Understand biological factors underlying early childhood caries disparity from the oral microbiome in early infancy
从婴儿早期口腔微生物组了解儿童早期龋齿差异背后的生物学因素
基本信息
- 批准号:10612957
- 负责人:
- 金额:$ 71.73万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-05-01 至 2027-01-31
- 项目状态:未结题
- 来源:
- 关键词:AddressAdvisory CommitteesAffectAfrican AmericanArchivesBacteriaBiologicalBiological FactorsBiometryBirthBlack raceCaries preventionChildChild DevelopmentChildhoodChronicCollectionCommunicable DiseasesCommunitiesComputer ModelsDataData SourcesDentalDental cariesDevelopmentDisadvantaged minorityDisciplineDiseaseDisparityEnsureEnvironmentEnvironmental Risk FactorExposure toGenesGeneticGoalsHealthHealth Disparities ResearchHumanImmuneImmunologic FactorsImmunologic MarkersInfantInfant DevelopmentLifeLife Cycle StagesLow incomeMachine LearningMedicalMetagenomicsMethodsMinorityModelingMothersMycosesNational Institute of Dental and Craniofacial ResearchOralOral healthPatternPerinatalPreschool ChildPreventionProfessional OrganizationsPublic HealthRaceResearch PersonnelRisk FactorsSalivaSalivarySamplingSeveritiesShapesSocioeconomic StatusStreptococcus mutansTestingTimeTrainingUnderserved PopulationWorkcohortcraniofacialearly childhoodearly onsetethnic minorityethnic minority populationfungushealth disparityhealth recordhigh dimensionalityinfancyinnovationmachine learning predictionmetagenomic sequencingmicrobialmicrobiomemicrobiome compositionmicrobiotaminority childrenmultidisciplinaryoral bacteriaoral microbial communityoral microbiomepredictive modelingprenatalracial disparityracial minorityracial minority populationracial populationsocioeconomic disadvantagesocioeconomic disparitystatistical and machine learningsuccesstooltransmission process
项目摘要
SUMMARY
Early childhood caries (ECC) is the most common chronic childhood disease. Although largely
preventable, ECC affects one third of socioeconomically disadvantaged and racial/ethnic minority preschool
children in the US. Effectively reducing ECC disparity requires a better understanding of its biological factors
from birth to early childhood including identifying differential exposure to risk factors by race and socioeconomic
status. While ECC is an infectious disease initiated by the oral microbiota (bacteria and fungi), the interplay
between host, environment, and oral microbiota affects the onset and severity of ECC. However, to date, few
studies have examined the early-life longitudinal development of oral microbiota in underserved children, and
none have utilized comprehensive methods to examine multiplatform (host and environmental) factors that
contribute to the establishment of cariogenic microflora and onset of ECC among the underserved children.
Oral Microbiome in Early Infancy (OMEI) study will address this urgent need to understand
biological factors related to ECC among underserved racial/ethnic minority groups. The OMEI leverages
a recently archived birth cohort that compromises 160 low-income minority infants (primarily Black/African
American) and a comprehensive collection of medical/oral health records and ~1760 salivary/supragingival
samples (obtained via NIDCR KL2TR001999 and K23DE027412, PI: Xiao). The OMEI builds upon our previous
work that 1) revealed racial background is associated with early-life oral microbiome development in the context
of ECC; 2) demonstrated oral bacterial-fungal cross-kingdom interactions and their associations with ECC; 3)
identified human genes related to Host-S. mutans-Dental caries interactions; and 4) developed machine-learning
prediction models for ECC. In Aim 1, we will use metagenomic analysis to define the critical assembly and
functional development of the oral microbiome (bacteria and fungi) in early infancy (birth to two years) among all
infants and their respective racial groups. In Aim 2, we will use computational modeling to identify determinants
(maternal, genetic, and immune factors) of infants’ oral microbiome development. In Aim 3, we will use high-
dimensional statistical machine learning approaches to integrate multi-platform (maternal, microbial, genetic,
immune, and environmental) data to identify biological factors underlying ECC etiopathogenesis and develop
ECC prediction models. The OMEI will be the first study that examines the early-life biological factors underlying
ECC disparity from an infants’ oral microbiome perspective. Risk factors revealed from OMEI could be used as
targets for ECC early prediction and prevention specifically suitable for underserved children. An integrated
health disparities research team with investigators from multiple disciplines (microbiome, perinatal oral health,
metagenomic sequencing, high-dimensional biostatistics, genetics, and health disparities), together with an
outstanding internal-external advisory committee, will ensure the success of the proposed OMEI project.
