Breaking Down Silos in Asthma Research: The Case for an Integrated Approach

Abstract

Asthma is a complex condition with heterogeneous patterns of symptoms underpinned by different underlying pathophysiological mechanisms and treatment responses. Analyses of data from birth cohorts and patient studies, from the subjective hypothesis-testing approach to the data-driven hypothesis-generating approach, have improved the current understanding of asthma’s heterogeneity. Despite the rapid proliferation of new sources of data and increasingly sophisticated methods for data mining and revealing structure, relatively few findings have been translated into clinically actionable solutions for targeted therapeutics or improved patient care. This review focusses on why an integrated approach may be a more powerful catalyst for improved patient outcomes compared with the artificial and imposed dichotomy of hypothesis-generating versus investigator-led subjective approaches. As the factors shaping the development and control of asthma affect individuals dynamically in response to treatment or environmental factors, deeper insights can be garnered through the integration of data with human expertise and experience. The authors describe how integrative approaches may have greater power to provide a more holistic understanding of the pathophysiological mechanisms driving asthma heterogeneity, discussing some of the key methodological challenges that limit the clinical use of findings from asthma research, and highlighting how recent examples of integrative approaches are building bridges to ensure that the power of emerging sources of data, coupled with rigorous scientific scrutiny, can lead to a more nuanced understanding of asthma.