{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T21:42:30Z","timestamp":1792100550059,"version":"4.4.0"},"reference-count":29,"publisher":"Microbiology Society","issue":"8","funder":[{"DOI":"10.13039\/100006108","name":"National Center for Advancing Translational Sciences","doi-asserted-by":"crossref","award":["UL1TR003015"],"award-info":[{"award-number":["UL1TR003015"]}],"id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,8,22]]},"abstract":"<jats:p>\n                  <jats:bold>Introduction.<\/jats:bold>\n                  <jats:italic>Lactobacillus<\/jats:italic> species predominate the human vagina and are associated with positive vaginal health, including an acidic pH (&lt;4.5). The prevalence of vaginal <jats:italic>Lactobacilli<\/jats:italic> increases with increased oestrogen due to increased glycogen production within the vagina. <jats:italic>Lactobacilli<\/jats:italic> produce lactic acid, thereby lowering vaginal pH, preventing growth of other bacteria, and lowering microbial diversity. Lower placental oestrogen levels in obese pregnant women could dampen the mechanism to initiate this process, which may be associated with vaginal dysbiosis and unfavourable pregnancy outcomes.<\/jats:p>\n               <jats:p>\n                  <jats:bold>Hypothesis.<\/jats:bold> We hypothesize that oestrogen and glycogen levels will be lower, vaginal pH will be higher, and vaginal microbiome diversity will be greater during pregnancy in obese and overweight women compared to healthy weight women.<\/jats:p>\n               <jats:p>\n                  <jats:bold>Aim.<\/jats:bold> Pregnancy complications (e.g. preterm birth) are more common in overweight and obese women. If vaginal dysbiosis plays a role, and quantifiable predictors of this increased risk can be determined, these measures could be used to prospectively identify women at risk for pregnancy complications early in pregnancy.<\/jats:p>\n               <jats:p>\n                  <jats:bold>Methodology.<\/jats:bold> Vaginal samples were collected at 10\u201314, 18\u201324, 26\u201330, and 34\u201337\u2009weeks gestation and at delivery from 67 pregnant participants (23 healthy weight, 22 overweight, 22 obese). A blood sample to quantify serum oestrogen was collected at 10\u201314\u2009weeks. Vaginal samples were collected to test vaginal pH using pH paper, glycogen abundance using fluorometry, and the vaginal microbiome using 16S rRNA amplicon sequencing.<\/jats:p>\n               <jats:p>\n                  <jats:bold>Results.<\/jats:bold> Vaginal pH was higher in obese participants compared to healthy weight participants (<jats:italic>P<\/jats:italic>=&lt;0.001). Vaginal glycogen levels increased over time in obese participants (<jats:italic>P<\/jats:italic>=0.033). The vaginal bacterial alpha diversity was higher in obese participants compared to healthy weight participants (<jats:italic>P<\/jats:italic>=0.033). The relative abundances of <jats:italic>Peptoniphilus<\/jats:italic> and <jats:italic>Anaerococcus<\/jats:italic> were increased in overweight and obese participants, as well as in complicated pregnancies, at 10\u201314\u2009weeks gestation.<\/jats:p>\n               <jats:p>\n                  <jats:bold>Conclusion<\/jats:bold>. The relative abundance of specific vaginal bacteria, like <jats:italic>Peptoniphilus<\/jats:italic> and <jats:italic>Anaerococcus<\/jats:italic>, in early pregnancy could predict pregnancy outcomes. Our goal is to use the information gathered in this pilot study to further determine the feasibility of assessing the vaginal environment during pregnancy to identify women at risk for negative pregnancy and birth outcomes in the context of a larger study.<\/jats:p>","DOI":"10.1099\/jmm.0.001874","type":"journal-article","created":{"date-parts":[[2024,8,22]],"date-time":"2024-08-22T11:23:33Z","timestamp":1724325813000},"source":"Crossref","is-referenced-by-count":7,"title":["Impact of obesity on the perinatal vaginal environment and bacterial microbiome: effects on birth outcomes"],"prefix":"10.1099","volume":"73","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-9708-9610","authenticated-orcid":false,"given":"Kelly","family":"Ingram","sequence":"first","affiliation":[{"name":"Virginia Tech Carilion School of Medicine, Roanoke, Virginia, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Embelle","family":"Ngalame Eko","sequence":"additional","affiliation":[{"name":"Carilion Clinic, Roanoke, Virginia, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jaclyn","family":"Nunziato","sequence":"additional","affiliation":[{"name":"Carilion Clinic, Roanoke, Virginia, USA"},{"name":"Virginia Tech Carilion School of Medicine, Roanoke, Virginia, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Monica","family":"Ahrens","sequence":"additional","affiliation":[{"name":"Fralin Biomedical Research Institute at VTC, Roanoke, Virginia, USA"},{"name":"Department of Statistics, Virginia Tech, Blacksburg, Virginia, USA"},{"name":"Virginia Tech Carilion School of Medicine, Roanoke, Virginia, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brittany","family":"Howell","sequence":"additional","affiliation":[{"name":"Department of Human Development and Family Science, Virginia Tech, Blacksburg, Virginia, USA"},{"name":"Fralin Biomedical Research Institute at VTC, Roanoke, Virginia, USA"},{"name":"Virginia Tech Carilion School of Medicine, Roanoke, Virginia, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"345","reference":[{"key":"R1","doi-asserted-by":"publisher","DOI":"10.3389\/fmed.2019.00201"},{"key":"R2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0102467"},{"key":"R3","doi-asserted-by":"publisher","DOI":"10.3390\/nu12020419"},{"key":"R4","doi-asserted-by":"publisher","DOI":"10.3389\/fmicb.2020.00551"},{"key":"R5","doi-asserted-by":"publisher","DOI":"10.1101\/cshperspect.a023051"},{"key":"R6","doi-asserted-by":"publisher","DOI":"10.1016\/j.chom.2016.11.010"},{"key":"R7","doi-asserted-by":"publisher","DOI":"10.1093\/infdis\/jiy705"},{"key":"R8","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajog.2013.10.081"},{"key":"R9","doi-asserted-by":"publisher","DOI":"10.1210\/jc.2014-2792"},{"key":"R10","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-022-24040-9"},{"key":"R11","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcjd.2012.05.004"},{"key":"R12","doi-asserted-by":"publisher","DOI":"10.3389\/fendo.2022.868441"},{"key":"R13","doi-asserted-by":"publisher","DOI":"10.18637\/jss.v067.i01"},{"key":"R14","doi-asserted-by":"publisher","DOI":"10.18637\/jss.v082.i13"},{"key":"R15","article-title":"_emmeans: estimated marginal means, aka least-squares means_. 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