Systems Biology and Clinical Practice in Respiratory Medicine. The Twain Shall Meet

The Constrained Disorder Principle Accounts for the Variability That Characterizes Breathing: A Method for Treating Chronic Respiratory Diseases and Improving Mechanical Ventilation

Variability characterizes breathing, cellular respiration, and the underlying quantum effects. Variability serves as a mechanism for coping with changing environments; however, this hypothesis does not explain why many of the variable phenomena of respiration manifest randomness. According to the constrained disorder principle (CDP), living organisms are defined by their inherent disorder bounded by variable boundaries. The present paper describes the mechanisms of breathing and cellular respiration, focusing on their inherent variability. It defines how the CDP accounts for the variability and randomness in breathing and respiration. It also provides a scheme for the potential role of respiration variability in the energy balance in biological systems. The paper describes the option of using CDP-based artificial intelligence platforms to augment the respiratory process's efficiency, correct malfunctions, and treat disorders associated with the respiratory system.

Gene signatures in U-BIOPRED severe asthma for molecular phenotyping and precision medicine: time for clinical use

INTRODUCTION

The use and generation of gene signatures have been established as a method to define molecular endotypes in complex diseases such as severe asthma. Bioinformatic approaches have now been applied to large omics datasets to define the various co-existing inflammatory and cellular functional pathways driving or characterizing a particular molecular endotype.

AREAS COVERED

Molecular phenotypes and endotypes of Type 2 inflammatory pathways and also of non-Type 2 inflammatory pathways, such as IL-6 trans-signaling, IL-17 activation, and IL-22 activation, have been defined in the Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes dataset. There has also been the identification of the role of mast cell activation and of macrophage dysfunction in various phenotypes of severe asthma.

EXPERT OPINION

Phenotyping on the basis of clinical treatable traits is not sufficient for understanding of mechanisms driving the disease in severe asthma. It is time to consider whether certain patients with severe asthma, such as those non-responsive to current therapies, including Type 2 biologics, would be better served using an approach of molecular endotyping using gene signatures for management purposes rather than the current sole reliance on blood eosinophil counts or exhaled nitric oxide measurements.

New insights into the pathophysiology and therapeutic targets of asthma and comorbid chronic rhinosinusitis with or without nasal polyposis

Asthma and chronic rhinosinusitis with nasal polyps (CRSwNP) or without (CRSsNP) are chronic respiratory diseases. These two disorders often co-exist based on common anatomical, immunological, histopathological, and pathophysiological basis. Usually, asthma with comorbid CRSwNP is driven by type 2 (T2) inflammation which predisposes to more severe, often intractable, disease. In the past two decades, innovative technologies and detection techniques in combination with newly introduced targeted therapies helped shape our understanding of the immunological pathways underlying inflammatory airway diseases and to further identify several distinct clinical and inflammatory subsets to enhance the development of more effective personalized treatments. Presently, a number of targeted biologics has shown clinical efficacy in patients with refractory T2 airway inflammation, including anti-IgE (omalizumab), anti-IL-5 (mepolizumab, reslizumab)/anti-IL5R (benralizumab), anti-IL-4R-α (anti-IL-4/IL-13, dupilumab), and anti-TSLP (tezepelumab). In non-type-2 endotypes, no targeted biologics have consistently shown clinical efficacy so far. Presently, multiple therapeutical targets are being explored including cytokines, membrane molecules and intracellular signalling pathways to further expand current treatment options for severe asthma with and without comorbid CRSwNP. In this review, we discuss existing biologics, those under development and share some views on new horizons.

The protective effect of inhaled corticosteroid on lung inflammation and breathing pattern complexity in a rat model of asthma

Asthma is a heterogeneous disease in which the complexity of the breathing pattern reduces as the severity of the disease increases. Since the pathophysiological basis of reduced breathing pattern complexity in asthma is unclear, in this study, we investigated the effect of reducing inflammation using an inhaled corticosteroid (fluticasone propionate) on the breathing pattern of a rat model of asthma. Detrended fluctuation analysis, sample entropy, and cross-sample entropy analysis of both inter-breath interval and respiratory volume time series showed that early treatment with inhaled corticosteroids not only diminishes lung inflammation and airway hyper-responsiveness, but also has a protective effect against the reduction of breathing pattern complexity due to asthma. However, late treatment had a partial effect on asthma-induced respiratory pattern changes. Since inflammation is a key factor in shifting breathing dynamics away from normal fluctuations, these findings further emphasize the importance of early treatment of asthma with corticosteroids.

Enabling health potential: exploring nonlinear and complex results of osteopathic manual medicine through complex systems theory

Osteopathic medicine is a holistic, patient-specific approach. Explaining the impact of osteopathic manipulative medicine (OMM) has been problematic because many of its effects are nonlinear. Complex systems theory (CST) is explored as a mechanism of understanding the interplay of the body's anatomy and physiology, an illness process, and the effects of OMM. Tensegrity is discussed as an example of an emergent property of the body's systems that affects not only biomechanics but also pathophysiology. Previous explanations of osteopathic philosophy are reviewed. The Host + Disease=Illness paradigm is a way to think through the impact of host and disease factors on an illness state, and how targeted interventions may affect the illness. The Osteopathic 5 Models are another way to view the body's complexity. The area of greatest restriction (AGR) screen can be understood to direct OMM in a way that respects complexity and enables asymmetric and nonlocal results to realize health potential. The impact of this framework is in coherently explaining the impact of osteopathic philosophy and OMM and exploring new approaches to research.

