First-in-Human Study to Assess the Safety, Pharmacokinetics, and Pharmacodynamics of BMS-986308: A Renal Outer Medullary Potassium Channel Inhibitor.

In patients with heart failure (HF) who respond inadequately to loop diuretic therapy, BMS-986308, an oral, selective, reversible renal outer medullary potassium channel (ROMK) inhibitor may represent an effective diuretic with a novel mechanism of action. We present data from the first-in-human study aimed to assess the safety, tolerability, pharmacokinetics (PK) and pharmacodynamics (PD) following single ascending doses of BMS-986308 in healthy adult participants. Forty healthy participants, aged from 20 to 55 years, and body mass index (BMI) from 19.8 to 31.6 kg/m2 were assigned to 1 of 5 dose cohorts (1, 3, 10, 30, and 100 mg) and randomized (6:2) to receive BMS-986308 oral solution or matching placebo. Following administration, BMS-986308 was rapidly absorbed with a median time to maximum concentration (Tmax) of 1.00 to 1.75 h and exhibiting a mean terminal half-life (t1/2) of approximately 13 h. Dose proportionality was evident in BMS-986308 area under the concentration-time curve (AUC), while maximum concentration (Cmax) was slightly greater than dose-proportional. We observed that urine output (or diuresis; mL) and urinary sodium excretion (or natriuresis; mmol) increased in a dose-dependent manner, starting at a minimum pharmacologically active dose of 30 mg. The largest mean changes from baseline in diuresis and natriuresis occurred in both the 6- and -24 h post-dose period following administration of 100 mg (1683.0 mL and 2055.3 mL, and 231.7 mmol and 213.7 mmol, respectively; ***P < 0.001). Overall, single-dose BMS-986308 was found to be safe, well-tolerated, with an excellent PK profile, and substantial diuretic and natriuretic activity.

Using a wearable patch to develop a digital monitoring biomarker of inflammation in response to LPS challenge.

Remote inflammation monitoring with digital health technologies (DHTs) would provide valuable information for both clinical research and care. Controlled perturbations of the immune system may reveal physiological signatures which could be used to develop a digital biomarker of inflammatory state. In this study, molecular and physiological profiling was performed following an in vivo lipopolysaccharide (LPS) challenge to develop a digital biomarker of inflammation. Ten healthy volunteers received an intravenous LPS challenge and were monitored for 24 h using the VitalConnect VitalPatch (VitalPatch). VitalPatch measurements included heart rate (HR), heart rate variability (HRV), respiratory rate (RR), and skin temperature (TEMP). Conventional episodic inpatient vital signs and serum proteins were measured pre- and post-LPS challenge. The VitalPatch provided vital signs that were comparable to conventional methods for assessing HR, RR, and TEMP. A pronounced increase was observed in HR, RR, and TEMP as well as a decrease in HRV 1-4 h post-LPS challenge. The ordering of participants by magnitude of inflammatory cytokine response 2 h post-LPS challenge was consistent with ordering of participants by change from baseline in vital signs when measured by VitalPatch (r = 0.73) but not when measured by conventional methods (r = -0.04). A machine learning model trained on VitalPatch data predicted change from baseline in inflammatory protein response (R2 = 0.67). DHTs, such as VitalPatch, can improve upon existing episodic measurements of vital signs by enabling continuous sensing and have the potential for future use as tools to remotely monitor inflammation.

Using an electronic diary and wristband accelerometer to detect exacerbations and activity levels in COPD: a feasibility study.

Background: Early and accurate identification of acute exacerbations of COPD may lead to earlier treatment and prevent hospital admission. Electronic diaries have been developed for symptom monitoring and accelerometers to monitor activity. However, it is unclear whether this technology is usable in the COPD population. This study aimed to assess the feasibility of an electronic diary (eDiary) for symptom reporting using the MoreCare app and activity monitoring with the Garmin Vivofit 2 in COPD. Methods: Participants were recruited from the London COPD Cohort. Participants were provided a Garmin Vivofit 2 activity monitor and an android tablet with the MoreCare app for a period of 3 months. Results: 25 COPD patients were recruited (mean±sd age 70.8±7.1 years, forced expiratory volume in 1 s (FEV1) 49.8±14.8% predicted). Age, gender, disease severity and exacerbation frequency had no impact on eDiary compliance. There was a moderate positive correlation between median daily very active minutes and FEV1 % pred (ρ=0.62, p=0.005). Daily step counts decreased during the initial 7 days of exacerbation and recovery compared to a pre-exacerbation baseline. A decision-tree model identified change in sputum colour, change in step count, severity of cold, exacerbation history and use of rescue medication as the most important predictors of acute exacerbations of COPD in this cohort. Conclusions: Symptom and activity monitoring using digital technology is feasible in COPD. Further large-scale digital health studies are needed to assess whether eDiaries can be used to identify patients at risk of exacerbation and guide early intervention.

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.

Assessing fatigue and sleep in chronic diseases using physiological signals from wearables: A pilot study.

