Omics methods predict the prognosis and treatment efficacy of chronic obstructive pulmonary disease.
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ABSTRACT:
SUBMITTER: Huang Y
PROVIDER: S-EPMC10836873 | biostudies-literature | 2024 Feb
REPOSITORIES: biostudies-literature
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Omics methods predict the prognosis and treatment efficacy of chronic obstructive pulmonary disease.
Huang Yan Y Xu Juanjuan J Ma Guanzhou G Wang Sufei S Yan Xiaojuan X Jin Yang Y He Jiafu J
Chinese medical journal 20240112 3
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Project description:Chronic Obstructive Pulmonary Disease (COPD) is the third leading cause of mortality in the United States; however, COPD has heterogeneous clinical phenotypes. This is the first large scale attempt which uses transcriptomics, proteomics, and metabolomics (multi-omics) to determine whether there are molecularly defined clusters with distinct clinical phenotypes that may underlie the clinical heterogeneity. Subjects included 3,278 subjects from the COPDGene cohort with at least one of the following profiles: whole blood transcriptomes (2,650 subjects); plasma proteomes (1,013 subjects); and plasma metabolomes (1,136 subjects). 489 subjects had all three contemporaneous -omics profiles. Autoencoder embeddings were performed individually for each -omics dataset. Embeddings underwent subspace clustering using MineClus, either individually by -omics or combined, followed by recursive feature selection based on Support Vector Machines. Clusters were tested for associations with clinical variables. Optimal single -omics clustering typically resulted in two clusters. Although there was overlap for individual -omics cluster membership, each -omics cluster tended to be defined by unique molecular pathways. For example, prominent molecular features of the metabolome-based clustering included sphingomyelin, while key molecular features of the transcriptome-based clusters were related to immune and bacterial responses. We also found that when we integrated the -omics data at a later stage, we identified subtypes that varied based on age, severity of disease, in addition to diffusing capacity of the lungs for carbon monoxide, and precent on atrial fibrillation. In contrast, when we integrated the -omics data at an earlier stage by treating all data sets equally, there were no clinical differences between subtypes. Similar to clinical clustering, which has revealed multiple heterogenous clinical phenotypes, we show that transcriptomics, proteomics, and metabolomics tend to define clusters of COPD patients with different clinical characteristics. Thus, integrating these different -omics data sets affords additional insight into the molecular nature of COPD and its heterogeneity.
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Project description:Background and objectiveThe Exacerbations of Chronic Obstructive Pulmonary Disease Tool-Patient-Reported Outcomes (EXACT-PRO) has been suggested as a reliable and valid measure for early assessment of COPD exacerbations and perceived recovery. However, there has been no evidence for EXACT-PRO efficacy in assessing recovery from treatment in a randomized controlled trial. The study evaluated the reliability, validity, and responsiveness of EXACT-PRO for the evaluation of the efficacy of acute treatment in patients with COPD exacerbation.MethodsIn a Phase III randomized controlled study for assessing the efficacy of antibiotic treatment on COPD exacerbation, EXACT-PRO was evaluated in the responders and non-responders.ResultsA total of 295 patients were analyzed (259 responders and 37 non-responders). Cronbach's α was 0.96 for EXACT total, 0.96 for the breathlessness domain, 0.89 for the cough and sputum domain, and 0.93 for the chest symptoms domain. The EXACT score correlated with the COPD assessment test (CAT) score (r=0.8, P<0.01). A stronger decrease in the EXACT score was found in the responder group than in the non-responder group from the fifth day after treatment. The difference in the EXACT score from exacerbation onset to recovery was -6.3 in responders and -1.9 in non-responders (P=0.01).ConclusionEXACT-PRO is a comprehensive and sensitive method for assessing symptomatic resolution of COPD exacerbations during treatment.