Variability of clinically measured lung clearance index in children with cystic fibrosis

RATIONALE

The lung clearance index (LCI) is increasingly being used in the clinical surveillance of patients with cystic fibrosis (CF). However, there are limited data on long-term variability and physiologically relevant changes in LCI during routine clinical surveillance.

OBJECTIVES

To evaluate the long-term variability of LCI and propose a threshold for a physiologically relevant change.

METHODS

In children aged 4-18 years with CF, LCI was measured every 3 months as part of routine clinical surveillance during 2011-2020 in two centers. The variability of LCI during periods of clinical stability was assessed using mixed-effects models and was used to identify thresholds for physiologically relevant changes.

RESULTS

Repeated LCI measurements of acceptable quality (N = 858) were available in 100 patients with CF; for 74 patients, 399 visits at clinical stability were available. The variability of repeated LCI measurements over time expressed as the coefficient of variation (CV%) was 7.4%. The upper limit of normal (ULN) for relative changes in LCI between visits was 19%.

CONCLUSION

We report the variability of LCI in children and adolescents with CF during routine clinical surveillance. According to our data, a change in LCI beyond 19% may be considered physiologically relevant. These findings will help guide clinical decisions according to LCI changes.

Evaluation of the effects of dexamethasone in modulating breathing pattern decomplexification in rats with 2-chloroethyl ethyl sulfide-induced lung injury

"Background and Objectives: Sulfur mustard is a functional alkylating chemical warfare agent that gives rise to appalling lung injury. In people with pulmonary diseases, including asthma, the complication of respirational dynamics is reduced. However, the complexity of breathing patterns in lung injury caused by chemical agents is not clear. In the current study, the outcome of 2-chloroethyl ethyl sulfide (CEES), and mustard analogue, upon breathing pattern of rats without or with treatment were reviewed. Methods: The interbeat interval (IBI) and respiratory volume (RV) data have been acquired from spontaneous respiration rats with lung injury by CEES using a whole-body plethysmograph. We calculated mean and coefficient of variation, alpha exponent derived from detrended fluctuation analysis (DFA), and sample entropy of IBI and RV. Finding: Entropy examination of respiratory variation displayed reduced inconsistency (less complication) in the breathing pattern of this rat model of lung injury. The mustard analogue also led to increased lung inflammation in damaged rats. However, treatment by NAC and dexamethasone had a compelling impact on the complication of the breathing rhythm and lung inflammation of rats with lung injury. Conclusion: Our findings show that inflammation could be the possible origin of respiratory dynamics shifting apart from the normal variation in CEES-induced lung injury"

Temporal variations in the pattern of breathing: techniques, sources, and applications to translational sciences

The breathing process possesses a complex variability caused in part by the respiratory central pattern generator in the brainstem; however, it also arises from chemical and mechanical feedback control loops, network reorganization and network sharing with nonrespiratory motor acts, as well as inputs from cortical and subcortical systems. The notion that respiratory fluctuations contain hidden information has prompted scientists to decipher respiratory signals to better understand the fundamental mechanisms of respiratory pattern generation, interactions with emotion, influences on the cortical neuronal networks associated with cognition, and changes in variability in healthy and disease-carrying individuals. Respiration can be used to express and control emotion. Furthermore, respiration appears to organize brain-wide network oscillations via cross-frequency coupling, optimizing cognitive performance. With the aid of information theory-based techniques and machine learning, the hidden information can be translated into a form usable in clinical practice for diagnosis, emotion recognition, and mental conditioning.

Novel Methods of Measuring Adherence Patterns Reveal Adherence Phenotypes with Distinct Asthma Outcomes

RATIONALE

Poor adherence with asthma controller medication contributes to worse symptom control and increased exacerbation risk. Adherence is often expressed as the mean proportion of prescribed doses taken over a period of 6-12 months. New metrics may capture individual day-to-day variability patterns linked with distinct clinical outcomes.

OBJECTIVES

To test the hypotheses that novel time- and dose-based adherence variability metrics offer independent value to mean adherence in identifying distinct adherence patterns, that are associated with symptom control (Asthma Control Test [ACT] score) and exacerbation risk, using electronically-recorded medication data from a 6-month cluster randomized trial examining the effect of inhaler reminders on adherence.

METHODS

Adherence metrics were calculated from the first two months (months 0-2) of the study period. In addition to mean adherence (%prescribed puffs/day taken, PTmean), we examined novel metrics including: time adherence area-under-curve (T-AUC), reflecting cumulative gaps in adherence over time, entropy (H), reflecting disorder in the ways in which a patient changed their medication dose adherence from day to day, and standard deviation of the %prescribed puffs/day taken (PTSD). Dominant metrics identified from factor analysis were included in hierarchical clustering analysis. We compared the resultant clusters in terms of outcomes over months 2-6, and exacerbation risk over the entire study period.

