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    HIV-associated vaginal microbiome and inflammation predict spontaneous preterm birth in Zambia.

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    Author
    Price, Joan T
    Vwalika, Bellington
    France, Michael
    Ravel, Jacques
    Ma, Bing
    Mwape, Humphrey
    Rittenhouse, Katelyn J
    De Paris, Kristina
    Hobbs, Marcia
    Nelson, Julie A
    Kasaro, Margaret P
    Stringer, Elizabeth M
    Stringer, Jeffrey S A
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    Date
    2022-05-20
    Journal
    Scientific Reports
    Publisher
    Springer Nature
    Type
    Article
    
    Metadata
    Show full item record
    See at
    https://doi.org/10.1038/s41598-022-12424-w
    Abstract
    A Lactobacillus-deficient, anaerobe-rich vaginal microbiome has been associated with local inflammation and spontaneous preterm birth (sPTB), but few studies have assessed this association in the setting of HIV. We performed metagenomic sequencing and inflammatory marker assays on vaginal swabs collected in pregnancy. We grouped samples into 7 metagenomic clusters (mgClust) using the non-redundant VIRGO catalogue, and derived inflammatory scores by factor analysis. Of 221 participants, median Shannon diversity index (SDI) was highest in HIV+ with detectable viral load (1.31, IQR: 0.85–1.66; p < 0.001) and HIV+ with undetectable virus (1.17, IQR: 0.51–1.66; p = 0.01) compared to HIV− (0.74, IQR: 0.35–1.26). Inflammatory scores positively correlated with SDI (+ 0.66, 95%CI 0.28, 1.03; p = 0.001), highest among anaerobe-rich mgClust2–mgClust6. HIV was associated with predominance of anaerobe-rich mgClust5 (17% vs. 6%; p = 0.02) and mgClust6 (27% vs. 11%; p = 0.002). Relative abundance of a novel Gardnerella metagenomic subspecies > 50% predicted sPTB (RR 2.6; 95%CI: 1.1, 6.4) and was higher in HIV+ (23% vs. 10%; p = 0.001). A novel Gardnerella metagenomic subspecies more abundant in women with HIV predicted sPTB. The risk of sPTB among women with HIV may be mediated by the vaginal microbiome and inflammation, suggesting potential targets for prevention.
    Data Availibility
    Individual de-identified participant data that underlie the results reported in this article are publicly available at Open Science Framework (https://doi.org/10.17605/OSF.IO/WT6Q8). Sequence read data have been deposited in the Sequence Read Archive (SRA) of the US National Institutes of Health (submission ID: SUB10306692).
    Data / Code Location
    https://doi.org/10.17605/OSF.IO/WT6Q8
    Rights/Terms
    © 2022. The Author(s).
    Keyword
    microbial communities
    HIV infections
    predictive markers
    Identifier to cite or link to this item
    http://hdl.handle.net/10713/18992
    ae974a485f413a2113503eed53cd6c53
    10.1038/s41598-022-12424-w
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