| Literature DB >> 34882748 |
Laura Olbrich1,2,3, Lisa Stockdale3,4,5, Robindra Basu Roy6, Rinn Song3,4,7, Luka Cicin-Sain8,9, Elizabeth Whittaker10,11, Andrew J Prendergast12,13, Helen Fletcher14, James A Seddon10,11,15.
Abstract
Over 1 million children develop tuberculosis (TB) each year, with a quarter dying. Multiple factors impact the risk of a child being exposed to Mycobacterium tuberculosis (Mtb), the risk of progressing to TB disease, and the risk of dying. However, an emerging body of evidence suggests that coinfection with cytomegalovirus (CMV), a ubiquitous herpes virus, impacts the host response to Mtb, potentially influencing the probability of disease progression, type of TB disease, performance of TB diagnostics, and disease outcome. It is also likely that infection with Mtb impacts CMV pathogenesis. Our current understanding of the burden of these 2 diseases in children, their immunological interactions, and the clinical consequence of coinfection is incomplete. It is also unclear how potential interventions might affect disease progression and outcome for TB or CMV. This article reviews the epidemiological, clinical, and immunological literature on CMV and TB in children and explores how the 2 pathogens interact, while also considering the impact of HIV on this relationship. It outlines areas of research uncertainty and makes practical suggestions as to potential studies that might address these gaps. Current research is hampered by inconsistent definitions, study designs, and laboratory practices, and more consistency and collaboration between researchers would lead to greater clarity. The ambitious targets outlined in the World Health Organization End TB Strategy will only be met through a better understanding of all aspects of child TB, including the substantial impact of coinfections.Entities:
Mesh:
Year: 2021 PMID: 34882748 PMCID: PMC8659711 DOI: 10.1371/journal.ppat.1010061
Source DB: PubMed Journal: PLoS Pathog ISSN: 1553-7366 Impact factor: 6.823
Studies that have evaluated the interaction between TB and CMV.
| Author, year | Population | Location | Type of study | Findings |
|---|---|---|---|---|
| Olaleye, 1990 [ | Adult TB patients | Nigeria | Cross-sectional serological study of CMV prevalence among 161 TB patients, 89 patients other than TB, and 110 healthy donors | Complement fixing antibodies to CMV were higher among TB patients compared with non-TB hospital patients and healthy controls |
| Nagu, 2017 [ | Adult PTB patients | Tanzania | Cross-sectional study of cellular IFN-γ responses to CMV and EBV antigens among 234 TB patients, 213 who survived, and 21 who died at end of treatment | PBMCs from patients who survived (after treatment completion) exhibited significantly stronger IFN-γ responses to CMV ( |
| Amran, 2016 [ | NTM patients and healthy controls | Australia | Cross-sectional serological study among 112 pulmonary NTM patients and 117 controls | Elevated levels of CMV antibodies were found in plasma from patients with pulmonary NTM disease. Exclusion criteria included HIV infection, excessive alcohol consumption and smoking. Total IgG levels were investigated with no association with anti-CMV antibody levels |
| Sirenko, 2003 [ | Children and adolescents | Russia | Cross-sectional study of 65 children and adolescents with respiratory TB | TB cases were 3 times as likely to be infected with CMV than non-TB individuals. Severity of TB disease was associated with increased CMV antibody levels compared with mild cases of TB |
| Fletcher, 2016 [ | Infants and adolescents | South Africa | Nested case–control study from a Phase 2b efficacy study of TB vaccine candidate MVA85A. Study included 53 TB case infants and 205 matched controls. Independent adolescent cohort used to verify findings | Association of activated HLA-DR+ CD4+ T cells and risk of TB disease. Positive correlation between T-cell activation and CMV IFN-γ response |
| Muller, 2019 [ | Infants and adolescents | South Africa | Cellular IFN-γ responses to CMV antigens. Same population as [ | A CMV-specific IFN-γ response was associated with CD8+ T-cell activation and increased risk of developing TB disease and shorter time to TB diagnosis |
| Stockdale, 2018 [ | All ages PTB | Uganda | Cross-sectional serological study of CMV IgG levels in 2,174 individuals in rural Uganda, 27 PTB cases | CMV seropositivity was 83% by 1 year of age, increasing to 95% by 5 years. Female sex, HIV positivity and PTB were associated with an increase in CMV IgG levels in adjusted analyses |
| Stockdale, 2019 [ | All ages PTB | Uganda | Cross-sectional serological study of CMV IgG levels in 2,189 individuals in rural Uganda, 27 PTB cases. Same population as [ | Higher CMV IgG levels (used as a measure of CMV exposure) were associated with lower levels of some antimycobacterial antibodies, but no increase in total IgG. HIV infection was associated with a decrease in all antimycobacterial antibodies measured and with an increase in total IgG. Analyses were adjusted for age and sex |
| Stockdale, 2020 [ | All ages | Uganda | Nested case–control study (nested within [ | IgG response to CMV, but not Epstein–Barr or herpes simplex virus, was associated with increased risk of active TB disease up to 10 years before diagnosis. Individuals with medium anti-CMV IgG were 2.8 times more likely to have PTB ( |
CMV, cytomegalovirus; EBV, Epstein–Barr virus; IFN, interferon; PBMC, peripheral blood mononuclear cells; PTB, pulmonary tuberculosis; NTM, nontuberculous mycobacteria; TB, tuberculosis.