RESULTS

Two factors explained >65% of the total variance in adherence, primarily driven by T-AUC and H. Two main patient clusters based on their adherence metrics were identified: Cluster 1 ("high time adherence", n=75) had better T-AUC, i.e. fewer gaps between medication-taking days, than Cluster 2 ("low time adherence", n=23). Though both clusters had similar symptom control at 2 months, Cluster 1 showed less subsequent decline in ACT over months 2-6 (median(IQR) change in ACT score: 1(-1, 4) vs -2(-3.75,0.75); p=0.012), and had better symptom control at 6 months (ACT score: 20(17, 23) vs 17 (15, 20); p=0.034). There were no significant differences between the clusters in terms of proportion of exacerbators or time to exacerbation.

CONCLUSIONS

Novel metrics showed that low time adherence was associated with greater risk of decline in asthma symptom control. Adherence patterns may exhibit 'memory' relevant to future clinical status, warranting validation in a larger dataset.

Lung function fluctuation patterns unveil asthma and COPD phenotypes unrelated to type 2 inflammation

BACKGROUND

In all chronic airway diseases, the dynamics of airway function are influenced by underlying airway inflammation and bronchial hyperresponsiveness along with limitations in reversibility owing to airway and lung remodeling as well as mucous plugging. The relative contribution of each component translates into specific clinical patterns of symptoms, quality of life, exacerbation risk, and treatment success.

OBJECTIVE

We aimed to evaluate whether subgrouping of patients with obstructive airway diseases according to patterns of fluctuation in lung function allows identification of specific phenotypes with distinct clinical characteristics.

METHODS

We applied the novel method of fluctuation-based clustering (FBC) to twice-daily FEV₁ measurements recorded over a 1-year period in a mixed group of 134 adults with mild-to-moderate asthma, severe asthma, or chronic obstructive pulmonary disease from the European BIOAIR cohort.

RESULTS

Independently of clinical diagnosis, FBC divided patients into 4 fluctuation-based clusters with progressively increasing alterations in lung function that corresponded to patterns of increasing clinical severity, risk of exacerbation, and lower quality of life. Clusters of patients with airway disease with significantly elevated levels of biomarkers relating to remodeling (osteonectin) and cellular senescence (plasminogen activator inhibitor-1), accompanied by a loss of airway reversibility, pulmonary hyperinflation, and loss of diffusion capacity, were identified. The 4 clusters generated were stable over time and revealed no differences in levels of markers of type 2 inflammation (blood eosinophils and periostin).

CONCLUSION

FBC-based phenotyping provides another level of information that is complementary to clinical diagnosis and unrelated to eosinophilic inflammation, which could identify patients who may benefit from specific treatment strategies or closer monitoring.

Precision medicine and treatable traits in chronic airway diseases - where do we stand?

PURPOSE OF REVIEW

To provide an update on the implementation of precision medicine, based on treatable traits and mechanisms, in the daily clinical management of chronic airways diseases.

RECENT FINDINGS

Recent insights into the complex and heterogeneous nature of chronic airway diseases including chronic obstructive pulmonary disease (COPD) and asthma identified several clinical and inflammatory phenotypes. This shifted the management focus of these diseases away from the prototypic disease labels and paved the way for developing novel targeted therapies.The concept of precision medicine aims to link the right patient to the right treatment, while minimizing the risk of adverse effects. Several treatable features ('treatable traits') have now been identified for these chronic airway diseases, including pulmonary, extra-pulmonary, and psychological/lifestyle/environmental traits. As the next step, innovative detection techniques should clarify underlying mechanisms and molecular pathways of these treatable traits and novel reliable point-of-care (composite) biomarkers to help predict responders to targeted therapies must be developed.

SUMMARY

Precision medicine links the right patient to the right treatment. Identification of treatable traits in asthma and COPD will help optimize the treatment approach in these heterogeneous diseases. Furthermore, in-depth identification of underlying molecular pathways and reliable biomarkers in chronic airways diseases to guide targeted treatment in individual patients is in progress.

An expert review on breaking barriers in severe asthma in Brazil: Time to act

Currently, Brazil lacks a national asthma management program and is burdened with nearly 200,000 hospitalizations due to the disease per year and approximately 5 deaths per day. The purpose of this article was to analyze the current issues surrounding severe asthma in Brazil, as the status of diagnosis and treatment is largely unknown, and to provide feasible recommendations to elicit imminent action. A panel of Brazilian medical experts in the field of severe asthma was provided with a series of relevant questions to address prior to a multi-day conference. Within this conference, each narrative was discussed and edited by the entire group. Through numerous rounds of discussion consensus was achieved. In order to overcome barriers to adequate asthma treatment, this panel recommends specific initiatives that can be implemented in the short-term to decrease the burden of severe asthma in Brazil. With increasing healthcare costs and limited resources globally, there is an opportunity to implement these recommendations in other countries in order to achieve adequate asthma care. Severe asthma is a heterogeneous and complex disease with various phenotypes that requires strict attention for diagnosis and management. Although this disease affects only a small proportion of the population with asthma, it poses a great burden to healthcare systems. Thus, barriers to diagnosis, treatment, and management should be overcome as quickly and efficiently as possible.

