Analysis of the microbiome in smokers without COPD and with COPD in China

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1 Analysis of the microbiome in smokers without COPD and with COPD in China ( ) JI Pulmonary

2 Overall Hypothesis Smoking Chronic inflammation Foods, antibiotics, BMI, etc? Change of lung microbiota, imbalance? Secondary immune responses, regulation of antiinflammatory capacity decline COPD? 2

3 Methods PKUTH UM subjects (40-71) BALF throat BGI 16S Clinical data Data analysis microbiome from BALF in COPD and noncopd BALF result microbiome from throat Erb-Downward JR, Thompson DL, Han MK, Freeman CM, McCloskey L, et al. (2011) Analysis of the Lung Microbiome in the Healthy Smoker and in COPD. PLoS ONE 6(2): e doi: /journal.pone

4 Clinical data of BAL from subjects COPD (n=32) Smoker (n=10) Male/female 32/0 8/2 Age, years 63.63± ±6.69 Body-mass index 24.32± ±2.93 Pack-years 36.97± ± MWT ± SGRQ 38.08± FEV 1 /FVC, % 56.93± ±6.23 FEV 1, liters 1.87± ±0.58 FEV 1, % predicted 61.28± ±

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6 Microbiome in the throat and BALF from COPD patients Throat BALF The most abundant lung associated bacteria are similar to those seen in US populations Some low abundant bacteria in BAL appear to be unique to China 6

7 Atypical bacteria are never seen in the lungs before OTUs Genera p-value Otu0001 Prevotella Otu0004 Fusobacterium Otu0008 Novosphingobium 0.03 Otu0011 Paracoccus Otu0013 Propionibacterium Otu0016 Corynebacterium Otu0017 Porphyromonas Otu0021 Acidovorax Otu0030 Pseudomonas Otu0031 Acinetobacter Otu0036 Delftia Otu0041 Devosia Otu0045 unclassified Otu0053 Staphylococcus

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10 BAL Microbiota (Chronic bronchitis or not) 10

11 Conclusion This is the first study of the microbiome in COPD patients in China BAL microbiota is not result of oral contamination There is no significant difference between healthy smokers and subjects with COPD The most abundant lung associated bacteria are similar to those seen in US populations Some low abundant bacteria in BAL appear to be unique to China 11

12 The Human Pulmonary Microbiome in COPD: A Multi-site International Study (NHLBI) DCC, sequencing, bioinformatics and biostatistics site University of Michigan Margaret Gyetko, MD (PI) MeiLan Han, MD Gary Huffnagle, PhD John Erb-Downward, PhD Cathie Spino, Sc.D Susan Murray, Sc.D Erica Bush Study sites: Bangladesh Dewan Alam, MBBS.Mmed, PhD Ali Tanweer Siddiquee, MBBS, PhD China Bei He, MD, PhD Ning Shen, MD Peru William Checkley, MD, PhD Jaime Miranda, PhD Phabiola Herrera Aldana, MD Nepal William Checkley

13 Our study At each site: Never smokers n=10 Healthy smokers (tobacco or biomass fuel exposed) n=20 Subjects with spirometrically defined COPD n=20 Samples were induced sputum. Samples were sequenced at UM using MiSeq 6,552,703 high-quality reads

14 CHINA NORMAL CONTROLS Predicted Age Gender FEV1 FEV1% 41 F F F M M M F M M M Mean Values: COPD AND SMOKE/BIOMASS EXPOSED Age Gender Smoking history Current Smoker Biomass Predicted FEV1 FEV1% 51 M Yes Yes No M Yes Yes No M Yes No Yes M Yes Yes No M Yes Yes No M Yes Yes No M Yes Yes No M Yes Yes No M Yes Yes No M Yes Yes No M Yes Yes No M Yes Yes No M Yes Yes No M Yes Yes No M Yes Yes No M Yes Yes No M Yes Yes No M Yes Yes No M Yes Yes No M Yes Yes No Mean Values: HEALTHY SMOKERS Age Gender Smoking history Current Smoker Biomass Predicted FEV1 FEV1% 41 Female Yes Yes No Male Yes Yes No Male Yes Yes No Male Yes Yes No Male Yes Yes No Male Yes Yes No Male Yes Yes No Male Yes Yes No Male Yes Yes No Male Yes Yes No Male Yes Yes No Female No Yes Male Yes Yes No Male Yes Yes No Male Yes Yes No Male Yes Yes No Male Yes Yes No Male Yes Yes No Male Yes Yes No Male Yes Yes No Mean Values:

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18 Familiar bacterial signals (Prevotella, Streptococcus, Fusobacterium, Porphyromonas, Neisseria) are seen in the main cluster. The sites that are away from the main cluster appear to driven by an unclassified Enterobacteriaceae, Haemophilus, Moraxella, Burkholderia and an unclassified Leptotrichiaceae. Many of these would suggest sicker subjects.

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20 p=0.031

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23 Conclusions 1) At a genus-level the microbiota of the sputum is similar across sites although there are significant differences depending on country 2) HS and COPD have significantly different bacterial communities in sputum independent of country 3) This difference is largely driven by a significant increase in Haemophilus spp. in the COPD population (p=0.026) 4) As FEV1 % Predicted decreased there was also a significant shift in the sputum microbiome, driven by significant increases in Haemophilus spp. (p=0.001) and Moraxella spp. (p=0.013) with decreased lung function 5) Biomass fuel exposure was associated with significantly different communities independent of country. This was driven by a significant decrease in Actinomyces spp. (p=0.002) and an increase in Granulicatella spp. (p=0.022) when biomass fuel exposed.

24 Conclusions 6) Studies addressing basic mechanisms in CNDs can be done within a collaborative international network. 7) Characterization of the pulmonary microbiome can be accomplished in the field by induced sputum. This method is safe, inexpensive, produces high quality samples with high yields, and can be used for longitudinal and interventional studies.