Association of low progesterone levels and periodontal disease with threatened preterm labor

Abstract

Periodontal disease has been reported to increase the risk of threatened preterm labor (TPL). However, studies analyzing the oral, vaginal, and rectal lumen commensal flora in women with TPL are limited. In this study, a total of 60 women were enrolled, including 30 with TPL and 30 without TPL. We assessed periodontal clinical parameters, salivary hormone levels, and the microbiome using next-generation sequencing. Probing pocket depth (PPD) and bleeding on probing were greater in the TPL than in the non-TPL group. The TPL group was associated with lower progesterone levels and an increase in PPD ≥ 4 mm. Significant differences in alpha diversity in only vaginal Faith’s phylogenetic diversity, and significant differences in beta diversity at all sites were observed. ANCOM showed decreased Lactobacillales in the saliva and Bifidobacterium in the rectal lumen, and increased Staphylococcus in the oral cavity and vagina in the TPL group. The peptidoglycan synthesis pathway was significantly upregulated in the oral and vaginal tissues in the TPL group. Overall, the TPL group had lower progesterone levels and more severe periodontal disease; furthermore, the low progesterone levels in the TPL group were associated with oral and vaginal dysbiosis of the microbiota.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-026-35944-1.

Introduction

Preterm births (PTBs) are defined by the World Health Organization as births occurring before 37 weeks of gestation. PTBs occur in approximately 5% of deliveries in Japan. Threatened preterm labor (TPL) is a major risk factor for PTB. Women with TPL are considered to be at high risk for PTB and account for 15% of all pregnancies in Japan. TPL is defined according to the clinical criteria of regular uterine contractions accompanied by a change in cervical dilatation, effacement, or both, or initial presentation with regular uterine contractions and cervical dilatation of at least 2 cm during gestation from 22 weeks and 0 days to 36 weeks 6 days^1,2. Prevention of PTBs is urgently required, as serious health problems often occur in premature newborns. The causes of TPL are unknown; periodontal pathogen infection, the changes in the level of inflammatory mediators, host immune response, gene polymorphism, and anti-phospholipid syndrome have been recognized as common pathogeneses of periodontal disease and adverse pregnancy outcomes³. Of note, the involvement of dysbiosis of the bacterial flora in TPL has been suggested⁴.

More than a thousand trillion bacteria live in symbiosis on the surface and in the lumen of the human body. The total number of cells in the human body, calculated for various organs and cell types, corresponds to 3.72 × 10¹³⁵. These bacterial populations are known as the bacterial flora, and each part of the body contains its own bacterial flora. The oral cavity is inhabited by 500–700 bacterial species, each of which constitutes a different flora on the tooth surface, supragingival, subgingival, tongue surface, buccal mucosa, and saliva, causing oral diseases such as dental caries and periodontal disease^6,7.

Pregnant women with periodontal disease have a seven times higher risk of PTBs and low birth weight (LBW) than those with healthy periodontal tissue⁸. Several systematic reviews have suggested that periodontal therapy is effective against PTB and LBW^9–11. Jang et al.¹² suggested that changes in the overall bacterial flora may also be involved in the association between periodontal disease and PTBs. Placental bacterial flora is similar to oral bacterial flora; oral bacterial flora may influence pregnancy and PTBs¹³. Other reports have discussed the possibility that gut microbiota may influence PTBs^14,15. Thus, the various bacterial flora in the body may mutually influence the PTB. Regarding biological mechanisms of adverse pregnancy outcomes, direct and indirect mechanisms have been suggested. Direct mechanisms are mediated by oral microorganisms or their components invading the fetal–placenta unit via hematogenous dissemination, or in an ascending route via the genitourinary tract. Indirect mechanisms are mediated by inflammatory mediators locally produced in periodontal tissues, directly affecting the fetal–placental unit, or circulating to the liver and increasing the systemic inflammation state through acute phase protein responses, such as C-reactive protein, which would later impact the fetal–placental unit¹⁶.

Women with low vaginal levels of Lactobacillus are at increased risk of PTBs¹⁷. He et al.¹⁸ reported that low serum progesterone in the first trimester is a significant risk factor for LBW. It is suspected that Lactobacillus dominance in the vagina is estradiol- and/or progesterone-dependent^19–21, suggesting that increased risk for LBW in low serum progesterone may be mediated by low vaginal levels of Lactobacillus.

