Genetically predicted the causal relationship between gut microbiota and infertility: bidirectional Mendelian randomization analysis in the framework of predictive, preventive, and personalized medicine.

Objective Several studies have reported the association between gut microbiota and infertility; however, the causal association between them remains unclear. This study aimed to explore the causal relationship between gut microbiota and infertility and evaluate how specific gut microbiota can support early monitoring and prevention of infertility in the context of predictive, preventive, and personalized medicine (PPPM/3PM).

The gut microbiota GWAS data included 18,340 individuals. Female infertility (6481 cases and 68,969 controls) and male infertility data (680 cases and 72,799 controls) were obtained from the FinnGen consortium. The inverse variance weighting (IVW), MR-Egger, weighted median (WM), Cochran Q tests, MR-PRESSO, and leave-one-out were used as a supplement to Mendelian randomization (MR) results and sensitivity analysis.

The results of MR analysis indicated a significant causal association between Eubacterium oxidoreducens (OR = 2.048, P = 0.008), Lactococcus (OR = 1.445, P = 0.042), Eubacterium ventriosum (OR = 0.436, P = 0.018), Eubacterium rectale (OR = 0.306, P = 0.002), and Ruminococcaceae NK4A214 (OR = 0.537, P = 0.045) and male infertility. Genetically predicted Eubacterium ventriosum (OR = 0.809, P = 0.018), Holdemania (OR = 0.836, P = 0.037), Lactococcus (OR = 0.867, P = 0.020), Ruminococcaceae NK4A214 (OR = 0.830, P < 0.050), Ruminococcus torques (OR = 0.739, P = 0.022), and Faecalibacterium (OR = 1.311, P = 0.007) were associated with female infertility. Sensitivity analysis did not detect heterogeneity and pleiotropy (P > 0.05).

Our results provided evidence for the causal relationship between some gut microbiota and male and female infertility. These findings might be valuable in providing personalized treatment options for preventing infertility and improving reproductive function by monitoring and regulating the gut microbiota of infertility patients in the context of PPPM. Moreover, detecting the abundance of microbiota in feces can support preventive and personalized strategies, which may benefit more infertility patients. Similar content being viewed by others Data availability All data could be found in the IEU OpenGWAS project (https://gwas.mrcieu.ac.uk/). Code availability The software and code used in the study could be obtained through the corresponding author. Abbreviations - PPPM/3PM : - Predictive, preventive, and personalized medicine - PCOS : - Polycystic ovary syndrome - MR : - Mendelian randomization - IVs : - Instrumental variables - TSMR : - Two-sample Mendelian randomization - mbTL : - Microbiome trait locus - GWAS : - Genome-Wide Association Studies - SNPs : - Single-nucleotide polymorphisms - LD : - Linkage disequilibrium - IVW : - Inverse variance weighting - WM : - Weighted median - GWG : - Gestational weight gain - UTIs : - Urinary tract infections - FMT : - Fecal microbiota transplantation

Inhorn MC, Patrizio P. Infertility around the globe: new thinking on gender, reproductive technologies and global movements in the 21st century. Hum Reprod Update. 2015;21(4):411–26. Starc A, Trampuš M, Pavan Jukić D, Rotim C, Jukić T, Polona Mivšek A. Infertility and sexual dysfunctions: a systematic literature review. Acta Clin Croat. 2019;58(3):508–15. Tamrakar SR, Bastakoti R. Determinants of infertility in couples. J Nepal Health Res Counc. 