Metabolomics Identifies Novel Blood Biomarkers of Pulmonary Function and COPD in the General Population

Determination of metabolomic signatures of pulmonary function and chronic obstructive pulmonary disease (COPD) in the general population could aid in identification and understanding of early disease processes. Metabolome measurements were performed on serum from 4742 individuals (2354 African-Americans and 1529 European-Americans from the Atherosclerosis Risk in Communities study and 859 Europeans from the Cooperative Health Research in the Region of Augsburg study). We examined 368 metabolites in relation to cross-sectional measures of forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), their ratio (FEV1/FVC) and COPD using multivariable regression followed by meta-analysis. At a false discovery rate of 0.05, 95 metabolites were associated with FEV1 and 100 with FVC (73 overlapping), including inverse associations with branched-chain amino acids and positive associations with glutamine. Ten metabolites were associated with FEV1/FVC and seventeen with COPD (393 cases). Enriched pathways of amino acid metabolism were identified. Associations with FEV1 and FVC were not driven by individuals with COPD. We identified novel metabolic signatures of pulmonary function and COPD in African and European ancestry populations. These may allow development of biomarkers in the general population of early disease pathogenesis, before pulmonary function has decreased to levels diagnostic for COPD.

[1]  C. Newgard,et al.  Metabolomics and Metabolic Diseases: Where Do We Stand? , 2017, Cell metabolism.

[2]  A. Hofman,et al.  Meta-analyses of genome-wide association studies identify multiple loci associated with pulmonary function , 2010, Nature Genetics.

[3]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[4]  Duanping Liao,et al.  Lung function and incident coronary heart disease: the Atherosclerosis Risk in Communities Study. , 2003, American journal of epidemiology.

[5]  Fabian J Theis,et al.  Metabolomics screening identifies reduced L-carnitine to be associated with progressive emphysema. , 2016, Clinical science.

[6]  C. Meisinger,et al.  The MONICA Augsburg surveys--basis for prospective cohort studies. , 2005, Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany)).

[7]  J. Riley,et al.  Targeted metabolomics identifies perturbations in amino acid metabolism that sub-classify patients with COPD. , 2012, Molecular bioSystems.

[8]  M. Svoboda,et al.  A pilot data analysis of a metabolomic HPLC-MS/MS study of patients with COPD. , 2018, Advances in clinical and experimental medicine : official organ Wroclaw Medical University.

[9]  Lining Guo,et al.  Untargeted Metabolomic Profiling as an Evaluative Tool of Fenofibrate-Induced Toxicology in Fischer 344 Male Rats , 2009, Toxicologic pathology.

[10]  B. McManus,et al.  Biomarker Development for Chronic Obstructive Pulmonary Disease. From Discovery to Clinical Implementation. , 2015, American journal of respiratory and critical care medicine.

[11]  Young Seok Lee,et al.  Increased urinary l-histidine in patients with asthma–COPD overlap: a pilot study , 2018, International journal of chronic obstructive pulmonary disease.

[12]  D. Prezant,et al.  Metabolomics of World Trade Center-Lung Injury: a machine learning approach , 2018, BMJ Open Respiratory Research.

[13]  J. Pankow,et al.  Non-Traditional Risk Factors are Important Contributors to the Racial Disparity in Diabetes Risk: The Atherosclerosis Risk in Communities Study , 2014, Journal of General Internal Medicine.

[14]  S Katharine Hammond,et al.  Secondhand smoke exposure, pulmonary function, and cardiovascular mortality. , 2007, Annals of epidemiology.

[15]  R. Bowler,et al.  Plasma sphingolipids associated with chronic obstructive pulmonary disease phenotypes. , 2015, American journal of respiratory and critical care medicine.

[16]  D. Mannino,et al.  The natural history of chronic airflow obstruction revisited: an analysis of the Framingham offspring cohort. , 2009, American journal of respiratory and critical care medicine.

[17]  J L Hankinson,et al.  Spirometric reference values from a sample of the general U.S. population. , 1999, American journal of respiratory and critical care medicine.

[18]  Ashutosh Kumar Singh,et al.  Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015 , 2016, Lancet.

[19]  Corey D. DeHaven,et al.  Integrated, nontargeted ultrahigh performance liquid chromatography/electrospray ionization tandem mass spectrometry platform for the identification and relative quantification of the small-molecule complement of biological systems. , 2009, Analytical chemistry.