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Project description:Despite recent advances in chronic obstructive pulmonary disease (COPD) research, few studies have identified the potential therapeutic targets systematically by integrating multiple-omics datasets. This project aimed to develop a systems biology pipeline to identify biologically relevant genes and potential therapeutic targets that could be exploited to discover novel COPD treatments via drug repurposing or de novo drug discovery. A computational method was implemented by integrating multi-omics COPD data from unpaired human samples of more than half a million subjects. The outcomes from genome, transcriptome, proteome, and metabolome COPD studies were included, followed by an in silico interactome and drug-target information analysis. The potential candidate genes were ranked by a distance-based network computational model. Ninety-two genes were identified as COPD signature genes based on their overall proximity to signature genes on all omics levels. They are genes encoding proteins involved in extracellular matrix structural constituent, collagen binding, protease binding, actin-binding proteins, and other functions. Among them, 70 signature genes were determined to be druggable targets. The in silico validation identified that the knockout or over-expression of SPP1, APOA1, CTSD, TIMP1, RXFP1, and SMAD3 genes may drive the cell transcriptomics to a status similar to or contrasting with COPD. While some genes identified in our pipeline have been previously associated with COPD pathology, others represent possible new targets for COPD therapy development. In conclusion, we have identified promising therapeutic targets for COPD. This hypothesis-generating pipeline was supported by unbiased information from available omics datasets and took into consideration disease relevance and development feasibility.
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Project description:Long-acting muscarinic antagonists (LAMAs), along with long-acting ?2-agonists (LABAs), are the mainstay for treatment of patients with COPD. Glycopyrrolate, or glycopyrronium bromide, like other LAMAs, inhibits parasympathetic nerve impulses by selectively blocking the binding of acetylcholine to muscarinic receptors. Glycopyrrolate is unusual in that it preferentially binds to M3 over M2 muscarinic receptors, thereby specifically targeting the primary muscarinic receptor responsible for bronchoconstriction occurring in COPD. Inhaled glycopyrrolate is slowly absorbed from the lungs and rapidly eliminated from the bloodstream, most likely by renal excretion in its unmetabolized form, limiting the potential for systemic adverse events. Inhaled glycopyrrolate is a fast-acting, efficacious treatment option for patients with moderate-severe COPD. It improves lung function, reduces the risk of exacerbations, and alleviates the symptoms of breathlessness, which in turn may explain the improvement seen in patients' quality of life. Inhaled formulations containing glycopyrrolate are well tolerated, and despite being an anticholinergic, few cardiovascular-related events have been reported. Inhaled glycopyrrolate is thus of value as both monotherapy and in combination with other classes of medication for maintenance treatment of COPD. This review covers the mechanism of action of inhaled glycopyrrolate, including its pharmacokinetic, pharmacodynamic, and safety profiles, and effects on mucus secretion. It also discusses the use of inhaled glycopyrrolate in the treatment of COPD, as monotherapy and in fixed-dose combinations with LABAs and inhaled corticosteroid-LABAs, including a triple therapy recently approved in Europe.
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Project description:BackgroundChronic obstructive pulmonary disease (COPD) is a common lung disorder characterized by persistent and progressive airflow limitation as well as systemic changes. Metabolic changes in blood may help detect COPD in an earlier stage and predict prognosis.MethodsWe conducted a comprehensive study of circulating metabolites, measured by proton Nuclear Magnetic Resonance Spectroscopy, in relation with COPD and lung function. The discovery sample consisted of 5557 individuals from two large population-based studies in the Netherlands, the Rotterdam Study and the Erasmus Rucphen Family study. Significant findings were replicated in 12,205 individuals from the Lifelines-DEEP study, FINRISK and the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) studies. For replicated metabolites further investigation of causality was performed, utilizing genetics in the Mendelian randomization approach.ResultsThere were 602 cases of COPD and 4955 controls used in the discovery meta-analysis. Our logistic regression results showed that higher levels of plasma Glycoprotein acetyls (GlycA) are significantly associated with COPD (OR = 1.16, P = 5.6 × 10- 4 in the discovery and OR = 1.30, P = 1.8 × 10- 6 in the replication sample). A bi-directional two-sample Mendelian randomization analysis suggested that circulating blood GlycA is not causally related to COPD, but that COPD causally increases GlycA levels. Using the prospective data of the same sample of Rotterdam Study in Cox-regression, we show that the circulating GlycA level is a predictive biomarker of COPD incidence (HR = 1.99, 95%CI 1.52-2.60, comparing those in the highest and lowest quartile of GlycA) but is not significantly associated with mortality in COPD patients (HR = 1.07, 95%CI 0.94-1.20).ConclusionsOur study shows that circulating blood GlycA is a biomarker of early COPD pathology.
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