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Apr 25, 2023 144 likes •349 views

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

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AREVIR 2019

TTV as a novel biomarker of delayed immune reconstitution in HIV infected patients

Livia Schmidt

Institute of Virology Düsseldorf

  • n behalf of the RESINA-Study Team
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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
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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

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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
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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
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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

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Patients‘ characteristics

Category n % Age (years), median 49 (range 25-92) Sex 301 Male 234 78 Female 67 22 HIV-RNA (cop/ml), median 48,394 (range 40 - 8,858,100) TTV-DNA (cop/ml), median 235,844 (range 0 - 2*109) CD4 baseline (cells/µl) <100 89 30 100-200 38 13 201-350 119 40 >350 55 18

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Number of analysed samples

  • 301 samples were analysed for TTV plasma levels

CD4 cell recovery (cells/µl) CD4 <50 50-200 >200 ∑ CD4 cells baseline (cells/µl) <100 11 41 37 89 101-200 10 14 14 38 201-350 22 48 49 119 >350 24 12 19 55 ∑ 67 115 119 301

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TTV plasma level increased with reduced CD4 cell count

  • p= 0.003
  • R2= 0.029

CD4 baseline (cells/µl)

  • 289/301 TTV viremic (96%)
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TTV plasma level correlate with baseline CD4 values

CI: 10-90 percentile p: 0.037

  • Baseline CD4 cell count is significantly negative correlated to TTV plasma level (p=0.037)

<100 101-200 201-350 >350 CD4 baseline

cells/µl N 89 38 119 55 Median TTV cop/ml 1,693,969 517,916 172,340 124,479

1.0× 1000 1.0× 1001 1.0× 1002 1.0× 1003 1.0× 1004 1.0× 1005 1.0× 1006 1.0× 1007 1.0× 1008 1.0× 1009 1.0× 1010

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Higher TTV plasma level with delayed CD4 recovery

  • 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)

P = 0.011

<50 50-200 >200 CD4 recovery cells/µl

N 67 115 119 Median TTV cop/ml 481.963 277.075 97.471

1.0× 1000 1.0× 1001 1.0× 1002 1.0× 1003 1.0× 1004 1.0× 1005 1.0× 1006 1.0× 1007 1.0× 1008 1.0× 1009 1.0× 1010

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  • 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

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

TTV and CD4 cell count as predictors

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Multivariate analysis of variances

  • TT viral load combined with baseline CD4 cell count are predictive for immune recovery (p <0.001)

Variable Total df F η2 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

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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

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Projects in detail

Case-control study comparing matched patients with AIDS event versus patients without AIDS event

  • Analysis of samples from the RESINA Cohort (Virology Cologne), experiments in

progress

  • Two groups:

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)

  • Project 1
  • Project 2
  • Project 3
  • Planned

projects

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Projects in detail

1. Prospective analysis to predict CD4 cell recovery (Project in REsina to

preDIct Cd4-cell recovery by TTV plasma concentration; PREDICTT Study)

– Confirmation of results from retrospective analysis – Analysis of 300 patients in 4 groups according to CD4 cell count (< 100 /µl, 100-200 /µl, 200-350 /µl, > 350/µl) – 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

  • Project 1
  • Project 2
  • Project 3
  • Planned

projects

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Projects in detail

2. TTV in TB/HIV co-infection and paradoxical TB-IRIS

– Background:

  • To date, prediction of TB IRIS not possible
  • approx. 30% of HIV/TB co-infected patients with impaired immune status initiating TB treatment affected
  • Prophylactic therapy without benefit (no reduction of mortality)

– 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
  • Project 1
  • Project 2
  • Project 3
  • Planned

projects

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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
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Acknowledgements

Düsseldorf University Hospital

Department of Gastroenterology, Hepatology and Infectious Diseases Dieter Häussinger Björn Jensen Falk Hüttig Institute of Virology Nadine Lübke Iris Hermann Ortwin Adams Claas Schmidt Jörg Timm AG Timm

RESINA und AREVIR Partner

Mark Oette, Martin Hover, Frank Wiesmann, Patrick Braun, Heribert Knechten and others

Cologne University Hospital

Institut of Virologie Rolf Kaiser Michael Böhm Lisa Hüsgen Claudia Müller Elena Knops Saleta Sierra-Aragon Veronica Di Cristanziano Eva Heger Pia Esser Oyuka Oyendere

Siena University Hospital, Department of Infectious Diseases

Andrea de Luca

Robert Koch Institute

Norbert Bannert, Barbara Bartmeyer, Osama Hamouda, Klaus Jansen, Claudia Kücherer