Introduction Respiratory pathogens such as influenza viruses may play an influential role in the ... more Introduction Respiratory pathogens such as influenza viruses may play an influential role in the pathogenesis of TB by negatively affecting immunity against Mycobacterium tuberculosis (MTB) We discovered and validated a transcriptomic signature of risk (SOR), based on mRNA expression of 11 IFN stimulated genes (ISG), which prospectively differentiates between incident TB cases and healthy controls The SOR score is computed from expression abundance of multiple ISG transcript pairs in peripheral blood, whereby each pair functions as a ?vote? for or against TB risk We aimed to identify respiratory pathogens other than MTB that might also associate with this SOR score and test whether the SOR score differentiates between individuals with and without respiratory pathogens Methods We conducted a nested cross-sectional study of the upper respiratory tract microbiome Upon consent, participants were consecutively enrolled into the study and provided one nasopharyngeal, one oropharyngeal and a PAXgene blood sample Host blood SOR scores were computed from Ct values for each of the 11 genes, measured by microfluidic qRT-PCR We used multiplex real-time PCR to detect 33 pathogens including bacteria, viruses and fungi in the nasopharyngeal and oropharyngeal samples Multivariate linear regression was used to identify pathogens associated with, and estimate their effect on, the SOR score Wilcoxon rank sum tests and receiver-operating-characteristic (ROC) curves were used to differentiate participants with and without respiratory pathogens Results 1,000 HIV-negative volunteers aged between 18 and 60 years were enrolled 13 viral and nine bacterial pathogens were detected Overall prevalence of respiratory pathogens was 43%: 4% were viruses only, 35 8% bacteria only, and 3 2% were a combination of viruses and bacteria Influenza C, rhinoviruses, coronavirus OC43, adenoviruses, and mycoplasma pneumoniae were significantly associated (Table 1) with a high SOR score In ROC curve analysis the SOR score differentiated participants as follows;virus vs no-pathogen (area under the curve;AUC) AUC=0 72, 95% CI: 0 63-0 81, virus vs bacteria AUC=0 72, 95% CI: 0 63-0 81, bacteria vs no-pathogen AUC=0 51, 95% CI: 0 48-0 55 (no difference) Participants with either viruses only or both viruses and bacteria had significantly higher (P=0 001) SOR scores (median 47% and 43%, respectively) compared to participants without pathogens (median 14%) or participants with bacteria only (median 13%) Conclusion Participants with upper respiratory tract viral colonization or infection had elevated SOR scores, suggesting induction of interferon signalling Infection or colonization with respiratory viruses is likely to result in false positive results for other transcriptomic signatures of tuberculosis based on ISGs (Table Presented)
Background Studies have shown a mixed association between socioeconomic status [SES] and prevalen... more Background Studies have shown a mixed association between socioeconomic status [SES] and prevalent HIV infection across and within settings in sub-Saharan Africa. In general, the relationship between years of formal education and HIV infection changed from a positive to a negative association with maturity of the HIV epidemic. Our objective was to determine the association between SES and HIV in women of reproductive age in the Free State [FSP] and Western Cape Provinces [WCP] of South Africa [SA]. Study design Cross sectional Setting South Africa Methods We conducted secondary analysis on 1906 women of reproductive age from a 2007-2008 survey that evaluated effectiveness of Prevention of Mother-to-Child HIV Transmission programs. SES was measured by household wealth quintiles, years of formal education and employment status. Our analysis principally utilized logistic regression for survey data. Results There was a significant negative trend between prevalent HIV infection and wealth quintile in WCP [p-value<0.001] and FSP [p-value=0.025]. In adjusted analysis, every additional year of formal education was associated with a 10% [adjusted Odds Ratio [aOR] 0.90 [95% Confidence Interval [CI]: 0.85-0.96] significant reduction in risk of prevalent HIV infection in WCP but no significant association was observed in FSP [aOR 0.99 CI: 0.89-1.11]. There was no significant association between employment and prevalent HIV in each province: [aOR 1.54 CI: 0.84-2.84] in WCP and [aOR 0.96 CI: 0.71-1.30] in FSP. Conclusion The association between HIV infection and SES differed by province and by measure of SES and underscores the disproportionately higher burden of prevalent HIV infection among poorer and lowly educated women. Our findings suggest the need for re-evaluation of whether current HIV prevention efforts meet needs of the least educated [in WCP] and the poorest women [both WCP and FSP], and point to the need to investigate additional or tailored strategies for these women
