Association of human adenovirus load and viral genotype diversity with respiratory disease severity in children: a systematic review and meta-analysis

Introduction

Acute respiratory diseases are the leading cause of hospital admissions in children. Among these, human adenoviruses (HAdVs) remain one of the most common viruses in pediatric outpatients worldwide (1) despite the relatively low rate of hospital admissions in patients with this disease (2). HAdV infections are widely distributed in nature and have been reported in various countries and regions (3). They account for a significant proportion of hospital admissions for pneumonia, acute bronchiolitis, and viral respiratory infection in children (4,5). A study in Argentina found that the mortality rate of children with adenoviral acute lower respiratory tract infection was as high as 16.7% (6). Of these cases, 71% were associated with pneumonia, and 86.4% of HAdV-infected children were younger than 5 years (7), suggesting that adenovirus (AdV) infection is a serious threat. Furthermore, a subset of pediatric patients infected with HAdV may develop severe chronic complications, notably post-infectious bronchiolitis obliterans (PIBO) and hemophagocytic syndrome, which represent potentially life-threatening sequelae (8). Timely and accurate assessment and prevention of AdV infection can improve the treatment of HAdV-associated respiratory diseases.

As methods for measuring viral load in respiratory samples have become standardized (9), the viral load of HAdVs has become an important indicator for assessing infection severity in clinical practice. Children with severe AdV pneumonia, especially those with prolonged fever (≥10.5 days) who develop respiratory distress or require invasive mechanical ventilation during the acute phase, are more likely to develop bronchiolitis obliterans (10). Specific genotypes such as HAdV-B3 are associated with increased viral load in respiratory samples and correlate with clinical presentation and outcome (11), with HAdV-1 and HAdV-31 strongly correlated with greater disease severity in children (12). The persistence of viral shedding in children with severe HAdV pneumonia varies by genotype; for instance, viral shedding of HAdV-7 may persist for more than 3 months and decline more slowly than that of HAdV-3. These genotype-specific variations in viral dynamics can inform clinical management strategies and enhance prognostic evaluations (13). Therefore, monitoring viral load kinetics in HAdV pneumonia, especially in severely ill children, is valuable for understanding the disease process, guiding clinical treatment strategies, and evaluating efficacy.

In China, a study of 1,447 children revealed that HAdV-3 and HAdV-7 are the dominant subtypes in childhood influenza-like illnesses (14). The major pathogenic targets of HAdVs include processes such as the cell cycle, mitosis, DNA replication, and intracellular transport of the virus (15). In cases of co-infection with other viruses, HAdV infection primarily presents with fever, cough, and sputum production. Specific genotypes, such as HAdV-B3, may influence disease severity (16). The prevalence trends and pathogenic potential of these genotypes vary by region, suggesting the need for region-specific studies of HAdV genotype diversity. New pathogenic genomic variants, such as HAdV-7, have been identified and associated with severe sequelae and high mortality (17). A study in South America has demonstrated an association between severe respiratory infections and subspecies B1 (18). Additionally, the high serum viral load associated with a severe cytokine storm following HAdV-7 infection may significantly contribute to the poor prognosis in children (19). However, the correlation between different genotypes and disease severity requires further investigation.

This meta-analysis assessed the association among HAdV load, genotypic diversity, and the severity of respiratory disease in children. We conducted a systematic review and quantitative analysis of the literature to address inconsistent findings and explore the role of viral load and the genotypic diversity of HAdVs in childhood respiratory diseases. We hypothesize that specific AdV genotypes are associated with the severity of respiratory disease in children and that HAdV viral load can predict disease severity. We expect this study to provide a more accurate clinical predictor and scientific basis for preventing and treating HAdV infections in children. We present this article in accordance with the MOOSE reporting checklist (available at https://tp.amegroups.com/article/view/10.21037/tp-2024-627/rc).

Methods

Literature search

To comprehensively evaluate the association among HAdV load, viral genotypic diversity, and severity of respiratory disease in children, we conducted a systematic search of Web of Science, PubMed, American Medical Association (AMA), Cochrane Library, China National Knowledge Infrastructure (CNKI), and European Society for Clinical Nutrition and Metabolism (ESPEN) databases to compare relevant studies on the association between respiratory AdV infections of different severity and viral load and genotyping. The main search terms included “adenovirus”, “pneumonia”, “bronchitis”, “viral load”, and “genotyping”, among others. The language of the literature was limited to English or Chinese. The selection of databases was based on their comprehensive coverage of biomedical literature (Web of Science, PubMed, AMA, Cochrane Library) and regional relevance (CNKI for Chinese studies, ESPEN for European context), while study inclusion prioritized alignment with research objectives through keywords addressing disease severity, viral load, and genotyping to ensure representativeness and minimize language bias.

