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• W4212974503 endingPage "e1009876" @default.
• W4212974503 startingPage "e1009876" @default.
• W4212974503 abstract "Emerging evidence suggests that host-microbe interaction in the cervicovaginal microenvironment contributes to cervical carcinogenesis, yet dissecting these complex interactions is challenging. Herein, we performed an integrated analysis of multiple omics datasets to develop predictive models of the cervicovaginal microenvironment and identify characteristic features of vaginal microbiome, genital inflammation and disease status. Microbiomes, vaginal pH, immunoproteomes and metabolomes were measured in cervicovaginal specimens collected from a cohort (n = 72) of Arizonan women with or without cervical neoplasm. Multi-omics integration methods, including neural networks (mmvec) and Random Forest supervised learning, were utilized to explore potential interactions and develop predictive models. Our integrated analyses revealed that immune and cancer biomarker concentrations were reliably predicted by Random Forest regressors trained on microbial and metabolic features, suggesting close correspondence between the vaginal microbiome, metabolome, and genital inflammation involved in cervical carcinogenesis. Furthermore, we show that features of the microbiome and host microenvironment, including metabolites, microbial taxa, and immune biomarkers are predictive of genital inflammation status, but only weakly to moderately predictive of cervical neoplastic disease status. Different feature classes were important for prediction of different phenotypes. Lipids (e.g. sphingolipids and long-chain unsaturated fatty acids) were strong predictors of genital inflammation, whereas predictions of vaginal microbiota and vaginal pH relied mostly on alterations in amino acid metabolism. Finally, we identified key immune biomarkers associated with the vaginal microbiota composition and vaginal pH (MIF), as well as genital inflammation (IL-6, IL-10, MIP-1α)." @default.
• W4212974503 created "2022-02-24" @default.
• W4212974503 creator A5000165682 @default.
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• W4212974503 creator A5080037453 @default.
• W4212974503 creator A5082470569 @default.
• W4212974503 date "2022-02-23" @default.
• W4212974503 modified "2023-10-05" @default.
• W4212974503 title "Multi-omics data integration reveals metabolome as the top predictor of the cervicovaginal microenvironment" @default.
• W4212974503 cites W1811186957 @default.
• W4212974503 cites W1926422794 @default.
• W4212974503 cites W1969732431 @default.
• W4212974503 cites W1998951533 @default.
• W4212974503 cites W2011301426 @default.
• W4212974503 cites W2013371150 @default.
• W4212974503 cites W2027297424 @default.
• W4212974503 cites W2047455878 @default.
• W4212974503 cites W2048201362 @default.
• W4212974503 cites W2062761055 @default.
• W4212974503 cites W2065342949 @default.
• W4212974503 cites W2071589972 @default.
• W4212974503 cites W2072087747 @default.
• W4212974503 cites W2088268917 @default.
• W4212974503 cites W2097493772 @default.
• W4212974503 cites W2111415362 @default.
• W4212974503 cites W2115190531 @default.
• W4212974503 cites W2127621564 @default.
• W4212974503 cites W2135785255 @default.
• W4212974503 cites W2136432779 @default.
• W4212974503 cites W2152821355 @default.
• W4212974503 cites W2154026962 @default.
• W4212974503 cites W2158353135 @default.
• W4212974503 cites W2166632132 @default.
• W4212974503 cites W2170027067 @default.
• W4212974503 cites W2201127965 @default.
• W4212974503 cites W2259627284 @default.
• W4212974503 cites W2270337160 @default.
• W4212974503 cites W2311142656 @default.
• W4212974503 cites W2321804599 @default.
• W4212974503 cites W2342602136 @default.
• W4212974503 cites W2401404581 @default.
• W4212974503 cites W2476742596 @default.
• W4212974503 cites W2552883321 @default.
• W4212974503 cites W2559683962 @default.
• W4212974503 cites W2582447685 @default.
• W4212974503 cites W2605928190 @default.
• W4212974503 cites W2735369591 @default.
• W4212974503 cites W2747619000 @default.
• W4212974503 cites W2758767377 @default.
• W4212974503 cites W2766612280 @default.
• W4212974503 cites W2771925862 @default.
• W4212974503 cites W2783722756 @default.
• W4212974503 cites W2786546763 @default.
• W4212974503 cites W2796210912 @default.
• W4212974503 cites W2806769319 @default.
• W4212974503 cites W2807194798 @default.
• W4212974503 cites W2808805770 @default.
• W4212974503 cites W2889019390 @default.
• W4212974503 cites W2892881193 @default.
• W4212974503 cites W2898490392 @default.
• W4212974503 cites W2904635536 @default.
• W4212974503 cites W2911964244 @default.
• W4212974503 cites W2929854681 @default.
• W4212974503 cites W2941842978 @default.
• W4212974503 cites W2945348578 @default.
• W4212974503 cites W2953236953 @default.
• W4212974503 cites W2954162762 @default.
• W4212974503 cites W2954610371 @default.
• W4212974503 cites W2955245499 @default.
• W4212974503 cites W2958564218 @default.
• W4212974503 cites W2963276645 @default.
• W4212974503 cites W2964487836 @default.
• W4212974503 cites W2966376468 @default.
• W4212974503 cites W2975619549 @default.
• W4212974503 cites W2977433364 @default.
• W4212974503 cites W2979981494 @default.
• W4212974503 cites W2987653794 @default.
• W4212974503 cites W2990249310 @default.
• W4212974503 cites W2990640021 @default.
• W4212974503 cites W2993250673 @default.
• W4212974503 cites W3007674389 @default.
• W4212974503 cites W3013498851 @default.
• W4212974503 cites W3018767052 @default.
• W4212974503 cites W3037620181 @default.
• W4212974503 cites W3040245690 @default.
• W4212974503 cites W3044813747 @default.
• W4212974503 cites W3046931682 @default.
• W4212974503 cites W3213732104 @default.
• W4212974503 doi "https://doi.org/10.1371/journal.pcbi.1009876" @default.
• W4212974503 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35196323" @default.
• W4212974503 hasPublicationYear "2022" @default.
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