Combined forced oscillation and fractional-order modeling in patients with work-related asthma: a case-control study analyzing respiratory biomechanics and diagnostic accuracy

BACKGROUND

Fractional-order (FrOr) models have a high potential to improve pulmonary science. These models could be useful for biomechanical studies and diagnostic purposes, offering accurate models with an improved ability to describe nature. This paper evaluates the performance of the Forced Oscillation (FO) associated with integer (InOr) and FrOr models in the analysis of respiratory alterations in work-related asthma (WRA).

METHODS

Sixty-two individuals were evaluated: 31 healthy and 31 with WRA with mild obstruction. Patients were analyzed pre- and post-bronchodilation. The diagnostic accuracy was evaluated using the area under the receiver operating characteristic curve (AUC). To evaluate how well do the studied models correspond to observed data, we analyzed the mean square root of the sum (MSEt) and the relative distance (Rd) of the estimated model values to the measured resistance and reactance measured values.

RESULTS AND DISCUSSION

Initially, the use of InOr and FrOr models increased our understanding of the WRA physiopathology, showing increased peripheral resistance, damping, and hysteresivity. The FrOr model (AUC = 0.970) outperformed standard FO (AUC = 0.929), as well as InOr modeling (AUC = 0.838) in the diagnosis of respiratory changes, achieving high accuracy. FrOr improved the curve fitting (MSEt = 0.156 ± 0.340; Rd = 3.026 ± 1.072) in comparison with the InOr model (MSEt = 0.367 ± 0.991; Rd = 3.363 ± 1.098). Finally, we demonstrated that bronchodilator use increased dynamic compliance, as well as reduced damping and peripheral resistance.

CONCLUSIONS

Taken together, these results show clear evidence of the utility of FO associated with fractional-order modeling in patients with WRA, improving our knowledge of the biomechanical abnormalities and the diagnostic accuracy in this disease.

Day-to-day variability of forced oscillatory mechanics for early detection of acute exacerbations in COPD

BACKGROUND

Telemonitoring trials for early detection of acute exacerbations of chronic obstructive pulmonary disease (AECOPD) have provided mixed results. Day-to-day variations in lung function measured by the forced oscillation technique (FOT) may yield greater insight. We evaluated the clinical utility of home telemonitoring of variability in FOT measures in terms of 1) the relationship with symptoms and quality of life (QoL); and 2) the timing of variability of FOT measures and symptom changes prior to AECOPD.

METHODS

Daily FOT parameters at 5 Hz (resistance (R) and reactance (X); Resmon Pro Diary, Restech Srl, Milan, Italy), daily symptoms (COPD Assessment Test (CAT)) and 4-weekly QoL data (St George's Respiratory Questionnaire (SGRQ)) were recorded over 8-9 months from chronic obstructive pulmonary disease (COPD) patients. Variability of R and X was calculated as the standard deviation (sd) over 7-day running windows and we also examined the effect of varying window size. The relationship of FOT versus CAT and SGRQ was assessed using linear mixed modelling, daily changes in FOT variability and CAT prior to AECOPD using one-way repeated measures ANOVA.

RESULTS

Fifteen participants with a mean±sd age of 69±10 years and a % predicted forced expiratory volume in 1 s (FEV₁) of 39±10% had a median (interquartile range (IQR)) adherence of 95.4% (79.0-98.8%). Variability of the inspiratory component of X (indicated by the standard deviation of inspiratory reactance (SDX_insp)) related to CAT and weakly to SGRQ (fixed effect estimates 1.57, 95% CI 0.65-2.49 (p=0.001) and 4.41, 95% CI -0.06 to 8.89 (p=0.05), respectively). SDX_insp changed significantly on the same day as CAT (1 day before AECOPD, both p=0.02) and earlier when using shorter running windows (3 days before AECOPD, p=0.01; accuracy=0.72 for 5-day windows).

CONCLUSIONS

SDX_insp from FOT telemonitoring reflects COPD symptoms and may be a sensitive biomarker for early detection of AECOPD.

Fluctuation-based clustering reveals phenotypes of patients with different asthma severity

Serial peak expiratory flow (PEF) measurements can identify phenotypes in severe adult asthma, enabling more targeted treatment. The feasibility of this approach in children has not been investigated.

Overall, 105 children (67% male, median age 12.4 years) with a range of asthma severities were recruited and followed up over a median of 92 days. PEF was measured twice daily. Fluctuation-based clustering (FBC) was used to identify clusters based on PEF fluctuations. The patients’ clinical characteristics were compared between clusters.

Three PEF clusters were identified in 44 children with sufficient measurements. Cluster 1 (27% of patients: n=12) had impaired spirometry (mean forced expiratory volume in 1 s (FEV₁) 71% predicted), significantly higher exhaled nitric oxide (≥35 ppb) and uncontrolled asthma (asthma control test (ACT) score <20 of 25).