Problems with fatigue and sleep are highly prevalent in patients with chronic diseases and often rated among the most disabling symptoms, impairing their activities of daily living and the health-related quality of life (HRQoL). Currently, they are evaluated primarily via Patient Reported Outcomes (PROs), which can suffer from recall biases and have limited sensitivity to temporal variations. Objective measurements from wearable sensors allow to reliably quantify disease state, changes in the HRQoL, and evaluate therapeutic outcomes. This work investigates the feasibility of capturing continuous physiological signals from an electrocardiography-based wearable device for remote monitoring of fatigue and sleep and quantifies the relationship of objective digital measures to self-reported fatigue and sleep disturbances. 136 individuals were followed for a total of 1,297 recording days in a longitudinal multi-site study conducted in free-living settings and registered with the German Clinical Trial Registry (DRKS00021693). Participants comprised healthy individuals (N = 39) and patients with neurodegenerative disorders (NDD, N = 31) and immune mediated inflammatory diseases (IMID, N = 66). Objective physiological measures correlated with fatigue and sleep PROs, while demonstrating reasonable signal quality. Furthermore, analysis of heart rate recovery estimated during activities of daily living showed significant differences between healthy and patient groups. This work underscores the promise and sensitivity of novel digital measures from multimodal sensor time-series to differentiate chronic patients from healthy individuals and monitor their HRQoL. The presented work provides clinicians with realistic insights of continuous at home patient monitoring and its practical value in quantitative assessment of fatigue and sleep, an area of unmet need.

Clinical and transcriptomic features of persistent exacerbation-prone severe asthma in U-BIOPRED cohort.

BACKGROUND: Exacerbation-prone asthma is a feature of severe disease. However, the basis for its persistency remains unclear. OBJECTIVES: To determine the clinical and transcriptomic features of frequent exacerbators (FEs) and persistent FEs (PFEs) in the U-BIOPRED cohort. METHODS: We compared features of FE (≥2 exacerbations in past year) to infrequent exacerbators (IE, <2 exacerbations) and of PFE with repeat ≥2 exacerbations during the following year to persistent IE (PIE). Transcriptomic data in blood, bronchial and nasal epithelial brushings, bronchial biopsies and sputum cells were analysed by gene set variation analysis for 103 gene signatures. RESULTS: Of 317 patients, 62.4% had FE, of whom 63.6% had PFE, while 37.6% had IE, of whom 61.3% had PIE. Using multivariate analysis, FE was associated with short-acting beta-agonist use, sinusitis and daily oral corticosteroid use, while PFE was associated with eczema, short-acting beta-agonist use and asthma control index. CEA cell adhesion molecule 5 (CEACAM5) was the only differentially expressed transcript in bronchial biopsies between PE and IE. There were no differentially expressed genes in the other four compartments. There were higher expression scores for type 2, T-helper type-17 and type 1 pathway signatures together with those associated with viral infections in bronchial biopsies from FE compared to IE, while there were higher expression scores of type 2, type 1 and steroid insensitivity pathway signatures in bronchial biopsies of PFE compared to PIE. CONCLUSION: The FE group and its PFE subgroup are associated with poor asthma control while expressing higher type 1 and type 2 activation pathways compared to IE and PIE, respectively.

Collagen Turnover Biomarkers Associate with Active Psoriatic Arthritis and Decrease with Guselkumab Treatment in a Phase 3 Clinical Trial (DISCOVER-2).

INTRODUCTION: Guselkumab, a novel interleukin-23p19 subunit monoclonal antibody, has been shown to effectively improve the diverse manifestations of active psoriatic arthritis (PsA) in two phase 3 trials (DISCOVER-1, DISCOVER-2). Serum concentrations of extracellular matrix (ECM) biomarkers at baseline and following treatment with guselkumab were evaluated in patients with active PsA, and the relationship of these biomarkers with baseline PsA characteristics and clinical response to guselkumab treatment was explored. METHODS: Serum samples were collected at weeks 0, 4, 24, and 52 from a selected subset (N = 260) of the 739 biologic-naïve patients with PsA treated with guselkumab 100 mg every 4 or 8 weeks or placebo in DISCOVER-2. Demographically matched healthy controls (N = 76) were used for comparison. The samples were analyzed for ECM biomarkers associated with collagen degradation (C1M, C2M, C3M, C4M, C6M, C10C) and collagen formation (PRO-C1, PRO-C2, PRO-C3, PRO-C4, PRO-C6). RESULTS: Baseline concentrations of collagen degradation biomarkers C1M, C3M, C4M, and C6M and collagen formation biomarkers PRO-C3 and PRO-C6 were significantly higher (i.e., ≥ 1.25-fold and false discovery rate adjusted p < 0.05) in PsA patients than in healthy controls. Serum C1M, C3M, C4M, and C6M levels declined from baseline in guselkumab-treated patients in both dosing regimens. In addition, guselkumab-treated ACR20 responders (≥ 20% improvement in American College of Rhematology response criteria) had significantly lower C1M levels than ACR20 nonresponders. CONCLUSION: These data demonstrate that serum collagen biomarkers are elevated in patients with PsA compared with healthy controls and that treatment with guselkumab decreases levels of C1M, C3M, C4M, and C6M. Importantly, C1M serves as a biomarker that associates with improvement of joint signs and symptoms. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT03158285.

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.