2019;17(1):85–9. Golubnitschaja O, Costigliola V. Epma: General report & recommendations in predictive, preventive and personalised medicine 2012: white paper of the European Association for Predictive, Preventive and Personalised Medicine. EPMA J. 2012;3(1):14. Ahmadian E, Rahbar Saadat Y, Hosseiniyan Khatibi SM, Nariman-Saleh-Fam Z, Bastami M, Zununi Vahed F, Ardalan M, Zununi Vahed S. Pre-eclampsia: microbiota possibly playing a role. Pharmacol Res. 2020;155:104692. Jiang I, Yong PJ, Allaire C, Bedaiwy MA. Intricate connections between the microbiota and endometriosis. Int J Mol Sci. 2021;22(11):5644. Guo J, Shao J, Yang Y, Niu X, Liao J, Zhao Q, Wang D, Li S, Hu J. Gut microbiota in patients with polycystic ovary syndrome: a systematic review. Reprod Sci. 2022;29(1):69–83. Lundy SD, Sangwan N, Parekh NV, Selvam MKP, Gupta S, McCaffrey P, Bessoff K, Vala A, Agarwal A, Sabanegh ES, et al. Functional and taxonomic dysbiosis of the gut, urine, and semen microbiomes in male infertility. Eur Urol. 2021;79(6):826–36. Bubnov R, Spivak M. Pathophysiology-based individualized use of probiotics and prebiotics for metabolic syndrome: implementing predictive, preventive, and personalized medical approach. In Microbiome in 3P Medicine Strategies edn. 2023;14(8):133–96. Gibson GR, Hutkins R, Sanders ME, Prescott SL, Reimer RA, Salminen SJ, Scott K, Stanton C, Swanson KS, Cani PD, et al. Expert consensus document: the International Scientific Association for Probiotics and Prebiotics (ISAPP) consensus statement on the definition and scope of prebiotics. Nat Rev Gastroenterol Hepatol. 2017;14(8):491–502. Qi X, Yun C, Sun L, Xia J, Wu Q, Wang Y, Wang L, Zhang Y, Liang X, Wang L, et al. Gut microbiota-bile acid-interleukin-22 axis orchestrates polycystic ovary syndrome. Nat Med. 2019;25(8):1225–33. Zhao Q, Huang JF, Cheng Y, Dai MY, Zhu WF, Yang XW, Gonzalez FJ, Li F. Polyamine metabolism links gut microbiota and testicular dysfunction. Microbiome. 2021;9(1):224. Bertele N, Karabatsiakis A, Buss C, Talmon A. How biomarker patterns can be utilized to identify individuals with a high disease burden: a bioinformatics approach towards predictive, preventive, and personalized (3P) medicine. EPMA J. 2021;12(4):507–16. Davey Smith G, Hemani G. Mendelian randomization: genetic anchors for causal inference in epidemiological studies. Hum Mol Genet. 2014;23(R1):R89-98. Golubnitschaja O, Baban B, Boniolo G, Wang W, Bubnov R, Kapalla M, Krapfenbauer K, Mozaffari MS, Costigliola V. Medicine in the early twenty-first century: paradigm and anticipation - EPMA position paper 2016. EPMA J. 2016;7(1):23. Golubnitschaja O, Kinkorova J, Costigliola V. Predictive, preventive and personalised medicine as the hardcore of ‘Horizon 2020’: EPMA position paper. EPMA J. 2014;5(1):6. Ran Y, He J, Peng W, Liu Z, Mei Y, Zhou Y, Yin N, Qi H. Development and validation of a transcriptomic signature-based model as the predictive, preventive, and personalized medical strategy for preterm birth within 7 days in threatened preterm labor women. EPMA J. 2022;13(1):87–106. Kurilshikov A, Medina-Gomez C, Bacigalupe R, Radjabzadeh D, Wang J, Demirkan A, Le Roy CI, Raygoza Garay JA, Finnicum CT, Liu X, et al. Large-scale association analyses identify host factors influencing human gut microbiome composition. Nat Genet. 2021;53(2):156–65. Lv BM, Quan Y, Zhang HY. Causal inference in microbiome medicine: principles and applications. Trends Microbiol. 2021;29(8):736–46. Jiang L, Miao L, Yi G, Li X, Xue C, Li MJ, Huang H, Li M. Powerful and robust inference of complex phenotypes’ causal genes with dependent expression quantitative loci by a median-based Mendelian randomization. Am J Hum Genet. 2022;109(5):838–56. Staley JR, Blackshaw J, Kamat MA, Ellis S, Surendran P, Sun BB, Paul DS, Freitag D, Burgess S, Danesh J, et al. PhenoScanner: a database of human genotype-phenotype associations. Bioinformatics. 2016;32(20):3207–9. Kamat MA, Blackshaw JA, Young R, Surendran P, Burgess S, Danesh J, Butterworth AS, Staley JR. PhenoScanner V2: an expanded tool for searching human genotype-phenotype associations. Bioinformatics. 2019;35(22):4851–3. Burgess S, Butterworth A, Thompson SG. Mendelian randomization analysis with multiple genetic variants using summarized data. Genet Epidemiol. 