Impact of Human Rhinovirus Types and Viral Load on the Severity of Illness in Hospitalized Children With Lower Respiratory Tract Infections

Xiao, Qiuyan; Zheng, Shouyan; Zhou, Lili; Luo, Ren; Xie, Xiaohong; Deng, Yu; Tian, Daiyin; Zhao, Yongkun; Fu, Zhou; Li, Tingyu; Huang, Aiping; Liu, Enmei

doi:10.1097/inf.0000000000000879

Cited by 34 publications

(32 citation statements)

References 34 publications

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“…In comparison, other reports on the quantification of HRV used only consensus RT-qPCR assays, quantified from standard curves generated from a single HRV genotype, and tested a limited number of HRV genotypes (14)(15)(16). Nevertheless, our findings confirm the results from some of these studies and show that assay quantification ability is linked to target variability and that accurate HRV quantification by a single RT-qPCR assay is not feasible for all HRV genotypes (17,18).…”

Section: Discussionsupporting

confidence: 80%

Superiority of Digital Reverse Transcription-PCR (RT-PCR) over Real-Time RT-PCR for Quantitation of Highly Divergent Human Rhinoviruses

et al. 2017

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Human rhinoviruses (HRV) comprise 3 species representing more than 150 genotypes. As an important human respiratory pathogen, molecular detection is an indispensable tool for diagnosis and surveillance. However, the sequence diversity of HRV genotypes poses challenges for developing robust molecular methods that detect all genotypes with equal efficiencies. This study compares the accuracies of reverse transcription-quantitative PCR (RT-qPCR) and reverse transcription-digital PCR (RT-dPCR) for quantifying HRV RNA using genotype-specific primers and probes and a consensus primer/probe set targeting the 5= noncoding region of HRV. When using consensus primers and probes for the quantification of HRV, RT-dPCR outperformed RT-qPCR by consistently and accurately quantifying HRV RNAs across more genotype groups, despite the presence of up to 2 target-sequence mismatches within the primer or probe binding region. Because it does not rely on amplification efficiency, which can be affected by sequence mismatches in primer/probe binding regions, RT-dPCR may be the optimal molecular method for future HRV quantification studies and for quantitating other viruses with high sequence diversity.KEYWORDS human rhinovirus, digital PCR, qPCR H uman rhinoviruses (HRV) are important human respiratory pathogens that are small positive-sense RNA viruses within the family Picornaviridae. There are more than 150 genotypes of HRV that have been recognized within species A, B, and C of the genus Enterovirus (1). Molecular assays, such as reverse-transcription PCR (RT-PCR), are the most useful methods for detecting HRV in clinical samples (2-4). Most HRV RT-PCR assays target the conserved 5= noncoding region (NCR), which exhibits the greatest sequence homology among the HRV genotypes. However, even in the 5= NCR, consensus primer and probe sets must be designed with degenerate and modified bases or multiple oligonucleotides to amplify all HRV genotypes (5-7).Although qualitative detection of HRV by RT-PCR is currently sufficient for determining HRV infection, accurate quantification of HRV RNA in clinical samples is needed for studies associating HRV viral load with viral transmission and with patient symptoms and outcomes. Viral load studies of other respiratory viruses have shown that a correlation exists between viral load and disease severity (8-10). Accurate quantification of HRV will also be required for evaluating the performances of future antiviral drugs. Real-time RT-PCR assays, when accompanied by the amplification of standard curves (RT-qPCR), can be used to quantify the number of viral copies in a sample. However, RT-qPCR assays using quantification with a consensus HRV primer and probe set may not give accurate results for all genotypes due to amplification inefficiencies caused by base mismatches between the primer and probe sequences and the specific

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Section: Discussionsupporting

confidence: 80%

Superiority of Digital Reverse Transcription-PCR (RT-PCR) over Real-Time RT-PCR for Quantitation of Highly Divergent Human Rhinoviruses

et al. 2017

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“…HRV‐C accounts for the majority of asthma attacks in children and causes more severe attacks than other HRV types and other viruses . In our previous study, we found that HRV infection was associated with asthma in our region . Some authors have demonstrated a close correlation between the HRV viral load and the disease severity in children with lower respiratory tract infections .…”

