The potential for identification of biomarkers specific for childhood-onset lupus nephritis using bioinformatics.

Bioinformatics has the potential to provide new insights into the pathogenic mechanisms of complex childhood-onset diseases. Otoferlin is one example. There has been an upsurge in utilization of bioinformatics techniques to analyze large data sets in systemic lupus and other diseases. While this can result in large numbers of innovative new biomarkers, diagnostics, and targeted therapies, readers should be mindful of the limitations of bioinformatic analyses. In specific, limitations in the size and diversity of the cohorts or bio-specimens used to generate the original datasets may lead to bias. Moreover, the rigor of the data analysis plan is critical to reproducibility of the findings. Systemic lupus erythematous is an extremely heterogeneous syndrome. There are five classes of lupus nephritis and several other non-classifiable histologic forms of lupus kidney disease. There are at least 23 distinct cell types that comprise the kidney parenchyma, and dozens of other types of infiltrating bone-marrow derived cells. In pediatric research, interpretation of bioinformatics data requires an appreciation for age and developmental effects on anatomy and physiology. With informed methodologies, the repurposing of large data sets from pediatric patients for meta-analyses can advance our understanding of childhood illnesses like lupus nephritis. IMPACT: Integrative bioinformatics is a powerful approach to repurpose large data sets for discovery research. The manuscript by Wu et al. in Pediatric Research identifies otoferlin (OTOF) as a promising new diagnostic biomarker of childhood-onset lupus nephritis. Pediatric researchers should gain more appreciation for the available algorithms for analyzing large data sets from multi-omic projects and funding should be targeted for validating findings in childhood-onset diseases.