Cluster 2 (45%: n=20) had normal spirometry, the highest proportion of difficult asthma and significantly more patients on a high dose of inhaled corticosteroids (≥800 µg budesonide).

Cluster 3 (27%: n=12) had mean FEV₁ 92% predicted, the highest proportion of patients with no bronchodilator reversibility, a low ICS dose (≤400 µg budesonide), and controlled asthma (ACT scores ≥20 of 25).

Three clinically relevant paediatric asthma clusters were identified using FBC analysis on PEF measurements, which could improve telemonitoring diagnostics. The method remains robust even when 80% of measurements were removed. Further research will determine clinical applicability.

Fluctuation-based clustering is a robust method that identifies clinically relevant subgroups of patients with asthma to refine referral strategies to a tertiary centrehttps://bit.ly/35g1ldb

Reduced expiratory variability index (EVI) is associated with controller medication withdrawal and symptoms in wheezy children aged 1-5 years

BACKGROUND

Lung function testing is an essential part of diagnostic workup and monitoring of asthma, but young children are lacking easy, routine testing methods. However, recent discoveries show reduced tidal breathing variability measured using impedance pneumography (IP) at home during sleep as a sign of airway obstruction. In this study, we assessed (a) the discriminative capacity of expiratory variability index (EVI) between healthy controls and young children with recurrent wheeze on-and-off controller medication, (b) association between EVI and parentally perceived obstructive symptoms (need for bronchodilator) and (c) measurement success rate.

METHODS

We included 68 patients (aged 1.0-5.6) and 40 healthy controls (aged 1.0-5.9 years). The patients were prescribed a three-month inhaled corticosteroid (ICS) treatment due to recurrent obstructive bronchitis. We measured EVI using IP at home at the end of the treatment (0W) and 2 (2W) and 4 (4W) weeks after ICS withdrawal.

RESULTS

EVI was higher in controls than in patients, and significant within-patient reduction occurred at 4W as compared to 2W or 0W. Area under curve of the ROC curve (controls vs all patients) at 4W was 0.78 (95% CI 0.70-0.85). Children who were administered bronchodilator by parental decision had lower EVI than those without bronchodilator need at 4W, but not at 0W or 2W. Patients with parent-reported airway infection, but no bronchodilator need, had normal EVI. Measurement success rate was 94%.

CONCLUSION

EVI was lower in patients than in controls and it reduced further after controller medication withdrawal, especially in the presence of parentally perceived wheeze symptoms. This technique shows a significant potential for routine lung function testing of wheezy young children.

The need for physiological phenotyping to develop new drugs for airways disease

Asthma and COPD make up the majority of obstructive airways diseases (OADs), which affects ∼11 % of the population. The main drugs used to treat OADs have not changed in the past five decades, with advancements mainly comprising variations on existing treatments. The recent biologics are beneficial to only specific subsets of patients. Part of this may lie in our inability to adequately characterise the tremendous heterogeneity in every aspect of OAD. The field is currently moving towards the concept of personalised medicine, based on a focus on treatable traits that are objective, measurable and modifiable. We propose extending this concept via the use of emerging clinical tools for comprehensive physiological phenotyping. We describe, based on published data, the evidence for the use of functional imaging, gas washout techniques and oscillometry, as well as potential future applications, to more comprehensively assess and predict treatment response in OADs. In this way, we hope to demonstrate how physiological phenotyping tools will improve the way in which drugs are prescribed, but most importantly, will facilitate development of new drugs for OADs.

Loss of adaptive capacity in asthmatic patients revealed by biomarker fluctuation dynamics after rhinovirus challenge

Asthma is a dynamic disease, in which lung mechanical and inflammatory processes interact in a complex manner, often resulting in exaggerated physiological, in particular, inflammatory responses to exogenous triggers. We hypothesize that this may be explained by respiratory disease-related systems instability and loss of adaptability to changing environmental conditions, manifested in highly fluctuating biomarkers and symptoms. Using time series of inflammatory (eosinophils, neutrophils, FeNO), clinical and lung function biomarkers (PEF, FVC,FEV₁), we estimated this loss of adaptive capacity (AC) during an experimental rhinovirus infection in 24 healthy and asthmatic human volunteers. Loss of AC was estimated by comparing similarities between pre- and post-challenge time series. Unlike healthy participants, the asthmatic’s post-viral-challenge state resembled more other rhinovirus-infected asthmatics than their own pre-viral-challenge state (hypergeometric-test: p=0.029). This reveals loss of AC and supports the concept that in asthma, biological processes underlying inflammatory and physiological responses are unstable, contributing to loss of control.

