Unexplained infertility is diagnosed when standard investigations—including assessments of ovulation, tubal patency, and semen parameters—fail to reveal a definitive cause for infertility. It accounts for approximately 15–30% of infertility cases worldwide, posing significant challenges in clinical decision-making and management strategies [1]. Assisted reproductive technologies (ART), particularly in vitro fertilization (IVF), are commonly employed in such cases. However, IVF success rates in this subgroup remain highly variable, suggesting the presence of unrecognized biological factors influencing implantation and pregnancy outcomes [2].

Recent advances in microbiome research have highlighted the critical role of the female reproductive tract microbiota in reproductive health. The vaginal microbiome, dominated by Lactobacillus species in healthy women, plays a protective role by maintaining acidic pH, producing bacteriocins, and preventing the colonization of pathogenic organisms [3]. Disruptions in this microbial equilibrium—termed dysbiosis—have been associated with gynecological disorders such as bacterial vaginosis, pelvic inflammatory disease, recurrent miscarriage, and preterm birth [4,5].

Several studies have suggested that non-Lactobacillus-dominant vaginal microbiota, especially those enriched with Gardnerella vaginalis, Atopobium vaginae, and Prevotella species, may contribute to impaired endometrial receptivity and lower IVF implantation rates [6,7]. It has been hypothesized that dysbiotic microbial communities generate pro-inflammatory cytokines, alter immune tolerance, and interfere with embryo-endometrial interaction, ultimately affecting pregnancy outcomes [8,9]. Conversely, the presence of Lactobacillus crispatus and other commensals has been associated with higher rates of embryo implantation and live birth [10].

Despite the growing body of evidence linking reproductive outcomes to vaginal microbial composition, the specific influence of vaginal microbiota in women with unexplained infertility undergoing IVF remains underexplored. Given the absence of identifiable pathologies in these patients, evaluating the vaginal microbial milieu could provide insights into subtle contributors to implantation failure.

Therefore, this study aims to investigate the association between vaginal microbiota composition and IVF success rates in women with unexplained infertility, using 16S rRNA gene sequencing to characterize microbial profiles and correlate them with clinical pregnancy outcomes.

Study Design and Participants

A total of 120 women aged 25 to 38 years, diagnosed with unexplained infertility and undergoing their first IVF cycle, were enrolled after obtaining informed written consent.

Inclusion and Exclusion Criteria

Inclusion criteria included women with regular menstrual cycles, normal ovarian reserve (AMH >1.5 ng/mL), and normal tubal and uterine evaluation. All male partners had normal semen parameters based on WHO 2010 guidelines. Women with known causes of infertility such as endometriosis, polycystic ovarian syndrome (PCOS), uterine anomalies, or chronic infections were excluded. Recent use of antibiotics, probiotics, or vaginal medications within four weeks of enrollment also led to exclusion.

Sample Collection and Microbiota Profiling

Vaginal samples were collected using sterile swabs during the early follicular phase (days 2–4 of the menstrual cycle), before the initiation of ovarian stimulation. Swabs were immediately placed in DNA preservation buffer and stored at −80°C until further analysis.

Microbial DNA was extracted using the QIAamp DNA Mini Kit following standard protocols. The V3–V4 hypervariable regions of the 16S rRNA gene were amplified and sequenced using Illumina MiSeq technology. Bioinformatic analysis was conducted using the QIIME2 pipeline. Taxonomic classification was performed using the SILVA database. Samples were categorized as Lactobacillus-dominant (LD) if Lactobacillus species constituted ≥80% of the total microbiota, and as non-Lactobacillus-dominant (NLD) if otherwise.

IVF Protocol and Outcome Assessment

All participants underwent controlled ovarian stimulation using a standard antagonist protocol. Oocyte retrieval was followed by intracytoplasmic sperm injection (ICSI), and embryo transfer was performed on day 5. Clinical pregnancy was confirmed by the presence of a gestational sac on transvaginal ultrasound 4–5 weeks post-embryo transfer.

Statistical Analysis

Data were analyzed using SPSS software version 25.0. Continuous variables were expressed as mean ± standard deviation, and categorical variables as frequencies and percentages. Group comparisons were performed using Student’s t-test or chi-square test, as appropriate. Logistic regression analysis was used to determine independent predictors of clinical pregnancy. A p-value of <0.05 was considered statistically significant.

A total of 120 women with unexplained infertility were included in the final analysis. Participants were categorized into two groups based on their vaginal microbiota composition: the Lactobacillus-dominant (LD) group (n = 68, 56.7%) and the non-Lactobacillus-dominant (NLD) group (n = 52, 43.3%).

Demographic and clinical characteristics between the two groups are summarized in Table 1. No statistically significant differences were observed in age, BMI, duration of infertility, or ovarian reserve markers, indicating comparable baseline characteristics.

Table 1: Baseline Characteristics of Study Participants

Analysis of 16S rRNA sequencing revealed distinct microbial patterns between groups. In the LD group, Lactobacillus crispatus and Lactobacillus iners were predominant, whereas the NLD group showed higher abundance of Gardnerella vaginalis, Atopobium vaginae, and Prevotella species (Table 2).

Table 2: Dominant Vaginal Microbiota Composition by Group

*Statistically significant

The clinical pregnancy rate was significantly higher in the LD group compared to the NLD group—48.5% (33/68) versus 21.2% (11/52), respectively (p = 0.002) (Table 3). Implantation rates and biochemical pregnancy rates also favored the LD group.

Table 3: IVF Outcomes in LD and NLD Groups

*Statistically significant

Multivariate logistic regression analysis identified Lactobacillus dominance as an independent predictor of clinical pregnancy (OR = 2.9; 95% CI: 1.4–6.1; p = 0.004). Other factors such as age, BMI, and ovarian reserve did not show a significant association.

These findings suggest a strong positive correlation between vaginal Lactobacillus-dominated microbiota and improved IVF outcomes in women with unexplained infertility (Tables 2 and 3).

The present study demonstrates a significant association between vaginal microbiota composition and IVF outcomes in women diagnosed with unexplained infertility. Specifically, we observed that dominance of Lactobacillus species, particularly L. crispatus and L. iners, was associated with improved clinical pregnancy and implantation rates, while the presence of potentially pathogenic species such as Gardnerella vaginalis and Atopobium vaginae correlated with reduced reproductive success.

The role of the vaginal microbiome in reproductive health has garnered increasing attention over the past decade. A healthy vaginal microbiota, typically dominated by Lactobacillus spp., contributes to local immune regulation, protection against pathogens, and maintenance of a favorable pH environment [1,2]. In contrast, microbial dysbiosis characterized by reduced Lactobacillus abundance and increased anaerobes has been linked to adverse gynecological and obstetric outcomes, including pelvic inflammatory disease, recurrent miscarriage, and preterm birth [3–5].

In the context of assisted reproduction, several studies have indicated that altered vaginal or endometrial microbial profiles may negatively impact embryo implantation and pregnancy maintenance. A study by Moreno et al. revealed that non-Lactobacillus-dominated endometrial microbiota was associated with significantly lower implantation and pregnancy rates in IVF patients [6]. Similarly, Koedooder et al. reported that women with a high relative abundance of Lactobacillus in their vaginal microbiota had a significantly higher likelihood of achieving a successful pregnancy following IVF treatment [7].

Our findings are in agreement with these observations and further reinforce the importance of microbial balance in the reproductive tract. The negative association of G. vaginalis and A. vaginae with IVF success in our cohort is consistent with previous reports that have identified these species as key contributors to bacterial vaginosis and pro-inflammatory responses in the female reproductive tract [8,9]. These organisms may disrupt the endometrial environment by producing cytotoxins and biofilms, impeding embryo implantation [10].

Interestingly, the presence of Lactobacillus iners—though traditionally considered protective—has shown a more nuanced role. While L. iners was common in our LD group, some studies suggest it may be less stable and potentially associated with transitional microbial states [11,12]. However, in our study, the LD group still showed significantly better IVF outcomes, suggesting that even partial dominance of Lactobacillus may confer benefit over pathogenic profiles.

One strength of this study is the use of 16S rRNA gene sequencing, which allows for comprehensive and high-resolution identification of vaginal microbial communities. This approach has been widely adopted in reproductive microbiome studies due to its ability to detect low-abundance taxa that may otherwise be missed by culture-based techniques [13]. Furthermore, the timing of sample collection—during the follicular phase prior to ovarian stimulation—minimizes potential hormonal influences on microbial composition.

Nevertheless, there are limitations to consider. First, we focused only on vaginal microbiota and did not analyze endometrial microbial communities, which may have a more direct impact on implantation [14]. Second, while our findings suggest a strong association, causality cannot be inferred. Interventional studies using probiotics or antibiotics to modulate the microbiota may help establish a clearer cause-effect relationship. Third, environmental and behavioral factors, such as diet, sexual activity, and hygiene practices, were not controlled, which may influence microbial profiles [15].

This study highlights a strong association between vaginal microbiota composition and IVF outcomes in women with unexplained infertility. Dominance of Lactobacillus species, particularly L. crispatus, was significantly linked to higher clinical pregnancy and implantation rates. These findings support the potential role of vaginal microbiome profiling as a non-invasive biomarker to predict IVF success and tailor fertility treatments. Future interventional studies are warranted to explore microbiota-targeted therapies for improving reproductive outcomes.

1. Koedooder R, Singer M, Schoenmakers S, Savelkoul PHM, Morré SA, de Jonge JD, et al. The vaginal microbiome as a predictor for outcome of in vitro fertilization with or without intracytoplasmic sperm injection: a prospective study. Hum Reprod. 2019;34(6):1042–54. doi:10.1093/humrep/dez065.
2. Leijdekkers JA, Eijkemans MJC, van Tilborg TC, Oudshoorn SC, van Golde RJT, Hoek A, et al. Cumulative live birth rates in low-prognosis women. Hum Reprod. 2019;34(6):1030–41. doi:10.1093/humrep/dez051.
3. van Hoogenhuijze NE, Mol F, Laven JSE, Groenewoud ER, Traas MAF, Janssen CAH, et al. Endometrial scratching in women with one failed IVF/ICSI cycle—outcomes of a randomized controlled trial (SCRaTCH). Hum Reprod. 2021;36(1):87–98. doi:10.1093/humrep/deaa268.
4. Maheshwari A, Bell JL, Bhide P, Brison D, Child T, Chong HY, et al. Elective freezing of embryos versus fresh embryo transfer in IVF: a multicentre randomized controlled trial in the UK (E-Freeze). Hum Reprod. 2022;37(3):476–87. doi:10.1093/humrep/deab279.
5. Leijdekkers JA, Eijkemans MJC, van Tilborg TC, Oudshoorn SC, McLernon DJ, Bhattacharya S, et al. Predicting the cumulative chance of live birth over multiple complete cycles of in vitro fertilization: an external validation study. Hum Reprod. 2018;33(9):1684–95. doi:10.1093/humrep/dey263.
6. Verpoest W, Staessen C, Bossuyt PM, Goossens V, Altarescu G, Bonduelle M, et al. Preimplantation genetic testing for aneuploidy by microarray analysis of polar bodies in advanced maternal age: a randomized clinical trial. Hum Reprod. 2018;33(9):1767–76. doi:10.1093/humrep/dey262.
7. Esteves SC, Yarali H, Vuong LN, Carvalho JF, Özbek İY, Polat M, et al. Cumulative delivery rate per aspiration IVF/ICSI cycle in POSEIDON patients: a real-world evidence study of 9073 patients. Hum Reprod. 2021;36(8):2157–69. doi:10.1093/humrep/deab152.
8. Guideline Group on Unexplained Infertility, Romualdi D, Ata B, Bhattacharya S, Bosch E, Costello M, et al. Evidence-based guideline: unexplained infertility. Hum Reprod. 2023;38(10):1881–90. doi:10.1093/humrep/dead150.
9. Hamdine O, Macklon NS, Eijkemans MJ, Laven JS, Cohlen BJ, Verhoeff A, et al. Comparison of early versus late initiation of GnRH antagonist co-treatment for controlled ovarian stimulation in IVF: a randomized controlled trial. Hum Reprod. 2013;28(12):3227–35. doi:10.1093/humrep/det374.
10. Pilegaard SP, Schmidt L, Stormlund S, Koert E, Bogstad JW, Prætorius L, et al. Psychosocial wellbeing shortly after allocation to a freeze-all strategy compared with a fresh transfer strategy in women and men: a sub-study of a randomized controlled trial. Hum Reprod. 2023;38(11):2175–86. doi:10.1093/humrep/dead188.
11. Thomsen LH, Kesmodel US, Erb K, Bungum L, Pedersen D, Hauge B, et al. The impact of luteal serum progesterone levels on live birth rates—a prospective study of 602 IVF/ICSI cycles. Hum Reprod. 2018;33(8):1506–16. doi:10.1093/humrep/dey226.
12. van Tilborg TC, Oudshoorn SC, Eijkemans MJC, Mochtar MH, van Golde RJT, Hoek A, et al. Individualized FSH dosing based on ovarian reserve testing in women starting IVF/ICSI: a multicentre trial and cost-effectiveness analysis. Hum Reprod. 2017;32(12):2485–95. doi:10.1093/humrep/dex321.
13. Koot YEM, Hviid Saxtorph M, Goddijn M, de Bever S, Eijkemans MJC, van Wely M, et al. What is the prognosis for a live birth after unexplained recurrent implantation failure following IVF/ICSI? Hum Reprod. 2019;34(10):2044–52. doi:10.1093/humrep/dez120.
14. van Tilborg TC, Torrance HL, Oudshoorn SC, Eijkemans MJC, Koks CAM, Verhoeve HR, et al. Individualized versus standard FSH dosing in women starting IVF/ICSI: an RCT. Part 1: The predicted poor responder. Hum Reprod. 2017;32(12):2496–505. doi:10.1093/humrep/dex318.
15. Groenewoud ER, Cohlen BJ, Al-Oraiby A, Brinkhuis EA, Broekmans FJ, de Bruin JP, et al. A randomized controlled, non-inferiority trial of modified natural versus artificial cycle for cryo-thawed embryo transfer. Hum Reprod. 2016;31(7):1483–92. doi:10.1093/humrep/dew120.