Bronchopulmonary dysplasia (BPD), a chronic lung disease predominantly afflicting premature infants, continues to challenge neonatologists and pulmonologists despite decades of research and clinical advances. Once regarded merely as a transient complication confined to the neonatal intensive care unit (NICU) phase, BPD has emerged as a chronic, evolving pathology with lifelong implications. This transformation in understanding necessitates a radical shift from traditional definitions and diagnostic frameworks, underscoring the urgency for precision medicine approaches that can capture the heterogeneous nature of BPD and guide tailored therapeutic interventions.
The historical context of BPD reveals a disease definition initially centered on phenotypic manifestations of oxygen dependency and radiographic abnormalities in preterm infants. While these criteria have served as a clinical shorthand, their limitations are increasingly apparent in the face of emerging data highlighting diverse pathophysiological trajectories. The static, binary models used to classify BPD fail to account for the dynamic progression of pulmonary disease from infancy through adulthood, obscuring critical nuances needed for personalized care.
Advanced longitudinal studies have illuminated that BPD is not a condition restricted to the neonatal period but instead precipitates persistent pulmonary morbidity across the lifespan. Survivors of BPD frequently contend with compromised lung function, increased susceptibility to respiratory infections, and progressive cardiopulmonary sequelae extending well into adolescence and beyond. These insights underscore the imperative to redefine BPD with a lifespan-oriented perspective, integrating variable risk factors, evolving clinical presentations, and long-term outcomes.
One of the formidable challenges in modern BPD research is the identification of meaningful biomarkers that can stratify patients based on distinct underlying pathobiological mechanisms, or endotypes. Unlike phenotypes—which describe observable traits—endotypes delve into the molecular and cellular pathways driving disease, offering the potential for targeted therapeutic strategies. However, despite technological advances in molecular biology and imaging, robust biomarkers that can reliably segregate BPD endotypes remain elusive.
Harnessing the power of precision medicine for BPD necessitates comprehensive, multicenter cohorts that employ deep phenotyping and integrate multi-omic platforms including genomics, transcriptomics, proteomics, and metabolomics. Such integrative data approaches are fundamental to unraveling the complexity of BPD’s heterogeneous manifestations and paving the way for individualized treatment modalities. Early pilot studies combining clinical phenotypes with genomic data have begun to reveal distinct clusters of disease, but larger collaborative networks are essential for validation and clinical translation.
The evolving landscape of BPD research calls for novel trial designs that move beyond traditional endpoints focused narrowly on survival or oxygen dependency at 36 weeks postmenstrual age. Instead, enriched trial designs incorporating longitudinal functional assessments, imaging biomarkers, and patient-centered outcomes will be pivotal. These multidimensional outcomes capture the progressive nature of BPD and better reflect its impact on quality of life and long-term health.
Central to this paradigm shift is the recognition of BPD as a chronic cardiopulmonary disease continuum rather than an isolated neonatal event. Prematurity-induced alterations extend beyond the lungs to encompass the cardiovascular system, with increased risks for pulmonary hypertension, right heart dysfunction, and systemic vascular complications documented in former preterm infants. Integrating cardiopulmonary phenotyping into BPD definitions strengthens the bridge between neonatal care and lifelong surveillance.
Collaborative data networks transcending institutional and geographical boundaries are crucial for achieving the sample sizes and data diversity needed for meaningful precision medicine initiatives. These consortia enable standardized data collection, harmonized biomarker assays, and shared computational pipelines aimed at dissecting disease heterogeneity. By fostering open science and data sharing, these collaborative efforts accelerate discovery and democratize access to advanced diagnostic tools.
Moreover, the integration of artificial intelligence (AI) and machine learning algorithms offers unprecedented opportunities to synthesize multifaceted datasets and identify latent patterns in BPD progression. AI-driven models can assimilate clinical, imaging, and multi-omic data to predict disease trajectories, stratify risk, and personalize therapeutic regimens. Although still in early stages, these computational approaches hold promise for transforming BPD management into a precision-guided endeavor.
The translational pipeline from biomarker discovery to bedside application faces hurdles, including reproducibility of findings, regulatory challenges, and implementation costs. Addressing these issues requires interdisciplinary collaboration among clinicians, researchers, bioinformaticians, and policy makers. Engaging patients and families as partners in research further enriches outcome relevance and adherence to personalized interventions.
Importantly, redefining BPD with a lifespan approach also has profound implications for healthcare systems and policy frameworks. Longitudinal care models incorporating subspecialty follow-up, pulmonary rehabilitation, and psychosocial support are essential to address the multifactorial burden of BPD survivors. Investments in preventive strategies targeting antenatal and early postnatal exposures remain a critical complementary avenue to reduce incidence and severity.
Emerging therapeutic avenues informed by precision medicine insights include modulation of inflammatory pathways, regenerative medicine approaches targeting alveolar repair, and novel pharmacotherapies tailored to specific molecular signatures. These innovative strategies underscore the aspirational goal of not only mitigating symptoms but altering disease course at its root.
In summary, the redefinition of bronchopulmonary dysplasia as a chronic, multifaceted cardiopulmonary disease spanning the lifespan marks a pivotal shift in neonatology and pulmonology. The integration of deep phenotyping, multi-omic data integration, collaborative data networks, and AI-driven analytics chart a compelling path forward. Embracing precision medicine promises to unravel BPD’s complexity, enabling individualized care that can improve outcomes for this vulnerable population from infancy through adulthood. This holistic approach resonates as a clarion call to the scientific community dedicated to transforming the future for survivors of prematurity.
Subject of Research: Bronchopulmonary dysplasia, its evolving definitions, pathophysiology, and precision medicine approaches for individualized therapy.
Article Title: Toward precision for bronchopulmonary dysplasia: Moving past current definitions.
Article References:
Kielt, M.J., Nelin, T.D., Abman, S.H. et al. Toward precision for bronchopulmonary dysplasia: Moving past current definitions. J Perinatol (2026). https://doi.org/10.1038/s41372-025-02539-z
Image Credits: AI Generated
DOI: 05 January 2026
Keywords: Bronchopulmonary dysplasia, BPD, prematurity, chronic lung disease, precision medicine, multi-omics, biomarkers, longitudinal studies, cardiopulmonary disease, neonatal care
