Mendez Kevin M, Kachroo Priyadarshini, Prince Nicole, Huang Mengna, Cote Margaret, Chu Su H, Chen Yulu, Sharma Rinku, Hecker Julian, Chen Liang, Gerszten Robert, Clish Clary, Avila Lydiana, Celedón Juan C, Wheelock Craig E, Weiss Scott T, McGeachie Michael, Broadhurst David I, Kelly Rachel S, Reinke Stacey N, Lasky-Su Jessica A
Brigham and Women's Hospital Channing Division of Network Medicine, Boston, Massachusetts, United States.
Brigham and Women's Hospital Channing Division of Network Medicine, Department of Systems Genetics & Genomics, Boston, Massachusetts, United States.
Am J Respir Crit Care Med. 2025 Feb 18. doi: 10.1164/rccm.202407-1382OC.
Pediatric asthma is heterogeneous, with varied clinical presentations and treatment responses. Metabolomic profiling may uncover shared and unique biological mechanisms across clinical traits that characterize pediatric asthma.
To characterize the varied clinical presentation of pediatric asthma by examining the metabolome's relationship with 22 clinical traits, categorized into 5 phenotypic domains: airway hyperresponsiveness (AHR), atopy, lung function (LF), blood eosinophil (B-EOS), and blood neutrophil (B-NEU).
Metabolomic profiling was conducted on plasma samples from children in the Childhood Asthma Management Program (CAMP) (n=953) and the Genetic Epidemiology of Asthma in Costa Rica Study (GACRS) (n=1,155) studies. We identified domain-specific and multi-domain metabolites using a fixed-effect meta-analysis of generalized linear models between metabolites and 22 clinical traits. Metabolomic Risk Scores (MRSs) were developed to summarize the metabolic processes for each domain at the patient level.
There were 154 unique metabolites significantly associated with at least one of 22 clinical traits (q-value<0.05). and were significant across 4 domains, while 7 metabolites- and -were significant across 3. Notable domain-specific metabolites include for AHR, for lung function, for B-EOS, and for B-NEUT. We then applied the domain-specific MRSs to previously identified patient clusters, enabling a more comprehensive characterization of each endotype.
This study demonstrated the power of the metabolome to capture the heterogeneity in the clinical presentation of pediatric asthma and to develop clinically relevant MRSs that inform our understanding of specific metabotypes to guide targeted treatment approaches.
儿童哮喘具有异质性,临床表现和治疗反应各不相同。代谢组学分析可能揭示出表征儿童哮喘的各种临床特征中共同的和独特的生物学机制。
通过研究代谢组与22种临床特征的关系来表征儿童哮喘的不同临床表现,这些临床特征分为5个表型领域:气道高反应性(AHR)、特应性、肺功能(LF)、血液嗜酸性粒细胞(B-EOS)和血液中性粒细胞(B-NEU)。
对儿童哮喘管理项目(CAMP)(n = 953)和哥斯达黎加哮喘遗传流行病学研究(GACRS)(n = 1155)中儿童的血浆样本进行代谢组学分析。我们使用代谢物与22种临床特征之间广义线性模型的固定效应荟萃分析来识别特定领域和多领域的代谢物。开发了代谢组学风险评分(MRS)以在患者层面总结每个领域的代谢过程。
有154种独特的代谢物与22种临床特征中的至少一种显著相关(q值<0.05)。 和 在4个领域中显著,而7种代谢物—— 和 ——在3个领域中显著。值得注意的特定领域代谢物包括AHR的 、肺功能的 、B-EOS的 和B-NEUT的 。然后我们将特定领域的MRS应用于先前确定的患者聚类,从而能够更全面地表征每种内型。
本研究证明了代谢组学在捕捉儿童哮喘临床表现异质性以及开发临床相关的MRS方面的能力,这些MRS有助于我们理解特定的代谢型,以指导靶向治疗方法。