Prevotella intermedia was increased in response to the female sex hormone, and its increase was responsible for the pregnancy gingivitis²². We previously examined salivary progesterone, estrogen, and microbiome from periodontally healthy pregnant and non-pregnant women and reported that salivary progesterone, estrogen, and Bifidobacterium were higher in periodontally healthy pregnant than in non-pregnant women²³. Estradiol enriches short-chain fatty acid-producing taxa such as Bifidobacterium²⁴. These results suggest that female sex hormones stimulate the growth of not only Prevotella intermedia but also symbiotic bacteria (e.g., Bifidobacterium and Lactobacillus) that can utilize the hormone as nutrients.

Although substantial knowledge exists regarding the association between periodontal disease and PTB or LBW, studies analyzing oral, vaginal, and rectal commensal flora in women with TPL remain limited. Therefore, we aimed to investigate differences in salivary female hormones, periodontal tissue status, and bacterial flora between women with and without TPL (TPL and non-TPL groups, respectively).

Results

Relationship among TPL, female hormones, periodontal status, and clinical manifestations

The infant birth weight in the TPL group (mean 2105.3 g, range 450 − 3210 g) was lower than that in the non-TPL group (mean 3042.0 g, range 2120 − 3775 g). The gestational age of the TPL group (mean 33.4 weeks, range 23 − 39 weeks) was shorter than that of the non-TPL group (mean 39.1 weeks, range 36–41 weeks). In the TPL group, 16 pregnant women had PTB (gestational age: mean 30.8 weeks, range 23–36 weeks), and 14 infants were delivered with LBW (infant birth weight: mean 1584 g, range 450–2482 g; gestational age: mean 30.8 weeks, range 23–36 weeks). In the non-TPL group, one was born with PTB (36 weeks, 2820 g) and two were born full-term with LBW (38 weeks, 2490 g; 37 weeks, 2120 g) (Table 1 and Supplementary Table S1). The mean probing pocket depth (PPD), PPD ≥ 4 mm, %bleeding on probing (BOP), periodontal epithelial surface area (PESA)²⁵, and periodontal inflamed surface area (PISA)²⁵ were significantly higher in the TPL group than in the non-TPL group (Table 1).

Table 1.

Clinical characteristics of the TPL and non-TPL groups.

	Non-TPL group	TPL group	p
	(n = 30)	(n = 30)
Age (years)	29.9 ± 4.1	29.8 ± 5.9	0.988
	(23–40)	(17–42)
Height (cm)	157.9 ± 6.3	157.3 ± 5.9	0.590
	(148.0–168.0)	(148.0–170.0)
Weight (kg)	63.3 ± 8.6	58.3 ± 10.4	0.045
	(44.0–86.0)	(43.3–81.4)
BMI	25.4 ± 3.5	23.5 ± 3.8	0.058
	(19.5–32.7)	(17.0–31.8)
Gestational age (weeks)	39.1 ± 1.3	33.4 ± 4.7	0.000
	(36–41)	(23–39)
Infant birth weight (g)	3042.0 ± 434.6	2105.3 ± 840.0	0.000
	(2120–3775)	(450–3210)
Estradiol (pg/mL)	64.0 ± 71.5	48.6 ± 70.0	0.010
	(11.9–267.0)	(1.4–200.0)
Progesterone (pg/mL)	1757.5 ± 1608.4	845.7 ± 1498.4	0.000
	(283.4–9187.0)	(61.0–7723.6)
E/P ratio	0.04 ± 0.05	0.12 ± 0.20	0.126
	(0.006–0.26)	(0.005–0.74)
Mean PPD (mm)	2.2 ± 0.3	2.5 ± 0.3	0.000
	(1.6–2.7)	(1.6–2.9)
PD ≥ 4 mm (%)	1.6 ± 3.8	6.1 ± 9.1	0.000
	(0–16.1)	(0–33.3)
%BOP	8.1 ± 8.5	21.1 ± 21.6	0.003
	(0–29.6)	(0–92.0)
PESA (mm2)	1218.3 ± 151.9	1382.8 ± 174.0	0.001
	(891.6–1571.2)	(1075.2–1799.6)
PISA (mm2)	110.3 ± 129.1	329.5 ± 389.8	0.005
	(0–521.0)	(0–1676.1)
Smoker	3	4	0.725
	(former)	(former)

Clinical cut-offs: PPD ≥ 4 mm and ≥ 10% BOP (definition of healthy: no probing attachment loss, PPD ≤ 3 mm and ≤ 10% BOP). Values are shown as mean ± standard deviation (SD) (range) or percentage ± SD (range). Statistical analysis of clinical parameters in the TPL and non-TPL groups was performed using the Mann–Whitney U-test. BMI, body mass index; E/P ratio, Estradiol/Progesterone ratio; PPD, probing pocket depth; BOP, bleeding on probing; PESA, periodontal epithelial surface area; PISA, periodontal inflamed surface area; DMF, decayed, missing, and filled teeth. TPL, women with threatened preterm labor; non-TPL, healthy pregnant women.

