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Integrating multi-omics data: Modeling biomarkers and mechanisms to reduce bacterial vaginosis recurrence

Integrating multi-omics data: Modeling biomarkers and mechanisms to reduce bacterial vaginosis recurrence
整合多组学数据:建模生物标志物和机制以减少细菌性阴道病复发
批准号:
10625316
负责人:
Johanna B. Holm
金额:
$9.29万
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-06-01 至 2026-05-31
关键词:
AffectAfricanAgeAmericanAnaerobic BacteriaAntibiotic TherapyArchivesAtopobium vaginaeAwardBacteriaBacterial VaginosisBasic ScienceBehavioralBig DataBioinformaticsBiological MarkersBiometryCase/Control StudiesCategoriesClinicalClinical ResearchCommunitiesComplementDataDiagnosisEcologyEpidemiologic MethodsEpidemiologyEthnic OriginEvaluationFundingFutureGenesGoalsGrantHIVHealthHygieneImmune TargetingImmune responseImmunologic MarkersInfectionInfertilityInflammatoryInterventionIrrigationK-Series Research Career ProgramsLactobacillusLearningLife StyleLongitudinal StudiesMarylandMentorsMetagenomicsMethodsMissionModelingMolecularMultiomic DataOutcomeParticipantPelvic Inflammatory DiseasePredispositionPremature BirthPrognostic FactorQuality of lifeRaceRecommendationRecurrenceReportingReproductive HealthResearchResearch DesignResearch PersonnelResearch SupportResourcesRiskSamplingScientistSex BehaviorSexually Transmitted DiseasesSourceStatistical ModelsSymptomsTrainingTranslatingUnited States National Institutes of HealthUniversitiesVaginaVisitWomanWomen&aposs HealthWorkagedcandidate identificationcandidate markercareer developmentcertificate programcervicovaginalclinical diagnosisclinical translationcomplex datadata integrationdata modelingdata reductionepidemiology studygenome sciencesimprovedinsightintraamniotic infectionmachine learning methodmedical schoolsmetabolomemetabolomicsmetagenomemicrobialmicrobiomemodel developmentmultiple omicsnovelpersonalized medicineprognostic indicatorprogramsreproductiveresearch studyscreeningsupervised learningtargeted treatmenttherapeutic targettoolvaginal microbiomevaginal microbiota

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中文摘要
翻译
细菌性阴道病(BV)的特征在于具有低丰度的乳杆菌属物种的阴道微生物群。和 厌氧菌的丰度较高,影响近30%的育龄北美妇女 接近50%的撒哈拉以南非洲妇女。BV的诊断是通过临床观察Amsel’s 标准(Amsel-BV),但仅在报告症状时才建议治疗, 未接受治疗的妇女比例。即使接受治疗,6个月内BV复发率也在50-70%之间, 会增加女性出现负面后遗症的风险无论症状如何,BV与严重不良反应相关, 健康结果,包括早产和艾滋病毒,并可能严重影响妇女的生活质量。理想BV 治疗可以消除复发。阴道微生物群和微环境共同提供了 BV状态的详细评估,并持有关键功能见解,以预测和理解Amsel-BV 复发该提案的目标是整合和操作微生物组(宏基因组), 微环境(代谢组和免疫标志物)数据,以开发复发性BV的预后指标, 并鉴定减少复发的候选生物标志物和因果机制。PI最近的工作 在功能上对阴道微生物组进行分类以用于大型临床研究(阴道宏基因组 社区状态类型,mgCST)。该提案中的广泛假设是,并非所有微生物组 与细菌性阴道病相关的阴道炎有相同的复发潜力。初步数据显示, BV复发更频繁地观察到只有两个9 mgCST含有BV相关细菌。 本研究建议使用NIH 1999年阴道纵向研究中存档的宫颈阴道样本。 植物群,参与者每季度进行一次为期一年的随访。将对基线样本进行多组学分析, 进行评估,以识别微生物(宏基因组学和代谢组学)和宿主(代谢组学和靶向免疫 标志物)标志对复发性BV的易感性。本提案的具体目标是:(1)开展一项 流行病学分析,以评估mgCST的人口统计学和生活方式相关性,以及(2)采用 有监督的机器学习和因果推理建模,以识别预后因素和驱动因素 阴道微生物群和微环境的变化导致复发性BV。病例定义为女性 在基线时使用Amsel-BV,然后在3个月后清除,然后在6个月时复发。控件 Amsel-BV患者在9个月内未复发。这笔赠款将支持PI的培训 在流行病学和生物统计学与临床研究证书课程完成。私家侦探很长- 长期目标是建立一个独立的研究计划,翻译阴道微生物组的基础科学 改善妇女的生殖健康成果。基因组科学研究所和牛津大学 医学的马里兰州学校独特地提供成功完成所需的资源和支持 该提案以及PI向独立研究者的过渡。
英文摘要