Literature inclusion criteria

The inclusion criteria for the literature were: (I) observational study; (II) comparison of the relationship between different levels of severity and AdV viral load and/or genotyping in children; (III) reporting of AdV viral load, disease severity, and genotyping-related indicators; and (IV) provision of reports of effect indicators or original data from which the corresponding indicators could be calculated.

Exclusion criteria for literature

The exclusion criteria for the literature were: (I) review studies, syntheses, or case reports; (II) no reporting of outcome indicators of respiratory disease severity; and (III) duplicate publications or duplicate data.

Data collection

Two reviewers independently searched and screened the literature to determine the study eligibility based on the inclusion and exclusion criteria. Disagreements were resolved by discussion and consensus. After data extraction, meta-analysis was performed using RevMan 5.3 software (Cochrane, London, UK) to assess the association among disease severity, HAdV load, and genotyping in children.

Quality assessment of the literature

Information including study type, sample size, effect indicator classification, and data were extracted from the included studies. Two researchers, R.Z. and X.Z., extracted the information independently, checked it for consistency, and entered it into the statistical software. The Cochrane Rating Tool was used to assess the risk of bias in the included trials. The assessment criteria were as follows: grade A, low risk of bias; grade B, moderate risk of bias; and grade C, high risk of bias. The process and results of the literature search are detailed in Figure 1.

Figure 1 Flowchart of literature inclusion in this study. CNKI, China National Knowledge Infrastructure; AMA, American Medical Association; ESPEN, European Society for Clinical Nutrition and Metabolism.

Statistical analyses

RevMan 5.3 software and STATA version 15.1 (StataCorp LLC, College Station, TX, USA) were used for the statistical analyses. Viral load was examined using odds ratio (OR) and standard error (SE) as effect sizes, and the association between viral genotyping and children with severe pneumonia was examined using true positive, false positive, true negative, and false negative as effect sizes. Heterogeneity between studies was assessed, with I²=0 indicating no statistical heterogeneity, I²<50% indicating moderate heterogeneity, and I²>50% indicating greater heterogeneity. Funnel plots and Deeks’ method were used to assess the presence of publication bias. Subgroup analyses were performed to assess the robustness of study results according to the study sample size and test method.

Results

Characteristics of the included studies

Twelve studies (13,19-29) published from 2015 to 2024 were ultimately retrieved. The studies covered five countries: China, Israel, Germany, Italy, and Vietnam. Three studies used nested polymerase chain reaction (PCR), eight used real-time fluorescence-based quantitative PCR (qPCR), and one used real-time PCR. The total sample size was 2,194 cases, of which 554 were severe. The relevant indices included four articles on viral load; six articles with a B3 viral type; eight articles with a B7 viral type; and two articles with the C1, C2, and C5 subtypes. The characteristics of each study and other relevant indices are shown in Table 1.

Quality evaluation of the included literature

As shown in Figure 2, most of the 12 articles were low risk and high quality, meeting the requirements for further analyses.

Figure 2 Quality risk assessment of the literature.

Comparison of methodological results

Association between viral load and severe pneumonia

Of the 12 papers, 4 examined viral load, including 158 cases of severe pneumonia, for a total sample size of 626 cases (Figure 3). The I² was 84.7%, indicating high heterogeneity in the literature, with a combined OR of 2.02 [95% confidence interval (CI): 1.64–2.47]. The risk of developing severe pneumonia among groups with variable viral load was statistically significant (Z=6.74; P<0.001). A high viral load increased the risk of severe pneumonia.

Figure 3 Forest plot of the relationship between viral load and the risk of developing severe pneumonia. HR, hazard ratio; CI, confidence interval; IV, pooled results of the four included studies.

