From comorbidities of chronic obstructive pulmonary disease to identification of shared molecular mechanisms by data integration

Spanish COPD Guideline (GesEPOC) Update: Comorbidities, Self-Management and Palliative Care

The current health care models described in GesEPOC indicate the best way to make a correct diagnosis, the categorization of patients, the appropriate selection of the therapeutic strategy and the management and prevention of exacerbations. In addition, COPD involves several aspects that are crucial in an integrated approach to the health care of these patients. The evaluation of comorbidities in COPD patients represents a healthcare challenge. As part of a comprehensive assessment, the presence of comorbidities related to the clinical presentation, to some diagnostic technique or to some COPD-related treatments should be studied. Likewise, interventions on healthy lifestyle habits, adherence to complex treatments, developing skills to recognize the signs and symptoms of exacerbation, knowing what to do to prevent them and treat them within the framework of a self-management plan are also necessary. Finally, palliative care is one of the pillars in the comprehensive treatment of the COPD patient, seeking to prevent or treat the symptoms of a disease, the side effects of treatment, and the physical, psychological and social problems of patients and their caregivers. Therefore, the main objective of this palliative care is not to prolong life expectancy, but to improve its quality. This chapter of GesEPOC 2021 presents an update on the most important comorbidities, self-management strategies, and palliative care in COPD, and includes a recommendation on the use of opioids for the treatment of refractory dyspnea in COPD.

Characterisation, identification, clustering, and classification of disease

The importance of quantifying the distribution and determinants of multimorbidity has prompted novel data-driven classifications of disease. Applications have included improved statistical power and refined prognoses for a range of respiratory, infectious, autoimmune, and neurological diseases, with studies using molecular information, age of disease incidence, and sequences of disease onset ("disease trajectories") to classify disease clusters. Here we consider whether easily measured risk factors such as height and BMI can effectively characterise diseases in UK Biobank data, combining established statistical methods in new but rigorous ways to provide clinically relevant comparisons and clusters of disease. Over 400 common diseases were selected for analysis using clinical and epidemiological criteria, and conventional proportional hazards models were used to estimate associations with 12 established risk factors. Several diseases had strongly sex-dependent associations of disease risk with BMI. Importantly, a large proportion of diseases affecting both sexes could be identified by their risk factors, and equivalent diseases tended to cluster adjacently. These included 10 diseases presently classified as "Symptoms, signs, and abnormal clinical and laboratory findings, not elsewhere classified". Many clusters are associated with a shared, known pathogenesis, others suggest likely but presently unconfirmed causes. The specificity of associations and shared pathogenesis of many clustered diseases provide a new perspective on the interactions between biological pathways, risk factors, and patterns of disease such as multimorbidity.

The Potential Roles of Exosomes in Chronic Obstructive Pulmonary Disease

Currently, chronic obstructive pulmonary disease (COPD) is one of the most common chronic lung diseases. Chronic obstructive pulmonary disease is characterized by progressive loss of lung function due to chronic inflammatory responses in the lungs caused by repeated exposure to harmful environmental stimuli. Chronic obstructive pulmonary disease is a persistent disease, with an estimated 384 million people worldwide living with COPD. It is listed as the third leading cause of death. Exosomes contain various components, such as lipids, microRNAs (miRNAs), long non-coding RNAs(lncRNAs), and proteins. They are essential mediators of intercellular communication and can regulate the biological properties of target cells. With the deepening of exosome research, it is found that exosomes are strictly related to the occurrence and development of COPD. Therefore, this review aims to highlight the unique role of immune-cell-derived exosomes in disease through complex interactions and their potentials as potential biomarkers new types of COPD.

Understanding allergic multimorbidity within the non-eosinophilic interactome

BACKGROUND

The mechanisms explaining multimorbidity between asthma, dermatitis and rhinitis (allergic multimorbidity) are not well known. We investigated these mechanisms and their specificity in distinct cell types by means of an interactome-based analysis of expression data.

