Torque Teno Virus as a Novel Biomarker Targeting the Efficacy of Immunosuppression After Lung Transplantation. (20th July 2018)

• Record Type: Journal Article
• Authors: Jaksch, Peter; Kundi, Michael; Görzer, Irene; Muraközy, Gabriella; Lambers, Christopher; Benazzo, Alberto; Hoetzenecker, Konrad; Klepetko, Walter; Puchhammer-Stöckl, Elisabeth
• Is Part Of: Journal of infectious diseases. Volume 218:Number 12(2018)
• Page Start: 1922
• Page End: 1928
• Publication Date: 2018-07-20
• Subjects: lung transplantation -- biomarker -- torque teno virus -- individualized immunosuppression; Communicable diseases -- Periodicals; Diseases -- Causes and theories of causation -- Periodicals; Medicine -- Periodicals; Communicable Diseases -- Periodicals; Electronic journals; 616.9
• DOI: 10.1093/infdis/jiy452
• Languages: English
• ISSNs: 0022-1899

Abstract

Abstract : Torque teno viruses are small DNA viruses of the genus Alphatorquevirus (ATV), whose replication is linked to immune status and may be an indicator for efficacy of immunosuppression in lung transplant recipients. ATV load predicts clinical events and may be useful to monitor immunosuppression after lung transplantation. Abstract: Torque teno viruses (TTV) are small DNA-viruses, of the genus Alphatorquevirus, whose replication is linked to immune status. TTV load may be an indicator for efficacy of IS in lung transplant recipients (LTRs). In a prospective single-center-study 143 LTRs were followed up and tested by quantitative TTV-DNA PCR. Using multivariate Cox-regression contribution of TTV-load to the occurrence of severe infections, chronic lung allograft dysfunction (CLAD), acute cellular rejection (ACR), and death was assessed. During follow-up 28 (20%) patients developed infections with a rate of 7.7 per 100 patient-years (PY). The hazard-ratio (HR) associated with a one-log10 increase of TTV-load before the event was 5.05. CLAD occurred with a rate of 6.0%-PY. HR for a 1 log10 increase of the lowest TTV level before the event was 0.71 (CI: 0.54–0.93). TTV-load predicts clinical events and may be useful to optimize IS during the first years of follow-up of LTRs.