Transcriptomics for child and adolescent tuberculosis.
Transcriptomics for child and adolescent tuberculosis.
复制标题
儿童和青少年结核病的转录组学。
DOI:
10.1111/imr.13116
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发表时间:
2022-08
影响因子:
8.7
通讯作者:
中科院分区:
文献类型:
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作者:
Tuberculosis (TB) in humans is caused by Mycobacterium tuberculosis (Mtb). It is estimated that 70 million children (<15 years) are currently infected with Mtb, with 1.2 million each year progressing to disease. Of these, a quarter die. The risk of progression from Mtb infection to disease and from disease to death is dependent on multiple pathogen and host factors. Age is a central component in all these transitions. The natural history of TB in children and adolescents is different to adults, leading to unique challenges in the development of diagnostics, therapeutics, and vaccines. The quantification of RNA transcripts in specific cells or in the peripheral blood, using high‐throughput methods, such as microarray analysis or RNA‐Sequencing, can shed light into the host immune response to Mtb during infection and disease, as well as understanding treatment response, disease severity, and vaccination, in a global hypothesis‐free manner. Additionally, gene expression profiling can be used for biomarker discovery, to diagnose disease, predict future disease progression and to monitor response to treatment. Here, we review the role of transcriptomics in children and adolescents, focused mainly on work done in blood, to understand disease biology, and to discriminate disease states to assist clinical decision‐making. In recent years, studies with a specific pediatric and adolescent focus have identified blood gene expression markers with diagnostic or prognostic potential that meet or exceed the current sensitivity and specificity targets for diagnostic tools. Diagnostic and prognostic gene expression signatures identified through high‐throughput methods are currently being translated into diagnostic tests.
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影响因子:
3.7
作者:
Dangor Z;Izu A;Moore DP;Nunes MC;Solomon F;Beylis N;von Gottberg A;McAnerney JM;Madhi SA
通讯作者:
Madhi SA
影响因子:
4.6
作者:
Bayaa R;Ndiaye MDB;Chedid C;Kokhreidze E;Tukvadze N;Banu S;Uddin MKM;Biswas S;Nasrin R;Ranaivomanana P;Raherinandrasana AH;Rakotonirina J;Rasolofo V;Delogu G;De Maio F;Goletti D;Endtz H;Ader F;Hamze M;Ismail MB;Pouzol S;Rakotosamimanana N;Hoffmann J;HINTT working group within the GABRIEL network
通讯作者:
HINTT working group within the GABRIEL network
影响因子:
64.8
作者:
通讯作者:
--
影响因子:
1.8
作者:
Carrillo-Avila, J. A.;de la Puente, R.;Aguilar-Quesada, R.
通讯作者:
Aguilar-Quesada, R.
影响因子:
12.3
作者:
Conesa A;Madrigal P;Tarazona S;Gomez-Cabrero D;Cervera A;McPherson A;Szcześniak MW;Gaffney DJ;Elo LL;Zhang X;Mortazavi A
通讯作者:
Mortazavi A