METHODS

Genes associated to the diseases were identified using data mining approaches, and their multimorbidity mechanisms in distinct cell types were characterized by means of an in silico analysis of the topology of the human interactome.

RESULTS

We characterized specific pathomechanisms for multimorbidities between asthma, dermatitis and rhinitis for distinct emergent non-eosinophilic cell types. We observed differential roles for cytokine signaling, TLR-mediated signaling and metabolic pathways for multimorbidities across distinct cell types. Furthermore, we also identified individual genes potentially associated to multimorbidity mechanisms.

CONCLUSIONS

Our results support the existence of differentiated multimorbidity mechanisms between asthma, dermatitis and rhinitis at cell type level, as well as mechanisms common to distinct cell types. These results will help understanding the biology underlying allergic multimorbidity, assisting in the design of new clinical studies.

Disease networks identify specific conditions and pleiotropy influencing multimorbidity in the general population

Multimorbidity is an emerging topic in public health policy because of its increasing prevalence and socio-economic impact. However, the age- and gender-dependent trends of disease associations at fine resolution, and the underlying genetic factors, remain incompletely understood. Here, by analyzing disease networks from electronic medical records of primary health care, we identify key conditions and shared genetic factors influencing multimorbidity. Three types of diseases are outlined: "central", which include chronic and non-chronic conditions, have higher cumulative risks of disease associations; "community roots" have lower cumulative risks, but inform on continuing clustered disease associations with age; and "seeds of bursts", which most are chronic, reveal outbreaks of disease associations leading to multimorbidity. The diseases with a major impact on multimorbidity are caused by genes that occupy central positions in the network of human disease genes. Alteration of lipid metabolism connects breast cancer, diabetic neuropathy and nutritional anemia. Evaluation of key disease associations by a genome-wide association study identifies shared genetic factors and further supports causal commonalities between nervous system diseases and nutritional anemias. This study also reveals many shared genetic signals with other diseases. Collectively, our results depict novel population-based multimorbidity patterns, identify key diseases within them, and highlight pleiotropy influencing multimorbidity.

miRNA-206 regulates human pulmonary microvascular endothelial cell apoptosis via targeting in chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is a leading cause of death due to tis high morbidity and mortality. microRNAs have emerged as new biomarkers for the prognosis and diagnosis of patients with COPD. In this study, we aimed to investigate the expression of microRNA-206 (miR-206) in lung tissues from COPD patients and to explore the regulatory role of miR-206 in the human pulmonary microvascular endothelial cells (HPMECs). Our results showed that cigarette smoke extract (CSE) promoted cell apoptosis, increased caspase-3 activity, and upregulated the expression of miR-206 in HPMECs, which was significantly reversed by the miR-206 knockdown. Transfection with miR-206 mimics led to cell apoptosis and was closely related to changes in the protein expression levels of caspase-3, caspase-9, and Bcl-2 in HPMECs. Further bioinformatics prediction analysis revealed that the 3'-untranslated region (3'UTR) of Notch3 and vascular endothelial growth factor-A (VEGFA) harbored miR-206-binding sites, and overexpression of miR-206 repressed the luciferase activity of the vectors containing Notch3 and VEGFA 3'UTR. Overexpression of either Notch3 or VEGFA attenuated miR-206-induced cell apoptosis in HPMECs. More importantly, miR-206 expression was upregulated in the lung tissues from COPD patients and was positively corrected with forced expiratory volume 1% predicted in COPD patients, while Notch3 and VEGFA mRNA levels were downregulated and were negatively correlated with the expression level of miR-206 in the lung tissues from COPD patients. In conclusion, our results showed that miR-206 was upregulated in COPD patients and CSE-treated HPMECs, promoted cell apoptosis via directly targeting Notch3 and VEGFA in HPMECs.