Association of B3 subtype with severe pneumonia

Among the infected cases, 360 had severe pneumonia. As determined with Stata/SE 15.1 software, the combined effect sizes were as follows: the pooled sensitivity was 0.42 (95% CI: 0.09–0.85), the pooled specificity was 0.99 (95% CI: 0.95–1.00), the pooled positive likelihood ratio was 34.4 (95% CI: 15.8–74.8), the pooled negative likelihood ratio was 0.58 (95% CI: 0.25–1.35), and the pooled diagnostic OR was 59 (95% CI: 20–170). An asymmetry test (Deeks’ method) yielded a P value of 0.18, suggesting no significant evidence of publication bias. The area under the pooled receiver operating characteristic (ROC) curve was 0.97 (95% CI: 0.95–0.98). See Figure 4 for more details.

Figure 4 Forest plots and funnel plots of the sensitivity and specificity of the B3 subtype and severe pneumonia. (A) Sensitivity and specificity of the B3 subtype to severe pneumonia. (B) SROC curve of B3 subtype severe pneumonia. (C) Funnel plot of the B3 subtype on severe pneumonia. Each circle represents the total effect size of each study. CI, confidence interval; SROC, summary receiver operating characteristic; SENS, sensitivity; SPEC, specificity; AUC, area under the curve; ESS, Epworth sleepiness scale.

Comparison of association between the B7 subtype and severe pneumonia

Of the 12 studies on AdV infection, 8 were related to subtype B7 and included 1,568 children with lung infections, 396 of whom had severe pneumonia. As shown in Figure 5, the sensitivity estimates from each study were relatively dispersed, while the specificity estimates were more clustered. The combined effect sizes, calculated using Stata/SE 15.1 software, were as follows: the pooled sensitivity was 0.71 (95% CI: 0.34–0.92), the pooled specificity was 0.97 (95% CI: 0.90–0.99), the pooled positive likelihood ratio was 26.6 (95% CI: 8.0–88.1), the pooled negative likelihood ratio was 0.30 (95% CI: 0.10–0.88), and the pooled diagnostic OR was 89 (95% CI: 23–344). The area under the combined ROC curve was 0.96 (95% CI: 0.94–0.98). An asymmetry test (Deeks’ method) yielded a P value of 0.74, suggesting no evidence of substantial publication bias. See Figure 5 for more details.

Figure 5 Diagnostic efficacy of the B7 subtype for severe pneumonia. (A) Sensitivity and specificity of the B7 subtype to severe pneumonia. (B) Diagnostic SROC curve of the B7 subtype for severe pneumonia. (C) Funnel plot of the B7 subtype for severe pneumonia. Each circle represents the total effect size of each study. CI, confidence interval; SROC, summary receiver operating characteristic; SENS, sensitivity; SPEC, specificity; AUC, area under the curve; ESS, Epworth sleepiness scale.

Subgroup analyses

Subgroup analysis of viral load

For sample sizes ≤100, the combined OR was 0.88 (95% CI: 0.41–1.90). For sizes >100, the OR was 2.15 (95% CI: 1.74–2.65). When the sample size increased to ≤200, the OR was 3.29 (95% CI: 2.18–4.95), and for >200, it was 1.72 (95% CI: 1.36–2.17). This shows that the combined OR increased with the increase in sample size. However, all CIs included a value of 1, indicating no significant association. The OR for real-time PCR was 0.45 (95% CI: 0.18–1.14). With qPCR, the combined OR increased to 2.18 (95% CI: 1.77–2.69), suggesting that the viral load determined by qPCR had more clinical value. For more details, refer to Table 2.

Subgroup analysis of viral genotyping

Subtype B3 viruses: for sample sizes ≤150, the combined sensitivity was 0.20 (95% CI: 0.13–0.28), and the combined specificity was 0.96 (95% CI: 0.95–0.97). For sample sizes >150, the combined sensitivity increased to 0.48 (95% CI: 0.43–0.53), while the combined specificity was 0.92 (95% CI: 0.85–0.98). For sample sizes ≤200, the combined sensitivity was 0.58 (95% CI: 0.55–0.60), and the combined specificity was 0.86 (95% CI: 0.85–0.87). For sample sizes >200, the combined sensitivity decreased to 0.26 (95% CI: 0.21–0.31), but the combined specificity increased to 0.99 (95% CI: 0.99–1.00). These results suggest a significant association between sample size and test performance, as the CI values did not include 1. In the comparison of assay methods, qPCR showed a combined sensitivity of 0.48 (95% CI: 0.43–0.53) and combined specificity of 0.92 (95% CI: 0.85–0.98). By contrast, nested PCR had a combined sensitivity of 0.20 (95% CI: 0.13–0.28) and combined specificity of 0.96 (95% CI: 0.95–0.97). These findings suggest that real-time qPCR assays for B3 subtype viruses have superior clinical value.