The salivary estradiol and progesterone levels were significantly lower in the TPL group than in the non-TPL group. Estradiol/Progesterone (E/P) ratio was higher in the TPL group than in the non-TPL group, but the difference was not statistically significant (Table 1). The progesterone levels were significantly positively correlated with gestational age (p = 0.00027) and infant birth weight (p = 0.001) and significantly negatively correlated with PPD ≥ 4 mm (p = 0.009) and %BOP (p = 0.029) in all participants (Supplementary Table S2). Gestational age was significantly negatively correlated with mean PPD (p = 0.00026), PPD ≥ 4 mm (p = 0.001), %BOP (p = 0.000015), PESA (p = 0.00004), and PISA (p = 0.0001) in all participants. The infant birth weight negatively correlated with PPD ≥ 4 mm (p = 0.009), %BOP (p = 0.023), and PESA (p = 0.020) in all participants (Supplementary Table S3).

Multiple logistic regression analysis showed that TPL was negatively associated with salivary progesterone (odds ratio = 0.033, 95% confidence interval [CI]: 0.006 − 0.185) and positively associated with PPD ≥ 4 mm (odds ratio = 12.048, 95% CI: 2.178 − 66.627) (Table 2).

Table 2.

Logistic regression analysis of the association between TPL and clinical parameters.

Variables	Regression coefficient	Standard error	Wald2	p	OR	95% CI
						Low	High
Progesterone	− 3.401	0.874	15.142	0.000	0.033	0.006	0.185
PPD ≥ 4 mm	2.489	0.873	8.136	0.004	12.048	2.178	66.627
(Constant)	1.405	1.551	0.820	0.365	4.075

OR: odds ratio; CI: confidence interval.

Dependent variable: threatened preterm labor (TPL).

Independent variables: age, height, weight, BMI, estradiol, progesterone, E/P ratio, mean PPD, %PPD ≥ 4 mm, %BOP, PESA, PISA, DMF, and smoking status.

Categories used in the logistic regression analysis were as follows: age (< 30 vs. ≥ 30 years); height (< 158.0 vs. ≥ 158.0 cm); weight (< 60.1 vs. ≥ 60.1 kg); BMI (< 24.21 vs. ≥ 24.21 kg/m²), estradiol (< 25.044 vs. ≥ 25.044); progesterone (< 950.521 vs. ≥ 950.521); E/P ratio (< 0.037 vs. ≥ 0.037); mean PPD (< 2.357 vs. ≥ 2.357 mm); PPD ≥ 4 mm (< 0.595 vs. ≥ 0.595); BOP (< 10.0% vs. ≥ 10.0%); PESA (< 1297.1 vs. ≥ 1297.1); PISA (< 99.6 vs. ≥ 99.6); DMF (< 6 vs. ≥ 6); and smoking status (non-smoker vs. smoker).

BMI, body mass index; E/P ratio, Estradiol/Progesterone ratio; PPD, probing pocket depth; BOP, bleeding on probing; PESA, periodontal epithelial surface area; PISA, periodontal inflamed surface area; DMF, decayed, missing, and filled teeth.

Microbiome analysis

All 60 samples were sequenced using the MiSeq system. The taxonomic identity of the reads was analyzed using the Quantitative Insights into Microbial Ecology2 software package (QIIME2, version 2021.2; https://qiime2.org). The observed operational taxonomic units (OTUs) and Shannon diversity indices did not significantly differ between the TPL and the non-TPL groups. In contrast, Faith’s phylogenetic diversity was significantly higher in the TPL group than in the non-TPL group (Fig. 1a). Additionally, the weighted and unweighted UniFrac distances of the microbial communities were significantly different in the saliva, buccal mucosa, and vaginal mucosa of the TPL and non-TPL groups (Fig. 1b). In the rectal lumen, the unweighted UniFrac distance significantly differed between the TPL and the non-TPL groups, but the weighted UniFrac distance was not.

Fig. 1.

