Application of non-invasive biomarkers in a birth cohort follow-up in relation to respiratory health outcome

Priorities for future research into asthma diagnostic tools: A PAN-EU consensus exercise from the European asthma research innovation partnership (EARIP)

The diagnosis of asthma is currently based on clinical history, physical examination and lung function, and to date, there are no accurate objective tests either to confirm the diagnosis or to discriminate between different types of asthma. This consensus exercise reviews the state of the art in asthma diagnosis to identify opportunities for future investment based on the likelihood of their successful development, potential for widespread adoption and their perceived impact on asthma patients. Using a two-stage e-Delphi process and a summarizing workshop, a group of European asthma experts including health professionals, researchers, people with asthma and industry representatives ranked the potential impact of research investment in each technique or tool for asthma diagnosis and monitoring. After a systematic review of the literature, 21 statements were extracted and were subject of the two-stage Delphi process. Eleven statements were scored 3 or more and were further discussed and ranked in a face-to-face workshop. The three most important diagnostic/predictive tools ranked were as follows: "New biological markers of asthma (eg genomics, proteomics and metabolomics) as a tool for diagnosis and/or monitoring," "Prediction of future asthma in preschool children with reasonable accuracy" and "Tools to measure volatile organic compounds (VOCs) in exhaled breath."

A Pediatric Asthma Risk Score to better predict asthma development in young children

BACKGROUND

Asthma phenotypes are currently not amenable to primary prevention or early intervention because their natural history cannot be reliably predicted. Clinicians remain reliant on poorly predictive asthma outcome tools because of a lack of better alternatives.

OBJECTIVE

We sought to develop a quantitative personalized tool to predict asthma development in young children.

METHODS

Data from the Cincinnati Childhood Allergy and Air Pollution Study (n = 762) birth cohort were used to identify factors that predicted asthma development. The Pediatric Asthma Risk Score (PARS) was constructed by integrating demographic and clinical data. The sensitivity and specificity of PARS were compared with those of the Asthma Predictive Index (API) and replicated in the Isle of Wight birth cohort.

RESULTS

PARS reliably predicted asthma development in the Cincinnati Childhood Allergy and Air Pollution Study (sensitivity = 0.68, specificity = 0.77). Although both the PARS and API predicted asthma in high-risk children, the PARS had improved ability to predict asthma in children with mild-to-moderate asthma risk. In addition to parental asthma, eczema, and wheezing apart from colds, variables that predicted asthma in the PARS included early wheezing (odds ratio [OR], 2.88; 95% CI, 1.52-5.37), sensitization to 2 or more food allergens and/or aeroallergens (OR, 2.44; 95% CI, 1.49-4.05), and African American race (OR, 2.04; 95% CI, 1.19-3.47). The PARS was replicated in the Isle of Wight birth cohort (sensitivity = 0.67, specificity = 0.79), demonstrating that it is a robust, valid, and generalizable asthma predictive tool.

CONCLUSIONS

The PARS performed better than the API in children with mild-to-moderate asthma. This is significant because these children are the most common and most difficult to predict and might be the most amenable to prevention strategies.

The analysis of volatile organic compounds in exhaled breath and biomarkers in exhaled breath condensate in children - clinical tools or scientific toys?

Current monitoring strategies for respiratory diseases are mainly based on clinical features, lung function and imaging. As airway inflammation is the hallmark of many respiratory diseases in childhood, noninvasive methods to assess the presence and severity of airway inflammation might be helpful in both diagnosing and monitoring paediatric respiratory diseases. At present, the measurement of fractional exhaled nitric oxide is the only noninvasive method available to assess eosinophilic airway inflammation in clinical practice. We aimed to evaluate whether the analysis of volatile organic compounds (VOCs) in exhaled breath (EB) and biomarkers in exhaled breath condensate (EBC) is helpful in diagnosing and monitoring respiratory diseases in children. An extensive literature search was conducted in Medline, Embase and PubMed on the analysis and applications of VOCs in EB and EBC in children. We retrieved 1165 papers, of which nine contained original data on VOCs in EB and 84 on biomarkers in EBC. These were included in this review. We give an overview of the clinical applications in childhood and summarize the methodological issues. Several VOCs in EB and biomarkers in EBC have the potential to distinguish patients from healthy controls and to monitor treatment responses. Lack of standardization of collection methods and analysis techniques hampers the introduction in clinical practice. The measurement of metabolomic profiles may have important advantages over detecting single markers. There is a lack of longitudinal studies and external validation to reveal whether EB and EBC analysis have added value in the diagnostic process and follow-up of children with respiratory diseases. In conclusion, the use of VOCs in EB and biomarkers in EBC as markers of inflammatory airway diseases in children is still a research tool and not validated for clinical use.

Biomarkers to predict asthma in wheezing preschool children

Wheezing in preschool children is a very common symptom. An adequate prediction of asthma in these children is difficult and cannot be reliably assessed with conventional clinical tools. The study of potential predictive biomarkers in various media, ranging from invasive sampling (e.g. bronchoscopy) to non-invasive sampling (lung function testing and exhaled breath analysis), was comprehensively reviewed. The evolution in biomarker discovery has resulted in an 'omics' approach, in which hundreds of biomarkers in the field of genomics, proteomics, metabolomics, and 'breath-omics' can be simultaneously studied. First, results on gene expression and exhaled breath profiles in predicting an early asthma diagnosis are promising. However, many hurdles need to be overcome before clinical implementation is possible. To reliably predict asthma in a wheezing child, probably a holistic approach is needed, combining clinical information with blood sampling, lung function tests, and potentially exhaled breath analysis. The further development of predictive, non-invasive biomarkers may eventually improve an early asthma diagnosis in wheezing preschool children and assist clinicians in early treatment decision-making.

Exhaled nitric oxide and nasal tryptase are associated with wheeze, rhinitis and nasal allergy in primary school children

Rhinitis and asthma are the most common respiratory diseases in children. We assessed whether airway inflammation markers were associated with nasal allergies and self-reported symptoms of wheeze and rhinitis in 130 children 6-12 year old in an epidemiological context. Independent of sex and age, the fraction of exhaled nitric oxide (FeNO) and nasal mast cell (MC) activation (tryptase ≥ 5 ng/mL) were positively associated with wheeze, rhinitis and with nasal allergy. Nasal eosinophil cationic protein (ECP) and exhaled breath condensate (EBC) markers (pH, 8-isoprostane, interleukin-1β) were not associated with symptoms or with nasal allergy. In conclusion, FeNO and nasal tryptase reflect allergic inflammation in the respiratory system.