006466). After running the analysis and correcting for multiple testing, we identified a 366 total of 11 significant (FDR < 0.05) genetic correlations. Selected genetic correlations between 367 polyps and various phenotypic categories such as anthropometrics, cardiovascular diseases, 368 genitourinary traits, mood disorders, sex hormones and surgical procedures are displayed in 369 Fig. 3, full results in Supplementary Table 5 . As expected, a positive genetic correlation was 370 observed with genitourinary traits and hysterectomy, emphasising that polyps are commonly 371 occurring incidental findings in gynaecological disorders. Furthermore, sex hormone -binding 372 globulin (SHBG) was negatively correlated with the risk of FGT polyps. We were not able to 373 detect a significant genetic correlation between FGT polyps and estradiol level or BMI, known 374 risk factors of FGT polyps, in our dataset. FGT polyps showed weak correlation with two of 375 the three endometrial cancer phenotypes tested (endometrial cancer and endometrial cancer - 376 endometrioid histology, both rg 0.25 -0.27, se 0.12 -0.13), but these associations were only 377 nominally significant (P = 0.03) and did not pass multiple testing correction threshold. 378 . CC-BY-NC-ND 4.0 International licenseIt is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint The copyright holder for thisthis version posted January 30, 2024. ; https://doi.org/10.1101/2024.01.29.24301773doi: medRxiv preprint 21 379 Figure 3: Results of genetic correlation analysis between endometrial polyps and other 380 relevant traits. 381 The plot displays selected genetic correlations between female genital tract polyps and traits 382 from various phenotypic categories such as anthropometrics, cardiovascular traits, 383 genitourinary traits, mood disorders, sex hormones and surgical procedures that are colour -384 coded. Significant associations after FDR multiple correction are shown in the lower panel, 385 while the upper panel shows selected traits of interest that do not pass the multiple testing 386 correction. The centre dot marks the estimated genetic correlation (rg) value, and error bars 387 indicate 95% confidence limits. The dotted red line indicates no genetic correlation. 388 Associations between polyps of FGT and other diagnosis codes 389 Additionally, to evaluate other phenotypes’ association with FGT polyps, we performed 390 a phenome-wide phenotype association analysis using the EstBB data for disease codes. All 391 239 phenotypic associations with a P < 2.5 x 10 -5 (corresponding to a Bonferroni -corrected 392 threshold of 0.05/2020) are shown in Supplementary Table 6. The most significant association 393 of FGT polyps related to other phenotypes were: i) leiomyoma of uterus (D25 ), which are 394 . CC-BY-NC-ND 4.0 International licenseIt is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint The copyright holder for thisthis version posted January 30, 2024. ; https://doi.org/10.1101/2024.01.29.24301773doi: medRxiv preprint 22 uterine fibroids known to often occur together with EPs (Kınay et al., 2016); ii) endometriosis 395 (N80), which has been correlated with a high prevalence of endometrial polyps; iii) excessive, 396 frequent and irregular menstruation (N92) which is one of the classical symptoms of EPs, and; 397 iv) other noninflammatory disorders of uterus except cervix (N85) (Fig. 4). Moreover, women 398 with a diagnosis for FGT polyps had significantly more diagnoses for benign neoplasms in 399 several tissues, such as the uterus (D26), ovary (D27), unspecified female genital organs (D28 400 and D39) and skin (D23) as well as malignant neoplasms of the uterus (C54) and skin (C44). 401 In our analysis, nasal polyps (J33) and K62 (which includes anal/rectal polyps) were also 402 nominally significant, which supports the idea of some systemic tissue overgrowth in epithelial 403 tissues similar to endometrial polyps harbouring glandular and luminal epithelium. 404 For the highlighted associations, we queried the FinnGen Risteys R7 portal to see if we 405 observe similar associations in the Finnish data. While the analysis in the Estonian data does 406 not consider which diagnosis in the tested pair comes first, the FinnGen data survival analysis 407 tests the association in both directions. Uterine leiomyoma, endometriosis, other benign 408 neoplasm of uterus, benign neoplasm of ovary, malignant neoplasm of uterus, and carcinoma 409 in situ of endometrium were significantly associated with FGT polyps in the survival analysis 410 in FinnGen data, (Supplementary Table 7) both if the diagnosis occurred before, or after the 411 FGT polyp diagnosis. 412 The results of phenotypic associations of FGT polyps are in concordance with the observed 413 genetic associations and point to the fact that benign and cancerous processes share some 414 mechanisms (such as cellular proliferation) on a genetic level. 