How does race and ethnicity effect the precision treatment of asthma?

EndoPRS: Incorporating endophenotype information to improve polygenic risk scores for clinical endpoints-A study in asthma

Polygenic risk score (PRS) prediction of complex diseases can be improved by leveraging related phenotypes. This has motivated the development of several multi-trait PRS methods that jointly model genetically correlated traits. However, these methods do not account for vertical pleiotropy, where one trait acts as a mediator for another. Here, we introduce endoPRS, a weighted lasso model that incorporates information from relevant endophenotypes to improve disease risk prediction without making assumptions about the genetic architecture underlying the endophenotype-disease relationship. Through extensive simulation analysis, we demonstrate the robustness of endoPRS in a variety of complex genetic frameworks. We also apply endoPRS to predict the risk of childhood-onset asthma in UK Biobank and All of Us by leveraging a paired genome-wide association study of eosinophil count, a relevant endophenotype. We find that endoPRS significantly improves prediction and transferability compared to many existing PRS methods, including multi-trait PRS methods MTAG and wMT-BLUP, which suggests advantages of endoPRS in real-life clinical settings.

Epigenetic patient stratification via contrastive machine learning refines hallmark biomarkers in minoritized children with asthma

Identifying and refining clinically significant patient stratification is a critical step toward realizing the promise of precision medicine in asthma. Several peripheral blood hallmarks, including total peripheral blood eosinophil count (BEC) and immunoglobulin E (IgE) levels, are routinely used in asthma clinical practice for endotype classification and predicting response to state-of-the-art targeted biologic drugs. However, these biomarkers appear ineffective in predicting treatment outcomes in some patients, and they differ in distribution between racially and ethnically diverse populations, potentially compromising medical care and hindering health equity due to biases in drug eligibility. Here, we propose constructing an unbiased patient stratification score based on DNA methylation (DNAm) and utilizing it to refine the efficacy of hallmark biomarkers for predicting drug response. We developed Phenotype Aware Component Analysis (PACA), a novel contrastive machine-learning method for learning combinations of DNAm sites reflecting biomedically meaningful patient stratifications. Leveraging whole-blood DNAm from Latino (discovery; n=1,016) and African American (replication; n=756) pediatric asthma case-control cohorts, we applied PACA to refine the prediction of bronchodilator response (BDR) to the short-acting β2-agonist albuterol, the most used drug to treat acute bronchospasm worldwide. While BEC and IgE correlate with BDR in the general patient population, our PACA-derived DNAm score renders these biomarkers predictive of drug response only in patients with high DNAm scores. BEC correlates with BDR in patients with upper-quartile DNAm scores (OR 1.12; 95% CI [1.04, 1.22]; P=7.9 e-4) but not in patients with lower-quartile scores (OR 1.05; 95% CI [0.95, 1.17]; P=0.21); and IgE correlates with BDR in above-median (OR for response 1.42; 95% CI [1.24, 1.63]; P=3.9e-7) but not in below-median patients (OR 1.05; 95% CI [0.92, 1.2]; P=0.57). These results hold within the commonly recognized type 2 (T2)-high asthma endotype but not in T2-low patients, suggesting that our DNAm score primarily represents an unknown variation of T2 asthma. Among T2-high patients with high DNAm scores, elevated BEC or IgE also corresponds to baseline clinical presentation that is known to benefit more from biologic treatment, including higher exacerbation scores, higher allergen sensitization, lower BMI, more recent oral corticosteroids prescription, and lower lung function. Our findings suggest that BEC and IgE, the traditional asthma biomarkers of T2-high asthma, are poor biomarkers for millions worldwide. Revisiting existing drug eligibility criteria relying on these biomarkers in asthma medical care may enhance precision and equity in treatment.

Racial bias in recruitment to clinical trials on paediatric asthma

Asthma is now the commonest chronic disease of childhood, but not all children with asthma receive equivalent standards of medical care which influences their clinical outcomes. In this paper we sought to determine the proportion of participants in registered clinical trials relating to paediatric or adolescent asthma over the last decade that were from white and non-white backgrounds. We searched the ClinicalTrials.gov database for all completed interventional studies between the dates 1st January 2011 and 1st January 2021 that were on the topic of 'asthma', and included participants below 18 years of age. Of the 500 studies returned, 208 had results available on the ClinicalTrials.gov website. In total, of the 112,327 patients studied, almost 69 % (77,333) of the patients were described as White or Caucasian, and fewer than 13 % (14,189) were described as Black, African, or African-American. Overall, approximately 30 % of study participants - some 34,207 children - were from non-white backgrounds. To redress this imbalance, researchers designing clinical trials must ensure that their study populations are as representative of the target population for the intervention as possible.

Analysis of the polymorphic variants of ADRB2 gene association with the β2-agonists response in patients with a rare theratype of asthma

Standard asthma therapy includes prescription of β2-agonists. Changes in the functional activity of β2-adrenergic receptor are associated with ADRB2 genepolymorphism and related to the low therapeutic response to β2-agonists. Identification of carriers of the clinically significant gene variants will help to avoidineffective treatment and prescribe an alternative therapy. This study aimed to assess clinical significance of the ADRB2 gene polymorphisms (Arg16Gly andGln27Glu) associated with the therapeutic response to β2-agonists in the group of asthma patients. We subjected a small group of adult nonsmoking patients(n = 21) with moderate asthma (III–IV stage of GINA) to clinical and genetic examination. The group included patients with the new theratype, those that poorlyrespond to β2-adrenergic drugs but significantly to M-cholinergic agonists. The first group included patients responding well to both salbutamol and ipratropiumbromide. The second group was comprised of the patients for whom salbutamol was not effective but who tested positive for response to ipratropium bromide. Theanalysis of distribution of polymorphic variants of Arg16Gly and Gln27Glu revealed no significant relationship between alleles and genotypes and the efficacy of β2-agonists(0.52 for the rs1042713 variant, p = 1.0; 1.0 for the rs1042714 variant, p = 0.74, respectively). The genotype of patients that did not respond to salbutamol waseither Arg16Gly or Gly16Gly. Further studies are needed that would involve a larger number of patients and an expanded list of the tested polymorphic variants.