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

作者信息

Gorla Aditya, Witonsky Jonathan, Elhawary Jennifer R, Chen Zeyuan Johnson, Mefford Joel, Perez-Garcia Javier, Huntsman Scott, Hu Donglei, Eng Celeste, Woodruff Prescott G, Sankararaman Sriram, Ziv Elad, Flint Jonathan, Zaitlen Noah, Burchard Esteban, Rahmani Elior

机构信息

Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, USA.

Division of Allergy, Immunology, and Bone Marrow Transplant, Department of Pediatrics, University of California San Francisco, San Francisco, CA, USA.

出版信息

Res Sq. 2024 Sep 13:rs.3.rs-5066762. doi: 10.21203/rs.3.rs-5066762/v1.


DOI:10.21203/rs.3.rs-5066762/v1
PMID:39315258
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11419268/
Abstract

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.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1689/11419268/57c512d7adc3/nihpp-rs5066762v1-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1689/11419268/52edc361fc5f/nihpp-rs5066762v1-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1689/11419268/57c512d7adc3/nihpp-rs5066762v1-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1689/11419268/52edc361fc5f/nihpp-rs5066762v1-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1689/11419268/57c512d7adc3/nihpp-rs5066762v1-f0002.jpg

相似文献

[1]
Epigenetic patient stratification via contrastive machine learning refines hallmark biomarkers in minoritized children with asthma.

Res Sq. 2024-9-13

[2]
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[3]
[Standard technical specifications for methacholine chloride (Methacholine) bronchial challenge test (2023)].

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[4]
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[5]
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[6]
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Ann Allergy Asthma Immunol. 2023-8

[7]
Epigenomic response to albuterol treatment in asthma-relevant airway epithelial cells.

Clin Epigenetics. 2023-10-3

[8]
Whole-Genome Sequencing of Pharmacogenetic Drug Response in Racially Diverse Children with Asthma.

Am J Respir Crit Care Med. 2018-6-15

[9]
Efficacy and safety of once-daily single-inhaler triple therapy (FF/UMEC/VI) versus FF/VI in patients with inadequately controlled asthma (CAPTAIN): a double-blind, randomised, phase 3A trial.

Lancet Respir Med. 2021-1

[10]
A genome-wide association study of bronchodilator response in Latinos implicates rare variants.

J Allergy Clin Immunol. 2013-8-29

本文引用的文献

[1]
Decoding the role of DNA methylation in allergic diseases: from pathogenesis to therapy.

Cell Biosci. 2024-7-4

[2]
Lnc-Clic5 as a sponge for miR-212-5p to inhibit cow barn PM-induced apoptosis in rat alveolar macrophages.

Toxicology. 2024-5

[3]
Genetic drivers of heterogeneity in type 2 diabetes pathophysiology.

Nature. 2024-3

[4]
Clinical Response and Remission in Patients With Severe Asthma Treated With Biologic Therapies.

Chest. 2024-2

[5]
Real-world characteristics of "super-responders" to mepolizumab and benralizumab in severe eosinophilic asthma and eosinophilic granulomatosis with polyangiitis.

ERJ Open Res. 2023-10-30

[6]
A cost comparison of benralizumab, mepolizumab, and dupilumab in patients with severe asthma: A US third-party payer perspective.

J Manag Care Spec Pharm. 2023-11

[7]
Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine.

Nat Med. 2023-10

[8]
Clinical Asthma Remission Obtained with Biologics in Real Life: Patients' Prevalence and Characteristics.

J Pers Med. 2023-6-20

[9]
Can we predict who will benefit most from biologics in severe asthma? A post-hoc analysis of two phase 3 trials.

Respir Res. 2023-5-2

[10]
A Race-neutral Approach to the Interpretation of Lung Function Measurements.

Am J Respir Crit Care Med. 2023-3-15

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