415 416 417 418 . CC-BY-NC-ND 4.0 International licenseIt is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint The copyright holder for thisthis version posted January 30, 2024. ; https://doi.org/10.1101/2024.01.29.24301773doi: medRxiv preprint 23 419 420 421 422 423 424 425 426 Figure 4: Association of Polyps of female genital tract (N84) with other phenotypes. 427 Each triangle in the plot corresponds to one ICD10 main code, and different colours represent 428 different diagnosis categories. The direction of the triangle represents the direction of effect and 429 upward-pointing triangles show increased significance of diagnosis code in female genital tract 430 polyps. The red line indicates the Bonferroni corrected threshold for statistical significance. 431

432 Gynaecological polyps are a common diagnosis in women, with potential negative 433 implications for women's reproductive health and well -being. We conducted the first large -434 scale GWAS meta -analysis to study the genetic underpinnings of FGT polyps and their 435 association with other phenotypic traits from two European ancestry biobanks. The analysis 436 revealed ten genomic risk loci, of which two (rs2277339 and rs193097753) tagged exonic 437 missense variants suggestive of plausible functional importance in the development of polyps. 438 Furthermore, several of the identified genetic risk loci have previously been associated with 439 (endometrial) cancer and/or uterine fibroids. Genetic correlation analysis additionally showed 440 negative correlation with SHBG levels, but no statistically significant genome-wide correlation 441 . CC-BY-NC-ND 4.0 International licenseIt is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint The copyright holder for thisthis version posted January 30, 2024. ; https://doi.org/10.1101/2024.01.29.24301773doi: medRxiv preprint 24 with endometrial cancer. PheWAS analysis showed an increased prevalence of endometriosis, 442 irregular and excessive menstruation, uterine fibroids and neoplasms of the uterus and other 443 tissues in women with FGT polyps. 444 Even though most EPs are benign, there is still a certain level of risk these polyps may 445 progress to malignant transformation (Antunes et al., 2007; Lenci et al., 2014). According to a 446 systematic review and meta -analysis, 2.7% -3.6% of EPs can be considered malignant, with 447 significant heterogeneity in prevalence among pre - and postmenopausal women (Lee et al., 448 2010; Sasaki et al., 2018; Uglietti et al., 2019). While we saw no statistically significant genetic 449 correlation between FGT polyps and endometrial cancer, several of the mapped genetic risk 450 loci/prioritised genes (rs1702136 -EEFSEC, rs800578 -TRPS1, rs2865375-BMPR1B, and 451 rs7705526-TERT-CLPTM1L) have previously been associated with cancer either in GWAS or 452 functional studies (Liang et al., 2012; Wu et al., 2014; Kho et al., 2021; Dos Santos et al., 453 2022), most likely reflecting the fact that both benign and malignant tissue overgrowths may 454 utilise the same cellular mechanisms to some extent. This is supported by the results of the 455 associated diagnoses analysis where women with a diagnosis of FGT polyp also have more 456 diagnoses related to benign and malignant neoplasms of the uterus, ovary, and skin. While the 457 associations with reproductive tract neoplasms may arise due to incidental findings during 458 diagnostic procedures, it cannot be ruled out that some women have a genetic predisposition to 459 tissue overgrowth that may manifest in either benign or malignant neoplasms in certain tissues. 460 Apart from a few small -scale reports (Unler et al. , 2016) , there are no relevant studies 461 evaluating the prevalence of different neoplasms among women with FGT polyps, therefore, 462 our observations need to be confirmed and further evaluated in future studies. 463 We further saw significant associations of FGT polyps with uterine leiomyoma and 464 endometriosis. Though the cellular composition, characteristics, and mechanism of origin of 465 uterine fibroids and endometrial polyps differ from each other, they can occur concurrently due 466 . CC-BY-NC-ND 4.0 International licenseIt is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint The copyright holder for thisthis version posted January 30, 2024. ; https://doi.org/10.1101/2024.01.29.24301773doi: medRxiv preprint 25 to common risk factors like advanced age, obesity, and hormonal dysregulation (Kınay et al., 467 2016; Pavone et al., 2018). Further, increased prevalence of endometriosis among women with 468 FGT polyps emphasises the reported evidence of a higher prevalence of endometrial polyps in 469 endometriosis patients (Shen et al., 2011; Zhang et al., 2018; Lin et al., 2020; Peters et al., 470 2022). 