Subtype B7 viruses: for sample sizes ≤120, the combined sensitivity was 0.80 (95% CI: 0.49–0.94), and the combined specificity was 0.95 (95% CI: 0.81–0.99). For sample sizes >120, the combined sensitivity was 0.63 (95% CI: 0.13–0.95), and the combined specificity was 0.98 (95% CI: 0.82–1.00). For sample sizes ≤200, the combined sensitivity was 0.84 (95% CI: 0.56–0.95), and the combined specificity was 0.94 (95% CI: 0.81–0.99). For sample sizes >200, the combined sensitivity was 0.37 (95% CI: 0.29–0.45), and the combined specificity was 0.99 (95% CI: 0.99–1.00). As sample size increased, the combined sensitivity and specificity improved, with no CI values of 1, indicating a significant correlation. Real-time qPCR yielded a combined sensitivity of 0.79 (95% CI: 0.29–0.97) and a specificity of 0.98 (95% CI: 0.85–1.00), while nested PCR showed a combined sensitivity of 0.63 (95% CI: 0.52–0.74) and specificity of 0.91 (95% CI: 0.85–0.97). These results suggest that real-time qPCR for the B7 subtype viruses have superior clinical value. See Table 3 for the detailed results.

Discussion

Early detection and timely intervention of HAdV infections are critical in clinical practice. The nonspecific clinical manifestations of AdV infections and the challenge of early detection in severe cases necessitate a comprehensive assessment (30). Combining viral load, genotype, and relevant laboratory markers could improve the recognition of severe AdV pneumonitis and treatment outcome (31). Our meta-analysis investigated the association among HAdV load, its genotypic diversity, and the severity of respiratory disease in children. The results indicated that disease severity in children increases with rising viral load, in accordance with other clinical observations and research. In the pediatric population, HAdV infection can manifest as a spectrum of conditions ranging from mild upper respiratory tract infections to severe pneumonia, with the latter associated with higher mortality rates and sequelae. Analyses of the diagnostic efficacy of the B3 and B7 virus subtypes for severe pneumonia in the present study revealed high combined sensitivity and specificity. This suggests a potential role for these subtypes in respiratory infections in children, particularly the development of severe pneumonia. This finding offers a crucial diagnostic reference for clinicians treating children with suspected adenoviral infections, aiding in earlier identification and intervention in severe cases. Furthermore, the real-time qPCR method demonstrated high sensitivity and specificity in detecting these two subtypes, potentially making it more suitable for clinical application. This study provides valuable insights into the role of AdV in childhood respiratory infections and may guide clinical diagnosis and the development of therapeutic strategies. Our findings support integrating qPCR-based HAdV subtyping (particularly for B7) into clinical workflows for children with severe respiratory symptoms, as high viral load and B7 detection correlate with worse outcomes. This enables early risk stratification, guiding decisions on antiviral therapy or intensive care allocation, while minimizing unnecessary interventions in low-risk cases through high specificity.