2013;37(7):658–65. Burgess S, Davey Smith G, Davies NM, Dudbridge F, Gill D, Glymour MM, Hartwig FP, Holmes MV, Minelli C, Relton CL, et al. Guidelines for performing Mendelian randomization investigations. Wellcome Open Res. 2019;4:186. Bowden J, Davey Smith G, Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int J Epidemiol. 2015;44(2):512–25. Lin L, Lin J, Qiu J, Wei F, Bai X, Ma W, Zeng J, Lin D. Gut microbiota alterations may increase the risk of prescription opioid use, but not vice versa: A two-sample bi-directional Mendelian randomization study. Front Microbiol. 2022;13:994170. Giri S, Grimshaw A, Bal S, Godby K, Kharel P, Djulbegovic B, Dimopoulos MA, Facon T, Usmani SZ, Mateos MV, et al. Evaluation of daratumumab for the treatment of multiple myeloma in patients with high-risk cytogenetic factors: a systematic review and meta-analysis. JAMA Oncol. 2020;6(11):1759–65. Rushing C, Bulusu A, Hurwitz HI, Nixon AB, Pang H. A leave-one-out cross-validation SAS macro for the identification of markers associated with survival. Comput Biol Med. 2015;57:123–9. Bodrova TA, Kostyushev DS, Antonova EN, Slavin S, Gnatenko DA, Bocharova MO, Legg M, Pozzilli P, Paltsev MA, Suchkov SV. Introduction into PPPM as a new paradigm of public health service: an integrative view. EPMA J. 2012;3(1):16. Ma LK, Xue Y, He TC, Zhang YM. Associations of socioeconomic factors, nutrients intake, and gut microbiota of healthy pregnant women in the third trimester with gestational weight gain. Zhongguo Yi Xue Ke Xue Yuan Xue Bao. 2018;40(5):630–6. Ding H, Wang Y, Li Z, Li Q, Liu H, Zhao J, Lu W, Wang J. Baogong decoction treats endometritis in mice by regulating uterine microbiota structure and metabolites. Microb Biotechnol. 2022;15(11):2786–99. Zhou L, Ni Z, Cheng W, Yu J, Sun S, Zhai D, Yu C, Cai Z. Characteristic gut microbiota and predicted metabolic functions in women with PCOS. Endocr Connect. 2020;9(1):63–73. Taghinezhad SS, Keyvani H, Bermúdez-Humarán LG, Donders GGG, Fu X, Mohseni AH. Twenty years of research on HPV vaccines based on genetically modified lactic acid bacteria: an overview on the gut-vagina axis. Cell Mol Life Sci. 2021;78(4):1191–206. Rampanti G, Ferrocino I, Harasym J, Foligni R, Cardinali F, Orkusz A, Milanović V, Franciosa I, Garofalo C, Mannozzi C, et al. Queijo serra da estrela PDO cheese: investigation into its morpho-textural traits, microbiota, and volatilome. Foods. 2022;12(1):169. Pozzi E, Fallara G, Belladelli F, Corsini C, Raffo M, Candela L, Schifano N, d’Arma A, Capogrosso P, Boeri L, et al. Clinical parameters associated with altered sperm DNA fragmentation index among primary infertile men: findings from a real-life cross-sectional study. Andrology. 2023. https://doi.org/10.1111/andr.13380. Marchiani S, Baccani I, Tamburrino L, Mattiuz G, Nicolò S, Bonaiuto C, Panico C, Vignozzi L, Antonelli A, Rossolini GM, et al. Effects of common Gram-negative pathogens causing male genitourinary-tract infections on human sperm functions. Sci Rep. 2021;11(1):19177. Li H, Li N, Lu Q, Yang J, Zhao J, Zhu Q, Yi S, Fu W, Luo T, Tang J, et al. Chronic alcohol-induced dysbiosis of the gut microbiota and gut metabolites impairs sperm quality in mice. Front Microbiol. 2022;13:1042923. Hasan H, Bhushan S, Fijak M, Meinhardt A. Mechanism of inflammatory associated impairment of sperm function, spermatogenesis and steroidogenesis. Front Endocrinol. 2022;13:897029. Tariq EF, Irshad Y, Khalil HB, Khakwani AS, Khan UA. Urinary tract infection caused by the novel pathogen, Lactococcus Garvieae: a case report. Cureus. 2020;12(7):e9462. Hao Y, Feng Y, Yan X, Chen L, Zhong R, Tang X, Shen W, Sun Q, Sun Z, Ren Y, et al. Gut microbiota-testis axis: FMT improves systemic and testicular micro-environment to increase semen quality in type 1 diabetes. Mol Med. 2022;28(1):45. Zhang T, Sun P, Geng Q, Fan H, Gong Y, Hu Y, Shan L, Sun Y, Shen W, Zhou Y. Disrupted spermatogenesis in a metabolic syndrome model: the role of vitamin A metabolism in the gut-testis axis. Gut. 2022;71(1):78–87. Wang Y, Xie Z. Exploring the role of gut microbiome in male reproduction. Andrology. 