Comparisons of alpha and beta diversity in saliva, buccal, vaginal, and rectal lumen microbiome using next-generation sequencing. Similarities in the microbial communities of saliva, buccal mucosa, vaginal mucosa, and rectal lumen between the TPL and non-TPL groups. (a) Rarefaction analysis of 16S rRNA gene sequences obtained by comparing TPL and non-TPL groups. (b) Principal coordinate analysis (PCoA) representing beta diversity estimated by the weighted and unweighted UniFrac distances of the 16S rRNA genes in the TPL and non-TPL groups. TPL, women with threatened preterm labor; non-TPL, women without threatened preterm labor.

We analyzed the bacterial DNA sequence profiles and identified significant differences in the microbial taxa between the TPL and the non-TPL groups by analysis of the composition of microbiome (ANCOM) features using the QIIME2 program. In the saliva, 237 bacterial genera were detected, with Prevotella, Streptococcus, and Veillonella being the most abundant genera in the non-TPL group. Genera Prevotella, Veillonella, and Neisseria were detected in the TPL group. The order Lactobacillale in the saliva differed between the TPL and non-TPL groups (W = 138). In the buccal mucosa, 157 genera of bacteria were detected; the most abundant genera, from the highest to lowest abundance, were Streptococcus, Staphylococcus, and Pseudomonas in the non-TPL group, and Staphylococcus, Haemophilus, and Neisseria in the TPL group. In the ANCOM, the TPL group had a lower percentage of Veillonella than the non-TPL group (W = 155), and the TPL group had a higher percentage of Staphylococcus (W = 145). In the vaginal mucosa, 154 genera of bacteria were detected; the most abundant genera, from the highest to lowest abundance, were Lactobacillus, Gardnerella, and Pseudomonas in the non-TPL group, and Lactobacillus, Haemophilus, and Staphylococcus in the TPL group. In the ANCOM, the TPL group had a higher percentage of the Muribaculaceae (W = 121), Alistipes (W = 116), and Staphylococcus (W = 114) than the non-TPL group. In the rectal lumen, a total of 253 genera of bacteria were detected; the most abundant genera, from the highest to lowest abundance, were Escherichia-Shigella and Bacteroides, and the order Enterobacteriaceae. Similar genera were also detected in the non-TPL group. In the ANCOM, the TPL group had a lower percentage of Bifidobacterium (W = 64) than the non-TPL group (Table 3 and Supplementary Figure S1).

Table 3.

ANCOM analysis results and relative abundances of microbial features in the TPL and non-TPL groups.

Site	Bacteria	Median percentile abundance		Max percentile abundance		W
		non-TPL	TPL	non-TPL	TPL
Saliva	Bacteria;p_Firmicutes;c_Bacilli;o_Lactobacillales;_	121.5	1	2013	2006	138
Buccal mucosa	Bacteria;p_Firmicutes;c_Negativicutes;o_Veillonellales-Selenomonadales;f_Veillonellaceae;g_Veillonella	171	9.5	22,409	2742	155
	Bacteria;p_Firmicutes;c_Bacilli;o_Staphylococcales;f_Staphylococcaceae;g_Staphylococcus	36.5	6242.5	49,872	74,929	145
Vaginal mucosa	Bacteria;p_Bacteroidota;c_Bacteroidia;o_Bacteroidales;f_Muribaculaceae;g_Muribaculaceae	1	1	8	255	121
	Bacteria;p_Bacteroidota;c_Bacteroidia;o_Bacteroidales;f_Rikenellaceae;g_Alistipes	1	4.5	9	87	116
	Bacteria;p_Firmicutes;c_Bacilli;o_Staphylococcales;f_Staphylococcaceae;g_Staphylococcus	7.5	89.5	2055	143,265	114
Rectal lumen	Bacteria;p_Actinobacteriota;c_Actinobacteria;o_Bifidobacteriales;f_Bifidobacteriaceae;g_Bifidobacterium	161.5	13	1716	353	64

ANCOM determined significant differential order abundances with their 50th percentile abundance (median), the highest sequence count found in a sample (max), and W statistics. TPL: threatened preterm labor; non-TPL: healthy pregnant women; ANCOM: analysis of composition of microbiomes.

