Raluca Datcu, Dionne Gesink, Gert Mulvad, Ruth Montgomery-Andersen, Elisabeth Rink, Anders Koch, Peter Ahrens and Jørgen Skov Jensen J. Clin. Microbiol. 2014, 52(1):218. DOI: 10.1128/JCM.02347-13. Published Ahead of Print 6 November 2013.
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Bacterial Vaginosis Diagnosed by Analysis of First-Void-Urine Specimens
Raluca Datcu,a Dionne Gesink,b Gert Mulvad,c Ruth Montgomery-Andersen,d Elisabeth Rink,e Anders Koch,a Peter Ahrens,a Jørgen Skov Jensena ‹Statens Serum Institut, Copenhagen, Denmarka; University of Toronto, Dalla Lana School of Public Health, Toronto, Ontario, Canadab; Center for Primary Care, Nuuk, Greenlandc; University of Greenland, Nuuk, Greenlandd; Montana State University, Bozeman, Montana, USAe
Bacterial vaginosis (BV) is traditionally diagnosed using vaginal samples. The aim of this study was to investigate whether BV can be diagnosed from first-void urine (FVU). Self-collected vaginal smears, vaginal swabs, and FVU were obtained from 176 women. BV was diagnosed by Nugent’s criteria. The FVU and vaginal swabs were analyzed by quantitative PCRs (qPCRs) for selected vaginal bacteria (Atopobium vaginae, Prevotella spp., Gardnerella vaginalis, bacterial vaginosis-associated bacterium 2, Eggerthella-like bacterium, “Leptotrichia amnionii,” Megasphaera type 1), and all had an area under the receiver operating characteristic (ROC) curve of >85%, suggesting good prediction of BV according to the Nugent score. All seven bacteria in FVU were significantly associated with BV in univariate analysis. An accurate diagnosis of BV from urine was obtained in this population by a combination of qPCRs for Megasphaera type 1 and Prevotella spp. The same two bacteria remained significantly associated with BV in a multivariate model after adjusting for the other five species. There was no statistically significant difference between the sensitivities and specificities of BV diagnosis by molecular methods performed on swabs and FVU samples. A linear regression analysis showed good agreement between bacterial loads from swabs and FVU, but Prevotella spp. could be detected in high numbers in a few FVU samples without being present in swabs. This method will allow diagnosis of BV in studies where only urine has been collected and where detection of BV is considered relevant.
B
acterial vaginosis (BV) is an alteration of the normal Lactobacillus sp.-dominated vaginal flora toward a more diverse bacterial flora with overgrowth of facultative and strict anaerobic microorganisms. The BV flora includes anaerobes such as Gardnerella vaginalis, Prevotella spp., Peptostreptococcus spp., Mobiluncus spp., and several uncultured species, e.g., bacterial vaginosis-associated bacteria (BVAB) 1, 2, 3, and TM7, Megasphaera spp., and Eggerthella-like uncultured bacteria (1, 2). The classical and most commonly used algorithms for diagnosing BV are represented by clinical and microscopic classification criteria. The former were established by Amsel et al. (3) and consist of a set of four characteristics, including a homogenous, white vaginal discharge, a fishy odor of the vaginal discharge before or after addition of 10% potassium hydroxide, pH of the vaginal fluid elevated above 4.5, and the presence of clue cells (squamous epithelial cells covered with adherent bacteria). At least three of the four criteria must be present to diagnose BV. Different microscopy scores to diagnose BV have been established, some of them based on Gram-stained vaginal smears (4–6) and others based on wet-smear microscopy (7, 8). Among these, the criteria published by Nugent et al. (5) are the most widely used and are considered the gold standard for diagnosing BV. Several studies on the diagnosis of BV using PCR have been published recently (9–13), but all these have used PCR for BVassociated bacteria in vaginal swabs. In some studies, vaginal swabs are not collected, and first-void urine (FVU) may be the only material from which BV can be diagnosed. In most settings, pregnant women are traditionally screened for glucose and leukocytes in urine, and thus urine would be easy to collect for BV studies. Therefore, we aimed to determine whether BV can be diagnosed from FVU by PCR using a panel of BV-associated bacteria that were the most sensitive and specific indicators for predicting BV in vaginal swabs compared to the Nugent score after
applying receiver operating characteristic (ROC) curve analysis (10). ROC curve analysis establishes a threshold/cutoff for optimal diagnosis of BV by quantitative PCR (qPCR) by analyzing samples with known normal and BV floras as determined by the Nugent score. We refer to results that consider cutoffs as “quantitative detection,” while positive/negative (presence/absence) results are referred to as “qualitative detection.”
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MATERIALS AND METHODS Study population and specimens. The population used in the present study was selected from Inuulluataarneq (the Greenland Sexual Health Project), which included 314 residents (196 women and 118 men) from Nuuk and Sisimiut, Greenland, between July 2008 and November 2009. Participants were recruited from the general population via the population registry, by direct contact via telephone calls, and by advertising in local media as previously described (14). The initial objective of this study was to determine the epidemiology of sexually transmitted infections (STIs) (14) and BV in Greenland (10). Each participant completed an interviewer-administered sexual health survey in either Greenlandic or Danish and provided a self-obtained vaginal smear, a vaginal swab sample collected with a flocked swab in UTM (Copan, Brescia, Italy), and an FVU
Received 26 August 2013 Returned for modification 27 September 2013 Accepted 28 October 2013 Published ahead of print 6 November 2013 Editor: P. Bourbeau Address correspondence to Jørgen Skov Jensen, [email protected]. Supplemental material for this article may be found at http://dx.doi.org/10.1128 /JCM.02347-13. Copyright © 2014, American Society for Microbiology. All Rights Reserved. doi:10.1128/JCM.02347-13
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Bacterial Vaginosis Diagnosed by Analysis of First-Void-Urine Specimens
Bacterial Vaginosis Diagnosis from Urine
Combination of bacteria
90
92
83
97
%
82–96
81–95
84–97
73–91
91–100
95% CI 95% CI
16–38
57–79
67–87
40–64
65–86
2–15
3–17
Specificity
%
26
68
78
52
77
7
8
A. vaginae and Prevotella spp. A. vaginae or Prevotella spp. Megasphaera type 1 and Prevotella spp. Megasphaera type 1 or Prevotella spp. A. vaginae and Megasphaera type 1 and Prevotella spp. A. vaginae or Megasphaera type 1 or Prevotella spp. A. vaginae and Megasphaera type 1 and Eggerthella-like bacterium A. vaginae or Megasphaera type 1 or Eggerthella-like bacterium
Sensitivity (%)
Specificity (%)
83 97 72 99 69
100 95 100 95 100
99
93
72
100
96
97
33 (12–99)
9 (4–26)
43 (15–138)
11 (5–26)
13 (3–121)
OR (95% CI)
0.02
⬍0.0001
⬍0.0001
⬍0.0001
⬍0.0001
⬍0.0001
P
90
92
87
81
88
78
91
%
81–95
84–97
78–94
70–89
79–95
67–87
82–96
95% CI
96
97
100
99
97
96
99
%
88–99
90–100
95–100
93–100
90–100
88–99
93–100
95% CI
ⱖ1,048,635
ⱖ1,362,476
ⱖ11,492
ⱖ317
ⱖ603
ⱖ286
ⱖ230,508
Cutoff (copies/ml urine)
204 (47–1,145)
426 (75–3,925)
⬁ (102–⬁)
302 (43–12,288)
272 (53–2,446)
84 (22–446)
730 (89–29,601)
OR (95% CI)
⬍0.0001
⬍0.0001
⬍0.0001
⬍0.0001
⬍0.0001
⬍0.0001
⬍0.0001
P
96
98
94
91
95
88
97
%
92–99
95–100
90–98
86–96
91–98
82–93
94–100
95% CI
Specificity
Quantitative detection
⬁ (1–⬁)
0.01
Sensitivity
⬁ (1–⬁)
Area under ROC curve
sample collected in GeneLock transport medium (Sierra Molecular Corp., Sonora, CA) as previously described (14). Ethics. The study was approved by the Greenland Ethics Committee and by the University of Toronto Research Ethics Board in Canada. Study subjects provided written informed consent before participating in the study. Microscopy. Vaginal smears were Gram stained and diagnosed by Nugent score (5). Nugent scores of 0 to 3 were considered representative of normal flora (Nugent grade I), scores of 4 to 6 were considered intermediate (Nugent grade II), and scores of 7 to 10 were classified as BV (Nugent grade III). All slides were scored by the same investigator (R.D.) blinded to any clinical or laboratory results. DNA extraction and positive controls for PCR assays. DNA from FVU was extracted as previously described (15). In brief, 1.9 ml of FVU was centrifuged at 30,000 ⫻ g for 15 min, and the pellet was resuspended in a 20% (wt/vol) Chelex slurry (Bio-Rad, Hercules, CA) in TE buffer (10 mM Tris-HCl [pH 8.0], 1 mM EDTA). The samples were placed in a heating block at 95°C for 10 min, and condensation droplets were collected by a brief centrifugation. Positive controls for the PCRs were obtained by DNA extraction from cultures of Atopobium vaginae (CCUG 38953T), “Leptotrichia amnionii” (DSM 16630) (not a validly described species but referred to by this name in accordance with the DSMZ designation), G. vaginalis (ATCC 3717T), and Prevotella bivia (clinical isolate identified by biochemical properties and matrix-assisted laser desorption ionization–time of flight [MALDITOF] mass spectrometry). For the uncultured bacteria BVAB 2, Megasphaera type 1, and Eggerthella-like bacterium, the 16S rRNA gene PCR product from a positive clinical sample was used as positive control after gel purification and DNA sequencing for verification (10). Standard curves for quantitative PCRs were generated using 10-fold dilutions from 107 genome equivalents (geq)/l to 1 geq/l in TE buffer containing 1 g/ml of calf thymus DNA (D-8661; Sigma-Aldrich). PCR analyses. qPCRs for A. vaginae, L. amnionii, BVAB 2, Megasphaera type 1, Eggerthella-like bacterium, G. vaginalis, and Prevotella spp. were performed using primers and reaction conditions previously described (10). Statistical methods. ROC curve analysis was used to calculate the bacterial load that provided the optimal cutoff for diagnosing BV in FVU, weighing sensitivity and specificity equally and considering normal flora and BV as diagnosed by Nugent score as the gold standard. Fisher’s exact test (univariate analysis) with odds ratios (OR) and confidence intervals (CI) was used to evaluate whether each studied bacterium in the FVU sample was significantly associated with BV (before and after applying ROC curve analysis). Spearman correlation analysis was used to examine the correlation between detection of bacteria in swabs and FVU samples. Cohen’s kappa (weighted) was used to measure the agreement between methods for diagnosing BV (the Nugent score and molecular methods