2022;10(3):441–50. Corrie L, Gulati M, Vishwas S, Kapoor B, Singh SK, Awasthi A, Khursheed R. Combination therapy of curcumin and fecal microbiota transplant: potential treatment of polycystic ovarian syndrome. Med Hypotheses. 2021;154:110644. Reid G, Abrahamsson T, Bailey M, Bindels LB, Bubnov R, Ganguli K, Martoni C, O’Neill C, Savignac HM, Stanton C, et al. How do probiotics and prebiotics function at distant sites? Benef Microbes. 2017;8(4):521–33. Chadchan SB, Singh V, Kommagani R. Female reproductive dysfunctions and the gut microbiota. J Mol Endocrinol. 2022;69(3):R81–94. Hao Y, Feng Y, Yan X, Chen L, Ma X, Tang X, Zhong R, Sun Z, Agarwal M, Zhang H, et al. Gut microbiota-testis axis: FMT mitigates high-fat diet-diminished male fertility via improving systemic and testicular metabolome. Microbiol Spectr. 2022;10(3):e0002822. Yan X, Feng Y, Hao Y, Zhong R, Jiang Y, Tang X, Lu D, Fang H, Agarwal M, Chen L, et al. Gut-testis axis: microbiota prime metabolome to increase sperm quality in young type 2 diabetes. Microbiol Spectr. 2022;10(5):e0142322. Bubnov RV, Babenko LP, Lazarenko LM, Mokrozub VV, Spivak MY. Specific properties of probiotic strains: relevance and benefits for the host. EPMA J. 2018;9(2):205–23. Slim K, Selvy M, Veziant J. Conceptual innovation: 4P Medicine and 4P surgery. J Visc Surg. 2021;158(3S):S12–7. Warren M. The approach to predictive medicine that is taking genomics research by storm. Nature. 2018;562(7726):181–3. Bowden J, Holmes MV. Meta-analysis and Mendelian randomization: a review. Res Synth Methods. 2019;10(4):486–96. Birney E. Mendelian randomization. Cold Spring Harb Perspect Med. 2022;12(4):a041302. Wang Y, Li T, Fu L, Yang S, Hu YQ. A novel method for Mendelian randomization analyses with pleiotropy and linkage disequilibrium in genetic variants from individual data. Front Genet. 2021;12:634394. Hashem NM, Gonzalez-Bulnes A. The use of probiotics for management and improvement of reproductive eubiosis and function. Nutrients. 2022;14(4):902. Quaranta G, Sanguinetti M, Masucci L. Fecal microbiota transplantation: a potential tool for treatment of human female reproductive tract diseases. Front Immunol. 2019;10:2653. Oroojalian F, Beygi M, Baradaran B, Mokhtarzadeh A, Shahbazi MA. Immune cell membrane-coated biomimetic nanoparticles for targeted cancer therapy. Small. 2021;17(12):e2006484.

We would like to express our gratitude to the participants and investigators of the FinnGen study. Thanks also to the MiBioGen consortium for publishing the GWAS summary statistics of the gut microbiota. Funding This study was supported by Wu Jieping Medical Foundation (No. 320.6750.2022–02-39). Author information Authors and Affiliations Contributions Y. J. X. and C. W. Z. conceived and designed the study. S. R. Z., Y. Q. F., and Y. K. Z. contributed to obtaining the data and analysis. Y. K. Z., G. S. D., and C. W. Z. provided support in the visualization of results. Y. J. X., C. W. Z., and Y. Q. F. drafted the manuscript. J. Q. W., W. W. and Y. J. X. critically revised this article. All authors gave final approval for the version to be published. Corresponding author Ethics declarations Consent to participate Not applicable to this study. Competing interests The authors declare no competing interests. Additional information Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Supplementary Information Below is the link to the electronic supplementary material. Rights and permissions Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. About this article Cite this article Xi, Y., Zhang, C., Feng, Y. et al. Genetically predicted the causal relationship between gut microbiota and infertility: bidirectional Mendelian randomization analysis in the framework of predictive, preventive, and personalized medicine. EPMA Journal 14, 405–416 (2023). https://doi.org/10.1007/s13167-023-00332-6 Received: Accepted: Published: Version of record: Issue date: DOI: https://doi.org/10.1007/s13167-023-00332-6