Phenotypic and genetic evaluation of children’s interstitial lung diseases

Diagnosing and classifying childhood interstitial lung disease (chILD) remains challenging due to its rarity and non-specific clinical presentation, often overlapping with more common respiratory conditions. Historically, diagnosis and classification have relied heavily on invasive procedures such as bronchoalveolar lavage and lung biopsies. However, these approaches frequently fail to identify the underlying aetiology, limiting treatment options to symptomatic management. Over the past decade, advances in genetic testing transformed the diagnostic landscape. A large retrospective study of 1,686 children with ILD demonstrated that broad genetic testing, substantially increased diagnostic yield and reduced the need for invasive procedures. Through integrative analysis of clinical, radiological, and molecular data, this work has expanded the known genetic spectrum of chILD – in most cases by identifying known systemic diseases and broaden their clinical spectrum to include ILD manifestations. In addition, the phenotypic range of FINCA syndrome, once defined by fatal ILD, has been extended to include children beyond infancy presenting primarily with neurological impairment rather than a severe respiratory phenotype. Furthermore, novel disease mechanisms were uncovered, such as pathogenic variants in CAPNS1 gene associated with pulmonary arterial hypertension. Among genetically analysed individuals, over half received a molecular diagnosis, and those recent discoveries contributed to a 3.6% increase in diagnostic yield. The study also highlighted the value of standardized phenotyping using Human Phenotype Ontology (HPO) terms to capture comorbidities and predict underlying systemic diseases. The consistent language allows the identification of genotype-specific phenotypic patterns and is expected to support future diagnostic processes through automated systems and artificial intelligence. Despite the progress within genetic analysis, a substantial proportion of patients still lack a definitive genetic diagnosis, often due to limitations of exome sequencing, which may miss single-exon deletions or duplications, mosaic variants, or non-coding alterations. Genome sequencing offers a more comprehensive alternative with the potential to close the diagnostic gap further. The early integration of comprehensive genetic testing into clinical workflows not only improves diagnostic precision and enables targeted therapeutic strategies but also lays the foundation for further expansion of genetic characterization in chILD in the future.