The genus Staphylococcus in the buccal mucosa was significantly and positively correlated with Staphylococcus in the vaginal mucosa (p = 0.019). The order Lactobacillales in the saliva was significantly positively correlated with the genus Bifidobacterium in the rectal lumen (p = 0.030) (Supplementary Table S4). Progesterone levels were significantly positively correlated with the order Lactobacillales (p = 0.011) in saliva, the genus Veillonella in the buccal mucosa (p = 0.038), and the genus Bifidobacterium in the rectal lumen (p = 0.002) in all participants. In contrast, progesterone levels were significantly negatively correlated with the genus Staphylococcus (p = 0.004) in the buccal and vaginal mucosa (p = 0.043), genus Muribaculaceae (p = 0.011), and genus Alistipes (p = 0.005) in the vaginal mucosa of all participants (Supplementary Table S5).

Data obtained from next-generation sequencing (NGS) were used to predict the metabolic pathways in the bacterial flora. Significant differences were observed in 80 MetaCyc pathways in saliva between the TPL and non-TPL groups; 44 MetaCyc pathways were decreased and 36 were increased in the TPL group compared to the non-TPL group. In the buccal mucosa, significant differences were observed in 208 MetaCyc pathways between the TPL and non-TPL groups, with 153 MetaCyc pathways decreased and 55 increased in the TPL group compared to the non-TPL group. In the vaginal mucosa, significant differences were observed in 178 MetaCyc pathways between the TPL and non-TPL groups, with 27 MetaCyc pathways downregulated and 151 MetaCyc pathways upregulated in the TPL group compared to the non-TPL group. In the rectal lumen, significant differences were observed in 12 MetaCyc pathways between the TPL and non-TPL groups. Ten MetaCyc pathways were downregulated, and two MetaCyc pathways were upregulated in the TPL group compared to those in the non-TPL group (Fig. 2). A search for pathways that were elevated or decreased in the saliva, buccal tissue, vagina, and rectal lumen revealed that no pathways were common to all 3 sites, and 16 pathways were common in all 3 sites, 9 of which were increased and 7 were decreased (Supplementary Table S6).

Fig. 2.

Functional pathway prediction. Alterations in the MetaCyc pathways of saliva, buccal, vaginal, and rectal lumen microbiota in the TPL and non-TPL groups were predicted from data obtained from 16S rRNA analysis using PICRUSt2 software. Pathways were significantly different between the TPL and non-TPL groups (p < 0.05). For visualization, the top 10 pathways with the smallest p-values in each site were selected and are shown in the bar plots. TPL, women with threatened preterm labor; non-TPL, women without threatened preterm labor.

Discussion

TPL is one of the most common causes of PTBs. In all births, TPL reportedly accounts for 15% and PTBs account for 5%. Causes of TPL include a history of PTBs, TPL, multiple pregnancies, placenta previa, infection, uterine disease, hypertension, collagen disease, lifestyle, and social background, such as emaciation, malnutrition, smoking, alcohol, psychological stress, and pregnancy at a young age^26–29. Patients with multiple pregnancies or placenta previa were excluded from this study, and only pregnant women with no history of systemic diseases or abnormalities in previous pregnancies were enrolled. The participants in the study were characterized by women with TPL being significantly underweight and having more severe periodontal disease than the healthy pregnant women (Table 1). Although periodontal disease is considered a risk factor for PTBs and LBW, the results of the logistic regression analysis in this study revealed the presence of PPD ≥ 4 mm to be an independent risk factor for TPL (Table 2).

Progesterone is a female hormone that increases during pregnancy as a pregnancy-maintenance hormone. Kato et al.²³ reported that the salivary progesterone levels in healthy pregnant women were significantly higher than those in non-pregnant women. In this study, salivary progesterone levels were higher in the TPL group than in non-pregnant women²³, but significantly lower than those in the non-TPL group (Table 1). As the analysis of all pregnant women showed that salivary progesterone levels were positively correlated with pregnancy-related indicators such as gestational age and infant birth weight, it is likely that lower progesterone levels were associated with PTB and LBW (Supplementary Table S2). Lachelin et al.³⁰ reported that salivary progesterone concentrations were lower than those in term pregnant women at the same gestational age, and that pregnant women with low salivary progesterone concentrations before 34 weeks had a higher risk of PTB. However, these results should be adopted with caution because the significantly lower levels of progesterone from TPL in this study may be influenced by the gestational week at the time of sampling. In addition, salivary assays are known to have high intra-individual variability and may not reflect serum concentrations accurately. However, saliva collection is non-invasive and easier compared with peripheral blood sample collection³¹. Despite challenges such as hormonal variability and method standardization, advances in technology are overcoming these barriers, making saliva a valuable tool in clinical practice³².

