oral microbiota in relation to hiv infection and oral...
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Oral microbiota in relation to HIV infection and oral infection in perinatally
HIV-infected adolescents
Jacqueline R. StarrKyu Ha Lee
Lina Faller
Barbara MoscickiRussell Van DykeMark RyderCaroline ShiboskiTJ Yao
2nd Int'l Workshop on Microbiome in HIV Pathogenesis,Treatment and Prevention
November 18, 2016
Bruce J. Paster
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Today’s discussion
• Oral microbiome—some background
• Do the oral microbiota differ in perinatallyHIV-infected (PHIV) and HIV-exposed, uninfected (PHEU) adolescents?
• Do disease-associated microorganisms differ in PHIV vs. PHEU?
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Combinatorial
Labeling and
Spectral Imaging
FISH (CLASI-FISH)
Courtesy Jessica Mark
Welsh & Gary Borisy
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• 50-100 billion oral bacteria/person
• At least 50 km (30 miles)
• Swallow millions of bacteria per day
• Worldwide, up to 1 x 1020 oral bacteria
• 10 to 50 tons
• Fill a large swimming pool
• More bacterial cells (1014) than human cells (1013)
Statistics
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The Oral Microbiome
• ~700 predominant species
• So what!
• <31% have not yet been cultivated
• Specific species associated with health and disease
• Site-specificity and subject-specificity
• www.homd.org; Human Oral Microbiome Database
• Whole genome sequences for 400 taxa
• Easily accessible
• May herald oral and systemic disease
• “More complex than previously believed”
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Pediatric HIV/AIDS Cohort Study
George Seage, ScD, MPH
Russell Van Dyke, MD
NICHD, NIDA, NIAID, OAR, NIMH, NINDS, NIDCD, NIDCR, NIAAA
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Pediatric HIV/AIDS Cohort AMP Study (PHACS)
• A longitudinal study of perinatally HIV-infected (PHIV) and
HIV-exposed, uninfected (PHEU) adolescents
• Adolescent Master Protocol (AMP): Oral Disease and Type of
Antiretroviral Therapy among PHIV Youth
• Goal--to examine the association between oral disease and
combination antiretroviral therapy (cART) regimen among
PHIV
• Clinical Results
o cART was successful at controlling opportunistic
(mucosal) infections
o High prevalence of gingivitis and periodontal disease,
but little difference between PHIV and PHEU
o PHIV had more caries than PHEU
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Specific aims-oral microbiome1. Do the oral microbiota differ in PHIV vs PHEU?
• What effect does HIV have on the oral microbial composition?
2. Do disease-associated microorganisms differ in PHIV vs. PHEU?
• E.g., S. mutans or other caries-associated species in both PHIV and PHEU?
• E.g., P. gingivalis and other periodontitis-associated species in both PHIV and PHEU?
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Background
HIVinfection
Hostimmune
suppression
Altered oral microbiome
Antiretroviral
therapy
Influence HIV clinical
course
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Sampling and processing
• Excluded subjects who had taken antibiotics within three months of sampling
• 2 types of samples
– Pooled subgingival plaque (n=289)—2 mesial buccal sites
– Throat wash expectorant (n=296)
• Extracted DNA
• 16S rDNA NGS sequencing (MiSeq)—V3-V4 region
• Compared levels of oral microbiota
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Identification of bacterial species & genera
MiSeq 441 bp, V3-V4 region,
~50,000 reads/sample
~600 ProbeSeq
species-level targets
~129 genus-level targets
Excluded low abundance
taxa
Estimated diversity
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“Exposure”: HIV
infection
“Outcome”: Oral
dysbiosis
Regression analysis:Levels of microbiota in PHIV versus PHEU
Levels of each
species or genusTwo
groups: PHIV vs PHEU
• Zero-inflated negative binomial regression
• Multiple univariate models
• Adjusted for – total counts
– age
• Controlled FDR (B-H)
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Are the same species or genera associated with caries or perio in PHIV versus PHEU?
HIV infection
Oral dysbiosis
Increased disease risk
• Logistic regression model
• Outcome is caries OR periodontitis
• Interaction term between HIV and microbiota
• Adjusted for total counts, age
• Controlled FDR (B-H)
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Conclusions and future studies• PHIV versus PHEU?
– Many taxa differed in PHIV vs PHEU– PHIV microbiome seemed less diverse– PHIV possibly fewer “health”-associated taxa
• Fewer Corynebacterium, Rothia, Actinomyces– HIV-infection, or its treatment, likely contributes to oral
dysbiosis• Oral disease-associated microorganisms differ?
– No difference between PHIV and PHEU, i.e., no taxa met significance threshold level
• Future studies– Higher n’s, e.g., effect modification analyses underpowered– Sampling of specific disease sites– Compare with never been exposed to HIV– Metatranscriptomics and other ‘omics
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Acknowledgments
under cooperative agreements HD052104 (PHACS
Coordinating Center, Tulane University School of Medicine)
and HD052102 (PHACS Data and Operations Center, Harvard
School of Public Health).
We thank the study participants, clinical sites, PHACS
Community Advisory Board, Frontier Science & Technology Research Foundation, and Westat.
PHACS is funded by: