Cell-free DNA levels associate with COPD exacerbations and mortality.

THE QUESTION ADDRESSED BY THE STUDY: Good biological indicators capable of predicting chronic obstructive pulmonary disease (COPD) phenotypes and clinical trajectories are lacking. Because nuclear and mitochondrial genomes are damaged and released by cigarette smoke exposure, plasma cell-free mitochondrial and nuclear DNA (cf-mtDNA and cf-nDNA) levels could potentially integrate disease physiology and clinical phenotypes in COPD. This study aimed to determine whether plasma cf-mtDNA and cf-nDNA levels are associated with COPD disease severity, exacerbations, and mortality risk. MATERIALS AND METHODS: We quantified mtDNA and nDNA copy numbers in plasma from participants enrolled in the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE, n = 2,702) study and determined associations with relevant clinical parameters. RESULTS: Of the 2,128 participants with COPD, 65% were male and the median age was 64 (interquartile range, 59-69) years. During the baseline visit, cf-mtDNA levels positively correlated with future exacerbation rates in subjects with mild/moderate and severe disease (Global Initiative for Obstructive Lung Disease [GOLD] I/II and III, respectively) or with high eosinophil count (≥ 300). cf-nDNA positively associated with an increased mortality risk (hazard ratio, 1.33 [95% confidence interval, 1.01-1.74] per each natural log of cf-nDNA copy number). Additional analysis revealed that individuals with low cf-mtDNA and high cf-nDNA abundance further increased the mortality risk (hazard ratio, 1.62 [95% confidence interval, 1.16-2.25] per each natural log of cf-nDNA copy number). ANSWER TO THE QUESTION: Plasma cf-mtDNA and cf-nDNA, when integrated into quantitative clinical measurements, may aid in improving COPD severity and progression assessment.

Low levels of endogenous anabolic androgenic steroids in females with severe asthma taking corticosteroids.

Rationale: Patients with severe asthma are dependent upon treatment with high doses of inhaled corticosteroids (ICS) and often also oral corticosteroids (OCS). The extent of endogenous androgenic anabolic steroid (EAAS) suppression in asthma has not previously been described in detail. The objective of the present study was to measure urinary concentrations of EAAS in relation to exogenous corticosteroid exposure. Methods: Urine collected at baseline in the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease outcomes) study of severe adult asthmatics (SA, n=408) was analysed by quantitative mass spectrometry. Data were compared to that of mild-to-moderate asthmatics (MMA, n=70) and healthy subjects (HC, n=98) from the same study. Measurements and main results: The concentrations of urinary endogenous steroid metabolites were substantially lower in SA than in MMA or HC. These differences were more pronounced in SA patients with detectable urinary OCS metabolites. Their dehydroepiandrosterone sulfate (DHEA-S) concentrations were <5% of those in HC, and cortisol concentrations were below the detection limit in 75% of females and 82% of males. The concentrations of EAAS in OCS-positive patients, as well as patients on high-dose ICS only, were more suppressed in females than males (p<0.05). Low levels of DHEA were associated with features of more severe disease and were more prevalent in females (p<0.05). The association between low EAAS and corticosteroid treatment was replicated in 289 of the SA patients at follow-up after 12-18 months. Conclusion: The pronounced suppression of endogenous anabolic androgens in females might contribute to sex differences regarding the prevalence of severe asthma.

Haemophilus influenzae and Moraxella catarrhalis in sputum of severe asthma with inflammasome and neutrophil activation.

BACKGROUND: Because of altered airway microbiome in asthma, we analysed the bacterial species in sputum of patients with severe asthma. METHODS: Whole genome sequencing was performed on induced sputum from non-smoking (SAn) and current or ex-smoker (SAs/ex) severe asthma patients, mild/moderate asthma (MMA) and healthy controls (HC). Data were analysed by asthma severity, inflammatory status and transcriptome-associated clusters (TACs). RESULTS: α-diversity at the species level was lower in SAn and SAs/ex, with an increase in Haemophilus influenzae and Moraxella catarrhalis, and Haemophilus influenzae and Tropheryma whipplei, respectively, compared to HC. In neutrophilic asthma, there was greater abundance of Haemophilus influenzae and Moraxella catarrhalis and in eosinophilic asthma, Tropheryma whipplei was increased. There was a reduction in α-diversity in TAC1 and TAC2 that expressed high levels of Haemophilus influenzae and Tropheryma whipplei, and Haemophilus influenzae and Moraxella catarrhalis, respectively, compared to HC. Sputum neutrophils correlated positively with Moraxella catarrhalis and negatively with Prevotella, Neisseria and Veillonella species and Haemophilus parainfluenzae. Sputum eosinophils correlated positively with Tropheryma whipplei which correlated with pack-years of smoking. α- and ß-diversities were stable at one year. CONCLUSIONS: Haemophilus influenzae and Moraxella catarrhalis were more abundant in severe neutrophilic asthma and TAC2 linked to inflammasome and neutrophil activation, while Haemophilus influenzae and Tropheryma whipplei were highest in SAs/ex and in TAC1 associated with highest expression of IL-13 type 2 and ILC2 signatures with the abundance of Tropheryma whipplei correlating positively with sputum eosinophils. Whether these bacterial species drive the inflammatory response in asthma needs evaluation.

IL1RAP expression and the enrichment of IL-33 activation signatures in severe neutrophilic asthma.

BACKGROUND: Interleukin (IL)-33 is an upstream regulator of type 2 (T2) eosinophilic inflammation and has been proposed as a key driver of some asthma phenotypes. OBJECTIVE: To derive gene signatures from in vitro studies of IL-33-stimulated cells and use these to determine IL-33-associated enrichment patterns in asthma. METHODS: Signatures downstream of IL-33 stimulation were derived from our in vitro study of human mast cells and from public datasets of in vitro stimulated human basophils, type 2 innate lymphoid cells (ILC2), regulatory T cells (Treg) and endothelial cells. Gene Set Variation Analysis (GSVA) was used to probe U-BIOPRED and ADEPT sputum transcriptomics to determine enrichment scores (ES) for each signature according to asthma severity, sputum granulocyte status and previously defined molecular phenotypes. RESULTS: IL-33-activated gene signatures were cell-specific with little gene overlap. Individual signatures, however, were associated with similar signalling pathways (TNF, NF-κB, IL-17 and JAK/STAT signalling) and immune cell differentiation pathways (Th17, Th1 and Th2 differentiation). ES for IL-33-activated gene signatures were significantly enriched in asthmatic sputum, particularly in patients with neutrophilic and mixed granulocytic phenotypes. IL-33 mRNA expression was not elevated in asthma whereas the expression of mRNA for IL1RL1, the IL-33 receptor, was up-regulated in the sputum of severe eosinophilic asthma. The mRNA expression for IL1RAP, the IL1RL1 co-receptor, was greatest in severe neutrophilic and mixed granulocytic asthma. CONCLUSIONS: IL-33-activated gene signatures are elevated in neutrophilic and mixed granulocytic asthma corresponding with IL1RAP co-receptor expression. This suggests incorporating T2-low asthma in anti-IL-33 trials.

Mapping atopic dermatitis and anti-IL-22 response signatures to type 2-low severe neutrophilic asthma.

BACKGROUND: Transcriptomic changes in patients who respond clinically to biological therapies may identify responses in other tissues or diseases. OBJECTIVE: We sought to determine whether a disease signature identified in atopic dermatitis (AD) is seen in adults with severe asthma and whether a transcriptomic signature for patients with AD who respond clinically to anti-IL-22 (fezakinumab [FZ]) is enriched in severe asthma. METHODS: An AD disease signature was obtained from analysis of differentially expressed genes between AD lesional and nonlesional skin biopsies. Differentially expressed genes from lesional skin from therapeutic superresponders before and after 12 weeks of FZ treatment defined the FZ-response signature. Gene set variation analysis was used to produce enrichment scores of AD and FZ-response signatures in the Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes asthma cohort. RESULTS: The AD disease signature (112 upregulated genes) encompassing inflammatory, T-cell, TH2, and TH17/TH22 pathways was enriched in the blood and sputum of patients with asthma with increasing severity. Patients with asthma with sputum neutrophilia and mixed granulocyte phenotypes were the most enriched (P < .05). The FZ-response signature (296 downregulated genes) was enriched in asthmatic blood (P < .05) and particularly in neutrophilic and mixed granulocytic sputum (P < .05). These data were confirmed in sputum of the Airway Disease Endotyping for Personalized Therapeutics cohort. IL-22 mRNA across tissues did not correlate with FZ-response enrichment scores, but this response signature correlated with TH22/IL-22 pathways. CONCLUSIONS: The FZ-response signature in AD identifies severe neutrophilic asthmatic patients as potential responders to FZ therapy. This approach will help identify patients for future asthma clinical trials of drugs used successfully in other chronic diseases.

Plasma proteins elevated in severe asthma despite oral steroid use and unrelated to Type-2 inflammation.

RATIONALE: Asthma phenotyping requires novel biomarker discovery. OBJECTIVES: To identify plasma biomarkers associated with asthma phenotypes by application of a new proteomic panel to samples from two well-characterised cohorts of severe (SA) and mild-to-moderate (MMA) asthmatics, COPD subjects and healthy controls (HCs). METHODS: An antibody-based array targeting 177 proteins predominantly involved in pathways relevant to inflammation, lipid metabolism, signal transduction and extracellular matrix was applied to plasma from 525 asthmatics and HCs in the U-BIOPRED cohort, and 142 subjects with asthma and COPD from the validation cohort BIOAIR. Effects of oral corticosteroids (OCS) were determined by a 2-week, placebo-controlled OCS trial in BIOAIR, and confirmed by relation to objective OCS measures in U-BIOPRED. RESULTS: In U-BIOPRED, 110 proteins were significantly different, mostly elevated, in SA compared to MMA and HCs. 10 proteins were elevated in SA versus MMA in both U-BIOPRED and BIOAIR (alpha-1-antichymotrypsin, apolipoprotein-E, complement component 9, complement factor I, macrophage inflammatory protein-3, interleukin-6, sphingomyelin phosphodiesterase 3, TNF receptor superfamily member 11a, transforming growth factor-ß and glutathione S-transferase). OCS treatment decreased most proteins, yet differences between SA and MMA remained following correction for OCS use. Consensus clustering of U-BIOPRED protein data yielded six clusters associated with asthma control, quality of life, blood neutrophils, high-sensitivity C-reactive protein and body mass index, but not Type-2 inflammatory biomarkers. The mast cell specific enzyme carboxypeptidase A3 was one major contributor to cluster differentiation. CONCLUSIONS: The plasma proteomic panel revealed previously unexplored yet potentially useful Type-2-independent biomarkers and validated several proteins with established involvement in the pathophysiology of SA.

Urinary metabotype of severe asthma evidences decreased carnitine metabolism independent of oral corticosteroid treatment in the U-BIOPRED study.

INTRODUCTION: Asthma is a heterogeneous disease with poorly defined phenotypes. Patients with severe asthma often receive multiple treatments including oral corticosteroids (OCS). Treatment may modify the observed metabotype, rendering it challenging to investigate underlying disease mechanisms. Here, we aimed to identify dysregulated metabolic processes in relation to asthma severity and medication. METHODS: Baseline urine was collected prospectively from healthy participants (n=100), patients with mild-to-moderate asthma (n=87) and patients with severe asthma (n=418) in the cross-sectional U-BIOPRED cohort; 12-18-month longitudinal samples were collected from patients with severe asthma (n=305). Metabolomics data were acquired using high-resolution mass spectrometry and analysed using univariate and multivariate methods. RESULTS: A total of 90 metabolites were identified, with 40 significantly altered (p<0.05, false discovery rate <0.05) in severe asthma and 23 by OCS use. Multivariate modelling showed that observed metabotypes in healthy participants and patients with mild-to-moderate asthma differed significantly from those in patients with severe asthma (p=2.6×10-20), OCS-treated asthmatic patients differed significantly from non-treated patients (p=9.5×10-4), and longitudinal metabotypes demonstrated temporal stability. Carnitine levels evidenced the strongest OCS-independent decrease in severe asthma. Reduced carnitine levels were associated with mitochondrial dysfunction via decreases in pathway enrichment scores of fatty acid metabolism and reduced expression of the carnitine transporter SLC22A5 in sputum and bronchial brushings. CONCLUSIONS: This is the first large-scale study to delineate disease- and OCS-associated metabolic differences in asthma. The widespread associations with different therapies upon the observed metabotypes demonstrate the need to evaluate potential modulating effects on a treatment- and metabolite-specific basis. Altered carnitine metabolism is a potentially actionable therapeutic target that is independent of OCS treatment, highlighting the role of mitochondrial dysfunction in severe asthma.

Medication Adherence in Patients With Severe Asthma Prescribed Oral Corticosteroids in the U-BIOPRED Cohort.

BACKGROUND: Although estimates of suboptimal adherence to oral corticosteroids in asthma range from 30% to 50%, no ideal method for measurement exists; the impact of poor adherence in severe asthma is likely to be particularly high. RESEARCH QUESTIONS: What is the prevalence of suboptimal adherence detected by self-reporting and direct measures? Is suboptimal adherence associated with disease activity? STUDY DESIGN AND METHODS: Data were included from individuals with severe asthma taking part in the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes) study and prescribed daily oral corticosteroids. Participants completed the Medication Adherence Report Scale, a five-item questionnaire used to grade adherence on a scale from 1 to 5, and provided a urine sample for analysis of prednisolone and metabolites by liquid chromatography-mass spectrometry. RESULTS: Data from 166 participants were included in this study: mean (SD) age, 54.2 (± 11.9) years; FEV1, 65.1% (± 20.5%) predicted; female, 58%; 37% completing the Medication Adherence Report Scale reported suboptimal adherence; and 43% with urinary corticosteroid data did not have detectable prednisolone or metabolites in their urine. Good adherence by both methods was detected in 49 of the 142 (35%) of participants in whom both methods were performed; adherence detection did not match between methods in 53%. Self-reported high adherers had better asthma control and quality of life, whereas directly measured high adherers had lower blood eosinophil levels. INTERPRETATION: Low adherence is a common problem in severe asthma, whether measured directly or self-reported. We report poor agreement between the two methods, suggesting some disassociation between self-assessment of medication adherence and regular oral corticosteroid use, which suggests that each approach may provide complementary information in clinical practice.

Urinary Leukotriene E4 and Prostaglandin D2 Metabolites Increase in Adult and Childhood Severe Asthma Characterized by Type 2 Inflammation. A Clinical Observational Study.

Rationale: New approaches are needed to guide personalized treatment of asthma.Objectives: To test if urinary eicosanoid metabolites can direct asthma phenotyping.Methods: Urinary metabolites of prostaglandins (PGs), cysteinyl leukotrienes (CysLTs), and isoprostanes were quantified in the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Diseases Outcomes) study including 86 adults with mild-to-moderate asthma (MMA), 411 with severe asthma (SA), and 100 healthy control participants. Validation was performed internally in 302 participants with SA followed up after 12-18 months and externally in 95 adolescents with asthma.Measurement and Main Results: Metabolite concentrations in healthy control participants were unrelated to age, body mass index, and sex, except for the PGE2 pathway. Eicosanoid concentrations were generally greater in participants with MMA relative to healthy control participants, with further elevations in participants with SA. However, PGE2 metabolite concentrations were either the same or lower in male nonsmokers with asthma than in healthy control participants. Metabolite concentrations were unchanged in those with asthma who adhered to oral corticosteroid treatment as documented by urinary prednisolone detection, whereas those with SA treated with omalizumab had lower concentrations of LTE4 and the PGD2 metabolite 2,3-dinor-11ß-PGF2α. High concentrations of LTE4 and PGD2 metabolites were associated with lower lung function and increased amounts of exhaled nitric oxide and eosinophil markers in blood, sputum, and urine in U-BIOPRED participants and in adolescents with asthma. These type 2 (T2) asthma associations were reproduced in the follow-up visit of the U-BIOPRED study and were found to be as sensitive to detect T2 inflammation as the established biomarkers.Conclusions: Monitoring of urinary eicosanoids can identify T2 asthma and introduces a new noninvasive approach for molecular phenotyping of adult and adolescent asthma.Clinical trial registered with www.clinicaltrials.gov (NCT01976767).

Sputum microbiome profiles identify severe asthma phenotypes of relative stability at 12 to 18 months.

BACKGROUND: Asthma is a heterogeneous disease characterized by distinct phenotypes with associated microbial dysbiosis. OBJECTIVES: Our aim was to identify severe asthma phenotypes based on sputum microbiome profiles and assess their stability after 12 to 18 months. A further aim was to evaluate clusters' robustness after inclusion of an independent cohort of patients with mild-to-moderate asthma. METHODS: In this longitudinal multicenter cohort study, sputum samples were collected for microbiome profiling from a subset of the Unbiased Biomarkers in Prediction of Respiratory Disease Outcomes adult patient cohort at baseline and after 12 to 18 months of follow-up. Unsupervised hierarchical clustering was performed by using the Bray-Curtis ß-diversity measure of microbial profiles. For internal validation, partitioning around medoids, consensus cluster distribution, bootstrapping, and topological data analysis were applied. Follow-up samples were studied to evaluate within-patient clustering stability in patients with severe asthma. Cluster robustness was evaluated by using an independent cohort of patients with mild-to-moderate asthma. RESULTS: Data were available for 100 subjects with severe asthma (median age 55 years; 42% males). Two microbiome-driven clusters were identified; they were characterized by differences in asthma onset, smoking status, residential locations, percentage of blood and/or sputum neutrophils and macrophages, lung spirometry results, and concurrent asthma medications (all P values < .05). The cluster 2 patients displayed a commensal-deficient bacterial profile that was associated with worse asthma outcomes than those of the cluster 1 patients. Longitudinal clusters revealed high relative stability after 12 to 18 months in those with severe asthma. Further inclusion of an independent cohort of 24 patients with mild-to-moderate asthma was consistent with the clustering assignments. CONCLUSION: Unbiased microbiome-driven clustering revealed 2 distinct robust phenotypes of severe asthma that exhibited relative overtime stability. This suggests that the sputum microbiome may serve as a biomarker for better characterizing asthma phenotypes.

Blood eosinophil count and airway epithelial transcriptome relationships in COPD versus asthma.

BACKGROUND: Whether the clinical or pathophysiologic significance of the "treatable trait" high blood eosinophil count in COPD is the same as for asthma remains controversial. We sought to determine the relationship between the blood eosinophil count, clinical characteristics and gene expression from bronchial brushings in COPD and asthma. METHODS: Subjects were recruited into a COPD (emphysema versus airway disease [EvA]) or asthma cohort (Unbiased BIOmarkers in PREDiction of respiratory disease outcomes, U-BIOPRED). We determined gene expression using RNAseq in EvA (n = 283) and Affymetrix microarrays in U-BIOPRED (n = 85). We ran linear regression analysis of the bronchial brushings transcriptional signal versus blood eosinophil counts as well as differential expression using a blood eosinophil > 200 cells/µL as a cut-off. The false discovery rate was controlled at 1% (with continuous values) and 5% (with dichotomized values). RESULTS: There were no differences in age, gender, lung function, exercise capacity and quantitative computed tomography between eosinophilic versus noneosinophilic COPD cases. Total serum IgE was increased in eosinophilic asthma and COPD. In EvA, there were 12 genes with a statistically significant positive association with the linear blood eosinophil count, whereas in U-BIOPRED, 1197 genes showed significant associations (266 positive and 931 negative). The transcriptome showed little overlap between genes and pathways associated with blood eosinophil counts in asthma versus COPD. Only CST1 was common to eosinophilic asthma and COPD and was replicated in independent cohorts. CONCLUSION: Despite shared "treatable traits" between asthma and COPD, the molecular mechanisms underlying these clinical entities are predominately different.

Asthma similarities across ProAR (Brazil) and U-BIOPRED (Europe) adult cohorts of contrasting locations, ethnicity and socioeconomic status.

BACKGROUND: Asthma prevalence is 339 million globally. 'Severe asthma' (SA) comprises subjects with uncontrolled asthma despite proper management. OBJECTIVES: To compare asthma from diverse ethnicities and environments. METHODS: A cross-sectional analysis of two adult cohorts, a Brazilian (ProAR) and a European (U-BIOPRED). U-BIOPRED comprised of 311 non-smoking with Severe Asthma (SAn), 110 smokers or ex-smokers with SA (SAs) and 88 mild to moderate asthmatics (MMA) while ProAR included 544 SA and 452 MMA. Although these projects were independent, there were similarities in objectives and methodology, with ProAR adopting operating procedures of U-BIOPRED. RESULTS: Among SA subjects, age, weight, proportion of former smokers and FEV1 pre-bronchodilator were similar. The proportion of SA with a positive skin prick tests (SPT) to aeroallergens, the scores of sino-nasal symptoms and quality of life were comparable. In addition, blood eosinophil counts (EOS) and the % of subjects with EOS > 300 cells/µl were not different. The Europeans with SA however, were more severe with a greater proportion of continuous oral corticosteroids (OCS), worse symptoms and more frequent exacerbations. FEV1/FVC pre- and post-bronchodilator were lower among the Europeans. The MMA cohorts were less comparable in control and treatment, but similar in the proportion of allergic rhinitis, gastroesophageal reflux disease and EOS >3%. CONCLUSIONS: ProAR and U-BIOPRED cohorts, with varying severity, ethnicity and environment have similarities, which provide the basis for global external validation of asthma phenotypes. This should stimulate collaboration between asthma consortia with the aim of understanding SA, which will lead to better management.

Biomarkers for severe eosinophilic asthma.

The last decade has seen the approval of several new biologics for the treatment of severe asthma-targeting specific endotypes and phenotypes. This review will examine how evidence generated from the mepolizumab clinical development program showed that blood eosinophil counts, rather than sputum or tissue eosinophil counts, evolved as a pharmacodynamic and predictive biomarker for the efficacy of treatment with mepolizumab in patients with severe eosinophilic asthma. Based on the available evidence and combined with clinical judgement, a baseline blood eosinophil threshold of 150 cells/µL or greater or a historical blood eosinophil threshold of 300 cells/µL or greater will allow selection of patients with severe eosinophilic asthma who are most likely to achieve clinically significant reductions in the rate of exacerbations with mepolizumab treatment.

Transcriptomic gene signatures associated with persistent airflow limitation in patients with severe asthma.

