Phenome-Wide Association Study of Actigraphy in the UK Biobank

Wrist-worn accelerometer actigraphy devices present the opportunity for large-scale data collection from people during their daily lives. Using data from approximately 100,000 participants in the UK Biobank, actigraphy-derived measures of physical activity, sleep, and diurnal rhythms were associated in exploration and validation cohorts with a full phenome-wide set of diagnoses, biomarkers and metadata. Rhythmicity was captured by two independent models based on accelerometer and skin temperature harnessing behavioral (diurnal) and molecular (circadian) components. We found that robust rhythms significantly with biomarkers, survival, and phenotypes including diabetes, hypertension, mood disorders, and chronic airway obstruction; these associations were comparable to those with physical activity and sleep. Surprisingly, associations were mostly consistent between the sexes, while modulation by age was significant. More importantly, rhythms were found to be powerful predictors of future diseases: a two standard deviation difference in wrist temperature rhythms corresponded to increases in rate of diagnosis of 61% in diabetes, 38% in chronic airway obstruction, 27% in anxiety disorders, and 22% in hypertension. Our PheWAS of actigraphy data in the UK Biobank establishes that rhythmicity is fundamental to modeling disease trajectories, as are physical activity and sleep. Integration of long-term remote biosensing into patient care could thus afford an individualized approach to risk management.

Decreased eosinophil counts and elevated lactate dehydrogenase predict severe COVID-19 in patients with underlying chronic airway diseases

BackgroundSeveral predictors of COVID-19 severity have been reported. However, chronic airway inflammation characterised by accumulated lymphocytes or eosinophils may affect the pathogenesis of COVID-19.MethodsIn this retrospective cohort study, we reviewed the medical records of all patients with laboratory-confirmed COVID-19 with chronic bronchitis, chronic obstructive pulmonary disease (COPD) and asthma admitted to the Sino-French New City Branch of Tongji Hospital, a large regional hospital in Wuhan, China, from 26 January to 3 April. The Tongji Hospital Ethics Committee approved this study.ResultsThere were 59 patients with chronic bronchitis, COPD and asthma. When compared with non-severe patients, severe patients were more likely to have decreased lymphocyte counts (0.6×10⁹/L vs 1.1×10⁹/L, p<0.001), eosinopaenia (<0.02×10⁹/L; 73% vs 24%, p<0.001), increased lactate dehydrogenase (LDH) (471.0 U/L vs 230.0 U/L, p<0.001) and elevated interleukin 6 level (47.4 pg/mL vs 5.7 pg/mL, p=0.002) on admission. Eosinopaenia and elevated LDH were significantly associated with disease severity in both univariate and multivariate regression models including the above variables. Moreover, eosinophil count and LDH level tended to return to normal range over time in both groups after treatment and severe patients recovered slower than non-severe patients, especially in eosinophil count.ConclusionsEosinopaenia and elevated LDH are potential predictors of disease severity in patients with COVID-19 with underlying chronic airway diseases. In addition, they could indicate disease progression and treatment effectiveness.

Cytokine Patterns in Iranian Patients with Asthma

Asthma is one of the most common respiratory diseases caused by chronic airway inflammation. A complex network of cytokines could affect asthma development. IL-4, IL-13, IL-17, and IL-33 have been identified as cytokines associated with asthma severity and these cytokines can be considered as candidate biomarkers for predicting the asthma severity while the IL-10 is lower in asthmatics compared with healthy subjects. There are many controversies about the IL-22, IL-25, and TGF-β levels between the Iranian publications. No significant differences have been observed between the healthy subjects and the asthmatic cases regarding the IL-6 and IL-8.

Cross-talk of inflammatory mediators and airway epithelium reveals CFTR as a major target

Airway inflammation, mucus hyperproduction and epithelial remodelling are hallmarks of many chronic airway diseases, including asthma, Chronic Obstructive Pulmonary Disease and Cystic Fibrosis. While several cytokines are dysregulated in these diseases, most studies focus on the response of airways to IL-4 and IL-13, which were shown to induce mucus hyperproduction and shift the airway epithelium towards a hypersecretory phenotype.We hypothesised that other cytokines might induce the expression of chloride (Cl−) channels/transporters, regulate epithelial differentiation and mucus production. To this end, fully-differentiated human airway basal cells (BCi-NS1.1) were treated with cytokines identified as dysregulated in those diseases, namely interleukins-8, 1β, 4, 17A, 10, 22, and tumour necrosis factor-α (TNF-α).Our results show that CFTR is the main Cl− channel modulated by inflammation, in contrast to TMEM16A, whose levels only changed with IL-4. Furthermore, we identified novel roles for IL-10 and IL-22 by influencing epithelial differentiation towards ciliated cells and away from pulmonary ionocytes. Contrarily, IL-1β and IL-4 reduced the number of ciliated cells while increasing club cells. Interestingly, while IL-1β, IL-4 and IL-10 upregulated CFTR expression, IL-4 was the only cytokine that increased both its function and the number of CFTR-expressing club cells, suggesting that this cell-type may be the main contributor for CFTR function. Additionally, all cytokines assessed increased mucus production through a differential upregulation of MUC5AC and MUC5B transcript levels.Altogether, this study reveals a novel insight into differentiation resulting from the cross-talk of inflammatory mediators and airway epithelial cells, which is particularly relevant for chronic airway diseases.