Understanding pulmonary hypertension: the need for an integrative metabolomics and transcriptomics approach.

Pulmonary hypertension (PH), characterised by mean pulmonary arterial pressure (mPAP) >20 mm Hg at rest, is a complex pathophysiological disorder associated with multiple clinical conditions. The high prevalence of the disease along with increased mortality and morbidity makes it a global health burden. Despite major advances in understanding the disease pathophysiology, much of the underlying complex molecular mechanism remains to be elucidated. Lack of a robust diagnostic test and specific therapeutic targets also poses major challenges. This review provides a comprehensive update on the dysregulated pathways and promising candidate markers identified in PH patients using the transcriptomics and metabolomics approach. The review also highlights the need of using an integrative multi-omics approach for obtaining insight into the disease at a molecular level. The integrative multi-omics/pan-omics approach envisaged to help in bridging the gap from genotype to phenotype is outlined. Finally, the challenges commonly encountered while conducting omics-driven studies are also discussed.

Bioinformatics analysis of hypoxia associated genes and inflammatory cytokine profiling in COPD-PH.

Pulmonary hypertension (PH) in chronic obstructive pulmonary disease (COPD) is associated with worse clinical outcomes and decreased survival rates. In absence of disease specific diagnostic/therapeutic targets and unclear pathophysiology, there is an urgent need for the identification of potential genetic/molecular markers and disease associated pathways. The present study aims to use a bioinformatics approach to identify and validate hypoxia-associated gene signatures in COPD-PH patients. Additionally, hypoxia-related inflammatory profile is also explored in these patients. Microarray dataset obtained from the Gene Expression Omnibus repository was used to identify differentially expressed genes (DEGs) in a hypoxic PH mice model. The top three hub genes identified were further validated in COPD-PH patients, with chemokine (C-X-C motif) ligand 9 (CXCL9) and CXCL12 showing significant changes in comparison to healthy controls. Furthermore, multiplexed analysis of 10 inflammatory cytokines, tumor necrosis factor alpha (TNF-α), transforming growth factor ß (TGF-ß), interleukin 1-beta (IL-1ß), IL-4, IL-5, IL-6, IL-13, IL-17, IL-18 and IL-21 was also performed. These markers showed significant changes in COPD-PH patients as compared to controls. They also exhibited the ability to differentially diagnose COPD-PH patients in comparison to COPD. Additionally, IL-6 and IL-17 showed significant positive correlation with systolic pulmonary artery pressure (sPAP). This study is the first report to assess the levels of CXCL9 and CXCL12 in COPD-PH patients and also explores their link with the inflammatory profile of these patients. Our findings could be extended to better understand the underlying disease mechanism and possibly used for tailoring therapies exclusive for the disease.

Global metabolome profiling of exhaled breath condensates in male smokers with asthma COPD overlap and prediction of the disease.

Asthma-chronic obstructive pulmonary disease (COPD) overlap, termed as ACO, is a complex heterogeneous disease characterised by persistent airflow limitation, which manifests features of both asthma and COPD. These patients have a worse prognosis, in terms of more frequent and severe exacerbations, more frequent symptoms, worse quality of life, increased comorbidities and a faster lung function decline. In absence of clear diagnostic or therapeutic guidelines, ACO presents as a challenge to clinicians. The present study aims to investigate whether ACO patients have a distinct exhaled breath condensate (EBC) metabolic profile in comparison to asthma and COPD. A total of 132 age and BMI matched male smokers were recruited in the exploratory phase which consisted of (i) controls = 33 (ii) asthma = 34 (iii) COPD = 30 and (iv) ACO = 35. Using nuclear magnetic resonance (NMR) metabolomics, 8 metabolites (fatty acid, propionate, isopropanol, lactate, acetone, valine, methanol and formate) were identified to be significantly dysregulated in ACO subjects when compared to both, asthma and COPD. The expression of these dysregulated metabolites were further validated in a fresh patient cohort consisting of (i) asthma = 32 (ii) COPD = 32 and (iii) ACO = 40, which exhibited a similar expression pattern. Multivariate receiver operating characteristic (ROC) curves generated using these metabolites provided a robust ACO classification model. The findings were also integrated with previously identified serum metabolites and inflammatory markers to develop a robust predictive model for differentiation of ACO. Our findings suggest that NMR metabolomics of EBC holds potential as a platform to identify robust, non-invasive biomarkers for differentiating ACO from asthma and COPD.

Metabolomic fingerprinting and systemic inflammatory profiling of asthma COPD overlap (ACO).