An integrative approach to develop computational pipeline for drug-target interaction network analysis

Understanding the general principles governing the functioning of biological networks is a major challenge of the current era. Functionality of biological networks can be observed from drug and target interaction perspective. All possible modes of operations of biological networks are confined by the interaction analysis. Several of the existing approaches in this direction, however, are data-driven and thus lack potential to be generalized and extrapolated to different species. In this paper, we demonstrate a systems pharmacology pipeline and discuss how the network theory, along with gene ontology (GO) analysis, co-expression analysis, module re-construction, pathway mapping and structure level analysis can be used to decipher important properties of biological networks with the aim to propose lead molecule for the therapeutic interventions of various diseases.

Age density patterns in patients medical conditions: A clustering approach

This paper presents a data analysis framework to uncover relationships between health conditions, age and sex for a large population of patients. We study a massive heterogeneous sample of 1.7 million patients in Brazil, containing 47 million of health records with detailed medical conditions for visits to medical facilities for a period of 17 months. The findings suggest that medical conditions can be grouped into clusters that share very distinctive densities in the ages of the patients. For each cluster, we further present the ICD-10 chapters within it. Finally, we relate the findings to comorbidity networks, uncovering the relation of the discovered clusters of age densities to comorbidity networks literature.

Age and sex of a patient can be directly related to susceptibilities to certain medical conditions. We present a method to generate clusters of human phenotype, based on the age of the population. This method helps extract knowledge on age and sex from the data. The age and sex correlations with disease conditions can help in a task of predicting the susceptibility of incoming patients to conditions.

Risk and temporal order of disease diagnosis of comorbidities in patients with COPD: a population health perspective

Introduction

Comorbidities in patients with chronic obstructive pulmonary disease (COPD) generate a major burden on healthcare. Identification of cost-effective strategies aiming at preventing and enhancing management of comorbid conditions in patients with COPD requires deeper knowledge on epidemiological patterns and on shared biological pathways explaining co-occurrence of diseases.

Methods

The study assesses the co-occurrence of several chronic conditions in patients with COPD using two different datasets: Catalan Healthcare Surveillance System (CHSS) (ES, 1.4 million registries) and Medicare (USA, 13 million registries). Temporal order of disease diagnosis was analysed in the CHSS dataset.

Results

The results demonstrate higher prevalence of most of the diseases, as comorbid conditions, in elderly (>65) patients with COPD compared with non-COPD subjects, an effect observed in both CHSS and Medicare datasets. Analysis of temporal order of disease diagnosis showed that comorbid conditions in elderly patients with COPD tend to appear after the diagnosis of the obstructive disease, rather than before it.

Conclusion

The results provide a population health perspective of the comorbidity challenge in patients with COPD, indicating the increased risk of developing comorbid conditions in these patients. The research reinforces the need for novel approaches in the prevention and management of comorbidities in patients with COPD to effectively reduce the overall burden of the disease on these patients.

Population-based analysis of patients with COPD in Catalonia: a cohort study with implications for clinical management

BACKGROUND

Clinical management of patients with chronic obstructive pulmonary disease (COPD) shows potential for improvement provided that patients' heterogeneities are better understood. The study addresses the impact of comorbidities and its role in health risk assessment.

OBJECTIVE

To explore the potential of health registry information to enhance clinical risk assessment and stratification.

DESIGN

Fixed cohort study including all registered patients with COPD in Catalonia (Spain) (7.5 million citizens) at 31 December 2014 with 1-year (2015) follow-up.

METHODS

A total of 264 830 patients with COPD diagnosis, based on the International Classification of Diseases (Ninth Revision) coding, were assessed. Performance of multiple logistic regression models for the six main dependent variables of the study: mortality, hospitalisations (patients with one or more admissions; all cases and COPD-related), multiple hospitalisations (patients with at least two admissions; all causes and COPD-related) and users with high healthcare costs. Neither clinical nor forced spirometry data were available.

