Update on metabolomic findings in COPD patients

Abstract

COPD is a heterogeneous disorder that shows diverse clinical presentations (phenotypes and “treatable traits”) and biological mechanisms (endotypes). This heterogeneity implies that to carry out a more personalised clinical management, it is necessary to classify each patient accurately. With this objective, and in addition to clinical features, it would be very useful to have well-defined biological markers. The search for these markers may either be done through more conventional laboratory and hypothesis-driven techniques or relatively blind high-throughput methods, with the omics approaches being suitable for the latter. Metabolomics is the science that studies biological processes through their metabolites, using various techniques such as gas and liquid chromatography, mass spectrometry and nuclear magnetic resonance. The most relevant metabolomics studies carried out in COPD highlight the importance of metabolites involved in pathways directly related to proteins (peptides and amino acids), nucleic acids (nitrogenous bases and nucleosides), and lipids and their derivatives (especially fatty acids, phospholipids, ceramides and eicosanoids). These findings indicate the relevance of inflammatory-immune processes, oxidative stress, increased catabolism and alterations in the energy production. However, some specific findings have also been reported for different COPD phenotypes, demographic characteristics of the patients, disease progression profiles, exacerbations, systemic manifestations, and even diverse treatments. Unfortunately, the studies carried out to date have some limitations and shortcomings and there is still a need to define clear metabolomic profiles with clinical utility for the management of COPD and its implicit heterogeneity.

Exploring the Potential Role of Metabolomics in COPD: A Concise Review

“…Differences in the metabolism of proteins and nucleic acids have been observed in COPD patients with frequent exacerbations. Specific alterations in cytokines and eicosanoids metabolism characterize the metabolomic profiles of individuals with asthma-COPD overlap (ACO) and COPD with a high blood eosinophil count [ 75 ].…”

Prognostic Value of the Triglyceride-Glucose Index in Patients With Chronic Obstructive Pulmonary Disease, Asthma and Their Overlap

“…Зважаючи на тенденції до все більшого використання персоніфікованої терапії у клінічній практиці, продовжується пошук маркерів, які б спростили здійснення контролю та прогнозування перебігу хронічних респіраторних захворювань [2]. Одним із таких альтернативних доступних маркерів може бути тригліцеридно-глюкозний індекс (ТГІ), адже відомо, що порушення вуглеводного та ліпідного обмінів відіграють одну із ключових ролей у прогресуванні даних захворювань, проте ефективність його застосування для прогнозування змін функції зовнішнього дихання не є чітко встановленою [3,[4][5][6][7][8][9].…”

“…Науковці стверджують, що порушення ліпідного обміну спостерігається як при ХОЗЛ, так і при БА [4,5]. Більше того, при їх поєднаному перебігу науковці відзначали змінені рівні експресії декількох речовин (холестерину в тому числі), порівняно з ХОЗЛ та БА і пояснювалось це порушеннями обміну стеролів та ліпідів [6].…”

Proteomic Blood Profiles Obtained by Totally Blind Biological Clustering in Stable and Exacerbated COPD Patients

“…Moreover, the majority of these latter studies have focused on specific groups of patients belonging to wide multicentric cohorts, with the advantages and disadvantages implicit in their particular inclusion criteria and a potential technical heterogeneity among the centers [9,11]. Furthermore, most of the proposed panels of biomarkers and/or models obtained with these two approaches have failed in the validation step carried out in new cohorts [12,13]. By contrast, the use of non-hypothesis-driven statistical methods (such as the clustering approach) in the second step of the analysis of omic data can provide some additional advantages for blindly classifying individuals into distinct groups, whose members will share biological features.…”