总结
幼儿龋病是最常见的儿童慢性疾病。虽然在很大程度上
幼儿保育是可以预防的,影响到三分之一的社会经济弱势群体和少数种族/族裔学龄前儿童。
美国的孩子。有效地减少ECC差异需要更好地了解其生物学因素
从出生到幼儿期,包括确定种族和社会经济因素对风险因素的不同影响
status.虽然ECC是一种由口腔微生物群(细菌和真菌)引发的传染病,
宿主、环境和口腔微生物群之间的相互作用影响ECC的发病和严重程度。然而,迄今为止,
研究已经检查了服务不足儿童口腔微生物群的早期纵向发展,
没有人利用综合方法来检查多平台(宿主和环境)因素,
有助于在服务不足的儿童中建立致龋微生物菌群和ECC的发病。
早期婴儿口腔微生物组(OMEI)研究将解决这一迫切需要了解的问题
在服务不足的种族/少数民族群体中,与幼儿保育有关的生物因素。OMEI利用
最近存档的出生队列,包括160名低收入少数民族婴儿(主要是黑人/非洲人
美国)和全面收集的医疗/口腔健康记录和~1760唾液/龈上
样品(通过NIDCR KL 2 TR 001999和K23 DE 027412获得,PI:Xiao)。OMEI建立在我们以前的
1)揭示种族背景的工作与早期生活中口腔微生物组的发育有关
2)证实了口腔细菌-真菌的跨王国相互作用及其与ECC的关联; 3)
发现了与宿主S相关的人类基因。突变体-龋齿相互作用;以及4)开发的机器学习
ECC预测模型在目标1中,我们将使用宏基因组分析来定义关键组装,
在婴儿早期(出生到两岁)口腔微生物组(细菌和真菌)的功能发育,
婴儿和他们各自的种族群体。在目标2中,我们将使用计算建模来确定决定因素
(母体、遗传和免疫因素)影响婴儿口腔微生物组发育。在目标3中,我们将使用高-
多维统计机器学习方法来整合多平台(母体,微生物,遗传,
免疫和环境)数据,以鉴定ECC发病机理和发展的生物学因素
ECC预测模型OMEI将是第一个研究早期生命的生物因素,
从婴儿口腔微生物组的角度来看ECC差异。OMEI中揭示的风险因素可用作
专为服务不足的儿童制定的幼儿保育早期预测和预防目标。集成
健康差异研究小组与来自多个学科(微生物组,围产期口腔健康,
宏基因组测序,高维生物统计学,遗传学和健康差异),以及
出色的内部和外部咨询委员会,将确保拟议的OMEI计划取得成功。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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STEVEN R. GILL其他文献
STEVEN R. GILL的其他文献
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{{ truncateString('STEVEN R. GILL', 18)}}的其他基金
Neurobiological and neurocognitive consequences of diverse microbiome functional trajectories
不同微生物组功能轨迹的神经生物学和神经认知后果
- 批准号:
10443912 - 财政年份:2022
- 资助金额:
$ 71.73万 - 项目类别:
Understand biological factors underlying early childhood caries disparity from the oral microbiome in early infancy
从婴儿早期口腔微生物组了解儿童早期龋齿差异背后的生物因素
- 批准号:
10765136 - 财政年份:2022
- 资助金额:
$ 71.73万 - 项目类别:
Understand biological factors underlying early childhood caries disparity from the oral microbiome in early infancy
从婴儿早期口腔微生物组了解儿童早期龋齿差异背后的生物因素
- 批准号:
10666930 - 财政年份:2022
- 资助金额:
$ 71.73万 - 项目类别:
Understand biological factors underlying early childhood caries disparity from the oral microbiome in early infancy
从婴儿早期口腔微生物组了解儿童早期龋齿差异背后的生物学因素
- 批准号:
10443354 - 财政年份:2022
- 资助金额:
$ 71.73万 - 项目类别:
Neurobiological and neurocognitive consequences of diverse microbiome functional trajectories
不同微生物组功能轨迹的神经生物学和神经认知后果
- 批准号:
10651895 - 财政年份:2022
- 资助金额:
$ 71.73万 - 项目类别:
Studies on gut microbiome-joint connections in arthritis
关节炎肠道微生物组与关节连接的研究
- 批准号:
10829141 - 财政年份:2021
- 资助金额:
$ 71.73万 - 项目类别:
Studies on gut microbiome-joint connections in arthritis
关节炎肠道微生物组与关节连接的研究
- 批准号:
10645002 - 财政年份:2021
- 资助金额:
$ 71.73万 - 项目类别:
Studies on gut microbiome-joint connections in arthritis
关节炎肠道微生物组与关节连接的研究
- 批准号:
10378478 - 财政年份:2021
- 资助金额:
$ 71.73万 - 项目类别:
Acquisition of a Fluidigm C1 Single-Cell Auto Prep System
收购 Fluidigm C1 单细胞自动制备系统
- 批准号:
8825724 - 财政年份:2015
- 资助金额:
$ 71.73万 - 项目类别:
Acquisition of an Illumina Hi-Seq 2500
购买 Illumina Hi-Seq 2500
- 批准号:
8447277 - 财政年份:2013
- 资助金额:
$ 71.73万 - 项目类别:
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