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A chemokine gene expression signature derived from meta-analysis predicts the pathogenicity of viral respiratory infections.

ABSTRACT: BACKGROUND:During respiratory viral infections host injury occurs due in part to inappropriate host responses. In this study we sought to uncover the host transcriptional responses underlying differences between high- and low-pathogenic infections. RESULTS:From a compendium of 12 studies that included responses to influenza A subtype H5N1, reconstructed 1918 influenza A virus, and SARS coronavirus, we used meta-analysis to derive multiple gene expression signatures. We compared these signatures by their capacity to segregate biological conditions by pathogenicity and predict pathogenicity in a test data set. The highest-performing signature was expressed as a continuum in low-, medium-, and high-pathogenicity samples, suggesting a direct, analog relationship between expression and pathogenicity. This signature comprised 57 genes including a subnetwork of chemokines, implicating dysregulated cell recruitment in injury. CONCLUSIONS:Highly pathogenic viruses elicit expression of many of the same key genes as lower pathogenic viruses but to a higher degree. This increased degree of expression may result in the uncontrolled co-localization of inflammatory cell types and lead to irreversible host damage.

SUBMITTER: Chang ST

PROVIDER: S-EPMC3297540 | biostudies-literature | 2011 Dec

REPOSITORIES: biostudies-literature

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A chemokine gene expression signature derived from meta-analysis predicts the pathogenicity of viral respiratory infections.

Chang Stewart T ST Tchitchek Nicolas N Ghosh Debashis D Benecke Arndt A Katze Michael G MG

BMC systems biology 20111222

<h4>Background</h4>During respiratory viral infections host injury occurs due in part to inappropriate host responses. In this study we sought to uncover the host transcriptional responses underlying differences between high- and low-pathogenic infections.<h4>Results</h4>From a compendium of 12 studies that included responses to influenza A subtype H5N1, reconstructed 1918 influenza A virus, and SARS coronavirus, we used meta-analysis to derive multiple gene expression signatures. We compared th ...[more]

PMID: 22189154

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Project description:With the global over 60-year-old population predicted to more than double over the next 35 years, caring for this aging population has become a major global healthcare challenge. In 2016 there were over 1 million deaths in >70 year olds due to lower respiratory tract infections; 13-31% of these have been reported to be caused by viruses. Since then, there has been a global COVID-19 pandemic, which has caused over 2.3 million deaths so far; increased age has been shown to be the biggest risk factor for morbidity and mortality. Thus, the burden of respiratory viral infections in the elderly is becoming an increasing unmet clinical need. Particular challenges are faced due to the interplay of a variety of factors including complex multimorbidities, decreased physiological reserve and an aging immune system. Moreover, their atypical presentation of symptoms may lead to delayed necessary care, prescription of additional drugs and prolonged hospital stay. This leads to morbidity and mortality and further nosocomial spread. Clinicians currently have limited access to sensitive detection methods. Furthermore, a lack of effective antiviral treatments means there is little incentive to diagnose and record specific non-COVID-19 viral infections. To meet this unmet clinical need, it is first essential to fully understand the burden of respiratory viruses in the elderly. Doing this through prospective screening research studies for all respiratory viruses will help guide preventative policies and clinical trials for emerging therapeutics. The implementation of multiplex point-of-care diagnostics as a mainstay in all healthcare settings will be essential to understand the burden of respiratory viruses, diagnose patients and monitor outbreaks. The further development of novel targeted vaccinations as well as anti-viral therapeutics and new ways to augment the aging immune system is now also essential.The reviews of this paper are available via the supplemental material section.

Project description:IntroductionBetter characterisation of the epidemiological data on respiratory viral infections among people with acute respiratory tract infection (ARTI) can help to implement efficient strategies to curb the burden of ARTI in Africa. We will conduct a systematic review and meta-analysis to determine the prevalence and factors associated with respiratory viral infection in people of all ages with ARTI residing in Africa.MethodsThis work will include cross-sectional studies published between January 1, 2000 and December 31, 2017, without any language restriction, on populations residing in African countries. We will consider studies that reported the prevalence of respiratory viruses in people with ARTI confirmed by a polymerase chain reaction technique. We will be searching PubMed, Embase, African Journals Online, Web of Science, and Global Index Medicus. The selection of relevant studies, extraction of data, and evaluation of the quality of the articles will be carried out independently by two review authors, and the discrepancies will be resolved by consensus or intervention of a third author. The heterogeneity of the studies will be assessed using the χ2 test on Cochrane's Q statistic. Publication bias will be assessed by the Egger test. Studies will be pooled using a random-effect meta-analysis model. Results will be presented by age group and sub-region of Africa. Using meta-regression models, we will identify factors associated with viral infections in people with ARTI.DiscussionThis systematic review and meta-analysis is based on published data and therefore does not require ethical approval. This work will serve as a basis for the development of strategies for prevention and control ARTI in Africa and will also serve to identify data gaps and guide future investigations. The final report will be published in peer-reviewed journals as a scientific article and presented in workshops, conferences, and scientific conferences.Systematic review registrationPROSPERO, CRD42018088261 .

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A chemokine gene expression signature derived from meta-analysis predicts the pathogenicity of viral respiratory infections.

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A chemokine gene expression signature derived from meta-analysis predicts the pathogenicity of viral respiratory infections.

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