Precision medicine for the discovery of treatable mechanisms in severe asthma

Although the complex disease of asthma has been defined as being heterogeneous, the extent of its endophenotypes remains unclear. The pharmacological approach to initiating treatment has, until recently, been based on disease control and severity. The introduction of antibody therapies targeting the Type 2 inflammation pathway for patients with severe asthma has resulted in the recognition of an allergic and an eosinophilic phenotype, which are not mutually exclusive. Concomitantly, molecular phenotyping based on a transcriptomic analysis of bronchial epithelial and sputum cells has identified a Type 2 high inflammation cluster characterized by eosinophilia and recurrent exacerbations, as well as Type 2 low clusters linked with IL-6 trans-signalling, interferon pathways, inflammasome activation and mitochondrial oxidative phosphorylation pathways. Systems biology approaches are establishing the links between these pathways or mechanisms, and clinical and physiologic features. Validation of these pathways contributes to defining endotypes and treatable mechanisms. Precision medicine approaches are necessary to link treatable mechanisms with treatable traits and biomarkers derived from clinical, physiologic and inflammatory features of clinical phenotypes. The deep molecular phenotyping of airway samples along with noninvasive biomarkers linked to bioinformatic and machine learning techniques will enable the rapid detection of molecular mechanisms that transgresses beyond the concept of treatable traits.

Integrated lung tissue mechanics one piece at a time: Computational modeling across the scales of biology

The lung is a delicately balanced and highly integrated mechanical system. Lung tissue is continuously exposed to the environment via the air we breathe, making it susceptible to damage. As a consequence, respiratory diseases present a huge burden on society and their prevalence continues to rise. Emergent function is produced not only by the sum of the function of its individual components but also by the complex feedback and interactions occurring across the biological scales - from genes to proteins, cells, tissue and whole organ - and back again. Computational modeling provides the necessary framework for pulling apart and putting back together the pieces of the body and organ systems so that we can fully understand how they function in both health and disease. In this review, we discuss models of lung tissue mechanics spanning from the protein level (the extracellular matrix) through to the level of cells, tissue and whole organ, many of which have been developed in isolation. This is a vital step in the process but to understand the emergent behavior of the lung, we must work towards integrating these component parts and accounting for feedback across the scales, such as mechanotransduction. These interactions will be key to unlocking the mechanisms occurring in disease and in seeking new pharmacological targets and improving personalized healthcare.

Dismantling airway disease with the use of new pulmonary function indices

We are currently limited in our abilities to diagnose, monitor disease status and manage chronic airway disease like asthma and chronic obstructive pulmonary disease (COPD). Conventional lung function measures often poorly reflect patient symptoms or are insensitive to changes, particularly in the small airways where disease may originate or manifest. Novel pulmonary function tests are becoming available which help us better characterise and understand chronic airway disease, and their translation and adoption from the research arena would potentially enable individualised patient care.

In this article, we aim to describe two emerging lung function tests yielding novel pulmonary function indices, the forced oscillation technique (FOT) and multiple breath nitrogen washout (MBNW). With a particular focus on asthma and COPD, this article demonstrates how chronic airway disease mechanisms have been dismantled with the use of the FOT and MBNW. We describe their ability to assess detailed pulmonary mechanics for diagnostic and management purposes including response to bronchodilation and other treatments, relationship with symptoms, evaluation of acute exacerbations and recovery, and telemonitoring. The current limitations of both tests, as well as open questions/directions for further research, are also discussed.

Spirometry is used to diagnose and manage airway disease such as asthma and COPD, but relates poorly to symptoms, lacks sensitivity and is effort dependent. FOT and MBNW are emerging clinical lung function tests that help us dismantle disease mechanisms.http://ow.ly/nM0G30nS6Ct

Respiratory resistance and reactance in adults with sickle cell anemia: Part 2-Fractional-order modeling and a clinical decision support system for the diagnosis of respiratory disorders

BACKGROUND

A better understanding of sickle cell anemia (SCA) and improvements in drug therapy and health policy have contributed to the emergence of a large population of adults living with this disease. The mechanisms by which SCA produces adverse effects on the respiratory system of these patients are largely unknown. Fractional-order (FrOr) models have a high potential to improve pulmonary clinical science and could be useful for diagnostic purposes, offering accurate models with an improved ability to mimic nature. Part 2 of this two-part study examines the changes in respiratory mechanics in patients with SCA using the new perspective of the FrOr models. These results are compared with those obtained in traditional forced oscillation (FOT) parameters, investigated in Part 1 of the present study, complementing this first analysis.

METHODOLOGY/PRINCIPAL FINDINGS

The data consisted of three categories of subjects: controls (n = 23), patients with a normal spirometric exam (n = 21) and those presenting restriction (n = 24). The diagnostic accuracy was evaluated by investigating the area under the receiver operating characteristic curve (AUC). Initially, it was observed that biomechanical changes in SCA included increased values of fractional inertance, as well as damping and hysteresivity (p<0.001). The correlation analysis showed that FrOr parameters are associated with functional exercise capacity (R = -0.57), pulmonary diffusion (R = -0.71), respiratory muscle performance (R = 0.50), pulmonary flows (R = -0.62) and airway obstruction (R = 0.60). Fractional-order modeling showed high diagnostic accuracy in the detection of early respiratory abnormalities (AUC = 0.93), outperforming spirometry (p<0.03) and standard FOT analysis (p<0.01) used in Part 1 of this study. A combination of machine learning methods with fractional-order modeling further improved diagnostic accuracy (AUC = 0.97).