The results of the periodontal examination showed that the TPL group had greater gingival inflammation and deeper PPD than the non-TPL group (Table 1). A systematic review reported that gingival inflammation increased in pregnant women without concomitant increases in plaque levels³³. Additionally, Kato et al.²³ reported an increased gingival index without an increase in BOP, even in pregnant women with good plaque control. Pregnancy-associated gingivitis improved after delivery³⁴, suggesting that female hormones might be responsible for pregnancy-associated gingivitis. In this study, salivary progesterone levels were negatively correlated with gingival BOP (Supplementary Table S2). Furthermore, the PPD was significantly deeper in women with TPL (Tables 1 and 2). However, clinical parameters such as calculus and dental plaque, as well as dental radiographic images, were not assessed in this study. Further studies are necessary to determine whether women with TPL have early periodontitis, which should be distinguished from pregnancy-associated gingivitis.

A comparison of the non-TPL and TPL groups revealed no significant differences in the alpha diversity of saliva, buccal, and rectal lumen microbiota, but a significant increase was observed in the vaginal microbiota (Fig. 1a). Additionally, changes in the composition and structure of the salivary, buccal, vaginal, and rectal lumen microbiota were observed in terms of beta diversity (Fig. 1b). The menstrual cycle deeply affects the vaginal microbiome, and to a lesser extent, the salivary microbiome, but not the rectum microbiome³⁵. In the intestine, the levels of active metabolites of sex hormones, such as dihydroprogesterone, tetrahydroprogesterone, dihydrotestosterone, and 17β-estradiol, were higher in the colon than in the plasma³⁶. These results suggest that the effects of progesterone on the microbiome vary depending on the mucosal sites, and the results of this study support these findings.

In the ANCOM, the order Lactobacillales in the saliva and the genus Bifidobacterium in the rectal lumen were lower in the TPL group (Table 2), which are symbiotic bacteria^37–39. A low percentage of Lactobacilli in the vaginal microbiota is associated with a less successful embryo transfer during infertility treatment⁴⁰. In contrast, an increase in Staphylococcus spp. was observed in the buccal and vaginal microbiota of women with TPL in the ANCOM (Table 3). Staphylococcus aureus, particularly, is known to cause various infections, including skin infections during pregnancy, methicillin-related S. aureus infections⁴¹, and periodontitis⁴². Further, S. aureus increases the risk of PTBs because of intrauterine infection, effects on the immune system, and abscess formation^43,44. The genus Staphylococcus, which increased in the ANCOM of the buccal and vaginal microbiota in the TPL group, also had the highest percentage in taxonomy (Table 3 and Supplementary Figure S1). As female hormones suppress Staphylococcus and Lactobacillus inhibit the growth of Staphylococcus^45,46, our results suggest that the increase in Staphylococcus in the TPL group may have been associated with inadequate female hormones (Supplementary Table S5). A study on progesterone administration in the TPL group reported that progesterone administration significantly reduced preterm labor⁴⁷.

Functional pathway prediction revealed common changes in several pathways in the salivary, buccal, vaginal, and rectal lumen microbiota in the TPL group (Fig. 2 and Supplementary Table S6). The pathways that declined were related to heme synthesis, and those that increased were related to nucleoside and peptidoglycan synthesis. The alteration of bacterial metabolism in the TPL was common in the oral and vaginal microbiomes, suggesting that host factors that affect bacterial metabolism, such as progesterone, were similar between the oral cavity and the vaginal mucosa. Progesterone might affect host immune responses, including immune responses and inflammation; contrarily, it is also possible that the microbiome altered by progesterone might affect host immune responses and inflammation. Further clarification of host responses is necessary to link microbiome, progesterone, and clinical outcomes in TPL.

Various studies have reported effective and ineffective effects of periodontal treatment during pregnancy on PTB and LBW^48–52. Tanigucgchi-Tabata et al.⁵³ suggested that periodontal treatment before conception might be recommended and that a good periodontal condition in the early stages of pregnancy, at the latest, is desirable for infant growth. Findings linking female hormones and periodontal disease to PTB in this study support that interventions for PTB should incorporate not only prenatal care but also preconception care.

A limitation of this study is that, as it was a cross-sectional study, it was not possible to determine whether the lower progesterone levels in women with TPL compared to healthy pregnant women affected periodontal tissue pathology and bacterial flora. In addition, we could not obtain appropriate temporal control. As hormonal and microbial profiles vary considerably throughout pregnancy, lack of temporal control undermines causal inference. Furthermore, the effect of medication (e.g., antibiotics) on the microbiome, or the lack of direct measurement of microbial functionality, might also be limitations of this study. This study was conducted in a relatively small cohort; therefore, validation in a larger cohort is necessary. Future longitudinal studies with larger numbers of patients are warranted.

