Serum cytokine biosignatures for identification of tuberculosis among HIV-positive inpatients.

BACKGROUND: Serum cytokines correlate with tuberculosis (TB) progression and are predictors of TB recurrence in people living with HIV. We investigated whether serum cytokine biosignatures could diagnose TB among HIV-positive inpatients. METHODS: We recruited HIV-positive inpatients with symptoms of TB and measured serum levels of inflammation biomarkers including IL-2, IL-4, IL-6, IL-10, tumour necrosis factor-alpha (TNF-α) and interferon-gamma (IFN-γ). We then built and tested our TB prediction model. RESULTS: 236 HIV-positive inpatients were enrolled in the first cohort and all the inflammation biomarkers were significantly higher in participants with microbiologically confirmed TB than those without TB. A binary support vector machine (SVM) model was built, incorporating the data of four biomarkers (IL-6, IL-10, TNF-α and IFN-γ). Efficacy of the SVM model was assessed in training (n=189) and validation (n=47) sets with area under the curve (AUC) of 0.92 (95% CI 0.88 to 0.96) and 0.85 (95% CI 0.72 to 0.97), respectively. In an independent test set (n=110), the SVM model yielded an AUC of 0.85 (95% CI 0.76 to 0.94) with 78% (95% CI 68% to 87%) specificity and 85% (95% CI 66% to 96%) sensitivity. Moreover, the SVM model outperformed interferon-gamma release assay (IGRA) among advanced HIV-positive inpatients irrespective of CD4+ T-cell counts, which may be an alternative approach for identifying Mycobacterium tuberculosis infection among HIV-positive inpatients with negative IGRA. CONCLUSIONS: The four-cytokine biosignature model successfully identified TB among HIV-positive inpatients. This diagnostic model may be an alternative approach to diagnose TB in advanced HIV-positive inpatients with low CD4+ T-cell counts.

Diverse immune responses in vaccinated individuals with and without symptoms after omicron exposure during the recent outbreak in Guangzhou, China.

Objectives: During the recent wave of coronavirus disease 2019 (COVID-19) infections in China, most individuals have been vaccinated and exposed to the omicron variant. In the present study, two cohorts were observed in the vaccinated population: vaccinated individuals with symptoms (VIWS) and those without symptoms (VIWOS). Our study aimed to characterize the antibody response in two cohorts: VIWS and VIWOS. Methods: A questionnaire survey was conducted in the community. Blood and saliva samples were collected from 124 individuals in the VIWS and VIWOS cohorts. Capture enzyme-linked immunosorbent assay (ELISA) was performed to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) specific antibodies. Results: The questionnaire survey revealed that 30.0 % (302/1005) of individuals in the older adult group (≥65 years) experienced no symptoms, whereas the rate of individuals without symptoms in the younger group (<65 years) was 17.8 % (166/932). Nucleocapsid (N)-specific IgM (N-IgM) was detected in the blood samples at a rate of 69.2 % (54/78) in the VIWS cohort. The positivity rate for N-specific IgA (N-IgA) was 93.6 % (73/78). In addition, the positivity rates of spike (S)-specific IgA (S-IgA) and N-IgA detected in saliva samples were 42 % (21/50) and 54 % (27/50), respectively. Both N-IgA positivity and negativity were observed in the VIWOS cohort. The detection rate of N-IgM positivity was 57.1 % (12/21) in the N-IgA-positive group. In addition, 54.3 % (25/46) of the vaccinated individuals without symptoms were IgA-negative. Conclusions: Our study indicates that substantial N-specific antibodies were induced during omicron infection and that testing for N-IgA in both blood and saliva may aid in the diagnosis of SARS-CoV-2 infection in vaccinated populations.