CONCLUSIONS

FrOr modeling improved our knowledge about the biomechanical abnormalities in adults with SCA. Changes in FrOr parameters are associated with functional exercise capacity decline, abnormal pulmonary mechanics and diffusion. FrOr modeling outperformed spirometric and traditional forced oscillation analyses, showing a high diagnostic accuracy in the diagnosis of early respiratory abnormalities that was further improved by an automatic clinical decision support system. This finding suggested the potential utility of this combination to help identify early respiratory changes in patients with SCA.

Systems Biology, Systems Medicine, Systems Pharmacology: The What and The Why

Systems biology is today such a widespread discipline that it becomes difficult to propose a clear definition of what it really is. For some, it remains restricted to the genomic field. For many, it designates the integrated approach or the corpus of computational methods employed to handle the vast amount of biological or medical data and investigate the complexity of the living. Although defining systems biology might be difficult, on the other hand its purpose is clear: systems biology, with its emerging subfields systems medicine and systems pharmacology, clearly aims at making sense of complex observations/experimental and clinical datasets to improve our understanding of diseases and their treatments without putting aside the context in which they appear and develop. In this short review, we aim to specifically focus on these new subfields with the new theoretical tools and approaches that were developed in the context of cancer. Systems pharmacology and medicine now give hope for major improvements in cancer therapy, making personalized medicine closer to reality. As we will see, the current challenge is to be able to improve the clinical practice according to the paradigm shift of systems sciences.

Variable ventilation decreases airway responsiveness and improves ventilation efficiency in a rat model of asthma

The optimal ventilation strategy in patients receiving mechanical ventilation for severe asthma remains unclear. The effect of conventional ventilation (with constant tidal volume and respiratory rate) and variable ventilation (with the same average but variable tidal volume and respiratory rate) on peak airway pressure and airway exacerbation induced by increasing doses of methacholine was compared in a rat model of asthma. The respiratory rate and tidal volume data were obtained from a spontaneously breathing intact rat during immobility using a whole-body plethysmograph. Peak airway pressure and airway responsiveness to cumulative doses of methacholine were significantly affected by ventilation mode and they were lower in variable ventilation group than in the conventional ventilation group. Also, variable ventilation improved oxygen saturation compared to conventional ventilation. Our results indicate that variable ventilation decreases airway responsiveness and enhances ventilation efficiency in a rat model of asthma. We suggest further investigations on beneficial effects of variable ventilation strategy in mechanically ventilated patients with severe asthma.

Exercise ventilatory irregularity can be quantified by approximate entropy to detect breathing pattern disorder

BACKGROUND

Breathing pattern disorder (BPD) is a prevalent cause of exertional dyspnea and yet there is currently no reliable objective measure for its diagnosis. We propose that statistical analysis of ventilatory irregularity, quantified by approximate entropy (ApEn), could be used to detect BPD when applied to cardiopulmonary exercise test (CPET) data. We hypothesised that ApEn of ventilatory variables (tidal volume (V_T), breathing frequency (B_f), minute ventilation (V_E)) would be greater, i.e. more irregular, in patients with BPD than healthy controls.

METHODS

We evaluated ventilatory ApEn in 20 adults (14 female) with exertional dyspnoea, undergoing CPET and independently diagnosed with BPD by a specialist respiratory physiotherapist. Data were compared with 15 age- gender- and BMI-matched controls. ApEn for V_T, B_f and V_E were calculated for an incremental cycle exercise test.

RESULTS

Patients with BPD more frequently rated breathlessness as the reason for exercise limitation and had a lower mean (SD) peak oxygen uptake compared with controls: 80 (18) vs. 124 (27) % predicted (P < 0.001). ApEn was significantly greater for V_T (p = .006) and V_E (p = .002) in BPD than controls. ApEn V_E was inversely related (r² = 0.24, p = .03) to peak oxygen uptake in BPD but not controls. ROC analysis revealed that ApEn V_E > 0.88, conferred a sensitivity and specificity of 70% and 87% respectively, for detection of BPD.

CONCLUSIONS

Non-linear statistical interrogation of CPET-acquired ventilatory data has utility in the detection of BPD. A simple calculation of approximate entropy of ventilation, during an incremental cardiopulmonary exercise test, provides a quantitative method to detect BPD.

Network Analysis to Risk Stratify Patients With Exercise Intolerance

RATIONALE

Current methods assessing clinical risk because of exercise intolerance in patients with cardiopulmonary disease rely on a small subset of traditional variables. Alternative strategies incorporating the spectrum of factors underlying prognosis in at-risk patients may be useful clinically, but are lacking.

OBJECTIVE

Use unbiased analyses to identify variables that correspond to clinical risk in patients with exercise intolerance.