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91
95–100
Qualitative detection
100
95–100
Sensitivity
100
TABLE 1 Sensitivity and specificity before (qualitative detection) and after (quantitative detection) ROC curve analysisa
Species
Atopobium vaginae Leptotrichia amnionii BVAB 2
Megasphaera type 1 Eggerthella-like bacterium Gardnerella vaginalis Prevotella spp.
a Odds ratios (OR) and 95% confidence intervals (CI) for each bacterial species for BV detection in FVU were calculated from Fisher’s exact test after qualitative or quantitative detection. A total of 78 urine samples from women with Nugent grade III (BV) and 73 urine samples from women with Nugent grade I (normal flora) were used for the evaluation. Intermediate flora is not included.
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TABLE 2 Diagnostic performance for quantitative detection (cutoff determined by ROC curve analysis) for combinations of bacteria
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FIG 1 Bacterial load in swabs and urine samples from 73 women with a normal flora, 25 women with an intermediate flora, and 78 women with BV as diagnosed from Nugent’s score. The median bacterial load is marked with a horizontal bar for each group.
Bacterial Vaginosis Diagnosis from Urine
TABLE 3 Rate of detection of seven bacterial species in urine Nugent I (0–3c) (nd ⫽ 73)
Nugent II (4–6) (n ⫽ 25)
Nugent III (7–10) (n ⫽ 78)
P for trend
Species
Qualitative detectiona
Quantitative detectionb
Qualitative detection
Quantitative detection
Qualitative detection
Quantitative detection
Qualitative detection
Quantitative detection
A. vaginae L. amnionii BVAB 2
54 (74) 23 (32) 16 (22)
1 (1) 3 (4) 2 (3)
20 (80) 12 (48) 15 (60)
10 (40) 6 (24) 9 (36)
76 (97) 65 (83) 72 (92)
71 (91) 61 (78) 69 (88)
0.0001 ⬍0.0001 ⬍0.0001
⬍0.0001 ⬍0.0001 ⬍0.0001
Megasphaera type 1 Eggerthella-like bacterium G. vaginalis Prevotella spp.
35 (48) 17 (23) 68 (93) 67 (92)
1 (1) 0 (0) 2 (3) 3 (4)
15 (60) 16 (64) 22 (88) 25 (100)
10 (40) 8 (32) 11 (44) 10 (40)
70 (90) 71 (91) 78 (100) 78 (100)
63 (81) 68 (87) 72 (92) 70 (90)
⬍0.0001 ⬍0.0001 0.11 0.0292
⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001
a
Before applying cutoffs (presence versus absence). After applying cutoffs as determined by ROC curve analysis by Nugent’s criteria (positive, ⱖcutoff; negative, ⬍cutoff). c Nugent’s score. d n, number of participants. b
performed on swabs and FVU samples). The McNemar test for matched pairs was used to compare differences in sensitivity and specificity between swabs and urine samples for diagnosis of BV. These statistical analyses were performed in StatsDirect version 2.7.8 (StatsDirect Ltd., Cheshire, United Kingdom). Logistic regression analysis was applied in an adjusted model with seven variables, with each bacterial species representing a variable for the purpose of determining the bacterial species optimally predicting BV. Data were used as log10 of the copy number ⫹ 1, and the outcome was presence of BV (as diagnosed by the Nugent score). Logistic regression analysis, linear regressions, comparisons between slopes, and the Cochran-Armitage trend test were performed in SAS version 9.2 (SAS Institute Inc., Cary, NC). Scatter plots and graphs illustrating linear regressions were created in GraphPad Prism version 5.00. The correlation between the presence of the seven studied species in FVU, determined from Spearman correlation coefficients and a cooccurrence heat map of bacterial taxa, was created by using the standard “correlation orders” in the R program package version 2.15.0 (The R Foundation for Statistical Computing). The significance level was 5%, two sided throughout.
RESULTS
From a total of 196 women enrolled in the Greenland Sexual Health Survey, 176 participants were included in the present analysis, as they provided vaginal swabs, suitable vaginal smears, and FVU. Seventythree women (42%) had a normal vaginal flora, 25 (14%) had an intermediate flora, and 78 (44%) had BV by Nugent’s criteria. The median age was 24 years (range, 15 to 65 years). STI prevalence was 12% Mycoplasma genitalium, 7% Chlamydia trachomatis, 1% Neisseria gonorrhoeae, and 0.5% Trichomonas vaginalis (14). No questions were asked about contraceptive use, douching, or recent antibiotic use. However, douching is not considered to be a common practice in Greenland (Ruth Montgomery-Andersen, personal communication). Six participants were in the age range 55 to 65 years, presumably postmenopausal women, but no questions about age of menopause were asked. Twelve women were registered as having no history of male or female sex partners, and four of them were diagnosed with BV on the basis of the Nugent score. Seven women reported having STI symptoms, but only 89 answered this question, and 15 of them did not know (10). Determination of bacterial load cutoff in urine for optimal BV prediction. The sensitivities and specificities of the seven as-
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says for BV-associated bacteria in urine (A. vaginae, Prevotella spp., G. vaginalis, BVAB 2, Eggerthella-like bacterium, L. amnionii, and Megasphaera type 1) were estimated using the Nugent score. The assays showed sensitivities between 83 to 100% but specificities of only 7 to 78% by qualitative detection (presence or absence) (Table 1). Intermediate flora was excluded from the evaluation. ROC curve analysis was used to determine the optimal cutoff for the number of gene copies/ml urine for women with and without BV, weighing sensitivity and specificity equally. For all seven bacteria, the sensitivity and specificity before and after ROC curve analysis (qualitative and quantitative detection, respectively) were calculated for 78 participants with BV and 73 participants without BV. All seven bacterial species had area under the curve (AUC) of ⱖ88%, suggesting a good diagnostic performance (16). In descending order, their AUCs were as follows: G. vaginalis, 98%; A. vaginae, 97%; Prevotella spp., 96%; BVAB 2, 95%; Eggerthella-like bacterium, 94%; Megasphaera type 1, 91%; L. amnionii, 88%. In quantitative detection, G. vaginalis had a sensitivity of 92%, followed by A. vaginae with 91% and Prevotella spp. with 90%, whereas the highest specificities were found for the Eggerthellalike bacterium (100%), Megasphaera type 1 (99%), and A. vaginae (99%). Differences in sensitivities or specificities of PCRs using swabs versus the use of FVU samples were not significant. Each of the seven bacteria was significantly associated with BV in univariate analysis (Table 1), but the odds ratio for BV increased dramatically when quantitative detection was introduced, reaching a value of 730 (95% CI, 89 to 29,601) for A. vaginae. Diagnostic characteristics of different combinations of PCR assays for detection of vaginal bacteria are presented in Table 2. Relationship between PCR results from urine and swabs and microscopy. For all seven bacteria, the bacterial load in urine samples increased significantly with the progression from normal to BV flora (P ⬍ 0.0001) (Fig. 1). Women with BV had significantly higher bacterial loads in swabs than in urine samples, except for those of Prevotella spp. (Fig. 1). Considering all women regardless of BV status, the bacterial loads were significantly higher in swabs than in urine samples for L. amnionii, the Eggerthella-like bacterium, and G. vaginalis, but the difference was not statistically significant for the remaining four bacteria analyzed. A significantly increasing trend in the positive rate was found with increasing BV grade in qualitative detection for all species
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No. (%) of samples positive
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except G. vaginalis and in quantitative detection for all seven bacteria (Table 3). The proportion of women with each of the seven species detected in urine according to the Nugent grade is shown in Table 3 for both qualitative and quantitative detection. G. vagi-
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nalis, Prevotella spp., and A. vaginae were present in almost all women with BV (100%, 100%, and 97%, respectively) by qualitative detection and in the highest proportions by quantitative detection (92%, 90%, and 91%, respectively) (Table 3). This is in
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FIG 2 Correlation between the bacterial load in swabs and urine samples. For each bacterium a regression line for the correlation between the log10 of 16S rRNA gene copies per ml ⫹ 1 in swabs versus FVU is shown. Nugent grades of vaginal smears are shown in color. The lower right graph shows the 7 regression lines in the same graph for easier comparison.