Bacterial vaginosis (BV) is characterized by a vaginal microbiota with a low abundance of Lactobacillus spp. and higher abundances of anaerobic bacteria and affects nearly 30% of reproductive-age North American women and closer to 50% of sub-Saharan African women. BV is diagnosed by clinical observation of Amsel’s criteria (Amsel-BV), but treatment is only recommended when symptoms are reported, leaving a significant proportion of women untreated. Even with treatment, BV recurrence rates range from 50-70% within 6 months, increasing a woman’s risk of negative sequelae. Regardless of symptoms, BV is associated with serious adverse health outcomes, including preterm birth and HIV, and can seriously impact a woman’s quality of life. Ideal BV treatment would eliminate recurrence. The vaginal microbiome and microenvironment together provide a detailed evaluation of BV states, and hold key functional insights to predict and understand Amsel-BV recurrence. The goal of this proposal is to integrate and operationalize microbiome (metagenomes) and microenvironment (metabolomes and immune markers) data to develop a prognostic indicator of recurrent BV, and identify candidate biomarkers and causal mechanisms which reduce recurrence. Recent work by the PI functionally categorized the vaginal microbiome for use in large clinical research studies (vaginal metagenomic community state types, mgCSTs). The broad hypothesis in this proposal is that not all microbiomes associated with bacterial vaginosis have the same potential for recurrence. Preliminary data suggest that BV recurrence is more frequently observed in only two of the nine mgCSTs containing BV-associated bacteria. This study proposes to utilize archived cervicovaginal samples from the NIH 1999 Longitudinal Study of Vaginal Flora in which participants were followed quarterly for one year. Multi-omic analyses of baseline samples will be assessed to identify microbial (metagenomic and metabolomic) and host (metabolomic and targeted immune markers) signatures of susceptibility to recurrent BV. Specific aims of this proposal are to: (1) conduct an epidemiological analysis to evaluate the demographic and lifestyle correlates of mgCSTs, and (2) employ supervised machine learning and causal inference modeling to identify prognostic factors and drivers of the vaginal microbiome and microenvironment which lead to recurrent BV. Cases are defined as women with Amsel-BV at baseline, then clearance 3 months later, followed by recurrence at six months. Controls are women with Amsel-BV that do not experience recurrence within 9 months. This grant will support the PI’s training in epidemiology and biostatistics with the completion of a Certificate Program in Clinical Research. The PI’s long- term goal is to create an independent research program translating the basic science of the vaginal microbiome to improve women’s reproductive health outcomes. The Institute for Genome Sciences and the University of Maryland School of Medicine uniquely provide the resources and support required for successful completion of this proposal and the PI’s transition to an independent investigator.
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Integrating multi-omics data: Modeling biomarkers and mechanisms to reduce bacterial vaginosis recurrence
  • 批准号:
    10412124
  • 项目类别:
  • 资助金额:
    $9.29万
  • 财政年份:
    2021
  • 负责人:
    Johanna B. Holm
  • 依托单位:
Integrating multi-omics data: Modeling biomarkers and mechanisms to reduce bacterial vaginosis recurrence
  • 批准号:
    10282850
  • 项目类别:
  • 资助金额:
    $9.29万
  • 财政年份:
    2021
  • 负责人:
    Johanna B. Holm
  • 依托单位:
海外基金