[20]  R. Banerjee,et al.  Transcriptomics, proteomics and metabolomics driven biomarker discovery in COPD: an update , 2016, Expert review of molecular diagnostics.

[21]  V. Mootha,et al.  Metabolite profiles and the risk of developing diabetes , 2011, Nature Medicine.

[22]  T. Griffin,et al.  Plasma sphingolipids in HIV-associated chronic obstructive pulmonary disease , 2017, BMJ Open Respiratory Research.

[23]  W Winkelstein,et al.  Pulmonary function is a long-term predictor of mortality in the general population: 29-year follow-up of the Buffalo Health Study. , 2000, Chest.

[24]  R. Crystal,et al.  Serum Metabolite Biomarkers Discriminate Healthy Smokers from COPD Smokers , 2015, PloS one.

[25]  C. Poole,et al.  Airflow Obstruction, Lung Function, and Incidence of Atrial Fibrillation: The Atherosclerosis Risk in Communities (ARIC) Study , 2014, Circulation.

[26]  J. Riley,et al.  Metabolic profiling detects biomarkers of protein degradation in COPD patients , 2011, European Respiratory Journal.

[27]  M. Zureik,et al.  Change in C-reactive protein levels and FEV1 decline: a longitudinal population-based study. , 2006, Respiratory medicine.

[28]  Nicholette D. Palmer,et al.  Metabolomic profile associated with insulin resistance and conversion to diabetes in the Insulin Resistance Atherosclerosis Study. , 2015, The Journal of clinical endocrinology and metabolism.

[29]  B. Rowe,et al.  Metabolomic profiling of asthma and chronic obstructive pulmonary disease: A pilot study differentiating diseases. , 2015, The Journal of allergy and clinical immunology.

[30]  A. Salavati,et al.  Metabolic effects of pulmonary obstruction on myocardial functioning: a pilot study using multiple time-point 18F-FDG-PET imaging , 2015, Nuclear medicine communications.

[31]  A. Folsom,et al.  The Atherosclerosis Risk in Communities (ARIC) Study: design and objectives. The ARIC investigators. , 1989, American journal of epidemiology.

[32]  G. Zhai.  Alteration of Metabolic Pathways in Osteoarthritis , 2019, Metabolites.

[33]  M. Daszykowski,et al.  Metabolomics provide new insights on lung cancer staging and discrimination from chronic obstructive pulmonary disease. , 2014, Journal of pharmaceutical and biomedical analysis.

[34]  R Holle,et al.  KORA - A Research Platform for Population Based Health Research , 2005, Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany)).

[35]  J. Celedón,et al.  Metabolomic profiling of lung function in Costa-Rican children with asthma. , 2017, Biochimica et biophysica acta. Molecular basis of disease.

[36]  P. Burney,et al.  Forced vital capacity, airway obstruction and survival in a general population sample from the USA , 2010, Thorax.

[37]  Julian P T Higgins,et al.  A re‐evaluation of fixed effect(s) meta‐analysis , 2018 .

[38]  J. Havelund,et al.  Biomarker Research in Parkinson’s Disease Using Metabolite Profiling , 2017, Metabolites.

[39]  David S. Wishart,et al.  MetaboAnalyst 3.0—making metabolomics more meaningful , 2015, Nucleic Acids Res..

[40]  Eyal Oren,et al.  Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016 , 2017, Lancet.

[41]  Aric Invest.  The Atherosclerosis Risk in Communities (ARIC) Study: design and objectives. The ARIC investigators , 1989 .

[42]  S. Spencer,et al.  Bronchodilator reversibility testing in chronic obstructive pulmonary disease , 2003, Thorax.

[43]  Alan C. Wilson,et al.  Correlates of Serum α- and γ-Tocopherol in the Women's Health Initiative , 2001 .

[44]  I. Stanimirova,et al.  Fusion of the 1H NMR data of serum, urine and exhaled breath condensate in order to discriminate chronic obstructive pulmonary disease and obstructive sleep apnea syndrome , 2015, Metabolomics.

[45]  C. Schmid,et al.  A new equation to estimate glomerular filtration rate. , 2009, Annals of internal medicine.

[46]  Jianchun Yu,et al.  Glutamine: a precursor of glutathione and its effect on liver. , 1999, World journal of gastroenterology.

[47]  Harry J de Koning,et al.  Genetic loci associated with chronic obstructive pulmonary disease overlap with loci for lung function and pulmonary fibrosis , 2017, Nature Genetics.