0.84
0.79–0.88
⬍0.0001
0.33
0.84
0.82
0.77–0.87
⬍0.0001
0.04
0.78
0.81
0.75–0.85
⬍0.0001
0.52
0.69
Megasphaera type 1 Eggerthella-like bacterium Gardnerella vaginalis Prevotella spp.
0.76
0.68–0.81
⬍0.0001
0.26
0.77
0.75
0.68–0.81
⬍0.0001
⫺0.45
0.82
G.vaginalis
0.82
0.77–0.87
⬍0.0001
⫺0.16
0.89
A.vaginae
0.71
0.63–0.78
⬍0.0001
2.42
0.59
a
0.57
0.8
1
Eggerthella
Atopobium vaginae Leptotrichia amnionii BVAB 2
BVAB2
Slopea
G.vaginalis
Intercepta
A.vaginae
P
Megasphaera 1
95% CI
Eggerthella BVAB2
Prevotella spp.
On regression lines using log data.
Megasphaera 1
good agreement with their AUCs, which were also the highest when calculated according to the Nugent score (Table 1). In order to correlate the bacterial load in vaginal swabs and urine, linear regression analysis was performed for each species after log transformation of the bacterial load, with vaginal bacterial load as the predictor (Fig. 2; Table 4). When slopes were compared pairwise, most were found to be similar. However, for 10 comparisons the slopes were statistically different (marked with a star in Table S1 in the supplemental material); all were comparisons involving Prevotella spp. or BVAB 2. The slope for Prevotella spp. was significantly different from those for all other bacteria. The slope for BVAB 2 was different from those for A. vaginae, Megasphaera type 1, the Eggerthella-like bacterium, and G. vaginalis (Table 5). Prevotella spp. and BVAB 2 differed mainly by the presence of these taxons in high numbers in some FVU samples from women with negative results from swabs (Fig. 2). The highest correlation between bacterial load in swabs and FVU samples was found for A. vaginae, with an r of 0.84, while the lowest correlation, r of 0.71, was found for Prevotella spp. (Table 4). Cooccurrence of bacterial taxa in urine was investigated by calculating Spearman correlation coefficients (Fig. 3; see Data Set S2 in the supplemental material). The lowest correlation coefficient was 0.57 between Megasphaera type 1 and Prevotella spp. The
L.amnionii
FIG 3 Hierarchically clustered Spearman correlation coefficients between bacterial species in urine showing cooccurrence of species. Correlation coefficients range from 0.57 to 1. A table with the coefficients is available (see Data Set S2 in the supplemental material).
highest positive correlation was between A. vaginae and G. vaginalis, with a value of 0.88 (Fig. 3; see Data Set S2). Generally, good or very good agreement was found between Nugent scoring and molecular diagnosis of BV for each bacterial species, both from FVU (Cohen’s kappa [weighted], 0.74 to 0.89) and swabs (kappa, 0.75 to 0.91), and also between FVU and swabs (0.77 to 0.91); very good agreement was found when all three diagnostic methods were compared (Table 6). Associations between different vaginal bacteria in urine and BV. In a multivariate logistic regression model considering the seven bacteria as variables, only Megasphaera type 1 and Prevotella spp. remained statistically significantly associated with BV, with P
TABLE 6 Cohen’s kappaa for agreement between BV diagnosis by Nugent scoringb and molecular methods using quantitative results Weighted Cohen’s kappa for c:
TABLE 5 Adjusted odds ratios with 95% confidence intervals and P values after multivariate logistic regression analysis for seven bacterial speciesa Logistic regression model value for: Species
Adjusted OR
95% CI
P
Atopobium vaginae Leptotrichia amnionii BVAB 2 Megasphaera type 1 Eggerthella-like bacterium Gardnerella vaginalis Prevotella spp.
1.2 0.6 0.5 3.6 3.9 2.1 4.3
0.5–2.9 0.2–2.1 0.1–1.8 1.2–10.3 0.9–15.9 0.6–7.5 1.06–17.5
0.6 0.4 0.3 0.01 0.052 0.2 0.04
a Analysis was based on 78 women with BV and 73 women with normal vaginal flora by Nugent score. Adjusted ORs and 95% CIs are log10 of the number of 16S rRNA gene copies per ml ⫹ 1.
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Species
Nugenturine
Nugentswab
Urineswab
Cohen’s kappa for Nugenturine-swab
Atopobium vaginae Leptotrichia amnionii BVAB 2 Megasphaera 1 Eggerthella-like bacterium Gardnerella vaginalis Prevotella spp.
0.89 0.74 0.85 0.79 0.87 0.89 0.85
0.88 0.78 0.85 0.80 0.75 0.80 0.91
0.88 0.91 0.84 0.91 0.83 0.77 0.84
0.88 0.80 0.85 0.83 0.81 0.82 0.87
a A kappa between 0.6 and 0.8 is considered good agreement between observations. A kappa of ⬎0.8 is considered very good agreement between observations. b Intermediate flora is excluded from these analyses. c Nugent-urine, Nugent’s score versus molecular methods using urine; Nugent-swab, Nugent’s score versus molecular methods using swabs; urine-swab, molecular methods using FVU versus swabs; Nugent-urine-swab, Nugent’s score versus molecular methods using swabs or FVU.
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Correlation coefficient
Species
L.amnionii
Correlation coefficient
Prevotella
TABLE 4 Spearman correlation coefficient with 95% confidence intervals for seven species in swabs and urine samples
spp.
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values of 0.01 and 0.04 and odds ratios of 3.6 and 4.3, respectively (Table 5), after adjusting for the other bacteria.
To the best of our knowledge, this is the first study to investigate the possibility of diagnosing BV from first-void urine by using species/genus-specific qPCR. A study using fluorescent in situ hybridization (FISH) of G. vaginalis biofilm in cells harvested from urine was recently reported (17), but a detailed validation of this approach was not presented. In the present study, seven BV-associated bacteria (A. vaginae, Prevotella spp., G. vaginalis, BVAB 2, an Eggerthella-like bacterium, L. amnionii, and Megasphaera type 1) were selected, as they had demonstrated good discriminatory power in diagnosis of BV from swabs (10, 13), with areas under ROC curves of ⬎85%. A Prevotella sp. assay was chosen in order to limit the number of assays needed to cover this species, as several species of this genus can be found in the vagina. From the high sensitivity of this assay, this approach appeared successful. qPCRs for these bacteria were performed on paired vaginal swabs and first-void-urine specimens, and all seven AUCs were ⬎85% in ROC curve analysis when normal flora and BV by Nugent’s criteria were considered. None of the assays had perfect sensitivity and specificity, and mainly the specificity was the limiting factor. Consequently, combinations of assays were tried in order to maximize both parameters. However, increasing sensitivity by combining assays always led to a decrease in specificity. One of the best combinations was detection of Megasphaera type 1 or Prevotella spp., which improved the sensitivity to 99%, while maintaining a good specificity of 95%. Thus, performing only these two qPCRs can diagnose BV from urine with a very high precision in this particular population. It is important to note, however, that cutoff levels as well as optimal combinations of assays may vary in different populations and may depend on the DNA extraction method and other assayrelated factors. The finding that combinations of assays were needed to obtain optimal sensitivity also suggests that BV can be classified into subgroups dominated by different BV-associated bacteria (10). Compared to the diagnosis of BV by molecular methods from swab samples, diagnosis from first-void urine had similar performance, with kappa values reaching 0.89 for A. vaginae and G. vaginalis. All seven bacteria in urine were significantly associated with BV, both in qualitative and quantitative detection in univariate analysis, while only Megasphaera type 1 and Prevotella spp. remained significantly associated with BV in a multivariate logistic regression model. This was in contrast to the findings for swabs from the same women, where A. vaginae and Prevotella spp. were associated with BV in the multivariate analysis. The reason for this discrepancy remains unclear. The bacterial load of each species in FVU increased with increasing Nugent score, and the highest median load in urine was found for Prevotella spp. for women with BV. For determination of the optimal cutoff quantity by ROC curve analysis, samples with intermediate scores (Nugent grade II) were excluded. Whether the possibility to dichotomize intermediate flora will make disease associations clearer in future studies remains to be seen. As expected, the median DNA load in swabs was higher than the corresponding load in FVU specimens for all seven species, but for all the assays a linear correlation between the vaginal and urine
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ACKNOWLEDGMENTS Christina Nørgaard, Birthe Dohn, and Susanne Cramer Larsson are thanked for valuable technical assistance. No author had any conflict of interest, either financial or personal.
REFERENCES 1. Donders G. 2010. Diagnosis and management of bacterial vaginosis and other types of abnormal vaginal bacterial flora: a review. Obstet. Gynecol. Surv. 65:462– 473. http://dx.doi.org/10.1097/OGX.0b013e3181e09621. 2. Fredricks DN, Fiedler TL, Marrazzo JM. 2005. Molecular identification of bacteria associated with bacterial vaginosis. N. Engl. J. Med. 353:1899 – 1911. http://dx.doi.org/10.1056/NEJMoa043802. 3. Amsel R, Totten PA, Spiegel CA, Chen KC, Eschenbach D, Holmes KK. 1983. Nonspecific vaginitis. Diagnostic criteria and microbial and epidemiologic associations. Am. J. Med. 74:14 –22. 4. Ison CA, Hay PE. 2002. Validation of a simplified grading of Gram
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DISCUSSION
bacterial loads could be found. It seems likely, therefore, that the DNA loads detected in the FVU specimen mainly represent vaginal secretions washed out by the urine more than a urinary tract infection (UTI), although the latter possibility should be considered in future studies on midstream urine. With DNA loads for all seven species exceeding 108 copies per ml of FVU in some specimens, the possibility that colonization of the bladder epithelium may occur should not be excluded. Swidsinsky et al. recently reported that G. vaginalis biofilm could be demonstrated in the endometrium and even in the fallopian tubes of one out of four women with BV (17). In that study, the BV diagnosis was based on the detection of vaginal epithelial cells in FVU carrying a typical G. vaginalis biofilm, as demonstrated by FISH with a species-specific probe. However, the presence of other cell morphologies was not reported. The possibility of colonization of the bladder was supported in our study by the finding that five women had swab samples negative for Prevotella spp. but still had high DNA loads in FVU, with a median of 1.8 ⫻ 105 copies/ml (range, 1.8 ⫻ 103 to 107 copies/ml). Unfortunately, no information about leukocyturia was collected, and no symptoms were recorded. It has earlier been shown that BV is associated with an increased risk of urinary tract infections (18), and urinary tract infections caused by G. vaginalis afflict women more often than men (19). There are far more descriptions of systemic infections caused by BV-associated bacteria, such as G. vaginalis, in women (20) than in men (21, 22). Similarly, a pigmented Prevotella sp. and L. amnionii have been isolated by culture or detected by PCR in urine specimens (23, 24). It has been suggested that lactobacillus probiotics such as vaginal suppositories may be effective in reducing the recurrence of UTIs following antimicrobial therapy and in maintaining a normal microflora (25, 26); however, in a recent metaanalysis (27) it was concluded that the number of trials was small and that more studies are needed before recommendations can be given. In conclusion, BV can be diagnosed with high accuracy from FVU using cutoffs determined by ROC curve analysis. However, a combination of qPCR results for two bacteria, such as Megasphaera type 1 and Prevotella spp., increases sensitivity or specificity depending on the combination. The possibility of using FVU as a diagnostic specimen may not gain widespread use, as vaginal swabs are very easy to obtain, even as a self-collected sample, but in particular settings it may prove useful. This may also allow analysis of stored FVU specimens collected as part of studies on classical STI pathogens where BV was not considered initially.
Bacterial Vaginosis Diagnosis from Urine
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15. Jensen JS, Björnelius E, Dohn B, Lidbrink P. 2004. Use of TaqMan 5= nuclease real-time PCR for quantitative detection of Mycoplasma genitalium DNA in males with and without urethritis who were attendees at a sexually transmitted disease clinic. J. Clin. Microbiol. 42:683– 692. http: //dx.doi.org/10.1128/JCM.42.2.683-692.2004. 16. Obuchowski NA. 2003. Receiver operating characteristic curves and their use in radiology. Radiology 229:3– 8. http://dx.doi.org/10.1148/radiol .2291010898. 17. Swidsinski A, Verstraelen H, Loening-Baucke V, Swidsinski S, Mendling W, Halwani Z. 2013. Presence of a polymicrobial endometrial biofilm in patients with bacterial vaginosis. PLoS One 8:e53997. http://dx .doi.org/10.1371/journal.pone.0053997. 18. Harmanli OH, Cheng GY, Nyirjesy P, Chatwani A, Gaughan JP. 2000. Urinary tract infections in women with bacterial vaginosis. Obstet. Gynecol. 95:710 –712. http://dx.doi.org/10.1016/S0029-7844(99)00632-8. 19. Catlin BW. 1992. Gardnerella vaginalis: characteristics, clinical considerations, and controversies. Clin. Microbiol. Rev. 5:213–237. 20. Reimer LG, Reller LB. 1984. Gardnerella vaginalis bacteremia: a review of thirty cases. Obstet. Gynecol. 64:170 –172. 21. Wilson JA, Barratt AJ. 1986. An unusual case of Gardnerella vaginalis septicaemia. Br. Med. J. 293:309. 22. Yoon HJ, Chun J, Kim JH, Kang SS, Na DJ. 2010. Gardnerella vaginalis septicaemia with pyelonephritis, infective endocarditis and septic emboli in the kidney and brain of an adult male. Int. J. STD AIDS 21:653– 657. http://dx.doi.org/10.1258/ijsa.2010.009574. 23. Brook I. 2004. Urinary tract and genito-urinary suppurative infections due to anaerobic bacteria. Int. J. Urol. 11:133–141. http://dx.doi.org/10 .1111/j.1442-2042.2003.00756.x. 24. Domann E, Hong G, Imirzalioglu C, Turschner S, Kuhle J, Watzel C, Hain T, Hossain H, Chakraborty T. 2003. Culture-independent identification of pathogenic bacteria and polymicrobial infections in the genitourinary tract of renal transplant recipients. J. Clin. Microbiol. 41:5500 – 5510. http://dx.doi.org/10.1128/JCM.41.12.5500-5510.2003. 25. Bruce AW, Reid G. 1988. Intravaginal instillation of lactobacilli for prevention of recurrent urinary tract infections. Can. J. Microbiol. 34:339 – 343. http://dx.doi.org/10.1139/m88-062. 26. Reid G, Bruce AW, Taylor M. 1992. Influence of three-day antimicrobial therapy and lactobacillus vaginal suppositories on recurrence of urinary tract infections. Clin. Ther. 14:11–16. 27. Grin PM, Kowalewska PM, Alhazzan W, Fox-Robichaud AE. 2013. Lactobacillus for preventing recurrent urinary tract infections in women: meta-analysis. Can. J. Urol. 20:6607– 6614.