471 Our genetic correlation analysis showed a significant negative correlation between 472 SHBG levels and the risk of FGT polyps. In females, testosterone and oestrogen levels are 473 regulated through their binding to SHBG, which helps maintain hormonal balance in the 474 bloodstream. Lower levels of SHBG can result in elevated levels of free testosterone and free 475 oestrogen. As EPs are oestrogen dependent , lower SHBG may directly stimulate EP 476 development. Moreover, the expression of aromatase 450 enzyme in the EPs, converts free 477 testosterone into oestrogen, further augments the stimulation of polyps' development (Filho et 478 al., 2007) . Thus, our study’s finding of the negative correlation of SHBG in FGT polyps 479 concords with this mechanism. Unexpectedly, our analysis did not reveal a genetic correlation 480 between oestradiol and EPs. The discrepancy between circulating plasma levels and localized 481 endometrial levels of oestradiol may underlie the lack of this correlation. In the literature, serum 482 levels of oestradiol were shown to be significantly lower (five times) than the endometrial 483 oestradiol concentration in the proliferative phase (Huhtinen et al., 2012). The same trend was 484 observed in women with abnormal uterine bleeding and hyperplasia (Cortés-Gallegos et al., 485 1975). Given that abnormal bleeding and hyperplasia are important symptoms of endometrial 486 polyps, it suggests that localised oestradiol may play a more crucial role in EP development. 487 Additionally, a study reported no significant difference in circulating oestradiol concentration 488 among women with and without endometrial polyps (Cortés-Gallegos et al. , 1975) , which 489 further supports our finding. This can also explain the lack of correlation of FGT polyps with 490 . CC-BY-NC-ND 4.0 International licenseIt is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint The copyright holder for thisthis version posted January 30, 2024. ; https://doi.org/10.1101/2024.01.29.24301773doi: medRxiv preprint 26 BMI to some extent, as higher BMI is often associated with increased circulating oestradiol 491 levels. 492 To understand how genetic variation impacts trait susceptibility, it is important to link 493 associated genetic variants with specific genes and mechanisms. We employed a diverse range 494 of data layers to map potential candidate genes for the identified genomic loci. Among others, 495 PRIM1 (rs2277339) and COL17A1 (rs193097753) were prioritised since the GWAS signals 496 tagged coding variants in these genes. In the literature, neither of these genes has been directly 497 correlated with FGT development. The PRIM1 gene is a key regulator of DNA replication 498 during cellular proliferation process. It has been shown that the PRIM1 expression was 499 upregulated in breast tumour tissues compared to healthy tissues, and its inhibition led to 500 tumour cell growth regression (Lee et al., 2019). Furthermore, the PRIM1-induced tumour cell 501 growth is stimulated by oestrogen through activation of the oestrogen receptor (ER) (Lee et al., 502 2019). As per one of the postulated hypotheses, polyp development is related to oestrogen 503 stimulation with predominantly increased ER alpha (ER -alpha) and decreased progesterone 504 receptors (PRs) A and B in the glandular epithelium. On the other hand, in the stromal cells of 505 polyps, lower concentrations of ER and PR hinder the decidualization process, preventing them 506 from shedding off during menstruation (Mittal et al., 1996; Peng et al., 2009; Nijkang et al., 507 2019). Since the PRIM1 gene signalling is oestrogen -associated, this can provide important 508 insights into the probable functional mechanisms underlying the development of polyps. The 509 COL17A1 gene is closely associated with epithelial tumour progression and invasiveness (Jones 510 et al. , 2020) , suggesting that a shared biological mechanism related to epithelial cell 511 proliferation could be associated with the development of EPs. However, further functional 512 assays on PRIM1 and COL17A1 genes are needed to confirm these associations. 513 While our study is a large -scale study, it had certain limitations. The cohort from 514 Estonian and Finnish biobanks encompasses women with all kinds of reproductive polyps, and 515 . CC-BY-NC-ND 4.0 International licenseIt is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint The copyright holder for thisthis version posted January 30, 2024. ; https://doi.org/10.1101/2024.01.29.24301773doi: medRxiv preprint 27 our phenotype definition did not differentiate between the types/location of polyps to increase 516 study sample size power. However, considering the overall occurrence of polyps in the general 517 population, endometrial polyps would be more prevalent than the other types. A complete 518 understanding of the transcriptome profile of endometrial polyps is still lacking, resulting in 519 knowledge gaps regarding the interplay between genomic loci and the regulation of gene 520 expression. By addressing these knowledge gaps, we can gain valuable insights into the genetic 521 factors and gene expression patterns that contribute to the pathogenesis of endometrial polyps 522 and potentially identify novel therapeutic targets for their management. 