Section: Introductionsupporting

confidence: 47%

Epidemiological analysis and follow‐up of human rhinovirus infection in children with asthma exacerbation

Zheng

Wang

Luo

et al. 2017

Journal of Medical Virology

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To determine the prevalence of human rhinovirus (HRV) infection in children with acute asthma exacerbations, investigation of HRV viral load and severity of asthma exacerbations is also required. Nasopharyngeal aspirates and swabs were collected and assessed for respiratory viruses. HRV-positive samples were sequenced to identify types and determine viral load. Outpatients with asthma exacerbations underwent follow-up evaluations, their swabs were collected and clinical outcomes were recorded at their next clinic visit 4 weeks later. One hundred forty-three inpatients and 131 outpatients, including 88 patients with asthma exacerbations and 43 controls with stable asthma were recruited. HRV-A was mainly detected in September and February (45.5% and 33.3%, respectively), while HRV-C was mainly detected in November and April (70.0% and 55.6%, respectively). HRV-C was the primary type and was primarily found in inpatients with severe asthma exacerbations. HRV-A viral load in the group of inpatients with severe exacerbations was higher than in the mild and moderate groups (P < 0.001 and P = 0.022). The HRV-A viral load of both inpatients and outpatients was higher than that of HRV-C (P < 0.001 and P = 0.036). The main genotypes were HRV-C53 and HRV-A20 among inpatients, and this genotype caused more severe clinical manifestations. HRV persisted for no more than 4 weeks, and their symptoms or signs of disease were well-controlled well. HRV-C was most frequently detected in asthma exacerbations. HRV-A with high viral load led to severe asthma exacerbations.

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“…Interpersonal variability and the unpredictable nature of respiratory viral infections pose a challenge to surveillance and preparedness programs [175]. Influenza seasons in particular vary with respect to case numbers and disease severity attributable to various viral subtypes and population strata [67,68,113,127]. The prospective monitoring of disease severity associated with laboratory-confirmed diagnoses will help to delineate vulnerable subpopulations expressing disease severity differently compared to the population average.…”

Section: Discussionmentioning

confidence: 99%

Influenza and other respiratory viruses: standardizing disease severity in surveillance and clinical trials

Rath

Conrad

Myles

et al. 2017

Expert Review of Anti-infective Therapy

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Influenza-Like Illness is a leading cause of hospitalization in children. Disease burden due to influenza and other respiratory viral infections is reported on a population level, but clinical scores measuring individual changes in disease severity are urgently needed. Areas covered: We present a composite clinical score allowing individual patient data analyses of disease severity based on systematic literature review and WHO-criteria for uncomplicated and complicated disease. The 22-item ViVI Disease Severity Score showed a normal distribution in a pediatric cohort of 6073 children aged 0-18 years (mean age 3.13; S.D. 3.89; range: 0 to 18.79). Expert commentary: The ViVI Score was correlated with risk of antibiotic use as well as need for hospitalization and intensive care. The ViVI Score was used to track children with influenza, respiratory syncytial virus, human metapneumovirus, human rhinovirus, and adenovirus infections and is fully compliant with regulatory data standards. The ViVI Disease Severity Score mobile application allows physicians to measure disease severity at the point-of care thereby taking clinical trials to the next level.

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Impact of Human Rhinovirus Types and Viral Load on the Severity of Illness in Hospitalized Children With Lower Respiratory Tract Infections

Cited by 34 publications

References 34 publications

Superiority of Digital Reverse Transcription-PCR (RT-PCR) over Real-Time RT-PCR for Quantitation of Highly Divergent Human Rhinoviruses

Superiority of Digital Reverse Transcription-PCR (RT-PCR) over Real-Time RT-PCR for Quantitation of Highly Divergent Human Rhinoviruses

Epidemiological analysis and follow‐up of human rhinovirus infection in children with asthma exacerbation

Influenza and other respiratory viruses: standardizing disease severity in surveillance and clinical trials

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