Objective: Diagnosis of childhood tuberculosis is limited by the paucibacillary respiratory sampl... more Objective: Diagnosis of childhood tuberculosis is limited by the paucibacillary respiratory samples obtained from young children with pulmonary disease. We aimed to compare accuracy of the Xpert® MTB/RIF assay, an automated nucleic acid amplification test, between induced sputum and gastric lavage samples from young children in a tuberculosis endemic setting. Methods: We analyzed standardized diagnostic data from HIV negative children younger than four years of age who were investigated for tuberculosis disease near Cape Town, South Africa [2009–2012]. Two paired, consecutive induced sputa and early morning gastric lavage samples were obtained from children with suspected tuberculosis. Samples underwent Mycobacterial Growth Indicator Tube [MGIT] culture and Xpert MTB/RIF assay. We compared diagnostic yield across samples using the two-sample test of proportions and McNemar’s χ2 test; and Wilson’s score method to calculate sensitivity and specificity. Results: 1,020 children were evaluated for tuberculosis during 1,214 admission episodes. Not all children had 4 samples collected. 57 of 4,463[1.3%] and 26 of 4,606[0.6%] samples tested positive for Mycobacterium tuberculosis on MGIT culture and Xpert MTB/RIF assay respectively. 27 of 2,198[1.2%] and 40 of 2,183[1.8%] samples tested positive [on either Xpert MTB/RIF assay or MGIT culture] on induced sputum and gastric lavage samples, respectively. 19/1,028[1.8%] and 33/1,017[3.2%] admission episodes yielded a positive MGIT culture or Xpert MTB/RIF assay from induced sputum and gastric lavage, respectively. Sensitivity of Xpert MTB/RIF assay was 8/30[26.7%; 95% CI: 14.2–44.4] for two induced sputum samples and 7/31[22.6%; 11.4–39.8] [p = 0.711] for two gastric lavage samples. Corresponding specificity was 893/893[100%;99.6–100] and 885/890[99.4%;98.7–99.8] respectively [p = 0.025]. Conclusion: Sensitivity of Xpert MTB/RIF assay was low, compared to MGIT culture, but diagnostic performance of Xpert MTB/RIF did not differ sufficiently between induced sputum and gastric lavage to justify selection of one sampling method over the other, in young children with suspected pulmonary TB
Introduction Respiratory pathogens such as influenza viruses may play an influential role in the ... more Introduction Respiratory pathogens such as influenza viruses may play an influential role in the pathogenesis of TB by negatively affecting immunity against Mycobacterium tuberculosis (MTB) We discovered and validated a transcriptomic signature of risk (SOR), based on mRNA expression of 11 IFN stimulated genes (ISG), which prospectively differentiates between incident TB cases and healthy controls The SOR score is computed from expression abundance of multiple ISG transcript pairs in peripheral blood, whereby each pair functions as a ?vote? for or against TB risk We aimed to identify respiratory pathogens other than MTB that might also associate with this SOR score and test whether the SOR score differentiates between individuals with and without respiratory pathogens Methods We conducted a nested cross-sectional study of the upper respiratory tract microbiome Upon consent, participants were consecutively enrolled into the study and provided one nasopharyngeal, one oropharyngeal and a PAXgene blood sample Host blood SOR scores were computed from Ct values for each of the 11 genes, measured by microfluidic qRT-PCR We used multiplex real-time PCR to detect 33 pathogens including bacteria, viruses and fungi in the nasopharyngeal and oropharyngeal samples Multivariate linear regression was used to identify pathogens associated with, and estimate their effect on, the SOR score Wilcoxon rank sum tests and receiver-operating-characteristic (ROC) curves were used to differentiate participants with and without respiratory pathogens Results 1,000 HIV-negative volunteers aged between 18 and 60 years were enrolled 13 viral and nine bacterial pathogens were detected Overall prevalence of respiratory pathogens was 43%: 4% were viruses only, 35 8% bacteria only, and 3 2% were a combination of viruses and bacteria Influenza C, rhinoviruses, coronavirus OC43, adenoviruses, and mycoplasma pneumoniae were significantly associated (Table 1) with a high SOR score In ROC curve analysis the SOR score differentiated participants as follows;virus vs no-pathogen (area under the curve;AUC) AUC=0 72, 95% CI: 0 63-0 81, virus vs bacteria AUC=0 72, 95% CI: 0 63-0 81, bacteria vs no-pathogen AUC=0 51, 95% CI: 0 48-0 55 (no difference) Participants with either viruses only or both viruses and bacteria had significantly higher (P=0 001) SOR scores (median 47% and 43%, respectively) compared to participants without pathogens (median 14%) or participants with bacteria only (median 13%) Conclusion Participants with upper respiratory tract viral colonization or infection had elevated SOR scores, suggesting induction of interferon signalling Infection or colonization with respiratory viruses is likely to result in false positive results for other transcriptomic signatures of tuberculosis based on ISGs (Table Presented)
