A recent study published in JAMA offers new insights into asthma endotypes in youths aged 6 to 20 years, using nasal transcriptomic profiles to identify distinct disease subtypes and their association with clinical and immunological characteristics. This research highlights the complexity of asthma in racially and ethnically diverse populations and underscores the need for personalized approaches to asthma treatment.
Background: Asthma in Racially and Ethnically Minoritized Youths
Asthma is the most common chronic respiratory condition in children, with rates particularly high among racial and ethnic minorities in the United States. Puerto Rican and non-Hispanic Black youths, in particular, experience higher rates of asthma-related emergency department visits compared to non-Hispanic White youths. While much of asthma research has focused on T helper 2 (T2)-high asthma, characterized by eosinophilic inflammation and high levels of interleukins (IL)-4, IL-5, and IL-13, less is known about other asthma subtypes, particularly T2-low asthma. These include T17-high asthma and paucigranulocytic asthma, which remain poorly understood and under-researched, especially in underserved populations.
Addressing these knowledge gaps is essential for developing more effective diagnostic and therapeutic strategies for diverse youth populations.
Study Overview: Leveraging Nasal Transcriptomics
The study utilized data from three significant investigations to analyze asthma endotypes using nasal RNA profiles from children and adolescents. These studies aimed to examine the molecular underpinnings of asthma across diverse populations, using transcriptomic analysis to identify distinct asthma subtypes.
Stress and Treatment Response in Puerto Rican and African American Children with Asthma (STAR): Conducted between 2018 and 2022, this study focused on youths aged 8-20 years from Puerto Rico and Pittsburgh. Participants underwent six-week responses to inhaled corticosteroids (ICS), alongside clinical assessments, including spirometry, blood tests, and nasal RNA sequencing.
Epigenetic Variation and Childhood Asthma in Puerto Ricans (EVA-PR): This study, conducted from 2014 to 2017, focused specifically on Puerto Rican youths aged 9-20 years. Participants provided nasal samples for gene expression analysis, and similar clinical data collection was performed as in the STAR study.
Vitamin D Kids Asthma (VDKA): This 48-week trial (2016-2019) investigated the effects of vitamin D3 supplementation on children aged 6-16 years with severe asthma. As an ancillary component, nasal samples were collected for transcriptomic analysis.
These studies received ethical approval and provided data that helped researchers identify T2 and T17 asthma endotypes across diverse youth populations.
Study Findings: Identifying Asthma Endotypes Through Nasal RNA Profiles
The analysis involved 459 participants with asthma, drawn from the three studies: STAR (n = 156), EVA-PR (n = 237), and VDKA (n = 66). These cohorts represented a range of demographic and clinical characteristics, with EVA-PR exclusively involving Puerto Rican participants, while STAR and VDKA were predominantly composed of African American or non-Hispanic Black participants.
The mean age of participants varied, with the youngest cohort being VDKA (mean age: 10.3 years), followed by STAR (14.2 years) and EVA-PR (15.4 years). Overweight or obesity was prevalent across all groups, affecting between 45.6% and 65.4% of participants, and most participants were insured through Medicaid or other forms of medical assistance, with only 1-4% uninsured.
Using K-means clustering of nasal transcriptomic profiles, the researchers identified three distinct asthma endotypes across the cohorts:
- T2-high (22.7%–29.1%)
- T17-high (35.0%–47.0%)
- T2-low/T17-low (30.3%–37.8%)
The study revealed that participants with T2-high asthma exhibited higher levels of total IgE, eosinophils, and allergen sensitization compared to those with T2-low profiles. Interestingly, while many participants in the T2-low group also exhibited allergen-specific IgE positivity (50% to 73.3%), they did not show the same elevated eosinophil levels or T2 cytokine signatures typical of T2-high asthma.
Clinical Findings Across Cohorts
The study’s clinical findings varied depending on the cohort. In the STAR cohort, T2-high participants were more likely to have allergic rhinitis, higher household incomes, and a higher number of asthma-related emergency visits. T17-high participants tended to be younger. Obesity was associated with T2-low profiles in the STAR and EVA-PR cohorts, but in VDKA, obesity was linked to T2-high profiles.
Importantly, lung function measures did not differ significantly across the asthma endotypes, suggesting that molecular factors, rather than just lung function, contribute to asthma severity and treatment response.
Biomarker and Gene Expression Analysis
The study conducted biomarker analysis in the STAR cohort, establishing cutoff values for identifying T2-high profiles based on total IgE (≥417.5 IU/mL), eosinophils (≥210.4 cells/μL), and fractional exhaled nitric oxide (FeNO ≥32.5 ppb). The researchers also developed a decision tree model integrating these biomarkers to improve the predictive accuracy for identifying T2-high asthma.
Differential gene expression analysis identified 3,516 genes associated with T2-high asthma, with a particular focus on IL-13 signaling. For T17-high asthma, 2,494 genes were associated, emphasizing cytokine and interferon-γ pathways. Key genes identified included FPR1, TREM1, and IL23A, suggesting novel therapeutic targets for T17-high asthma.
Conclusion: Implications for Precision Medicine
This study underscores the clinical and molecular diversity of asthma endotypes, particularly in racially and ethnically minoritized youth populations. It highlights the need for personalized approaches to asthma treatment that account for the varying molecular mechanisms underlying the disease.
The study also revealed that T2-low asthma endotypes, including T17-high and T2-low/T17-low profiles, were more prevalent than T2-high asthma among these youth populations. The use of single biomarkers like IgE and eosinophils for identifying T2-high asthma proved to be limited, but a decision tree model integrating IgE and FeNO improved prediction accuracy.
Furthermore, novel therapeutic targets for T17-high asthma, including FPR1, TREM1, and IL23A, were identified, offering new avenues for precision treatment in asthma care. These findings pave the way for endotype-specific treatments, advancing personalized medicine strategies in managing asthma and improving outcomes for diverse populations.
Final Thoughts
This study provides critical insights into the molecular underpinnings of asthma in youths and emphasizes the importance of considering endotype-specific approaches to asthma treatment. As asthma care moves toward precision medicine, these findings will be pivotal in designing tailored interventions that more effectively address the diverse needs of young patients, especially those from underserved communities.
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