RESULTS

Multimorbidity, assessed with the adjusted morbidity grouper, was the covariate with the highest impact in the predictive models, which in turn showed high performance measured by the C-statistics: (1) mortality (0.83), (2 and 3) hospitalisations (all causes: 0.77; COPD-related: 0.81), (4 and 5) multiple hospitalisations (all causes: 0.80; COPD-related: 0.87) and (6) users with high healthcare costs (0.76). Fifteen per cent of individuals with highest healthcare costs to year ratio represented 59% of the overall costs of patients with COPD.

CONCLUSIONS

The results stress the impact of assessing multimorbidity with the adjusted morbidity grouper on considered health indicators, which has implications for enhanced COPD staging and clinical management.

TRIAL REGISTRATION NUMBER

NCT02956395.

Chronic Obstructive Pulmonary Disease (COPD) as a disease of early aging: Evidence from the EpiChron Cohort

BACKGROUND

Aging is an important risk factor for most chronic diseases. Patients with COPD develop more comorbidities than non-COPD subjects. We hypothesized that the development of comorbidities characteristically affecting the elderly occur at an earlier age in subjects with the diagnosis of COPD.

METHODS AND FINDINGS

We included all subjects carrying the diagnosis of COPD (n = 27,617), and a similar number of age and sex matched individuals without the diagnosis, extracted from the 727,241 records of individuals 40 years and older included in the EpiChron Cohort (Aragon, Spain). We compared the cumulative number of comorbidities, their prevalence and the mortality risk between both groups. Using network analysis, we explored the connectivity between comorbidities and the most influential comorbidities in both groups. We divided the groups into 5 incremental age categories and compared their comorbidity networks. We then selected those comorbidities known to affect primarily the elderly and compared their prevalence across the 5 age groups. In addition, we replicated the analysis in the smokers' subgroup to correct for the confounding effect of cigarette smoking. Subjects with COPD had more comorbidities and died at a younger age compared to controls. Comparison of both cohorts across 5 incremental age groups showed that the number of comorbidities, the prevalence of diseases characteristic of aging and network's density for the COPD group aged 56-65 were similar to those of non-COPD 15 to 20 years older. The findings persisted after adjusting for smoking.

CONCLUSION

Multimorbidity increases with age but in patients carrying the diagnosis of COPD, these comorbidities are seen at an earlier age.

What does endotyping mean for treatment in chronic obstructive pulmonary disease?

Chronic obstructive pulmonary disease (COPD) is a complex and heterogeneous disease, both at the clinical and biological level. However, COPD is still diagnosed and treated according to simple clinical measures (level of airflow limitation, symptoms, and frequency of previous exacerbations). To address this clinical and biological complexity and to move towards precision medicine in COPD, we need to integrate (bioinformatics) and interpret (clinical science) the vast amount of high-throughput information that existing technology provides (systems biology and network medicine) so diagnosis, stratification, and treatment of patients with COPD can occur on the basis of their pathobiological mechanism (ie, endotypes). Therefore, this Series paper discusses a possible new taxonomy of COPD, the role of endotypes and associated biomarkers and phenotypes, the gaps (and opportunities) in existing knowledge of COPD pathobiology, how systems biology and network medicine can improve understanding of the disease and help to identify relevant endotypes and their specific biomarkers, and how endotypes and their biomarkers can improve the precision, effectiveness, and safety of the treatment of patients with COPD.

Metabolic Disorder in Chronic Obstructive Pulmonary Disease (COPD) Patients: Towards a Personalized Approach Using Marine Drug Derivatives

Metabolic disorder has been frequently observed in chronic obstructive pulmonary disease (COPD) patients. However, the exact correlation between obesity, which is a complex metabolic disorder, and COPD remains controversial. The current study summarizes a variety of drugs from marine sources that have anti-obesity effects and proposed potential mechanisms by which lung function can be modulated with the anti-obesity activity. Considering the similar mechanism, such as inflammation, shared between obesity and COPD, the study suggests that marine derivatives that act on the adipose tissues to reduce inflammation may provide beneficial therapeutic effects in COPD subjects with high body mass index (BMI).