Different pattern of stool and plasma gastrointestinal damage biomarkers during primary and chronic HIV infection.
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Different pattern of stool and plasma gastrointestinal damage biomarkers during primary and chronic HIV infection.
Methods: PHI-individuals (n = 57) were identified as HIV-seronegative/HIV-RNA positive and were followed up for one year at the Manhiça District Hospital in Mozambique. Ten plasma and 12 stool biomarkers were quantified by Luminex or ELISA and levels were compared to CHI-naive (n = 26), CHI on antiretroviral-treatment (ART; n = 30) and HIV-uninfected individuals (n = 58). Regression models adjusted by time point were used to estimate the association of the biomarkers with HIV-disease markers. Receiver operating curves were compared for the best accuracy to distinguish PHI from CHI.
Results: Soluble (s)CD14 was significantly associated with the CD4/CD8 ratio (P 0.05) and viremia levels (P 0.0001) during PHI. Plasma zonulin and stool lactoferrin were significantly higher in PHI as compared to CHI-individuals (P 0.05). Plasma zonulin demonstrated the best accuracy to identify PHI among HIV-infected individuals (AUC = 0.85 [95% CI 0.75-0.94]). Using a cutoff value of plasma zonulin ≥ 8.75 ng/mL the model identified PHI with 87.7% sensitivity (95% CI 76.3-94.9) and 69.2% specificity (95% CI 48.2-85.7). An adjusted multivariate model including age, plasma zonulin and sCD14 further increased the classification performance (AUC = 0.92 [95% CI 0.86-0.99]).
Conclusion: Soluble (s)CD14 was significantly associated with the CD4/CD8 ratio (P 0.05) and viremia levels (P 0.0001) during PHI. Plasma zonulin and stool lactoferrin were significantly higher in PHI as compared to CHI-individuals (P 0.05). Plasma zonulin demonstrated the best accuracy to identify PHI among HIV-infected individuals (AUC = 0.85 [95% CI 0.75-0.94]). Using a cutoff value of plasma zonulin ≥ 8.75 ng/mL the model identified PHI with 87.7% sensitivity (95% CI 76.3-94.9) and 69.2% specificity (95% CI 48.2-85.7). An adjusted multivariate model including age, plasma zonulin and sCD14 further increased the classification performance (AUC = 0.92 [95% CI 0.86-0.99]).