Conclusions

The results of this study suggest that women with TPL have lower progesterone levels, more severe periodontal disease, and increased Staphylococcus in the buccal and vaginal microbiota than healthy pregnant women.

Methods

Study population and clinical examination

This study was approved by the Health Sciences University of Hokkaido Dental Ethics Review Committee (certificate numbers 103 and 124). All procedures performed in this study, including human participation, were in accordance with the ethical standards of the institutional research committee and the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

The participants constituted two groups of gestation (TPL and non-TPL groups): the TPL group comprised 30 pregnant women who were hospitalized in the Department of Obstetrics and Gynecology at the Kagoshima City Hospital with the diagnosis of TPL by obstetricians; the non-TPL group included 30 healthy pregnant women at 35 weeks of gestation recruited from the private obstetrics clinic of Kagoshima City (Kakinoki Hospital). In this study, we could not obtain appropriate temporal control for ethical reasons. All the samples from healthy pregnant women were obtained at 35 weeks of gestation, which is not the same as the samples obtained from TPL participants. Pregnancy outcomes, including age, height, weight, infant birth weight, and delivery status, were recorded after delivery. All participants agreed to participate in the study, signed a written informed consent form, and completed a questionnaire on smoking habits (never, former, or current). The participants had no systemic disease (i.e., no diabetes, endocrine disorders, or hypertension) and had not used antibiotics or steroid hormones within the preceding 3 months. All participants were from medium-income households with national insurance. Saliva and oral tissue mucosa swab samples were collected, and clinical examinations were conducted on the same day. The participants were asked to avoid eating, drinking, and brushing their teeth for 60 min before sampling. All pregnant women were instructed by obstetricians not to consume alcohol during pregnancy. Unstimulated saliva was collected immediately before clinical examination. After saliva and oral mucosa sampling, the participants underwent periodontal examination, including assessment of PPD, BOP, tooth mobility, PESA, PISA, and decayed, missing, and filled teeth. The clinical examinations were conducted by a periodontal specialist. Healthy periodontal status was defined as no probing attachment loss, PPD ≤ 3 mm, and ≤ 10% BOP⁵⁴.

Sampling of saliva and swab from the buccal mucosa, vaginal mucosa, and rectal lumen

Unstimulated saliva was collected from each participant using an OMNIgene Oral OM-505 (DNA Genotek Inc., Ottawa, ON, Canada) according to the manufacturer’s protocol. Oral, vaginal mucosal tissues, and rectal lumen were collected using an eSwab (Becton). The oral mucosa was collected after the collection of saliva. The swab was rubbed up and down against the inside of the buccal mucosa of each participant 20 times. The tissue mucosa of the vagina and rectal lumen were collected at the time of examination. Vaginal mucosal samples were aseptically collected from the midpoint of the vagina. The eSwab was gently rubbed against the mid-vaginal wall for 20 s. The rectal lumen was sampled from the eSwab. Swabs were inserted approximately 5 cm apart to ensure sampling of the rectum. All swabs were stored at -80 °C.

Estradiol and progesterone assay

A saliva collection aid (Salimetrics, LLC, State College, PA, USA) was used to collect unstimulated saliva samples in a vial. After sampling, the samples were stored at -80 °C. On the day of the assay, the samples were centrifuged at 1,500 × g for 15 min to remove particulate matter, and the cleared samples were subjected to an enzyme-linked immunosorbent assay to detect estradiol (Salivary 17b-Estradiol Enzyme Immunoassay Kit; Salimetrics) or progesterone (Salivary Progesterone Enzyme Immunoassay Kit; Salimetrics). Estradiol and progesterone assays are competitive immunoassay kits. Estradiol or progesterone in standards and samples compete with estradiol or progesterone conjugated to horseradish peroxidase for the antibody binding sites on a microtiter plate. After incubation, unbound components are washed away. Bound estradiol or progesterone enzyme conjugate was measured by the reaction of the horseradish peroxidase enzyme to the substrate tetramethylbenzidine.

Extraction of bacterial DNA from saliva and tissue mucosa

QIAamp® MinElute Virus Spin (Qiagen, Hilden, Germany) was used for bacterial DNA extraction from saliva, and QIAamp UCP DNA Micro Kit (Qiagen) for bacterial DNA extraction from each swab according to the manufacturer’s protocol. In brief, the sample is lysed under high-denaturing conditions at elevated temperatures in the presence of proteinase K. The DNA then binds to the QIAamp column membrane, and contaminants are washed away during two washing steps. The DNA is eluted from the QIAamp column using a small volume of water. DNA extracts were stored at − 20 °C and used for 16S rRNA amplicon sequencing or real-time polymerase chain reaction (PCR).

