RESUMEN
BACKGROUND & AIMS: T cells play a critical role in viral infection. We examined whether T-cell effector and regulatory responses can define clinical stages of chronic hepatitis B (CHB). METHODS: We enrolled 200 adults with CHB who participated in the National Institutes of Health-supported Hepatitis B Research Network from 2011 through 2013 and 20 uninfected individuals (controls). Peripheral blood lymphocytes from these subjects were analyzed for T-cell responses (proliferation and production of interferon gamma and interleukin 10) to overlapping hepatitis B virus (HBV) peptides (preS, S, preC, core, and reverse transcriptase), influenza matrix peptides, and lipopolysaccharide. T-cell expression of regulatory markers FOXP3, programmed death-1, and cytotoxic T lymphocyte-associated antigen-4 was examined by flow cytometry. Immune measures were compared with clinical parameters, including physician-defined immune-active, immune-tolerant, or inactive CHB phenotypes, in a blinded fashion. RESULTS: Compared with controls, patients with CHB had weak T-cell proliferative, interferon gamma, and interleukin 10 responses to HBV, with increased frequency of circulating FOXP3(+)CD127(-) regulatory T cells and CD4(+) T-cell expression of programmed death-1 and cytotoxic T lymphocyte-associated antigen-4. T-cell measures did not clearly distinguish between clinical CHB phenotypes, although the HBV core-specific T-cell response was weaker in hepatitis B e antigen (HBeAg)(+) than HBeAg(-) patients (percent responders: 3% vs 23%; P = .00008). Although in vitro blockade of programmed death-1 or cytotoxic T lymphocyte-associated antigen-4 increased T-cell responses to HBV, the effect was weaker in HBeAg(+) than HBeAg(-) patients. Furthermore, T-cell responses to influenza and lipopolysaccharide were weaker in CHB patients than controls. CONCLUSIONS: HBV persists with virus-specific and global T-cell dysfunction mediated by multiple regulatory mechanisms, including circulating HBeAg, but without distinct T-cell-based immune signatures for clinical phenotypes. These findings suggest additional T-cell-independent or regulatory mechanisms of CHB pathogenesis that warrant further investigation.
Asunto(s)
Virus de la Hepatitis B/patogenicidad , Hepatitis B Crónica/virología , Activación de Linfocitos , Linfocitos T/virología , Adulto , Estudios de Casos y Controles , Proliferación Celular , Células Cultivadas , Femenino , Antígenos e de la Hepatitis B/sangre , Virus de la Hepatitis B/inmunología , Hepatitis B Crónica/sangre , Hepatitis B Crónica/inmunología , Interacciones Huésped-Patógeno , Humanos , Interferón gamma/inmunología , Interferón gamma/metabolismo , Interleucina-10/inmunología , Interleucina-10/metabolismo , Lipopolisacáridos/farmacología , Activación de Linfocitos/efectos de los fármacos , Masculino , Orthomyxoviridae/inmunología , Fenotipo , Linfocitos T/efectos de los fármacos , Linfocitos T/inmunología , Linfocitos T/metabolismo , Linfocitos T Reguladores/inmunología , Linfocitos T Reguladores/virología , Estados UnidosRESUMEN
OBJECTIVES: Collective intelligence, the "wisdom of the crowd," seeks to improve the quality of judgments by aggregating multiple individual inputs. Here, we evaluate the success of collective intelligence strategies applied to probabilistic diagnostic judgments. METHODS: We compared the performance of individual and collective intelligence judgments on two series of clinical cases requiring probabilistic diagnostic assessments, or "forecasts". We assessed the quality of forecasts using Brier scores, which compare forecasts to observed outcomes. RESULTS: On both sets of cases, the collective intelligence answers outperformed nearly every individual forecaster or team. The improved performance by collective intelligence was mediated by both improved resolution and calibration of probabilistic assessments. In a secondary analysis looking at the effect of varying number of individual inputs in collective intelligence answers from two different data sources, nearly identical curves were found in the two data sets showing 11-12% improvement when averaging two independent inputs, 15% improvement averaging four independent inputs, and small incremental improvements with further increases in number of individual inputs. CONCLUSIONS: Our results suggest that the application of collective intelligence strategies to probabilistic diagnostic forecasts is a promising approach to improve diagnostic accuracy and reduce diagnostic error.