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支气管肺发育不良中的基因组学、微生物组学、蛋白质组学和代谢组学。

Genomics, microbiomics, proteomics, and metabolomics in bronchopulmonary dysplasia.

机构信息

Division of Neonatology, Department of Pediatrics, University of Alabama at Birmingham, Women and Infants Center, 176F Suite 9380, 619 South 19th Street, Birmingham, AL 35249-7335, United States.

Department of Pediatrics, Drexel University, Philadelphia, PA, United States.

出版信息

Semin Perinatol. 2018 Nov;42(7):425-431. doi: 10.1053/j.semperi.2018.09.004. Epub 2018 Oct 2.

DOI:10.1053/j.semperi.2018.09.004
PMID:30487069
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8862637/
Abstract

Bronchopulmonary Dysplasia (BPD) is a disorder with a multifactorial etiology and highly variable clinical phenotype. Several traditional biomarkers have been identified, but due to the complex disease phenotype, these biomarkers have low predictive accuracy for BPD. In recent years, newer technologies have facilitated the in-depth and unbiased analysis of 'big data' in delineating the diagnosis, pathogenesis, and mechanisms of diseases. Novel systems-biology based 'omic' approaches, including but not limited to genomics, microbiomics, proteomics, and metabolomics may help define the multiple cellular and humoral interactions that regulate normal as well as abnormal lung development and response to injury that are the hallmarks of BPD.

摘要

支气管肺发育不良(BPD)是一种病因复杂、临床表现高度异质的疾病。已经鉴定出了一些传统的生物标志物,但由于疾病表型复杂,这些生物标志物对 BPD 的预测准确性较低。近年来,新技术促进了“大数据”的深入和无偏分析,有助于描绘疾病的诊断、发病机制和机制。基于新型系统生物学的“组学”方法,包括但不限于基因组学、微生物组学、蛋白质组学和代谢组学,可能有助于确定调节正常和异常肺发育以及对损伤反应的多种细胞和体液相互作用,这些是 BPD 的标志。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51c7/8862637/143dad0b5573/nihms-1064051-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51c7/8862637/143dad0b5573/nihms-1064051-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51c7/8862637/143dad0b5573/nihms-1064051-f0001.jpg

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Children (Basel). 2025 Mar 28;12(4):424. doi: 10.3390/children12040424.
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