Introduction Respiratory pathogens such as influenza viruses may play an influential role in the ... more Introduction Respiratory pathogens such as influenza viruses may play an influential role in the pathogenesis of TB by negatively affecting immunity against Mycobacterium tuberculosis (MTB) We discovered and validated a transcriptomic signature of risk (SOR), based on mRNA expression of 11 IFN stimulated genes (ISG), which prospectively differentiates between incident TB cases and healthy controls The SOR score is computed from expression abundance of multiple ISG transcript pairs in peripheral blood, whereby each pair functions as a ?vote? for or against TB risk We aimed to identify respiratory pathogens other than MTB that might also associate with this SOR score and test whether the SOR score differentiates between individuals with and without respiratory pathogens Methods We conducted a nested cross-sectional study of the upper respiratory tract microbiome Upon consent, participants were consecutively enrolled into the study and provided one nasopharyngeal, one oropharyngeal and a PAXgene blood sample Host blood SOR scores were computed from Ct values for each of the 11 genes, measured by microfluidic qRT-PCR We used multiplex real-time PCR to detect 33 pathogens including bacteria, viruses and fungi in the nasopharyngeal and oropharyngeal samples Multivariate linear regression was used to identify pathogens associated with, and estimate their effect on, the SOR score Wilcoxon rank sum tests and receiver-operating-characteristic (ROC) curves were used to differentiate participants with and without respiratory pathogens Results 1,000 HIV-negative volunteers aged between 18 and 60 years were enrolled 13 viral and nine bacterial pathogens were detected Overall prevalence of respiratory pathogens was 43%: 4% were viruses only, 35 8% bacteria only, and 3 2% were a combination of viruses and bacteria Influenza C, rhinoviruses, coronavirus OC43, adenoviruses, and mycoplasma pneumoniae were significantly associated (Table 1) with a high SOR score In ROC curve analysis the SOR score differentiated participants as follows;virus vs no-pathogen (area under the curve;AUC) AUC=0 72, 95% CI: 0 63-0 81, virus vs bacteria AUC=0 72, 95% CI: 0 63-0 81, bacteria vs no-pathogen AUC=0 51, 95% CI: 0 48-0 55 (no difference) Participants with either viruses only or both viruses and bacteria had significantly higher (P=0 001) SOR scores (median 47% and 43%, respectively) compared to participants without pathogens (median 14%) or participants with bacteria only (median 13%) Conclusion Participants with upper respiratory tract viral colonization or infection had elevated SOR scores, suggesting induction of interferon signalling Infection or colonization with respiratory viruses is likely to result in false positive results for other transcriptomic signatures of tuberculosis based on ISGs (Table Presented)
Background Studies have shown a mixed association between socioeconomic status [SES] and prevalen... more Background Studies have shown a mixed association between socioeconomic status [SES] and prevalent HIV infection across and within settings in sub-Saharan Africa. In general, the relationship between years of formal education and HIV infection changed from a positive to a negative association with maturity of the HIV epidemic. Our objective was to determine the association between SES and HIV in women of reproductive age in the Free State [FSP] and Western Cape Provinces [WCP] of South Africa [SA]. Study design Cross sectional Setting South Africa Methods We conducted secondary analysis on 1906 women of reproductive age from a 2007-2008 survey that evaluated effectiveness of Prevention of Mother-to-Child HIV Transmission programs. SES was measured by household wealth quintiles, years of formal education and employment status. Our analysis principally utilized logistic regression for survey data. Results There was a significant negative trend between prevalent HIV infection and wealth quintile in WCP [p-value<0.001] and FSP [p-value=0.025]. In adjusted analysis, every additional year of formal education was associated with a 10% [adjusted Odds Ratio [aOR] 0.90 [95% Confidence Interval [CI]: 0.85-0.96] significant reduction in risk of prevalent HIV infection in WCP but no significant association was observed in FSP [aOR 0.99 CI: 0.89-1.11]. There was no significant association between employment and prevalent HIV in each province: [aOR 1.54 CI: 0.84-2.84] in WCP and [aOR 0.96 CI: 0.71-1.30] in FSP. Conclusion The association between HIV infection and SES differed by province and by measure of SES and underscores the disproportionately higher burden of prevalent HIV infection among poorer and lowly educated women. Our findings suggest the need for re-evaluation of whether current HIV prevention efforts meet needs of the least educated [in WCP] and the poorest women [both WCP and FSP], and point to the need to investigate additional or tailored strategies for these women
