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TTV as a novel biomarker of delayed immune reconstitution in HIV infected patients Livia Schmidt Institute of Virology Dsseldorf on behalf of the RESINA-Study Team AREVIR 2019 TTV project Objective To evaluate the presence and load


  1. TTV as a novel biomarker of delayed immune reconstitution in HIV infected patients Livia Schmidt Institute of Virology Düsseldorf on behalf of the RESINA-Study Team AREVIR 2019

  2. TTV project Objective • – To evaluate the presence and load of TTV in peripheral blood as a novel biomarker for immune- competence in HIV infected patients Hypothesis • – TTV plasma concentration can be used for prediction of the course of immune reconstitution (IR) upon initiation of combined antiretroviral therapy (cART) • Contribution to guide individualized treatment

  3. TTV project Aim • – Correlation of TTV plasma concentrations with immunological, virological and biophysical parameters ฀ predict IR for therapy naïve HIV-infected patients during cART – Parameters: CD4 cell count HI viral load Age Sex

  4. Inclusion criteria HIV-1 infection • No AIDS-Event before start of cART or during the first 3 months on cART • CD4 cell count <500/µl at therapy start • HI viral load decrease <200 copies/ml without rebound during the first year on cART •

  5. Material Blood samples from RESINA cohort , selected independent of HI viral load • Collected from 2001 to 2016 • Baseline plasma samples -> before cART initiation • One sample per patient •

  6. Methods DNA extraction of plasma samples • TTV-DNA quantification by use of Realtime-PCR • Primers and probe: • AMTS 5‘-GTG CCG IAG GTG AGT TTA-3‘ 18 bp • AMTAS 5‘-AGC CCG GCC AGT CC-3‘ 14 bp • AMTPTU 5’-FAM-TCA AGG GGC AAT TCG GGC T-3’TAMRA 19 bp • PCR protocol and standards from Vienna (Maggi, F., et al., 2003) • – Standards were stabilized in Cologne Quantification was validated in a collaborative trial • Statistical elements were performed with ANOVA, • multivariate analysis of variances https://www.biocompare.com/Product-Reviews/167240-Solid- workhorse-machine/

  7. Patients‘ characteristics Category n % Age (years), median 49 (range 25-92) Sex 301 Male 234 78 Female 67 22 48,394 HIV-RNA (cop/ml), median (range 40 - 8,858,100) 235,844 TTV-DNA (cop/ml), median (range 0 - 2*10 9 ) CD4 baseline (cells/µl) <100 89 30 100-200 38 13 201-350 119 40 >350 55 18

  8. Number of analysed samples CD4 cell recovery (cells/µl) CD4 <50 50-200 >200 ∑ <100 11 41 37 89 baseline CD4 cells (cells/µl) 101-200 10 14 14 38 201-350 22 48 49 119 >350 24 12 19 55 ∑ 67 115 119 301 301 samples were analysed for TTV plasma levels •

  9. TTV plasma level increased with reduced CD4 cell count  p= 0.003  R 2 = 0.029 CD4 baseline (cells/µl) 289/301 TTV viremic (96%) •

  10. TTV plasma level correlate with baseline CD4 values 1.0 × 10 10 1.0 × 10 09 1.0 × 10 08 1.0 × 10 07 1.0 × 10 06 CI: 10-90 percentile 1.0 × 10 05 p: 0.037 1.0 × 10 04 1.0 × 10 03 1.0 × 10 02 1.0 × 10 01 1.0 × 10 00 <100 101-200 201-350 >350 CD4 baseline cells/µl N 89 38 119 55 Median TTV 1,693,969 517,916 172,340 124,479 cop/ml  Baseline CD4 cell count is significantly negative correlated to TTV plasma level (p=0.037)

  11. Higher TTV plasma level with delayed CD4 recovery P = 0.011 1.0 × 10 10 1.0 × 10 09 1.0 × 10 08 1.0 × 10 07 1.0 × 10 06 1.0 × 10 05 1.0 × 10 04 1.0 × 10 03 1.0 × 10 02 1.0 × 10 01 1.0 × 10 00 <50 50-200 >200 CD4 recovery cells/µl N 67 115 119 Median TTV 481.963 277.075 97.471 cop/ml Patients with a CD4 cell recovery <50 cells/µl were 100% TTV viremic • Significant higher TTV plasma level with CD4 recovery <50 cells/µl in contrast to CD4 recovery >200 • cells/µl (p=0.011)