523 In conclusion, the first GWAS meta-analysis of FGT polyps highlights and clarifies the 524 genetic mechanisms shared between EP development (tissue overgrowth) and cancerous 525 processes. Furthermore, an analysis of associated diagnoses showed that women diagnosed with 526 EPs have an increased prevalence of other diagnoses, such as endometriosis, uterine fibroids 527 and both benign and malignant neoplasms, which could have implications for patient 528 management and counselling. 529 Supplementary data: Supplementary data are available at Human reproduction online. 530 Data availability: FinnGen cohort level summary statistics can be accessed as described here: 531 https://www.finngen.fi/en/access_results. Protocol for accessing the Estonian Biobank data is 532 described here: https://genomics.ut.ee/en/content/estonian-biobank. GWAS meta -analysis 533 summary statistics will be made available via the GWAS Catalogue (data upload pending). 534 Author’s roles: Authors A.D.S.P., N.P.G, A.S., M.P and T.L. participated in the conception of 535 the study, data analysis, and interpretation of the data, and writing the manuscript. V.R., J.D., 536 and R.M. contributed to data analysis and interpretation. T.L., M.S., M.P., V.R., J.D. and A.S. 537 critically reviewed and provided feedback on each version of the manuscript and all the authors 538 approved the final version. The EstBB Research Team provided the EstBB genotype and 539 phenotype data. 540 . 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We want to acknowledge the participants of the Estonian Biobank and 541 the participants and investigators of the FinnGen study. We also acknowledge the Estonian 542 Biobank Research team members Andres Metspalu, Tonu Esko, Mari Nelis, Georgi Hudjashov, 543 and Lili Milani. 544 Funding: N.P.G. was supported by MATER Marie Sklodowska-Curie which received funding 545 from the European Union’s Horizon 2020 research and innovation programme under grant 546 agreement No. 813707. T.L. was supported by the Estonian Research Council grant PSG776. 547 This study was funded by European Union through the European Regional Development Fund 548 Project No. 2014-2020.4.01.15-0012 GENTRANSMED. Computations were performed in the 549 High-Performance Computing Center of University of Tartu. The study was also supported by 550 the Estonian Research Council (grant no. PRG1076 and MOBJD1056 ) and Horizon 2020 551 innovation grant (ERIN, grant no. EU952516). 552 Conflict of interest: All the authors declared no conflict of interest. 553 554

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CC-BY-NC-ND 4.0 International licenseIt is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint The copyright holder for thisthis version posted January 30, 2024. ; https://doi.org/10.1101/2024.01.29.24301773doi: medRxiv preprint 37 Supplementary materials: 758 Supplementary figure 1: Genome-wide gene association analysis of our GWAS dataset 759 using ‘Multi-marker Analysis of GenoMic Annotation (MAGMA) wherein input SNPs 760 were mapped to 18895 protein -coding genes. On the Manhattan plot, the y -axis represents 761 −log10(P-values) for the association of variants identified in polyps of the female genital tract. 762 The horizontal red dashed line represents the genome -wide significance threshold (P < 5 × 763 10−8) and prioritised genes for each locus are shown. Genes associated with exonic missense 764 variants are denoted in red text. 765 766 Supplementary Tables: 767 ST 1 Genes mapped by expression quantitative trait loci (eQTL) and Chromatin interactions 768 by Functional Mapping and Annotation of Genome-Wide Association Studies (FUMA 769 GWAS) 770 ST 2 Results of the Multi -marker Analysis of GenoMic Annotation (MAGMA) gene -based 771 analysis 772 ST 3 Results of the GWAS catalogue lookup 773 ST 4 Look-up of the 10 lead variants in endometrial cancer summary statistics 774 (https://pubmed.ncbi.nlm.nih.gov/31040137/) 775 ST 5 Genetic correlation between female genital tract polyps and other traits 776 ST 6 Phenotypes associated with Polyps of the female genital tract 777 ST 7 Results of survival analysis lookup in FinnGen data 778 779 780 781 . CC-BY-NC-ND 4.0 International licenseIt is made available under a perpetuity. is the author/funder, who has granted medRxiv a license to display the preprint in(which was not certified by peer review)preprint The copyright holder for thisthis version posted January 30, 2024. ; https://doi.org/10.1101/2024.01.29.24301773doi: medRxiv preprint