Sequencing library preparation

The PCR targeted the V3–V4 regions of bacterial 16S rRNA genes. Sequencing libraries of the V3–V4 regions in the saliva samples were prepared according to the 16S metagenomic sequencing library preparation instructions (Illumina, San Diego, CA, USA). Briefly, the V3–V4 regions of the 16S rRNA gene were amplified using a two-step PCR protocol with KAPA HiFi HS ReadyMix (Nippon Genetics, Tokyo, Japan) and V3–V4 region–specific primers. Index PCR was performed using a KAPA HiFi HS ReadyMix and a Nextera XT index kit (Illumina). Libraries were cleaned using Agencourt AMPure XP (Beckman Coulter, Brea, MA, USA) and quantified on a Qubit 3 device (Thermo Fisher Scientific, Waltham, MA, USA). The library was diluted to 8 pM (final concentration), mixed with PhiX (Illumina), and applied to an Illumina MiSeq system for sequencing using a MiSeq reagent kit v3 (600 cycles, Illumina). Data were analyzed using the MiSeq Reporter Metagenomics Workflow (Illumina)^23,55.

Microbiome data processing

16S rRNA sequencing data were processed using QIIME2 with taxonomic assignment based on the SILVA v13.8 database. Amplicon sequence variants were generated using the DADA2 pipeline. Sequencing depth was determined by alpha rarefaction, resulting in 8,500 reads for saliva, 9,045 reads for the buccal mucosa, 8,008 reads for the vaginal mucosa, and 7,870 reads for the rectal lumen.

Alpha diversity metrics, including observed features, Shannon diversity index, and Faith’s phylogenetic diversity, were calculated. Beta diversity was computed using weighted and unweighted UniFrac distances, and microbial community differences were visualized by three-dimensional principal coordinate analysis (PCoA). Microbial taxon abundance was evaluated using the ANCOM tool in QIIME2. Functional profiles were predicted using PICRUSt2⁵⁶ (https://qiime2.org) based on marker gene sequences, and functional abundance profiles were generated using STAMP (https://beikolab.cs.dal.ca/software/STAMP). Clinical parameters and bacterial counts were obtained and prepared for statistical evaluation.

Statistical analysis

Differences in alpha diversity metrics were assessed across groups based on the rarefaction depth using the Kruskal–Wallis test, followed by the Benjamini–Hochberg FDR method, with a significance level of q < 0.05.

Beta diversity differences were evaluated using permutational multivariate analysis of variance (PERMANOVA) applied to weighted and unweighted UniFrac distance matrices, with Bonferroni correction and a significance threshold of q < 0.05. Differences in microbial taxon abundance between groups were assessed using ANCOM, and significance was expressed as the empirical distribution of W.

Functional pathway differences predicted by PICRUSt2 were analyzed using STAMP. Welch’s t-test was used for two-group comparisons, and CIs were calculated using Welch’s inverted CI method. Multiple testing correction was performed using the Benjamini–Hochberg FDR method, and statistical significance was defined as q < 0.05.

Comparisons of clinical parameters between groups were conducted using the Mann–Whitney U-test, with a significance level of p < 0.05. Associations between clinical parameters and bacterial counts were evaluated using Spearman’s correlation coefficients and multiple regression analysis. All statistical analyses were performed using SPSS Statistics version 26 (IBM).

Author contributions

NS, SK, TN, and YF designed the study, performed the experimental work, performed the data analysis, and wrote the manuscript. NS, SS, and OU performed the 16S rRNA amplicon sequencing. KH-N, KN, YS, MH, HK, and MK coordinated the sample collection and aided patient management in Kagoshima City. All the authors contributed to the writing, editing, and review of the manuscript.

Funding

This study was supported by grants from Grants-in-Aid for Scientific Research (C) #19K10157, #22K10004, and #25K13036 (https://www.jsps.go.jp/). The founder had no role in the study design, data collection and analysis, decision to publish, or manuscript preparation. No additional external funding was received for this study.

Data availability

The data have been deposited in the DDBJ BioProject database with links to BioProject accession numbers PRJDB 9791 and 37552.

Declarations

Competing interests

The authors declare no competing interests.