The main similarities and differences between the present study and other studies are detailed below. Our results suggest that high viral loads are associated with the severity of respiratory illness in children. This finding aligns with the studies by Franz et al. (32) and Martin et al. (33). Moreover, Gao et al. (34) found that Mycoplasma pneumoniae pneumonia was more severe in children with HAdV coinfections than in those with single M. pneumoniae alone. Additionally, Isik et al. (35). reported that a higher initial viral load in adenoviral keratoconjunctivitis may predict inflammatory sequelae. The I² value of 90% indicates high heterogeneity in the literature, which may be attributed to differences in sample sizes, regions, study designs, and assay methods across studies. Regarding the specificity and sensitivity of B3 and B7 isoforms, our analyses showed high combined sensitivity and specificity, consistent with the study by Wang et al. (36), which found that HAdV-3 and HAdV-7 were the predominant types in children hospitalized with acute respiratory infections in Beijing. The authors showed that HAdV-7 infections caused a more pronounced inflammatory response, severe pulmonary symptoms, and extended hospitalization than HAdV-3, suggesting a need for further clinical typing of HAdV. Although these results are in line with our findings overall, we could not include the data from the study by Wang et al. (36) due to a lack of specific genotyping information for severe pneumonia cases. Li et al. (37) found that 13.8% (76/552) of patients with acute respiratory infections were HAdV-positive, with the prevalence varying by region: 20.1% in north central areas and 8.2% in eastern areas. Xu et al. (38). reported that among AdV-infected children, only 4% had HAdV-55, while 53% had HAdV-7. HAdV-55 infections were mainly detected in March and April, whereas HAdV-7 infections occurred year-round. Our study also found that real-time qPCR showed high sensitivity and specificity in virus detection. These results are in accordance with the studies by Heim et al. (39), Lin et al. (40), and Wong et al. (41), which highlighted the advantages of real-time fluorescence-based qPCR in detecting multiple pathogens. Qiu et al. (42) demonstrated rapid, differential detection and quantitative determination of HAdV serotypes 2, 3, and 7 using triple real-time qPCR, consistent with our findings. We assessed the publication bias using Deeks’ method, finding no significant bias, which lends credibility to our results. This underscores the importance of considering potential bias in epidemiological studies. Our results align with the existing literature, confirming the association among HAdV load, the B3 and B7 subtypes, and the severity of respiratory disease in children. The findings support the importance of real-time qPCR in clinical applications, contributing to a better understanding and management of adenoviral infections in children.

This study had several methodological limitations that may affect the accuracy and reliability of its findings and conclusions. First, the quantity and quality of available literature restrict the value of the findings. Using an observational study, we could not infer causality or completely exclude the influence of confounding factors. Second, study definitions and adjudication criteria varied widely; for example, the definition of a vomiting episode differed among studies, potentially introducing categorical bias, and was not confirmed by subgroup analyses. Additionally, follow-up lengths varied and were sometimes short, with neonatal adverse events possibly being omitting, thus reducing result accuracy. Third, potential publication bias might have affected the generalizability of the results, despite efforts to ensure comprehensive analyses. Publication bias risk also suggests that the effect sizes might have been overestimated, but this was not quantitatively assessed. Finally, the high study heterogeneity was not thoroughly analyzed or corrected for by a random effects model, which could have reduced precision; meanwhile, unrecorded factors such as pregnancy complications might have confounded the results. Considering the multiple subtypes of HAdV, more comprehensiveness analyses beyond only two subtypes could be performed to explore the relationship between a greater array of subtypes and disease severity. We did not adequately account for other factors that may influence disease severity, such as host immune status, comorbidities, and environmental factors. The study’s limitations—including design and definition issues, incomplete and poor-quality data, and unrecorded or underanalyzed confounders—may compromise its accuracy and reliability. Future studies should address these shortcomings, employ more rigorous methodologies, and collect comprehensive, high-quality data to produce more accurate, objective findings to more reliably inform clinical prevention and treatment rationale.

Conclusions

Using meta-analysis, this study thoroughly investigated the association among HAdV load, the B3 and B7 subtypes, and the severity of respiratory disease in children, providing new insights and scientific evidence for clinical treatment. The results showed a significant association between high viral load and increased risk of severe pneumonia, further confirming the importance of viral load in the assessment of disease severity. Meanwhile, this study also found high combined sensitivity and specificity for the B3 and B7 subtypes, suggesting the potential role of these two subtypes in childhood respiratory infections, particularly in the progression to severe pneumonia. In addition, the real-time qPCR method examined in this study showed high sensitivity and specificity for detecting the B3 and B7 virus subtypes, which may be a critical tool for the clinical diagnosis and the development of therapeutic strategies. The study’s scientific value is that it provides a novel perspective in assessing the impact of viral load and specific subtypes on children’s health using quantitative methods, which enriches the existing body of medical knowledge and provides a new direction for future research.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the MOOSE reporting checklist. Available at https://tp.amegroups.com/article/view/10.21037/tp-2024-627/rc

Peer Review File: Available at https://tp.amegroups.com/article/view/10.21037/tp-2024-627/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://tp.amegroups.com/article/view/10.21037/tp-2024-627/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

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(English Language Editor: J. Gray)