Objective: Diagnosis of childhood tuberculosis is limited by the paucibacillary respiratory sampl... more Objective: Diagnosis of childhood tuberculosis is limited by the paucibacillary respiratory samples obtained from young children with pulmonary disease. We aimed to compare accuracy of the Xpert® MTB/RIF assay, an automated nucleic acid amplification test, between induced sputum and gastric lavage samples from young children in a tuberculosis endemic setting. Methods: We analyzed standardized diagnostic data from HIV negative children younger than four years of age who were investigated for tuberculosis disease near Cape Town, South Africa [2009–2012]. Two paired, consecutive induced sputa and early morning gastric lavage samples were obtained from children with suspected tuberculosis. Samples underwent Mycobacterial Growth Indicator Tube [MGIT] culture and Xpert MTB/RIF assay. We compared diagnostic yield across samples using the two-sample test of proportions and McNemar’s χ2 test; and Wilson’s score method to calculate sensitivity and specificity. Results: 1,020 children were evaluated for tuberculosis during 1,214 admission episodes. Not all children had 4 samples collected. 57 of 4,463[1.3%] and 26 of 4,606[0.6%] samples tested positive for Mycobacterium tuberculosis on MGIT culture and Xpert MTB/RIF assay respectively. 27 of 2,198[1.2%] and 40 of 2,183[1.8%] samples tested positive [on either Xpert MTB/RIF assay or MGIT culture] on induced sputum and gastric lavage samples, respectively. 19/1,028[1.8%] and 33/1,017[3.2%] admission episodes yielded a positive MGIT culture or Xpert MTB/RIF assay from induced sputum and gastric lavage, respectively. Sensitivity of Xpert MTB/RIF assay was 8/30[26.7%; 95% CI: 14.2–44.4] for two induced sputum samples and 7/31[22.6%; 11.4–39.8] [p = 0.711] for two gastric lavage samples. Corresponding specificity was 893/893[100%;99.6–100] and 885/890[99.4%;98.7–99.8] respectively [p = 0.025]. Conclusion: Sensitivity of Xpert MTB/RIF assay was low, compared to MGIT culture, but diagnostic performance of Xpert MTB/RIF did not differ sufficiently between induced sputum and gastric lavage to justify selection of one sampling method over the other, in young children with suspected pulmonary TB
Introduction Respiratory pathogens such as influenza viruses may play an influential role in the ... more Introduction Respiratory pathogens such as influenza viruses may play an influential role in the pathogenesis of TB by negatively affecting immunity against Mycobacterium tuberculosis (MTB) We discovered and validated a transcriptomic signature of risk (SOR), based on mRNA expression of 11 IFN stimulated genes (ISG), which prospectively differentiates between incident TB cases and healthy controls The SOR score is computed from expression abundance of multiple ISG transcript pairs in peripheral blood, whereby each pair functions as a ?vote? for or against TB risk We aimed to identify respiratory pathogens other than MTB that might also associate with this SOR score and test whether the SOR score differentiates between individuals with and without respiratory pathogens Methods We conducted a nested cross-sectional study of the upper respiratory tract microbiome Upon consent, participants were consecutively enrolled into the study and provided one nasopharyngeal, one oropharyngeal and a PAXgene blood sample Host blood SOR scores were computed from Ct values for each of the 11 genes, measured by microfluidic qRT-PCR We used multiplex real-time PCR to detect 33 pathogens including bacteria, viruses and fungi in the nasopharyngeal and oropharyngeal samples Multivariate linear regression was used to identify pathogens associated with, and estimate their effect on, the SOR score Wilcoxon rank sum tests and receiver-operating-characteristic (ROC) curves were used to differentiate participants with and without respiratory pathogens Results 1,000 HIV-negative volunteers aged between 18 and 60 years were enrolled 13 viral and nine bacterial pathogens were detected Overall prevalence of respiratory pathogens was 43%: 4% were viruses only, 35 8% bacteria only, and 3 2% were a combination of viruses and bacteria Influenza C, rhinoviruses, coronavirus OC43, adenoviruses, and mycoplasma pneumoniae were significantly associated (Table 1) with a high SOR score In ROC curve analysis the SOR score differentiated participants as follows;virus vs no-pathogen (area under the curve;AUC) AUC=0 72, 95% CI: 0 63-0 81, virus vs bacteria AUC=0 72, 95% CI: 0 63-0 81, bacteria vs no-pathogen AUC=0 51, 95% CI: 0 48-0 55 (no difference) Participants with either viruses only or both viruses and bacteria had significantly higher (P=0 001) SOR scores (median 47% and 43%, respectively) compared to participants without pathogens (median 14%) or participants with bacteria only (median 13%) Conclusion Participants with upper respiratory tract viral colonization or infection had elevated SOR scores, suggesting induction of interferon signalling Infection or colonization with respiratory viruses is likely to result in false positive results for other transcriptomic signatures of tuberculosis based on ISGs (Table Presented)
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