Julian Hecker, Anshul Tiwari, Rinku Sharma, Kevin Mendez, Jiang Li, Sofina Begum, Qingwen Chen, Albert Smith, Juan C Celedón, Scott T Weiss, Rachel S Kelly, Jessica A Lasky-Su, Kelan G Tantisira, Michael McGeachie
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引用次数: 0
Abstract
Asthma poses a significant public health burden. Despite identifying more than a hundred genetic risk loci in genome-wide association studies (GWAS), the underlying functional mechanisms remain poorly understood. Studying omics, especially microRNAs (miRNAs), is a promising approach to facilitate our understanding of the biological pathways of asthma. Here, we performed miRNA expression quantitative trait loci (miRNA-QTL) analyses using whole-genome sequencing and serum-based miRNA expression data from two independent cohorts of children with asthma (Genetic Epidemiology of Asthma in Costa Rica Study (GACRS), (NCT00021840, 2005-06-23) (N = 980, Discovery) and the Childhood Asthma Management Program (CAMP) (NCT00000575, 2005-06-23) (N = 354, Replication)). Our robust discovery analysis identified 28 significant cis-miRNA-QTL associations, where 12 were not reported in three independent miRNA-QTL studies. Three of these 12 signals were replicated in CAMP. The QTLs colocalize with expression and splicing QTL in asthma-relevant tissues and cells, and overlap with asthma-related and blood cell trait GWAS hits.
NPJ Genomic MedicineBiochemistry, Genetics and Molecular Biology-Molecular Biology
CiteScore
9.40
自引率
1.90%
发文量
67
审稿时长
17 weeks
期刊介绍:
npj Genomic Medicine is an international, peer-reviewed journal dedicated to publishing the most important scientific advances in all aspects of genomics and its application in the practice of medicine.
The journal defines genomic medicine as "diagnosis, prognosis, prevention and/or treatment of disease and disorders of the mind and body, using approaches informed or enabled by knowledge of the genome and the molecules it encodes." Relevant and high-impact papers that encompass studies of individuals, families, or populations are considered for publication. An emphasis will include coupling detailed phenotype and genome sequencing information, both enabled by new technologies and informatics, to delineate the underlying aetiology of disease. Clinical recommendations and/or guidelines of how that data should be used in the clinical management of those patients in the study, and others, are also encouraged.