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| Name | Class |
|---|---|
| The University of Texas Medical Branch, Galveston | OTHER |
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Hominids and hominins serve as remarkable hosts to microbes, and we have co-evolved over the past 4.5 million years as highly plethoric communities. Human-associated microorganisms (the "microbiome") are present in numbers exceeding the quantities of human cells by at least 10-fold beginning in the neonatal period. The collective genome (the "metagenome") exceeds our human genome in terms of gene content by more than 150-fold. With respect to microbiota and preterm birth, it has generally assumed that the majority of intrauterine infections originate in the lower genital tract, with microbiota ascending into the otherwise sterile intrauterine environment to infect the placenta (preterm birth), fetal membranes (chorioamnionitis), umbilical cord (funisitis), and the fetus (sepsis). However, we and others have recently demonstrated that the vaginal and gut microbiome communities are distinctly structured in pregnancy, and the placenta is in fact not sterile, but rather harbors a low-abundance microbiome which is likely acquired through hematogenous transmission of the oral microbiome.
Based on our prior studies and preliminary data, our central hypothesis is that a distinct and largely commensal resident microbiome in pregnancy renders risk for preterm birth. By utilizing our state-of-the-science technology and analysis tools in a longitudinal case-cohort of preterm birth subjects, we will be able to transform "discovery based" metagenomics and multi'omics science into readily translatable mechanistic studies at a previously unparalleled level.
Specific Aim 1. Longitudinal maternal (vaginal, oral, skin, gut), fetal (oral, skin, gut) and placental (basal plate and parenchyma) 16S-based metagenomic profiling with inferred metagenomics will reveal distinct microbial communities in association with preterm birth. Methods: We will enroll 526 at-risk gravidae to yield an approximated 135 preterm births with 401 at-risk term controls. Starting in the first/early second trimester, we will sample multiple body sites (vagina, oral, stool, placenta) at multiple time points (antenatal through delivery), isolate microbial DNA, and perform 16S-based determination of niche-specific microbial communities found in association with preterm birth. With our case-cohort longitudinal design, we will be able to apply our well-developed supervised learning approaches to reveal which taxa contribute to risk of preterm birth, and at what body sites and gestational ages they are predictive of preterm birth.
Specific Aim 2. Whole-genome shotgun (WGS) metagenomics from selected subjects and body sites will enable species identification, generation of microbial gene catalogues, and metabolic reconstructions to determine the structure, function and diversity of the preterm birth microbiome. Methods: To probe metabolic functionality and describe pathogen-related mechanisms, we will analyze changes in total gene content using shotgun metagenomics on a subset of samples. We will build on our functional computational pipelines to fully characterize targeted subjects' metagenomic signatures.
Specific Aim 3. Integrated host genomics, metatranscriptomics and metabonomics data will reveal molecular mechanisms and networks underlying preterm birth in a limited subset of samples. Methods: We will interrogate and integrate our concomitantly acquired clinical metadata, microbial and host gene expression data (RNA-Seq metatranscriptomics), and metabonomics profiling with advanced computational and biostatistical approaches. We will be guided in our choice of subjects by our data from Aims 1 and 2.
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| Measure | Description | Time Frame |
|---|---|---|
| Characterization of Maternal-Fetal microbiome | Longitudinally characterize the maternal, placental, and infant microbiome in a cohort at risk of preterm birth. Not all the women will ultimately deliver preterm; we we will be able to see if there are microbiome changes associated with preterm birth. | Conception to 4-6 weeks postpartum |
| Association of maternal microbiome (gut, oral, vaginal, placenta) with preterm birth | Longitudinally characterize the maternal, placental, and infant microbiome in a cohort at risk of preterm birth. Not all the women will ultimately deliver preterm; we we will be able to see if there are microbiome changes associated with preterm birth. | Conception to 4-6 weeks postpartum |
| Measure | Description | Time Frame |
|---|---|---|
| Rate of Preterm Birth | Measure rate of preterm birth <37 and <34 weeks gestation, as defined by best obstetrical estimate of last menstrual period consistent with <24 week sonogram, OR <24 week sonogram with unknown last menstrual period, OR skilled examination and <24 week sonogram | Conception to date of date of delivery, <37 weeks |
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Inclusion Criteria:
Exclusion Criteria:
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Women who are currently pregnant who are at high risk for preterm birth; Pregnant with one baby (not twins or triplets) and who attend regular prenatal visits. They will spend an extra 20 minutes at 5-6 priority scheduled visits to obtain study samples and complete questionnaires, with the last visit occurring around 6 weeks after delivery.
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| Name | Affiliation | Role |
|---|---|---|
| Kjersti Aagaard, MD/PhD | Associate Professor / Vice Chair for Research | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Baylor College of Medicine | Houston | Texas | 77030 | United States |
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| ID | Term |
|---|---|
| D047928 | Premature Birth |
| ID | Term |
|---|---|
| D007752 | Obstetric Labor, Premature |
| D007744 | Obstetric Labor Complications |
| D011248 | Pregnancy Complications |
| D005261 | Female Urogenital Diseases and Pregnancy Complications |
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Samples with DNA, RNA and metabolites
| Rate of Term Birth |
Measure rate of term birth, as defined by best obstetrical estimate of last menstrual period consistent with <24 week sonogram, OR <24 week sonogram with unknown last menstrual period, OR skilled examination and <24 week sonogram |
| Conception to date of date of delivery |
| D000091642 | Urogenital Diseases |