作者
Siddharth Madapoosi,Charmion Cruickshank‐Quinn,Kristopher Opron,John R. Erb‐Downward,Lesa Begley,Gen Li,Igor Barjaktarević,R. Graham Barr,Alejandro P. Comellas,David Couper,Christopher B. Cooper,Christine M. Freeman,MeiLan K. Han,Robert J. Kaner,Wassim W. Labaki,Fernando J. Martínez,Victor E. Ortega,Stephen P. Peters,Robert Paine,Prescott G. Woodruff,Jeffrey L. Curtis,Gary B. Huffnagle,Kathleen A. Stringer,Russell P. Bowler,Charles R. Esther,Nichole Reisdorph,Yvonne J. Huang,Neil E. Alexis,Wayne H. Anderson,Mehrdad Arjomandi,Lori A. Bateman,Surya P. Bhatt,Eugene R. Bleecker,Richard C. Boucher,Stephanie A. Christenson,Gerard J. Criner,Ronald G. Crystal,Claire M. Doerschuk,Mark T. Dransfield,Brad Drummond,Craig J. Galbán,Nadia N. Hansel,Annette T. Hastie,Eric A. Hoffman,Richard E. Kanner,Eric C. Kleerup,Jerry A. Krishnan,Lisa M. LaVange,Stephen C. Lazarus,Deborah A. Meyers,Wendy C. Moore,John D. Newell,Laura M. Paulin,Cheryl Pirozzi,Nirupama Putcha,Elizabeth C. Oelsner,Wanda K. O’Neal,Sanjeev Raman,Stephen I. Rennard,Donald P. Tashkin,J. Michael Wells,Robert A. Wise
摘要
Rationale: Chronic obstructive pulmonary disease (COPD) is variable in its development. Lung microbiota and metabolites collectively may impact COPD pathophysiology, but relationships to clinical outcomes in milder disease are unclear. Objectives: Identify components of the lung microbiome and metabolome collectively associated with clinical markers in milder stage COPD. Methods: We analyzed paired microbiome and metabolomic data previously characterized from bronchoalveolar lavage fluid in 137 participants in the SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study), or (GOLD [Global Initiative for Chronic Obstructive Lung Disease Stage 0–2). Datasets used included 1) bacterial 16S rRNA gene sequencing; 2) untargeted metabolomics of the hydrophobic fraction, largely comprising lipids; and 3) targeted metabolomics for a panel of hydrophilic compounds previously implicated in mucoinflammation. We applied an integrative approach to select features and model 14 individual clinical variables representative of known associations with COPD trajectory (lung function, symptoms, and exacerbations). Measurements and Main Results: The majority of clinical measures associated with the lung microbiome and metabolome collectively in overall models (classification accuracies, >50%, P < 0.05 vs. chance). Lower lung function, COPD diagnosis, and greater symptoms associated positively with Streptococcus, Neisseria, and Veillonella, together with compounds from several classes (glycosphingolipids, glycerophospholipids, polyamines and xanthine, an adenosine metabolite). In contrast, several Prevotella members, together with adenosine, 5′-methylthioadenosine, sialic acid, tyrosine, and glutathione, associated with better lung function, absence of COPD, or less symptoms. Significant correlations were observed between specific metabolites and bacteria (Padj < 0.05). Conclusions: Components of the lung microbiome and metabolome in combination relate to outcome measures in milder COPD, highlighting their potential collaborative roles in disease pathogenesis.