Back

Vaginal Microbiome and Preterm Birth in Pregnant Indian Women

Singh, A.; Modi, D.; Chhabria, K.; Vashist, N.; Singh, S.; Suneja, G.; Hussein, A.; Das, G.; Choprai, S.; Urhekar, A.; Kumar, S.

2026-02-24 obstetrics and gynecology
10.64898/2026.02.19.26346663 medRxiv
Show abstract

ObjectivePreterm birth (PTB) is a leading cause of neonatal morbidity and mortality worldwide, with India alone contributing nearly 27% of the global PTB burden. Although alterations in the vaginal microbiome have been implicated in PTB, its association in the Indian context is underexplored. This study aimed to investigate the association of vaginal microbiome and PTB in Indian women at the time of delivery. Study designThe vaginal swabs were collected at the time of delivery from 72 women (31 term, 41 preterm) admitted to a tertiary care hospital in Western India. Microbial DNA was extracted, and the V3-V4 region of the 16S rRNA gene was sequenced. Community composition, alpha and beta diversity, and differential taxonomic abundance were assessed using bioinformatics pipelines. ResultsAt the time of delivery, there were no significant differences in alpha or beta diversity between term and preterm groups. Principal coordinate and unsupervised clustering analyses showed no group-wise segregation. The relative abundance of individual Lactobacillus species, including L. iners and L. helveticus, did not differ significantly between the two groups. However, a modest difference in the relative abundance of Streptococcus was observed between the two groups after adjustment. ConclusionThis study found no major microbial shifts in the vaginal microbiome associated with preterm birth in this cross sectional cohort of Indian women, suggesting that vaginal dysbiosis at the time of delivery may not be a principal driver of PTB in this population. These findings underscore the need for larger, longitudinal, and ethnically diverse studies using standardized methodologies better to understand the microbiomes role in PTB risk.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

1
PLOS ONE
4510 papers in training set
Top 3%
29.1%
2
Scientific Reports
3102 papers in training set
Top 2%
15.1%
3
BMC Pregnancy and Childbirth
20 papers in training set
Top 0.1%
8.8%
50% of probability mass above
4
PeerJ
261 papers in training set
Top 3%
3.2%
5
mSystems
361 papers in training set
Top 4%
2.2%
6
BMJ Open
554 papers in training set
Top 7%
2.2%
7
Frontiers in Medicine
113 papers in training set
Top 3%
2.0%
8
Journal of Advanced Research
15 papers in training set
Top 0.1%
2.0%
9
Obesity
19 papers in training set
Top 0.2%
2.0%
10
Frontiers in Cellular and Infection Microbiology
98 papers in training set
Top 2%
2.0%
11
Cell Communication and Signaling
35 papers in training set
Top 0.3%
1.9%
12
Frontiers in Public Health
140 papers in training set
Top 4%
1.7%
13
Nature Communications
4913 papers in training set
Top 53%
1.6%
14
Journal of Clinical Pathology
12 papers in training set
Top 0.3%
0.9%
15
F1000Research
79 papers in training set
Top 3%
0.9%
16
Acta Neuropsychiatrica
12 papers in training set
Top 0.8%
0.8%
17
Cureus
67 papers in training set
Top 4%
0.8%
18
Placenta
18 papers in training set
Top 0.2%
0.8%
19
International Journal of Molecular Sciences
453 papers in training set
Top 14%
0.8%
20
Computational and Structural Biotechnology Journal
216 papers in training set
Top 8%
0.8%
21
Metabolites
50 papers in training set
Top 1%
0.8%
22
BMC Medical Genomics
36 papers in training set
Top 1%
0.8%
23
Contemporary Clinical Trials Communications
11 papers in training set
Top 0.6%
0.8%
24
Annals of Translational Medicine
17 papers in training set
Top 1%
0.8%
25
Pathogens
53 papers in training set
Top 2%
0.7%
26
Applied Sciences
24 papers in training set
Top 1%
0.5%
27
Pain
70 papers in training set
Top 0.9%
0.5%
28
BMJ Open Quality
15 papers in training set
Top 1.0%
0.5%
29
Pediatric Research
18 papers in training set
Top 0.5%
0.5%
30
BMC Biology
248 papers in training set
Top 6%
0.5%