METHODS AND RESULTS

Data from 738 consecutive patients referred for invasive cardiopulmonary exercise testing at a single center (2011-2015) were analyzed retrospectively (derivation cohort). A correlation network of invasive cardiopulmonary exercise testing parameters was assembled using |r|>0.5. From an exercise network of 39 variables (ie, nodes) and 98 correlations (ie, edges) corresponding to P<9.5e-46 for each correlation, we focused on a subnetwork containing peak volume of oxygen consumption (pVo2) and 9 linked nodes. K-mean clustering based on these 10 variables identified 4 novel patient clusters characterized by significant differences in 44 of 45 exercise measurements (P<0.01). Compared with a probabilistic model, including 23 independent predictors of pVo2 and pVo2 itself, the network model was less redundant and identified clusters that were more distinct. Cluster assignment from the network model was predictive of subsequent clinical events. For example, a 4.3-fold (P<0.0001; 95% CI, 2.2-8.1) and 2.8-fold (P=0.0018; 95% CI, 1.5-5.2) increase in hazard for age- and pVo2-adjusted all-cause 3-year hospitalization, respectively, were observed between the highest versus lowest risk clusters. Using these data, we developed the first risk-stratification calculator for patients with exercise intolerance. When applying the risk calculator to patients in 2 independent invasive cardiopulmonary exercise testing cohorts (Boston and Graz, Austria), we observed a clinical risk profile that paralleled the derivation cohort.

CONCLUSIONS

Network analyses were used to identify novel exercise groups and develop a point-of-care risk calculator. These data expand the range of useful clinical variables beyond pVo2 that predict hospitalization in patients with exercise intolerance.

Effect of Rho-kinase inhibition on complexity of breathing pattern in a guinea pig model of asthma

Asthma represents an episodic and fluctuating behavior characterized with decreased complexity of respiratory dynamics. Several evidence indicate that asthma severity or control is associated with alteration in variability of lung function. The pathophysiological basis of alteration in complexity of breathing pattern in asthma has remained poorly understood. Regarding the point that Rho-kinase is involved in pathophysiology of asthma, in present study we investigated the effect of Rho-kinase inhibition on complexity of respiratory dynamics in a guinea pig model of asthma. Male Dunkin Hartley guinea pigs were exposed to 12 series of inhalations with ovalbumin or saline. Animals were treated by the Rho-kinase inhibitor Y-27632 (1mM aerosols) prior to each allergen challenge. We recorded respiration of conscious animals using whole-body plethysmography. Exposure to ovalbumin induced lung inflammation, airway hyperresponsiveness and remodeling including goblet cell hyperplasia, increase in the thickness of airways smooth muscles and subepithelial collagen deposition. Complexity analysis of respiratory dynamics revealed a dramatic decrease in irregularity of respiratory rhythm representing less complexity in asthmatic guinea pigs. Inhibition of Rho-kinase reduced the airway remodeling and hyperreponsiveness, but had no significant effect on lung inflammation and complexity of respiratory dynamics in asthmatic animals. It seems that airway hyperresponsiveness and remodeling do not significantly affect the complexity of respiratory dynamics. Our results suggest that inflammation might be the probable cause of shift in the respiratory dynamics away from the normal fluctuation in asthma.

Proteomics in asthma: the clinicians were right after all, were not they?

Clinical disease phenotypes with underlying information of molecular and biological signatures for the same, is a prerequisite for improving medical care and developing more effective, stratified management strategies. This commentary reviews the research carried out by Cao et al. to unravel biological networks associated with different clinical categories of asthma. It finally comments on the utility of using data from multiple platforms aided by integrated systems approaches to effectively find out the obvious underlying physiological disease signatures related to clinical disease sub-types.

What is precision medicine?

The term “precision medicine” has become very popular over recent years, fuelled by scientific as well as political perspectives. Despite its popularity, its exact meaning, and how it is different from other popular terms such as “stratified medicine”, “targeted therapy” or “deep phenotyping” remains unclear. Commonly applied definitions focus on the stratification of patients, sometimes referred to as a novel taxonomy, and this is derived using large-scale data including clinical, lifestyle, genetic and further biomarker information, thus going beyond the classical “signs-and-symptoms” approach.

While these aspects are relevant, this description leaves open a number of questions. For example, when does precision medicine begin? In which way does the stratification of patients translate into better healthcare? And can precision medicine be viewed as the end-point of a novel stratification of patients, as implied, or is it rather a greater whole?

To clarify this, the aim of this paper is to provide a more comprehensive definition that focuses on precision medicine as a process. It will be shown that this proposed framework incorporates the derivation of novel taxonomies and their role in healthcare as part of the cycle, but also covers related terms.

Effect of airway remodeling and hyperresponsiveness on complexity of breathing pattern in rat

The complexity of respiratory dynamics is decreased, in association with disease severity, in patients with asthma. However, the pathophysiological basis of decreased complexity of breathing pattern in asthma is not clear. In the present study, we investigated the effect of airway remodeling and hyperresponsiveness induced by repeated bronchoconstriction (using methacholine) on breathing pattern in rats with or without allergen-induced sensitization. Entropy analysis of respiratory variability showed decreased irregularity (less complexity) of respiratory rhythm in this rat model of asthma. Airway remodeling and hyperresponsiveness induced by repeated bronchoconstriction also led to increased regularity of respiratory dynamics in sensitized rats. However, these airway alterations had no significant effect on the complexity of breathing pattern in non-sensitized rats. Our results indicate that mechanical respiratory alterations cannot per se attenuate the complexity of respiratory dynamics, unless there is an underlying inflammation. We suggest further studies on underlying mechanisms of breathing variability with focus on respiratory control alterations due to airway inflammation.