Understanding the burden for CMV–TB interaction.
| Question | Knowledge gap (summary) | Potential study designs | Parameters and samples to be evaluated |
|---|---|---|---|
| How prevalent are CMV–TB coinfections, and what are risk factors for these infections? | - Quantifying the burden, timing, and outcome of TB–CMV coinfections across different sites and in different risk groups- Impact of co-factors on CMV–TB prevalence- Identifying individual risk factors associated with TB–CMV coinfection- Identifying individual characteristics associated with poor outcome | - Systematic review of existing literature- Cross-sectional and longitudinal cohorts (observational, diagnostic, and randomised intervention studies in humans nested within well-characterised TB cohorts) to quantify prevalence and risk factors for CMV–TB coinfection- Modelling studies to evaluate the number of deaths from TB–CMV coinfections, given number of cases, the proportion diagnosed, and expected mortality treated and untreated | Acute versus latent infection (CMV)- Viral detection: whole blood (EDTA) for viral load (PCR), respiratory specimen, and others- Serology (plasma/serum): quantitative IgG, IgM, and IgG avidity |
| How do TB, CMV, and HIV interact? | - Impact of HIV on prevalence of CMV–TB coinfections and disease course- Impact of CMV in HIV-infected on TB progression and clinical presentation- Impact of CMV–TB coinfection on course of HIV | - In vitro models including isolated cell populations and mechanistic models- Observational, diagnostic, and randomised intervention studies in humans- In vivo models including mouse and nonhuman primate coinfection- Longitudinal cohorts from varying geographical areas and with different patient populations | Acute versus latent infection (CMV)- Viral detection: whole blood (EDTA) for viral load (PCR), respiratory specimen, and others- Serology (plasma/serum): quantitative IgG, IgM, and IgG avidity- Evidence for exacerbation of TB disease or activation of latent TB infection in CMV/MTB coinfected animals |
CMV, cytomegalovirus; PCR, polymerase chain reaction; TB, tuberculosis.
Understanding the underlying pathogenesis and immunology of CMV–TB interaction.
| Question | Knowledge gap (summary) | Potential study designs | Parameters and samples to be evaluated |
|---|---|---|---|
| Does CMV impact the host response to | - Mechanisms through which CMV impacts acquisition of, and progression to, TB disease (or vice versa)- Evaluation of effects of one infection on the immune response to the other (direct versus indirect)- Mycobacterial or viral characteristics: impact of different strain types of | - In vitro models including isolated cell populations and mechanistic models- Mechanistic models based on both animal models and human specimens from affected populations to study underlying mechanisms, but also as a tool for evaluation of further hypothesis- Immunological studies characterising immune response (esp. T-cell response and activation; host omics—transcriptomics, proteomics, and metabolomics) | Animal model- Dynamics of T-cell and antibody responses specific for CMV and MTB in coinfected animals- Quantification of CMV and MTB in lung, spleen, lymph nodes, and other tissues of coinfected animals- Impact of CMV on myeloid inflammatory responses in animal models |
| Does CMV impact the natural history and pathogenesis of TB? | - Correlation between CMV DNA and progression to TB disease- Impact of relative timing of CMV and TB infection on disease progression- Description of relative risk of TB progression in CMV–seropositive children | - Observational studies in humans- Longitudinal cohorts from varying geographical areas and with different patient populations to characterise which patients develop CMV–TB coinfections (risk factors) | Acute versus latent infection (CMV)- Viral detection: whole blood (EDTA) for viral load (PCR), respiratory specimen and others- Serology (plasma/serum): IgG, IgM |
CMV, cytomegalovirus; PCR, polymerase chain reaction; TB, tuberculosis.
Understanding the clinical impact of CMV–TB interaction.
| Question | Knowledge gap (summary) | Potential study designs | Parameters and samples to be evaluated |
|---|---|---|---|
| Does CMV impact the severity of childhood TB? | Morbidity:- Frequency of severe clinical presentation in CMV–positive versus CMV–negative children- Association of CMV positivity with other morbidities that influence TB presentation (HIV and malnutrition) | - Systematic review of existing literature- Autopsy studies of deaths from clinical TB/pulmonary infections, etc.- Observational, diagnostic, and randomised intervention studies in humans- Longitudinal cohorts from varying geographical areas and with different patient populations to characterise which patients develop CMV–TB coinfections (risk factors)- Using biobanked clinical samples from TB cohorts | Acute versus latent infection (CMV)- Viral detection: Whole blood (EDTA) for viral load (PCR), respiratory specimen and others- Serology (plasma/serum): IgG, IgM |
| How does CMV affect the way child TB is diagnosed? | - Reliable and feasible reference standards for both CMV and TB- Impact of CMV on disease presentation and diagnosis of children with TB- Diagnostics needed: | - Observational, diagnostic, and randomised intervention studies in humans | Acute versus latent infection (CMV)- Viral detection: Whole blood (EDTA) for viral load (PCR), respiratory specimen and others- Serology (plasma/serum): IgG, IgM |
CMV, cytomegalovirus; PBMC, peripheral blood mononuclear cell; PCR, polymerase chain reaction; TB, tuberculosis.
Interventions that might reduce the impact of CMV on TB progression from infection to disease.
| Question | Knowledge gap (summary) | Potential study designs | Parameters and samples to be evaluated |
|---|---|---|---|
| Identifying interventions | - Identifying easy-to-implement interventions (e.g., parenting practices around handwashing and avoiding kissing, etc.) | - Systematic review of existing literature- | Acute versus latent infection (CMV) |
| Evaluating interventions | - Impact of easy-to-implement intervention on CMV prevalence and its influence on TB epidemiology (e.g., parenting practices around handwashing, kissing, etc.) | - Systematic review of existing literature | Acute versus latent infection (CMV) |
CMV, cytomegalovirus; PCR, polymerase chain reaction; TB, tuberculosis.