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stained vaginal smears for use in genitourinary medicine clinics. Sex. Transm. Infect. 78:413– 415. http://dx.doi.org/10.1136/sti.78.6.413. Nugent RP, Krohn MA, Hillier SL. 1991. Reliability of diagnosing bacterial vaginosis is improved by a standardized method of gram stain interpretation. J. Clin. Microbiol. 29:297–301. Verhelst R, Verstraelen H, Claeys G, Verschraegen G, Van Simaey L, De Ganck C, De Backer E, Temmerman M, Vaneechoutte M. 2005. Comparison between Gram stain and culture for the characterization of vaginal microflora: definition of a distinct grade that resembles grade I microflora and revised categorization of grade I microflora. BMC Microbiol. 5:61. http://dx.doi.org/10.1186/1471-2180-5-61. Donders GG. 1999. Microscopy of the bacterial flora on fresh vaginal smears. Infect. Dis. Obstet. Gynecol. 7:126 –127. Schmidt H, Hansen JG. 2000. Diagnosis of bacterial vaginosis by wet mount identification of bacterial morphotypes in vaginal fluid. Int. J. STD AIDS 11:150 –155. http://dx.doi.org/10.1258/0956462001915589. Cartwright CP, Lembke BD, Ramachandran K, Body BA, Nye MB, Rivers CA, Schwebke JR. 2012. Development and validation of a semiquantitative, multitarget PCR assay for diagnosis of bacterial vaginosis. J. Clin. Microbiol. 50:2321–2329. http://dx.doi.org/10.1128/JCM.00506-12. Datcu R, Gesink D, Mulvad G, Montgomery-Andersen R, Rink E, Koch A, Ahrens P, Jensen JS. 2013. Vaginal microbiome in women from Greenland assessed by microscopy and quantitative PCR. BMC Infect. Dis. 13:480. http://dx.doi.org/10.1186/1471-2334-13-480. Fredricks DN, Fiedler TL, Thomas KK, Oakley BB, Marrazzo JM. 2007. Targeted PCR for detection of vaginal bacteria associated with bacterial vaginosis. J. Clin. Microbiol. 45:3270 –3276. http://dx.doi.org/10.1128 /JCM.01272-07. Menard JP, Fenollar F, Henry M, Bretelle F, Raoult D. 2008. Molecular quantification of Gardnerella vaginalis and Atopobium vaginae loads to predict bacterial vaginosis. Clin. Infect. Dis. 47:33– 43. http://dx.doi.org /10.1086/588661. Shipitsyna E, Roos A, Datcu R, Hallen A, Fredlund H, Jensen JS, Engstrand L, Unemo M. 2013. Composition of the vaginal microbiota in women of reproductive age—sensitive and specific molecular diagnosis of bacterial vaginosis is possible? PLoS One 8:e60670. http://dx.doi.org/10 .1371/journal.pone.0060670. Gesink DC, Mulvad G, Montgomery-Andersen R, Poppel U, Montgomery-Andersen S, Binzer A, Vernich L, Frosst G, Stenz F, Rink E, Olsen OR, Koch A, Jensen JS. 2012. Mycoplasma genitalium presence, resistance and epidemiology in Greenland. Int. J. Circumpolar Health 71:1– 8. http: //dx.doi.org/10.3402/ijch.v71i0.18203.
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Bacterial Vaginosis Diagnosed by Analysis of First-Void-Urine Specimens
Raluca Datcu,a Dionne Gesink,b Gert Mulvad,c Ruth Montgomery-Andersen,d Elisabeth Rink,e Anders Koch,a Peter Ahrens,a Jørgen Skov Jensena ‹Statens Serum Institut, Copenhagen, Denmarka; University of Toronto, Dalla Lana School of Public Health, Toronto, Ontario, Canadab; Center for Primary Care, Nuuk, Greenlandc; University of Greenland, Nuuk, Greenlandd; Montana State University, Bozeman, Montana, USAe
Bacterial vaginosis (BV) is traditionally diagnosed using vaginal samples. The aim of this study was to investigate whether BV can be diagnosed from first-void urine (FVU). Self-collected vaginal smears, vaginal swabs, and FVU were obtained from 176 women. BV was diagnosed by Nugent’s criteria. The FVU and vaginal swabs were analyzed by quantitative PCRs (qPCRs) for selected vaginal bacteria (Atopobium vaginae, Prevotella spp., Gardnerella vaginalis, bacterial vaginosis-associated bacterium 2, Eggerthella-like bacterium, “Leptotrichia amnionii,” Megasphaera type 1), and all had an area under the receiver operating characteristic (ROC) curve of >85%, suggesting good prediction of BV according to the Nugent score. All seven bacteria in FVU were significantly associated with BV in univariate analysis. An accurate diagnosis of BV from urine was obtained in this population by a combination of qPCRs for Megasphaera type 1 and Prevotella spp. The same two bacteria remained significantly associated with BV in a multivariate model after adjusting for the other five species. There was no statistically significant difference between the sensitivities and specificities of BV diagnosis by molecular methods performed on swabs and FVU samples. A linear regression analysis showed good agreement between bacterial loads from swabs and FVU, but Prevotella spp. could be detected in high numbers in a few FVU samples without being present in swabs. This method will allow diagnosis of BV in studies where only urine has been collected and where detection of BV is considered relevant.
B
acterial vaginosis (BV) is an alteration of the normal Lactobacillus sp.-dominated vaginal flora toward a more diverse bacterial flora with overgrowth of facultative and strict anaerobic microorganisms. The BV flora includes anaerobes such as Gardnerella vaginalis, Prevotella spp., Peptostreptococcus spp., Mobiluncus spp., and several uncultured species, e.g., bacterial vaginosis-associated bacteria (BVAB) 1, 2, 3, and TM7, Megasphaera spp., and Eggerthella-like uncultured bacteria (1, 2). The classical and most commonly used algorithms for diagnosing BV are represented by clinical and microscopic classification criteria. The former were established by Amsel et al. (3) and consist of a set of four characteristics, including a homogenous, white vaginal discharge, a fishy odor of the vaginal discharge before or after addition of 10% potassium hydroxide, pH of the vaginal fluid elevated above 4.5, and the presence of clue cells (squamous epithelial cells covered with adherent bacteria). At least three of the four criteria must be present to diagnose BV. Different microscopy scores to diagnose BV have been established, some of them based on Gram-stained vaginal smears (4–6) and others based on wet-smear microscopy (7, 8). Among these, the criteria published by Nugent et al. (5) are the most widely used and are considered the gold standard for diagnosing BV. Several studies on the diagnosis of BV using PCR have been published recently (9–13), but all these have used PCR for BVassociated bacteria in vaginal swabs. In some studies, vaginal swabs are not collected, and first-void urine (FVU) may be the only material from which BV can be diagnosed. In most settings, pregnant women are traditionally screened for glucose and leukocytes in urine, and thus urine would be easy to collect for BV studies. Therefore, we aimed to determine whether BV can be diagnosed from FVU by PCR using a panel of BV-associated bacteria that were the most sensitive and specific indicators for predicting BV in vaginal swabs compared to the Nugent score after
applying receiver operating characteristic (ROC) curve analysis (10). ROC curve analysis establishes a threshold/cutoff for optimal diagnosis of BV by quantitative PCR (qPCR) by analyzing samples with known normal and BV floras as determined by the Nugent score. We refer to results that consider cutoffs as “quantitative detection,” while positive/negative (presence/absence) results are referred to as “qualitative detection.”