[48]  R. Bowler,et al.  Metabolomics and transcriptomics pathway approach reveals outcome-specific perturbations in COPD , 2018, Scientific Reports.

[49]  S. Stanojevic,et al.  Multi-ethnic reference values for spirometry for the 3–95-yr age range: the global lung function 2012 equations , 2012, European Respiratory Journal.

[50]  M. Burdick,et al.  Pilot analysis of the plasma metabolite profiles associated with emphysematous Chronic Obstructive Pulmonary Disease phenotype. , 2011, Biochemical and biophysical research communications.

[51]  Yufu Tang,et al.  Metabonomic Profiling of Serum and Urine by 1H NMR-Based Spectroscopy Discriminates Patients with Chronic Obstructive Pulmonary Disease and Healthy Individuals , 2013, PloS one.

[52]  C. Gieger,et al.  Human metabolic individuality in biomedical and pharmaceutical research , 2011, Nature.

[53]  Christian Gieger,et al.  Metabolomic markers reveal novel pathways of ageing and early development in human populations , 2013, International journal of epidemiology.

[54]  David S. Wishart,et al.  HMDB 3.0—The Human Metabolome Database in 2013 , 2012, Nucleic Acids Res..

[55]  D. Postma,et al.  Untargeted lipidomic analysis in chronic obstructive pulmonary disease. Uncovering sphingolipids. , 2014, American journal of respiratory and critical care medicine.

[56]  Svati H Shah,et al.  A branched-chain amino acid-related metabolic signature that differentiates obese and lean humans and contributes to insulin resistance. , 2009, Cell metabolism.

[57]  Bryan C. Batch,et al.  Branched-chain amino acid levels are associated with improvement in insulin resistance with weight loss , 2012, Diabetologia.

[58]  R. Hopkins,et al.  Forced expiratory volume in one second: not just a lung function test but a marker of premature death from all causes , 2007, European Respiratory Journal.

[59]  T. Spector,et al.  Circulating levels of antioxidant vitamins correlate with better lung function and reduced exposure to ambient pollution. , 2015, American journal of respiratory and critical care medicine.

[60]  Å. Wheelock,et al.  Metabolomics analysis identifies sex-associated metabotypes of oxidative stress and the autotaxin–lysoPA axis in COPD , 2017, European Respiratory Journal.

[61]  R. Trengove,et al.  Metabolomics Approaches for the Diagnosis and Understanding of Kidney Diseases , 2019, Metabolites.

[62]  A. Kristal,et al.  Correlates of serum alpha- and gamma-tocopherol in the Women's Health Initiative. , 2001, Annals of epidemiology.

[63]  J. Soriano,et al.  Lung-Function Trajectories Leading to Chronic Obstructive Pulmonary Disease. , 2015, The New England journal of medicine.

[64]  E. Villa,et al.  The OMICs Window into Nonalcoholic Fatty Liver Disease (NAFLD) , 2019, Metabolites.

[65]  K. Kilk,et al.  Phenotyping of Chronic Obstructive Pulmonary Disease Based on the Integration of Metabolomes and Clinical Characteristics , 2018, International journal of molecular sciences.

[66]  Madhukar S. Dasika,et al.  (1)H nuclear magnetic resonance metabolomics analysis identifies novel urinary biomarkers for lung function. , 2010, Journal of proteome research.

[67]  B. Nordestgaard,et al.  Elevated plasma fibrinogen associated with reduced pulmonary function and increased risk of chronic obstructive pulmonary disease. , 2001, American journal of respiratory and critical care medicine.

[68]  D. Mannino,et al.  Lung function and mortality in the United States: data from the First National Health and Nutrition Examination Survey follow up study , 2003, Thorax.

[69]  Lorna M. Lopez,et al.  Genome-wide association analysis identifies six new loci associated with forced vital capacity , 2014, Nature Genetics.

[70]  Haifeng Zhao,et al.  Metabolic reprogramming in the pathogenesis of chronic lung diseases, including BPD, COPD, and pulmonary fibrosis. , 2018, American journal of physiology. Lung cellular and molecular physiology.

[71]  J. Coresh,et al.  Lung Function and Incident Kidney Disease: The Atherosclerosis Risk in Communities (ARIC) Study. , 2017, American journal of kidney diseases : the official journal of the National Kidney Foundation.