Daily Respiratory Research Analysis
Three impactful respiratory studies span phenotyping, guidelines, and critical care. A large prospective cohort disentangles preschool wheeze into predominantly nonallergic trajectories with distinct microbiome signatures; ERS/EULAR issue comprehensive evidence-based guidelines for CTD-associated ILD; and a multicenter latent class analysis identifies two ARDS phenotypes after hematopoietic cell transplantation with divergent outcomes.
Summary
Three impactful respiratory studies span phenotyping, guidelines, and critical care. A large prospective cohort disentangles preschool wheeze into predominantly nonallergic trajectories with distinct microbiome signatures; ERS/EULAR issue comprehensive evidence-based guidelines for CTD-associated ILD; and a multicenter latent class analysis identifies two ARDS phenotypes after hematopoietic cell transplantation with divergent outcomes.
Research Themes
- Data-driven respiratory phenotyping and microbiome links
- Evidence-based guidance for CTD-associated interstitial lung disease
- ARDS stratification after hematopoietic cell transplantation
Selected Articles
1. Early-preschool wheeze trajectories are predominantly nonallergic with distinct biologic and microbiome traits.
In 2,902 children from the CHILD cohort, six early-childhood respiratory phenotypes were identified; 88.3% were nonallergic and accounted for most asthma diagnoses and healthcare utilization by age five. Distinct, largely nonoverlapping 1-year microbiome signatures were associated with each phenotype alongside differences in lung function, eosinophils, comorbidities, and growth.
Impact: This study reframes preschool wheeze as predominantly nonatopic with discrete microbiome-linked phenotypes, challenging assumptions that allergic pathways dominate early asthma risk. It provides actionable stratification for early identification and intervention.
Clinical Implications: Nonatopic wheeze phenotypes drive most early-childhood healthcare burden and asthma diagnoses, indicating a need to tailor management beyond eosinophil/IgE-focused strategies and to consider microbiome-informed risk stratification.
Key Findings
- Identified six wheeze/sensitization trajectories in 2,902 children; 88.3% were nonallergic.
- Nonallergic phenotypes accounted for 61.4% of asthma diagnoses by age five and > two-thirds of healthcare utilization.
- Distinct 1-year gut microbiome signatures (from 1,439 infants) associated with each phenotype.
- Phenotypes differed in lung function, blood eosinophils, allergic comorbidities, and weight-for-age z-scores.
Methodological Strengths
- Prospective population-based cohort with longitudinal phenotyping (n=2,902).
- Group-based trajectory modeling integrated with shotgun metagenomics (n=1,439) to link biology and microbiome.
Limitations
- Observational design limits causal inference between microbiome signatures and phenotypes.
- Generalizability may be constrained to similar settings as the CHILD cohort; residual confounding possible.
Future Directions: Validate phenotypes and microbiome signatures in diverse populations; test microbiome-targeted or phenotype-tailored interventions to reduce morbidity.
2. ERS/EULAR clinical practice guidelines for connective tissue diseases associated interstitial lung disease.
ERS and EULAR convened a multidisciplinary task force to produce evidence-graded recommendations for CTD-associated ILD across six diseases, covering screening, diagnosis, monitoring, and treatment. Algorithms are provided, while key evidence gaps (e.g., risk assessment in MCTD/SjD/SLE and pirfenidone outside RA-ILD) are highlighted.
Impact: This guideline standardizes care for CTD-ILD using GRADE across diseases and disciplines, likely influencing practice and research priorities across pulmonology and rheumatology.
Clinical Implications: Provides algorithms for when and how to screen, diagnose, monitor, and treat CTD-ILD (e.g., SSc, RA, myositis, SjD, SLE, MCTD), supporting multidisciplinary decision-making while identifying areas where shared decision-making is needed due to low-certainty evidence.
Key Findings
- GRADE-based recommendations for 25 PICO and 28 narrative questions across six CTDs.
- Standardized algorithms for screening, diagnosis, monitoring, and treatment of CTD-ILD.
- Evidence gaps identified (e.g., progression risk assessment in MCTD/SjD/SLE; pirfenidone in non–RA-ILD).
Methodological Strengths
- Formal GRADE methodology with Evidence to Decision framework.
- Multidisciplinary task force including clinicians, methodologists, and patient representatives.
Limitations
- Several recommendations are based on low-certainty or insufficient evidence.
- Guidelines may require adaptation to local resources and practices; not a substitute for individualized care.
Future Directions: Prioritize trials and prospective studies to fill gaps (e.g., progression risk tools in MCTD/SjD/SLE; antifibrotic use beyond RA-ILD) and validate algorithms in diverse settings.
3. Acute Respiratory Distress Syndrome Phenotypes After Stem Cell Transplantation: A Latent Class Analysis.
Using latent class analysis in 166 post-HCT ARDS patients, two phenotypes emerged: a later-onset, more hypoxemic, hypercapnic, cholestatic class with higher idiopathic pneumonia syndrome and 90-day mortality; and a neutropenic, peri-engraftment class with lower mortality. A six-variable model achieved 0.90 classification accuracy.
Impact: Phenotyping ARDS after HCT with simple clinical variables enables risk stratification and aligns with recognized lung injury syndromes, informing targeted therapies and trial enrichment.
Clinical Implications: At ICU admission, readily available variables can classify post-HCT ARDS into high- versus lower-risk phenotypes, supporting tailored ventilatory, immunomodulatory, and supportive strategies and guiding conversations about prognosis.
Key Findings
- Two ARDS phenotypes post-HCT distinguished by P/F ratio (157 vs 210), Pco2 (41 vs 36 mmHg), and bilirubin (1.4 vs 0.9 mg/dL).
- Class 1 had more allogeneic HCT (70.4%), later occurrence (30 vs 11.9 days), more idiopathic pneumonia syndrome, and higher 90-day mortality (72.8% vs 48.2%).
- A six-variable parsimonious model (WBC, platelets, bilirubin, Pco2, BMI, temperature) classified phenotypes with 0.90 accuracy.
Methodological Strengths
- Multicenter cohort with rigorous latent class analysis and multiple model selection metrics.
- Development of a parsimonious classifier using routinely available variables.
Limitations
- Retrospective design and moderate sample size limit causal inference and external validity.
- No mechanistic biomarkers included; external validation of the classifier is needed.
Future Directions: Externally validate the six-variable model, integrate biomarkers (e.g., cytokines, alveolar injury markers), and test phenotype-targeted therapies in prospective trials.