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Montoro J.,University of Valencia | Del Cuvillo A.,Hospital Of Jerez | Mullol J.,Institute dInvestigacions Biome Diques August Pi i Sunyer IDIBAPS | Mullol J.,Research Center Biomedica en Red en Enfermedades Respiratorias | And 7 more authors.
Allergy: European Journal of Allergy and Clinical Immunology | Year: 2012

Background A modified allergic rhinitis and its impact on asthma (ARIA) (m-ARIA) criterion to classify the severity of allergic rhinitis (AR) has recently been validated in both treated and untreated adult patients; however, such information in children is lacking. The aim of this study was to validate this m-ARIA severity criterion, which allows for discrimination between moderate and severe AR, in a large pediatric patient sample population. Methods The m-ARIA classification categorizes AR severity into mild (no affected items), moderate (1-3 affected items), and severe (all four affected items). We applied this modified criterion to untreated AR pediatric patients aged 6-12 years, through an observational, cross-sectional, and multicenter study. AR symptoms were assessed using the Total Four Symptom Score (T4SS), and the severity was evaluated by both ARIA severity items and visual analogue scale (VAS). Results Allergic rhinitis pediatric patients (N = 1269) from 271 centers were included. Among them, 59.5% had intermittent and 40.5% persistent disease; 89.9% had moderate/severe AR using the original ARIA (o-ARIA) classification and 59.5% had moderate, while 30.5% had severe AR using the m-ARIA criterion. Using the m-ARIA, significantly higher T4SS and VAS scores were obtained when comparing severe with moderate AR. Conclusions The m-ARIA severity classification is a useful clinical tool to discriminate moderate from severe AR among untreated pediatric patients. © 2012 John Wiley & Sons A/S.

Davidsen P.K.,University of Liverpool | Davidsen P.K.,University of Birmingham | Herbert J.M.,University of Liverpool | Antczak P.,University of Liverpool | And 16 more authors.
Genome Medicine | Year: 2014

Background: A relatively large percentage of patients with chronic obstructive pulmonary disease (COPD) develop systemic co-morbidities that affect prognosis, among which muscle wasting is particularly debilitating. Despite significant research effort, the pathophysiology of this important extrapulmonary manifestation is still unclear. A key question that remains unanswered is to what extent systemic inflammatory mediators might play a role in this pathology. Cigarette smoke (CS) is the main risk factor for developing COPD and therefore animal models chronically exposed to CS have been proposed for mechanistic studies and biomarker discovery. Although mice have been successfully used as a pre-clinical in vivo model to study the pulmonary effects of acute and chronic CS exposure, data suggest that they may be inadequate models for studying the effects of CS on peripheral muscle function. In contrast, recent findings indicate that the guinea pig model (Cavia porcellus) may better mimic muscle wasting. Methods: We have used a systems biology approach to compare the transcriptional profile of hindlimb skeletal muscles from a Guinea pig rodent model exposed to CS and/or chronic hypoxia to COPD patients with muscle wasting. Results: We show that guinea pigs exposed to long-term CS accurately reflect most of the transcriptional changes observed in dysfunctional limb muscle of severe COPD patients when compared to matched controls. Using network inference, we could then show that the expression profile in whole lung of genes encoding for soluble inflammatory mediators is informative of the molecular state of skeletal muscles in the guinea pig smoking model. Finally, we show that CXCL10 and CXCL9, two of the candidate systemic cytokines identified using this pre-clinical model, are indeed detected at significantly higher levels in serum of COPD patients, and that their serum protein level is inversely correlated with the expression of aerobic energy metabolism genes in skeletal muscle. Conclusions: We conclude that CXCL10 and CXCL9 are promising candidate inflammatory signals linked to the regulation of central metabolism genes in skeletal muscles. On a methodological level, our work also shows that a system level analysis of animal models of diseases can be very effective to generate clinically relevant hypothesis. © 2014 Davidsen et al.; licensee BioMed Central.

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