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MATERIALS AND METHODS Study population and specimens. The population used in the present study was selected from Inuulluataarneq (the Greenland Sexual Health Project), which included 314 residents (196 women and 118 men) from Nuuk and Sisimiut, Greenland, between July 2008 and November 2009. Participants were recruited from the general population via the population registry, by direct contact via telephone calls, and by advertising in local media as previously described (14). The initial objective of this study was to determine the epidemiology of sexually transmitted infections (STIs) (14) and BV in Greenland (10). Each participant completed an interviewer-administered sexual health survey in either Greenlandic or Danish and provided a self-obtained vaginal smear, a vaginal swab sample collected with a flocked swab in UTM (Copan, Brescia, Italy), and an FVU
Received 26 August 2013 Returned for modification 27 September 2013 Accepted 28 October 2013 Published ahead of print 6 November 2013 Editor: P. Bourbeau Address correspondence to Jørgen Skov Jensen, [email protected]. Supplemental material for this article may be found at http://dx.doi.org/10.1128 /JCM.02347-13. Copyright © 2014, American Society for Microbiology. All Rights Reserved. doi:10.1128/JCM.02347-13
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Bacterial Vaginosis Diagnosed by Analysis of First-Void-Urine Specimens
Bacterial Vaginosis Diagnosis from Urine
Combination of bacteria
90
92
83
97
%
82–96
81–95
84–97
73–91
91–100
95% CI 95% CI
16–38
57–79
67–87
40–64
65–86
2–15
3–17
Specificity
%
26
68
78
52
77
7
8
A. vaginae and Prevotella spp. A. vaginae or Prevotella spp. Megasphaera type 1 and Prevotella spp. Megasphaera type 1 or Prevotella spp. A. vaginae and Megasphaera type 1 and Prevotella spp. A. vaginae or Megasphaera type 1 or Prevotella spp. A. vaginae and Megasphaera type 1 and Eggerthella-like bacterium A. vaginae or Megasphaera type 1 or Eggerthella-like bacterium
Sensitivity (%)
Specificity (%)
83 97 72 99 69
100 95 100 95 100
99
93
72
100
96
97
33 (12–99)
9 (4–26)
43 (15–138)
11 (5–26)
13 (3–121)
OR (95% CI)
0.02
⬍0.0001
⬍0.0001
⬍0.0001
⬍0.0001
⬍0.0001
P
90
92
87
81
88
78
91
%
81–95
84–97
78–94
70–89
79–95
67–87
82–96
95% CI
96
97
100
99
97
96
99
%
88–99
90–100
95–100
93–100
90–100
88–99
93–100
95% CI
ⱖ1,048,635
ⱖ1,362,476
ⱖ11,492
ⱖ317
ⱖ603
ⱖ286
ⱖ230,508
Cutoff (copies/ml urine)
204 (47–1,145)
426 (75–3,925)
⬁ (102–⬁)
302 (43–12,288)
272 (53–2,446)
84 (22–446)
730 (89–29,601)
OR (95% CI)
⬍0.0001
⬍0.0001
⬍0.0001
⬍0.0001
⬍0.0001
⬍0.0001
⬍0.0001
P
96
98
94
91
95
88
97
%
92–99
95–100
90–98
86–96
91–98
82–93
94–100
95% CI
Specificity
Quantitative detection
⬁ (1–⬁)
0.01
Sensitivity
⬁ (1–⬁)
Area under ROC curve
sample collected in GeneLock transport medium (Sierra Molecular Corp., Sonora, CA) as previously described (14). Ethics. The study was approved by the Greenland Ethics Committee and by the University of Toronto Research Ethics Board in Canada. Study subjects provided written informed consent before participating in the study. Microscopy. Vaginal smears were Gram stained and diagnosed by Nugent score (5). Nugent scores of 0 to 3 were considered representative of normal flora (Nugent grade I), scores of 4 to 6 were considered intermediate (Nugent grade II), and scores of 7 to 10 were classified as BV (Nugent grade III). All slides were scored by the same investigator (R.D.) blinded to any clinical or laboratory results. DNA extraction and positive controls for PCR assays. DNA from FVU was extracted as previously described (15). In brief, 1.9 ml of FVU was centrifuged at 30,000 ⫻ g for 15 min, and the pellet was resuspended in a 20% (wt/vol) Chelex slurry (Bio-Rad, Hercules, CA) in TE buffer (10 mM Tris-HCl [pH 8.0], 1 mM EDTA). The samples were placed in a heating block at 95°C for 10 min, and condensation droplets were collected by a brief centrifugation. Positive controls for the PCRs were obtained by DNA extraction from cultures of Atopobium vaginae (CCUG 38953T), “Leptotrichia amnionii” (DSM 16630) (not a validly described species but referred to by this name in accordance with the DSMZ designation), G. vaginalis (ATCC 3717T), and Prevotella bivia (clinical isolate identified by biochemical properties and matrix-assisted laser desorption ionization–time of flight [MALDITOF] mass spectrometry). For the uncultured bacteria BVAB 2, Megasphaera type 1, and Eggerthella-like bacterium, the 16S rRNA gene PCR product from a positive clinical sample was used as positive control after gel purification and DNA sequencing for verification (10). Standard curves for quantitative PCRs were generated using 10-fold dilutions from 107 genome equivalents (geq)/l to 1 geq/l in TE buffer containing 1 g/ml of calf thymus DNA (D-8661; Sigma-Aldrich). PCR analyses. qPCRs for A. vaginae, L. amnionii, BVAB 2, Megasphaera type 1, Eggerthella-like bacterium, G. vaginalis, and Prevotella spp. were performed using primers and reaction conditions previously described (10). Statistical methods. ROC curve analysis was used to calculate the bacterial load that provided the optimal cutoff for diagnosing BV in FVU, weighing sensitivity and specificity equally and considering normal flora and BV as diagnosed by Nugent score as the gold standard. Fisher’s exact test (univariate analysis) with odds ratios (OR) and confidence intervals (CI) was used to evaluate whether each studied bacterium in the FVU sample was significantly associated with BV (before and after applying ROC curve analysis). Spearman correlation analysis was used to examine the correlation between detection of bacteria in swabs and FVU samples. Cohen’s kappa (weighted) was used to measure the agreement between methods for diagnosing BV (the Nugent score and molecular methods
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91
95–100
Qualitative detection
100
95–100
Sensitivity
100
TABLE 1 Sensitivity and specificity before (qualitative detection) and after (quantitative detection) ROC curve analysisa
Species
Atopobium vaginae Leptotrichia amnionii BVAB 2
Megasphaera type 1 Eggerthella-like bacterium Gardnerella vaginalis Prevotella spp.
a Odds ratios (OR) and 95% confidence intervals (CI) for each bacterial species for BV detection in FVU were calculated from Fisher’s exact test after qualitative or quantitative detection. A total of 78 urine samples from women with Nugent grade III (BV) and 73 urine samples from women with Nugent grade I (normal flora) were used for the evaluation. Intermediate flora is not included.
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TABLE 2 Diagnostic performance for quantitative detection (cutoff determined by ROC curve analysis) for combinations of bacteria
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FIG 1 Bacterial load in swabs and urine samples from 73 women with a normal flora, 25 women with an intermediate flora, and 78 women with BV as diagnosed from Nugent’s score. The median bacterial load is marked with a horizontal bar for each group.
Bacterial Vaginosis Diagnosis from Urine
TABLE 3 Rate of detection of seven bacterial species in urine Nugent I (0–3c) (nd ⫽ 73)
Nugent II (4–6) (n ⫽ 25)
Nugent III (7–10) (n ⫽ 78)
P for trend
Species
Qualitative detectiona
Quantitative detectionb
Qualitative detection
Quantitative detection
Qualitative detection
Quantitative detection
Qualitative detection
Quantitative detection
A. vaginae L. amnionii BVAB 2
54 (74) 23 (32) 16 (22)
1 (1) 3 (4) 2 (3)
20 (80) 12 (48) 15 (60)
10 (40) 6 (24) 9 (36)
76 (97) 65 (83) 72 (92)
71 (91) 61 (78) 69 (88)
0.0001 ⬍0.0001 ⬍0.0001
⬍0.0001 ⬍0.0001 ⬍0.0001
Megasphaera type 1 Eggerthella-like bacterium G. vaginalis Prevotella spp.
35 (48) 17 (23) 68 (93) 67 (92)
1 (1) 0 (0) 2 (3) 3 (4)
15 (60) 16 (64) 22 (88) 25 (100)
10 (40) 8 (32) 11 (44) 10 (40)
70 (90) 71 (91) 78 (100) 78 (100)
63 (81) 68 (87) 72 (92) 70 (90)
⬍0.0001 ⬍0.0001 0.11 0.0292
⬍0.0001 ⬍0.0001 ⬍0.0001 ⬍0.0001
a
Before applying cutoffs (presence versus absence). After applying cutoffs as determined by ROC curve analysis by Nugent’s criteria (positive, ⱖcutoff; negative, ⬍cutoff). c Nugent’s score. d n, number of participants. b
performed on swabs and FVU samples). The McNemar test for matched pairs was used to compare differences in sensitivity and specificity between swabs and urine samples for diagnosis of BV. These statistical analyses were performed in StatsDirect version 2.7.8 (StatsDirect Ltd., Cheshire, United Kingdom). Logistic regression analysis was applied in an adjusted model with seven variables, with each bacterial species representing a variable for the purpose of determining the bacterial species optimally predicting BV. Data were used as log10 of the copy number ⫹ 1, and the outcome was presence of BV (as diagnosed by the Nugent score). Logistic regression analysis, linear regressions, comparisons between slopes, and the Cochran-Armitage trend test were performed in SAS version 9.2 (SAS Institute Inc., Cary, NC). Scatter plots and graphs illustrating linear regressions were created in GraphPad Prism version 5.00. The correlation between the presence of the seven studied species in FVU, determined from Spearman correlation coefficients and a cooccurrence heat map of bacterial taxa, was created by using the standard “correlation orders” in the R program package version 2.15.0 (The R Foundation for Statistical Computing). The significance level was 5%, two sided throughout.