BACKGROUND: Asthma-COPD overlap (ACO) refers to a group of poorly studied and characterised patients reporting with disease presentations of both asthma and COPD, thereby making both diagnosis and treatment challenging for the clinicians. They exhibit a higher burden in terms of both mortality and morbidity in comparison to patients with only asthma or COPD. The pathophysiology of the disease and its existence as a unique disease entity remains unclear. The present study aims to determine whether ACO has a distinct metabolic and immunological mediator profile in comparison to asthma and COPD. METHODS: Global metabolomic profiling using two different groups of patients [discovery (D) and validation (V)] were conducted. Serum samples obtained from moderate and severe asthma [n = 34(D); n = 32(V)], moderate and severe COPD [n = 30(D); 32(V)], ACO patients [n = 35(D); 40(V)] and healthy controls [n = 33(D)] were characterized using gas chromatography mass spectrometry (GC-MS). Multiplexed analysis of 25 immunological markers (IFN-γ (interferon gamma), TNF-α (tumor necrosis factor alpha), IL-12p70 (interleukin 12p70), IL-2, IL-4, IL-5, IL-13, IL-10, IL-1α, IL-1ß, TGF-ß (transforming growth factor), IL-6, IL-17E, IL-21, IL-23, eotaxin, GM-CSF (granulocyte macrophage-colony stimulating factor), IFN-α (interferon alpha), IL-18, NGAL (neutrophil gelatinase-associated lipocalin), periostin, TSLP (thymic stromal lymphopoietin), MCP-1 (monocyte chemoattractant protein- 1), YKL-40 (chitinase 3 like 1) and IL-8) was also performed in the discovery cohort. RESULTS: Eleven metabolites [serine, threonine, ethanolamine, glucose, cholesterol, 2-palmitoylglycerol, stearic acid, lactic acid, linoleic acid, D-mannose and succinic acid] were found to be significantly altered in ACO as compared with asthma and COPD. The levels and expression trends were successfully validated in a fresh cohort of subjects. Thirteen immunological mediators including TNFα, IL-1ß, IL-17E, GM-CSF, IL-18, NGAL, IL-5, IL-10, MCP-1, YKL-40, IFN-γ, IL-6 and TGF-ß showed distinct expression patterns in ACO. These markers and metabolites exhibited significant correlation with each other and also with lung function parameters. CONCLUSIONS: The energy metabolites, cholesterol and fatty acids correlated significantly with the immunological mediators, suggesting existence of a possible link between the inflammatory status of these patients and impaired metabolism. The present findings could be possibly extended to better define the ACO diagnostic criteria, management and tailoring therapies exclusively for the disease.

Metabolomic signatures of asthma-COPD overlap (ACO) are different from asthma and COPD.

INTRODUCTION: Asthma-chronic obstructive pulmonary disease (COPD) overlap, termed as ACO, is a complex heterogeneous disease without any clear diagnostic or therapeutic guidelines. The pathophysiology of the disease, its characteristic features, and existence as a unique disease entity remains unclear. Individuals with ACO have a faster lung function decline, more frequent exacerbations, and worse quality of life than those with COPD or asthma alone. OBJECTIVES: The present study aims to determine whether ACO has a distinct metabolic profile in comparison to asthma and COPD. METHODS: Two different groups of patients were recruited as discovery (D) and validation (V) cohorts. Serum samples obtained from moderate and severe asthma patients diagnosed as per GINA guidelines [n = 34(D); n = 32(V)], moderate and severe COPD cases identified by GOLD guidelines [n = 30(D); 32(V)], ACO patients diagnosed by joint GOLD and GINA guidelines [n = 35(D); 40(V)] and healthy controls [n = 33(D)] were characterized using nuclear magnetic resonance (NMR) spectrometry. RESULTS: Multivariate and univariate analysis indicated that 12 metabolites [lipid, isoleucine, N-acetylglycoproteins (NAG), valine, glutamate, citric acid, glucose, L-leucine, lysine, asparagine, phenylalanine and histidine] were dysregulated in ACO patients when compared with both asthma and COPD. These metabolites were further validated in a fresh cohort of patients, which again exhibited a similar expression pattern. CONCLUSIONS: Our findings suggest that ACO has an enhanced energy and metabolic burden associated with it as compared to asthma and COPD. It is anticipated that our results will stimulate researchers to further explore ACO and unravel the pathophysiological complexities associated with the disease.

Reference equation for spirometry interpretation for Eastern India.

INTRODUCTION: Spirometry measurements are interpreted by comparing with reference values for healthy individuals that have been derived from multiple regression equations from earlier studies. There are only two such studies from Eastern India, both by Chatterjee et al., one each for males and females. These are however single center and approximately two decades old studies. AIMS: (1) to formulate a new regression equation for predicting FEV1 and FVC for eastern India and (2) to compare the results to the previous two studies by Chatterjee et al. MATERIALS AND METHODS: Healthy nonsmokers were recruited through health camps under the initiative of four large hospitals of Kolkata. Predicted equations were derived for FEV1, FVC and FEV1/FVC in males and females separately using multiple linear regression, which were then compared with the older equations using Bland-Altman method. RESULTS: The Bland-Altman analyses show that the mean bias for females for FVC was 0.39 L (95% limits of agreement 1.32 to -0.54 L) and for FEV1 was 0.334 L (95% limits of agreement of 1.08 to -0.41 L). For males the mean bias for FEV1 was -0.141 L, (95% limits of agreement 0.88 to -1.16 L) while that for FVC was -0.112 L (95% limits of agreement 0.80 to -1.08 L). CONCLUSION: New updated regression equations are needed for predicting reference values for spirometry interpretation. The regression equations proposed in this study may be considered appropriate for use in current practice for eastern India until further studies are available.