  12. TTV and CD4 cell count as predictors Univariate analysis Multivariate analysis Variable Total OR (95% CI) p value OR (95% CI) p value TTV DNA in cop/ml 301 1 0.742 (0.602-0.915) 0.005 HIV RNA in cop/ml 301 1 1.017 (0.716-1.443) 0.926 CD4 baseline value in cells/µl 301 1 0.994 (0.992-0.997) <0.001 <100 89 0.383 (0.190-0.773) 0.006 100-200 38 1.262 (0.579-2.750) 0.559 201-350 119 0.729 (0.414-1.285) 0.275 >350 55 3.554 (1.903-6.639) <0.001 Sex 300 1 0.855 (0.424-1.723) 0.661 Male 234 0.915 (0.816-1.107) 0.499 Female 66 1.184 (0.732-1.915) 0.503 Age 301 1 0.995 (0.970-1.020) 0.679 No correlation of HIV RNA, sex and age to CD4 recovery • Significant correlation of TTV plasma level and baseline CD4 cell count to CD4 recovery • TTV plasma level and baseline CD4 cell count on their own are not sufficient to predict CD4 recovery •

  13. Multivariate analysis of variances Variable Total df F η 2 p value TTV DNA in cop/ml 301 2 4.860 0.032 0.008 HIV RNA 301 2 0.436 0.003 0.647 CD4 baseline plasma level in cells/µl 301 2 9.619 0.062 <0.001 Sex 300 2 0.353 0.002 0.703 Age 301 2 0.054 <0.001 0.9619 TT viral load combined with baseline CD4 cell count are predictive for immune recovery (p <0.001) •

  14. Summary and conclusions High TTV prevalence in RESINA cohort (96%) • Baseline CD4 cell count is significantly negative correlated to TTV plasma level before cART initiation • Significant higher TTV plasma level with CD4 recovery <50 cells/µl compared to CD4 recovery >200 • cells/µl No correlation of HIV RNA, sex and age to CD4 recovery • CD4 baseline value and TTV plasma level on their own are not sufficient to predict CD4 recovery • ฀ TTV plasma level combined with initial CD4 cell count are predictive for immune recovery

  15. Projects in detail Case-control study comparing matched patients with AIDS event versus patients Project 1 • without AIDS event Project 2 • Analysis of samples from the RESINA Cohort (Virology Cologne), experiments in • Project 3 • progress Planned • Two groups: • projects a. AIDS event + Hodkin's lymphoma, exclusion of tuberculosis b. AIDS Event Tuberculosis Match (1:2) according to: • Age ( ± 10 years) – gender – CD4 cell count ( ± 50 /µl) – HIV plasma concentration (< 1,000, 1,000-10,000, 10,000-100,000, > 100,000 /µl) –

  16. Projects in detail Project 1 1. Prospective analysis to predict CD4 cell recovery ( P roject in RE sina to • pre DI ct C d4-cell recovery by TT V plasma concentration; PREDICTT Study ) Project 2 • Confirmation of results from retrospective analysis – Project 3 • Analysis of 300 patients in 4 groups according to CD4 cell count (< 100 /µl, 100-200 – Planned • /µl, 200-350 /µl, > 350/µl) projects Determination of TTV plasma concentration to baseline and in the course, analysis – after 48, 96 and 240 weeks Implementation with new members of the RESINA cohort –

  17. Projects in detail Project 1 2. TTV in TB/HIV co-infection and paradoxical TB-IRIS • Project 2 • Background: – To date, prediction of TB IRIS not possible • Project 3 • approx. 30% of HIV/TB co-infected patients with impaired immune status initiating TB treatment affected • Prophylactic therapy without benefit (no reduction of mortality) • Planned • projects Plan: – Inclusion of approx. 160 ART-naive HIV/TB co-infected patients (CD4 ≤ 200/µl) in Asella and Adama, • Central Ethiopia (Hirsch Institute of Tropical Medicine) Follow up during TB treatment, identification of patients with TB IRIS (expected: approx. 30%) • Analysis of differences in TTV plasma concentration between patients with and without TB IRIS •

  18. Conclusions  The course of chronic HIV infection (AIDS, response to therapy, etc.) differs greatly between individuals  Predictions are not yet possible  There is evidence that TTV plasma concentration may have a benefit as biomarker for the functional state of the immune system and may serve as a predictor for individual progression  Further studies to evaluate this benefit are needed

  19. Acknowledgements Düsseldorf University Hospital Cologne University Hospital Department of Gastroenterology, Hepatology and Infectious Diseases Institut of Virologie Dieter Häussinger Rolf Kaiser Michael Böhm Björn Jensen Lisa Hüsgen Claudia Müller Falk Hüttig Elena Knops Saleta Sierra-Aragon Veronica Di Cristanziano Eva Heger Institute of Virology Pia Esser Oyuka Oyendere Nadine Lübke Iris Hermann Ortwin Adams Claas Schmidt Siena University Hospital, Department of Infectious Diseases Jörg Timm AG Timm Andrea de Luca RESINA und AREVIR Partner Robert Koch Institute Mark Oette, Martin Hover, Frank Wiesmann, Patrick Braun, Heribert Norbert Bannert, Barbara Bartmeyer, Osama Hamouda, Klaus Jansen, Knechten and others Claudia Kücherer

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