A proportion of severe asthma patients suffers from persistent airflow limitation (PAL), often associated with more symptoms and exacerbations. Little is known about the underlying mechanisms. Here, our aim was to discover unexplored potential mechanisms using Gene Set Variation Analysis (GSVA), a sensitive technique that can detect underlying pathways in heterogeneous samples.Severe asthma patients from the U-BIOPRED cohort with PAL (post-bronchodilator forced expiratory volume in 1 s/forced vital capacity ratio below the lower limit of normal) were compared with those without PAL. Gene expression was assessed on the total RNA of sputum cells, nasal brushings, and endobronchial brushings and biopsies. GSVA was applied to identify differentially enriched predefined gene signatures based on all available gene expression publications and data on airways disease.Differentially enriched gene signatures were identified in nasal brushings (n=1), sputum (n=9), bronchial brushings (n=1) and bronchial biopsies (n=4) that were associated with response to inhaled steroids, eosinophils, interleukin-13, interferon-α, specific CD4+ T-cells and airway remodelling.PAL in severe asthma has distinguishable underlying gene networks that are associated with treatment, inflammatory pathways and airway remodelling. These findings point towards targets for the therapy of PAL in severe asthma.

Gene expression changes caused by the p38 MAPK inhibitor dilmapimod in COPD patients: analysis of blood and sputum samples from a randomized, placebo-controlled clinical trial.

The p38 mitogen-activated protein kinase (MAPK) intracellular signaling pathway responds to a variety of extracellular stimuli, including cytokines, Toll-like receptor agonists, and components of cigarette smoke to influence the expression of proinflammatory mediators. Activation of p38 MAPK is increased within the lungs of chronic obstructive pulmonary disease (COPD) patients. In clinical trials, treatment of COPD patients with p38 MAPK inhibitors has been shown to reduce systemic inflammation plasma biomarkers C-reactive protein (CRP) and fibrinogen. As CRP and fibrinogen have been associated with poor clinical outcomes in COPD patients, such as mortality, exacerbation, and hospitalization, we analyzed gene expression data from COPD subjects treated with dilmapimod with the aim of understanding the effects of p38 MAPK inhibition on the inflammatory genome of immune cells within the systemic circulation. Whole blood and induced sputum samples were used to measure mRNA levels by gene array and PCR. Pathway and network analysis showed STAT1, MMP-9, CAV1, and IL-1ß as genes regulated by dilmapimod that could also influence fibrinogen levels, while only IL-1ß was identified as a gene regulated by dilmapimod that could influence CRP levels. This suggests that p38 MAPK inhibits specific inflammatory pathways, leading to to differential effects on CRP and fibrinogen levels in COPD patients.

Ozanezumab dose selection for amyotrophic lateral sclerosis by pharmacokinetic-pharmacodynamic modelling of immunohistochemistry data from patient muscle biopsies.

Amyotrophic Lateral Sclerosis (ALS) is a rare and fatal neurodegenerative disease with a high unmet medical need. In this context, a potential therapy should be brought to patients in the most expeditious way and early exploration of pharmacology is highly beneficial. Ozanezumab, a humanised IgG monoclonal antibody against Nogo-A protein which is an inhibitor of neurite outgrowth, is currently under development for the treatment of ALS and has been recently assessed in 76 patients in a first-in-human study. Inadequate target engagement has been recognised as a major contributing reason for drug trial failures. In this work, we describe the development of a pharmacokinetic-pharmacodynamic (PKPD) model using immunohistochemistry (IHC) data of co-localization of ozanezumab with Nogo-A in skeletal muscle as a surrogate measure of target engagement. The rich plasma concentration data and the sparse IHC data after one or two intravenous doses of ozanezumab were modelled simultaneously using a non-linear mixed-effect approach. The final PKPD model was a two-compartment PK model combined with an effect compartment PD model that accounted for the delay in ozanezumab concentrations to reach the site of action which is skeletal muscle. Diagnostic plots showed a satisfactory fit of both PK and IHC data. The model was used as a simulation tool to design a dose regimen for sustained drug-target co-localization in a phase II study.