Lung Microbiota and Metabolites Collectively Associate with Clinical Outcomes in Milder Stage Chronic Obstructive Pulmonary Disease
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.
| Errataetall: |
CommentIn: Am J Respir Crit Care Med. 2022 Aug 15;206(4):365-368. - PMID 35584334 |
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| Medienart: |
E-Artikel |
| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:206 |
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| Enthalten in: |
American journal of respiratory and critical care medicine - 206(2022), 4 vom: 15. Aug., Seite 427-439 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Madapoosi, Siddharth S [VerfasserIn] |
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| Links: |
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| Anmerkungen: |
Date Completed 17.08.2022 Date Revised 14.09.2023 published: Print CommentIn: Am J Respir Crit Care Med. 2022 Aug 15;206(4):365-368. - PMID 35584334 Citation Status MEDLINE |
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| doi: |
10.1164/rccm.202110-2241OC |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM340650508 |
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| 100 | 1 | |a Madapoosi, Siddharth S |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Lung Microbiota and Metabolites Collectively Associate with Clinical Outcomes in Milder Stage Chronic Obstructive Pulmonary Disease |
| 264 | 1 | |c 2022 | |
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| 500 | |a Date Completed 17.08.2022 | ||
| 500 | |a Date Revised 14.09.2023 | ||
| 500 | |a published: Print | ||
| 500 | |a CommentIn: Am J Respir Crit Care Med. 2022 Aug 15;206(4):365-368. - PMID 35584334 | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a 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 | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, N.I.H., Extramural | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 4 | |a bronchoscopy | |
| 650 | 4 | |a chronic obstructive pulmonary disease | |
| 650 | 4 | |a lung function | |
| 650 | 4 | |a metabolomics | |
| 650 | 7 | |a RNA, Ribosomal, 16S |2 NLM | |
| 650 | 7 | |a Adenosine |2 NLM | |
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| 700 | 1 | |a Cruickshank-Quinn, Charmion |e verfasserin |4 aut | |
| 700 | 1 | |a Opron, Kristopher |e verfasserin |4 aut | |
| 700 | 1 | |a Erb-Downward, John R |e verfasserin |4 aut | |
| 700 | 1 | |a Begley, Lesa A |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Gen |e verfasserin |4 aut | |
| 700 | 1 | |a Barjaktarevic, Igor |e verfasserin |4 aut | |
| 700 | 1 | |a Barr, R Graham |e verfasserin |4 aut | |
| 700 | 1 | |a Comellas, Alejandro P |e verfasserin |4 aut | |
| 700 | 1 | |a Couper, David J |e verfasserin |4 aut | |
| 700 | 1 | |a Cooper, Christopher B |e verfasserin |4 aut | |
| 700 | 1 | |a Freeman, Christine M |e verfasserin |4 aut | |
| 700 | 1 | |a Han, MeiLan K |e verfasserin |4 aut | |
| 700 | 1 | |a Kaner, Robert J |e verfasserin |4 aut | |
| 700 | 1 | |a Labaki, Wassim |e verfasserin |4 aut | |
| 700 | 1 | |a Martinez, Fernando J |e verfasserin |4 aut | |
| 700 | 1 | |a Ortega, Victor E |e verfasserin |4 aut | |
| 700 | 1 | |a Peters, Stephen P |e verfasserin |4 aut | |
| 700 | 1 | |a Paine, Robert |e verfasserin |4 aut | |
| 700 | 1 | |a Woodruff, Prescott |e verfasserin |4 aut | |
| 700 | 1 | |a Curtis, Jeffrey L |e verfasserin |4 aut | |
| 700 | 1 | |a Huffnagle, Gary B |e verfasserin |4 aut | |
| 700 | 1 | |a Stringer, Kathleen A |e verfasserin |4 aut | |
| 700 | 1 | |a Bowler, Russell P |e verfasserin |4 aut | |
| 700 | 1 | |a Esther, Charles R |c Jr |e verfasserin |4 aut | |
| 700 | 1 | |a Reisdorph, Nichole |e verfasserin |4 aut | |
| 700 | 1 | |a Huang, Yvonne J |e verfasserin |4 aut | |
| 700 | 0 | |a SPIROMICS Research Group |e verfasserin |4 aut | |
| 700 | 1 | |a Alexis, Neil E |e investigator |4 oth | |
| 700 | 1 | |a Anderson, Wayne H |e investigator |4 oth | |
| 700 | 1 | |a Arjomandi, Mehrdad |e investigator |4 oth | |
| 700 | 1 | |a Bateman, Lori A |e investigator |4 oth | |
| 700 | 1 | |a Bhatt, Surya P |e investigator |4 oth | |
| 700 | 1 | |a Bleecker, Eugene R |e investigator |4 oth | |
| 700 | 1 | |a Boucher, Richard C |e investigator |4 oth | |
| 700 | 1 | |a Christenson, Stephanie A |e investigator |4 oth | |
| 700 | 1 | |a Criner, Gerard J |e investigator |4 oth | |
| 700 | 1 | |a Crystal, Ronald G |e investigator |4 oth | |
| 700 | 1 | |a Doerschuk, Claire M |e investigator |4 oth | |
| 700 | 1 | |a Dransfield, Mark T |e investigator |4 oth | |
| 700 | 1 | |a Drummond, Brad |e investigator |4 oth | |
| 700 | 1 | |a Galban, Craig |e investigator |4 oth | |
| 700 | 1 | |a Hansel, Nadia N |e investigator |4 oth | |
| 700 | 1 | |a Hastie, Annette T |e investigator |4 oth | |
| 700 | 1 | |a Hoffman, Eric A |e investigator |4 oth | |
| 700 | 1 | |a Kanner, Richard E |e investigator |4 oth | |
| 700 | 1 | |a Kleerup, Eric C |e investigator |4 oth | |
| 700 | 1 | |a Krishnan, Jerry A |e investigator |4 oth | |
| 700 | 1 | |a LaVange, Lisa M |e investigator |4 oth | |
| 700 | 1 | |a Lazarus, Stephen C |e investigator |4 oth | |
| 700 | 1 | |a Meyers, Deborah A |e investigator |4 oth | |
| 700 | 1 | |a Moore, Wendy C |e investigator |4 oth | |
| 700 | 1 | |a Newell, John D |c Jr |e investigator |4 oth | |
| 700 | 1 | |a Paulin, Laura |e investigator |4 oth | |
| 700 | 1 | |a Pirozzi, Cheryl |e investigator |4 oth | |
| 700 | 1 | |a Putcha, Nirupama |e investigator |4 oth | |
| 700 | 1 | |a Oelsner, Elizabeth C |e investigator |4 oth | |
| 700 | 1 | |a O'Neal, Wanda K |e investigator |4 oth | |
| 700 | 1 | |a Raman, Sanjeev |e investigator |4 oth | |
| 700 | 1 | |a Rennard, Stephen I |e investigator |4 oth | |
| 700 | 1 | |a Tashkin, Donald P |e investigator |4 oth | |
| 700 | 1 | |a Wells, J Michael |e investigator |4 oth | |
| 700 | 1 | |a Wise, Robert A |e investigator |4 oth | |
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