RESULTS
From a total of 196 women enrolled in the Greenland Sexual Health Survey, 176 participants were included in the present analysis, as they provided vaginal swabs, suitable vaginal smears, and FVU. Seventythree women (42%) had a normal vaginal flora, 25 (14%) had an intermediate flora, and 78 (44%) had BV by Nugent’s criteria. The median age was 24 years (range, 15 to 65 years). STI prevalence was 12% Mycoplasma genitalium, 7% Chlamydia trachomatis, 1% Neisseria gonorrhoeae, and 0.5% Trichomonas vaginalis (14). No questions were asked about contraceptive use, douching, or recent antibiotic use. However, douching is not considered to be a common practice in Greenland (Ruth Montgomery-Andersen, personal communication). Six participants were in the age range 55 to 65 years, presumably postmenopausal women, but no questions about age of menopause were asked. Twelve women were registered as having no history of male or female sex partners, and four of them were diagnosed with BV on the basis of the Nugent score. Seven women reported having STI symptoms, but only 89 answered this question, and 15 of them did not know (10). Determination of bacterial load cutoff in urine for optimal BV prediction. The sensitivities and specificities of the seven as-
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says for BV-associated bacteria in urine (A. vaginae, Prevotella spp., G. vaginalis, BVAB 2, Eggerthella-like bacterium, L. amnionii, and Megasphaera type 1) were estimated using the Nugent score. The assays showed sensitivities between 83 to 100% but specificities of only 7 to 78% by qualitative detection (presence or absence) (Table 1). Intermediate flora was excluded from the evaluation. ROC curve analysis was used to determine the optimal cutoff for the number of gene copies/ml urine for women with and without BV, weighing sensitivity and specificity equally. For all seven bacteria, the sensitivity and specificity before and after ROC curve analysis (qualitative and quantitative detection, respectively) were calculated for 78 participants with BV and 73 participants without BV. All seven bacterial species had area under the curve (AUC) of ⱖ88%, suggesting a good diagnostic performance (16). In descending order, their AUCs were as follows: G. vaginalis, 98%; A. vaginae, 97%; Prevotella spp., 96%; BVAB 2, 95%; Eggerthella-like bacterium, 94%; Megasphaera type 1, 91%; L. amnionii, 88%. In quantitative detection, G. vaginalis had a sensitivity of 92%, followed by A. vaginae with 91% and Prevotella spp. with 90%, whereas the highest specificities were found for the Eggerthellalike bacterium (100%), Megasphaera type 1 (99%), and A. vaginae (99%). Differences in sensitivities or specificities of PCRs using swabs versus the use of FVU samples were not significant. Each of the seven bacteria was significantly associated with BV in univariate analysis (Table 1), but the odds ratio for BV increased dramatically when quantitative detection was introduced, reaching a value of 730 (95% CI, 89 to 29,601) for A. vaginae. Diagnostic characteristics of different combinations of PCR assays for detection of vaginal bacteria are presented in Table 2. Relationship between PCR results from urine and swabs and microscopy. For all seven bacteria, the bacterial load in urine samples increased significantly with the progression from normal to BV flora (P ⬍ 0.0001) (Fig. 1). Women with BV had significantly higher bacterial loads in swabs than in urine samples, except for those of Prevotella spp. (Fig. 1). Considering all women regardless of BV status, the bacterial loads were significantly higher in swabs than in urine samples for L. amnionii, the Eggerthella-like bacterium, and G. vaginalis, but the difference was not statistically significant for the remaining four bacteria analyzed. A significantly increasing trend in the positive rate was found with increasing BV grade in qualitative detection for all species
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No. (%) of samples positive
Datcu et al.
except G. vaginalis and in quantitative detection for all seven bacteria (Table 3). The proportion of women with each of the seven species detected in urine according to the Nugent grade is shown in Table 3 for both qualitative and quantitative detection. G. vagi-
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nalis, Prevotella spp., and A. vaginae were present in almost all women with BV (100%, 100%, and 97%, respectively) by qualitative detection and in the highest proportions by quantitative detection (92%, 90%, and 91%, respectively) (Table 3). This is in
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FIG 2 Correlation between the bacterial load in swabs and urine samples. For each bacterium a regression line for the correlation between the log10 of 16S rRNA gene copies per ml ⫹ 1 in swabs versus FVU is shown. Nugent grades of vaginal smears are shown in color. The lower right graph shows the 7 regression lines in the same graph for easier comparison.
0.84
0.79–0.88
⬍0.0001
0.33
0.84
0.82
0.77–0.87
⬍0.0001
0.04
0.78
0.81
0.75–0.85
⬍0.0001
0.52
0.69
Megasphaera type 1 Eggerthella-like bacterium Gardnerella vaginalis Prevotella spp.
0.76
0.68–0.81
⬍0.0001
0.26
0.77
0.75
0.68–0.81
⬍0.0001
⫺0.45
0.82
G.vaginalis
0.82
0.77–0.87
⬍0.0001
⫺0.16
0.89
A.vaginae
0.71
0.63–0.78
⬍0.0001
2.42
0.59
a
0.57
0.8
1
Eggerthella
Atopobium vaginae Leptotrichia amnionii BVAB 2
BVAB2
Slopea
G.vaginalis
Intercepta
A.vaginae
P
Megasphaera 1
95% CI
Eggerthella BVAB2
Prevotella spp.
On regression lines using log data.
Megasphaera 1
good agreement with their AUCs, which were also the highest when calculated according to the Nugent score (Table 1). In order to correlate the bacterial load in vaginal swabs and urine, linear regression analysis was performed for each species after log transformation of the bacterial load, with vaginal bacterial load as the predictor (Fig. 2; Table 4). When slopes were compared pairwise, most were found to be similar. However, for 10 comparisons the slopes were statistically different (marked with a star in Table S1 in the supplemental material); all were comparisons involving Prevotella spp. or BVAB 2. The slope for Prevotella spp. was significantly different from those for all other bacteria. The slope for BVAB 2 was different from those for A. vaginae, Megasphaera type 1, the Eggerthella-like bacterium, and G. vaginalis (Table 5). Prevotella spp. and BVAB 2 differed mainly by the presence of these taxons in high numbers in some FVU samples from women with negative results from swabs (Fig. 2). The highest correlation between bacterial load in swabs and FVU samples was found for A. vaginae, with an r of 0.84, while the lowest correlation, r of 0.71, was found for Prevotella spp. (Table 4). Cooccurrence of bacterial taxa in urine was investigated by calculating Spearman correlation coefficients (Fig. 3; see Data Set S2 in the supplemental material). The lowest correlation coefficient was 0.57 between Megasphaera type 1 and Prevotella spp. The
L.amnionii
FIG 3 Hierarchically clustered Spearman correlation coefficients between bacterial species in urine showing cooccurrence of species. Correlation coefficients range from 0.57 to 1. A table with the coefficients is available (see Data Set S2 in the supplemental material).
highest positive correlation was between A. vaginae and G. vaginalis, with a value of 0.88 (Fig. 3; see Data Set S2). Generally, good or very good agreement was found between Nugent scoring and molecular diagnosis of BV for each bacterial species, both from FVU (Cohen’s kappa [weighted], 0.74 to 0.89) and swabs (kappa, 0.75 to 0.91), and also between FVU and swabs (0.77 to 0.91); very good agreement was found when all three diagnostic methods were compared (Table 6). Associations between different vaginal bacteria in urine and BV. In a multivariate logistic regression model considering the seven bacteria as variables, only Megasphaera type 1 and Prevotella spp. remained statistically significantly associated with BV, with P
TABLE 6 Cohen’s kappaa for agreement between BV diagnosis by Nugent scoringb and molecular methods using quantitative results Weighted Cohen’s kappa for c:
TABLE 5 Adjusted odds ratios with 95% confidence intervals and P values after multivariate logistic regression analysis for seven bacterial speciesa Logistic regression model value for: Species
Adjusted OR
95% CI
P
Atopobium vaginae Leptotrichia amnionii BVAB 2 Megasphaera type 1 Eggerthella-like bacterium Gardnerella vaginalis Prevotella spp.
1.2 0.6 0.5 3.6 3.9 2.1 4.3
0.5–2.9 0.2–2.1 0.1–1.8 1.2–10.3 0.9–15.9 0.6–7.5 1.06–17.5
0.6 0.4 0.3 0.01 0.052 0.2 0.04
a Analysis was based on 78 women with BV and 73 women with normal vaginal flora by Nugent score. Adjusted ORs and 95% CIs are log10 of the number of 16S rRNA gene copies per ml ⫹ 1.
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Species
Nugenturine
Nugentswab
Urineswab
Cohen’s kappa for Nugenturine-swab
Atopobium vaginae Leptotrichia amnionii BVAB 2 Megasphaera 1 Eggerthella-like bacterium Gardnerella vaginalis Prevotella spp.
0.89 0.74 0.85 0.79 0.87 0.89 0.85
0.88 0.78 0.85 0.80 0.75 0.80 0.91
0.88 0.91 0.84 0.91 0.83 0.77 0.84
0.88 0.80 0.85 0.83 0.81 0.82 0.87
a A kappa between 0.6 and 0.8 is considered good agreement between observations. A kappa of ⬎0.8 is considered very good agreement between observations. b Intermediate flora is excluded from these analyses. c Nugent-urine, Nugent’s score versus molecular methods using urine; Nugent-swab, Nugent’s score versus molecular methods using swabs; urine-swab, molecular methods using FVU versus swabs; Nugent-urine-swab, Nugent’s score versus molecular methods using swabs or FVU.
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Correlation coefficient
Species
L.amnionii
Correlation coefficient
Prevotella
TABLE 4 Spearman correlation coefficient with 95% confidence intervals for seven species in swabs and urine samples
spp.
Bacterial Vaginosis Diagnosis from Urine
Datcu et al.
values of 0.01 and 0.04 and odds ratios of 3.6 and 4.3, respectively (Table 5), after adjusting for the other bacteria.
To the best of our knowledge, this is the first study to investigate the possibility of diagnosing BV from first-void urine by using species/genus-specific qPCR. A study using fluorescent in situ hybridization (FISH) of G. vaginalis biofilm in cells harvested from urine was recently reported (17), but a detailed validation of this approach was not presented. In the present study, seven BV-associated bacteria (A. vaginae, Prevotella spp., G. vaginalis, BVAB 2, an Eggerthella-like bacterium, L. amnionii, and Megasphaera type 1) were selected, as they had demonstrated good discriminatory power in diagnosis of BV from swabs (10, 13), with areas under ROC curves of ⬎85%. A Prevotella sp. assay was chosen in order to limit the number of assays needed to cover this species, as several species of this genus can be found in the vagina. From the high sensitivity of this assay, this approach appeared successful. qPCRs for these bacteria were performed on paired vaginal swabs and first-void-urine specimens, and all seven AUCs were ⬎85% in ROC curve analysis when normal flora and BV by Nugent’s criteria were considered. None of the assays had perfect sensitivity and specificity, and mainly the specificity was the limiting factor. Consequently, combinations of assays were tried in order to maximize both parameters. However, increasing sensitivity by combining assays always led to a decrease in specificity. One of the best combinations was detection of Megasphaera type 1 or Prevotella spp., which improved the sensitivity to 99%, while maintaining a good specificity of 95%. Thus, performing only these two qPCRs can diagnose BV from urine with a very high precision in this particular population. It is important to note, however, that cutoff levels as well as optimal combinations of assays may vary in different populations and may depend on the DNA extraction method and other assayrelated factors. The finding that combinations of assays were needed to obtain optimal sensitivity also suggests that BV can be classified into subgroups dominated by different BV-associated bacteria (10). Compared to the diagnosis of BV by molecular methods from swab samples, diagnosis from first-void urine had similar performance, with kappa values reaching 0.89 for A. vaginae and G. vaginalis. All seven bacteria in urine were significantly associated with BV, both in qualitative and quantitative detection in univariate analysis, while only Megasphaera type 1 and Prevotella spp. remained significantly associated with BV in a multivariate logistic regression model. This was in contrast to the findings for swabs from the same women, where A. vaginae and Prevotella spp. were associated with BV in the multivariate analysis. The reason for this discrepancy remains unclear. The bacterial load of each species in FVU increased with increasing Nugent score, and the highest median load in urine was found for Prevotella spp. for women with BV. For determination of the optimal cutoff quantity by ROC curve analysis, samples with intermediate scores (Nugent grade II) were excluded. Whether the possibility to dichotomize intermediate flora will make disease associations clearer in future studies remains to be seen. As expected, the median DNA load in swabs was higher than the corresponding load in FVU specimens for all seven species, but for all the assays a linear correlation between the vaginal and urine
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ACKNOWLEDGMENTS Christina Nørgaard, Birthe Dohn, and Susanne Cramer Larsson are thanked for valuable technical assistance. No author had any conflict of interest, either financial or personal.
REFERENCES 1. Donders G. 2010. Diagnosis and management of bacterial vaginosis and other types of abnormal vaginal bacterial flora: a review. Obstet. Gynecol. Surv. 65:462– 473. http://dx.doi.org/10.1097/OGX.0b013e3181e09621. 2. Fredricks DN, Fiedler TL, Marrazzo JM. 2005. Molecular identification of bacteria associated with bacterial vaginosis. N. Engl. J. Med. 353:1899 – 1911. http://dx.doi.org/10.1056/NEJMoa043802. 3. Amsel R, Totten PA, Spiegel CA, Chen KC, Eschenbach D, Holmes KK. 1983. Nonspecific vaginitis. Diagnostic criteria and microbial and epidemiologic associations. Am. J. Med. 74:14 –22. 4. Ison CA, Hay PE. 2002. Validation of a simplified grading of Gram
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DISCUSSION
bacterial loads could be found. It seems likely, therefore, that the DNA loads detected in the FVU specimen mainly represent vaginal secretions washed out by the urine more than a urinary tract infection (UTI), although the latter possibility should be considered in future studies on midstream urine. With DNA loads for all seven species exceeding 108 copies per ml of FVU in some specimens, the possibility that colonization of the bladder epithelium may occur should not be excluded. Swidsinsky et al. recently reported that G. vaginalis biofilm could be demonstrated in the endometrium and even in the fallopian tubes of one out of four women with BV (17). In that study, the BV diagnosis was based on the detection of vaginal epithelial cells in FVU carrying a typical G. vaginalis biofilm, as demonstrated by FISH with a species-specific probe. However, the presence of other cell morphologies was not reported. The possibility of colonization of the bladder was supported in our study by the finding that five women had swab samples negative for Prevotella spp. but still had high DNA loads in FVU, with a median of 1.8 ⫻ 105 copies/ml (range, 1.8 ⫻ 103 to 107 copies/ml). Unfortunately, no information about leukocyturia was collected, and no symptoms were recorded. It has earlier been shown that BV is associated with an increased risk of urinary tract infections (18), and urinary tract infections caused by G. vaginalis afflict women more often than men (19). There are far more descriptions of systemic infections caused by BV-associated bacteria, such as G. vaginalis, in women (20) than in men (21, 22). Similarly, a pigmented Prevotella sp. and L. amnionii have been isolated by culture or detected by PCR in urine specimens (23, 24). It has been suggested that lactobacillus probiotics such as vaginal suppositories may be effective in reducing the recurrence of UTIs following antimicrobial therapy and in maintaining a normal microflora (25, 26); however, in a recent metaanalysis (27) it was concluded that the number of trials was small and that more studies are needed before recommendations can be given. In conclusion, BV can be diagnosed with high accuracy from FVU using cutoffs determined by ROC curve analysis. However, a combination of qPCR results for two bacteria, such as Megasphaera type 1 and Prevotella spp., increases sensitivity or specificity depending on the combination. The possibility of using FVU as a diagnostic specimen may not gain widespread use, as vaginal swabs are very easy to obtain, even as a self-collected sample, but in particular settings it may prove useful. This may also allow analysis of stored FVU specimens collected as part of studies on classical STI pathogens where BV was not considered initially.
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