Multicenter comparison of genotypic tropism testing: results from - - PowerPoint PPT Presentation

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Multicenter comparison of genotypic tropism testing: results from - - PowerPoint PPT Presentation

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HIV Genotypischer Resistenzalgorithmus Deutschland Multicenter comparison of genotypic tropism testing: results from viral RNA and proviral DNA M. Obermeier 5/2012 Aims of the study Genotypic tropism testing from viral RNA is widely

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  • M. Obermeier 5/2012

Multicenter comparison of genotypic tropism testing: results from viral RNA and proviral DNA

HIV Genotypischer Resistenzalgorithmus Deutschland

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Aims of the study

 Genotypic tropism testing from viral RNA is widely

accepted as routine diagnostic method. It‘s usage is implemented by local and European guidelines.

 Although there is a huge interest in performing tropism

testing in patients with low or undetectable viral load, data about tropism testing from proviral DNA ist still limited

 To better assess the usage of tropism testing from

proviral DNA, we conducted a multicenter study to compare V3 loop sequence pairs from viral RNA and proviral DNA in routine diagnostic samples

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HIV in Germany

Ref.: RKI

69500 HIV-pos. ~ 20% female 2700 Infections/year 700 deaths/year < 2% of newborns HIV-pos

Rolf Kaiser Univ Cologne Patrick Braun Lab Dr. Knechten Aachen Martin Obermeier Lab Dr. Berg Berlin Eva Wolf Lab Jäger Munich Labor Lademannbogen Hamburg Martin Däumer Lab Dr. Thiele Kaiserslautern Lab Fenner Hamburg Martin Stürmer

  • Univ. Frankfurt

Hauke Walter Univ Erlangen Alexander Thielen MPI Informatik Josef Eberle Univ Munich

The HI V-GRADE laboratory network

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Specification of the samples

 Sequencing from viral RNA and

proviral DNA was performed in 210 samples

 Viral load range was between <50

copies/ml and 8.1 million cop./ml

 HIV1-Subtype was in most cases B

(71%)

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Subtype distribution of samples

Subtype was determined using COMET tool (http://comet.retrovirology.lu/)

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Coreceptor-tropism classification

 2 Classification systems were used  Geno2pheno[coreceptor] (http://www.geno2pheno.org)

  • Cut-offs for coreceptor tropism classification were used as

implemented in the german guidelines

  • FPR <12.5% -> CXCR4
  • FPR >20% -> CCR5
  • FPR 12.5% – 20% -> equivocal

 WebPSSM

(http://indra.mullins.microbiol.washington.edu/)

  • Cut-offs as described in: Jensen, M.A. u. a. Improved

coreceptor usage prediction and genotypic monitoring of R5-to-X4 transition by motif analysis of human immunodeficiency virus type 1 env V3 loop sequences. J. Virol 77, 13376-13388 (2003).

  • FPR > -2.88 -> CXCR4
  • FPR < -6.96 -> CCR5
  • FPR -2.88 - -6.96 -> equivocal
  • Ambiguous positions in Sequences were resolved with

using the highest potential score of any possible sequences

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Comparison using geno2pheno (N=210)

86%

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Comparison using WebPSSM (N=191)

82%

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Range of FPR values for geno2pheno (all samples N=210)

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Range of FPR values for geno2pheno (divergent samples N=29)

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Range of scores for WebPSSM (all samples N=191)

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Range of scores for WebPSSM (divergent samples N=33)

{

p=0.04

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Range of scores for WebPSSM (divergent samples N=33)

PSSM score viral proviral R5

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Viral vs proviral geno2pheno WebPSSM

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Conclusions:

 Genotypic tropism testing from viral RNA

and proviral DNA shows a high level of concordance

 In routine diagnostics tropism testing can be

performed from proviral DNA alone and can replace tropism testing from viral RNA to simplify routine diagnostic procedures

 Genotypic tropism testing from proviral DNA

shows at least a trend towards an higher CXCR4 classification

 If performing genotypic tropism testing from

proviral DNA cut-offs should be lowered compared to cut-offs in viral RNA

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HIV-1 coreceptor tropism HIV-GRADE study – correlation to HIV-1 subtype

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Aims

 Differences of coreceptor tropism for

HIV-1 subtypes?

 Identification of polymorphisms

responsible for subtype dependent coreceptor tropism differences

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Methods

 V3-RT-PCR from plasma  or proviral V3-DNA-PCR from EDTA-blood

samples

 Sequencing of PCR amplicons  HIV-1 subtyping by COMET tool  Coreceptor tropism prediction by geno2pheno

(FPR>10% => R5)

 CHi2 test of absolute values and expected

values

 expected values were calculated by the

normalized mean of each subtype-specific R5-X4 ratio

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Results – subtype distribution

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Results – subtype tropism

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Results – statistical analyses

0.001 0.610 0.015 0.171 0.010 0.919 0.022 CHi2

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Summary

 Difference of percentages for

subtypes detected

 Normalized overall mean: 70.5% R5

  • vs. 29.5% X4

 Higher rate of X4 tropism prediction

for subtypes CRF01_AE and D

 Higher rate of R5 tropism prediction

for subytpes A1 and G

 No differences for all other subtypes

(B, C, F)

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Discussion

 Higher rate of X4 prediction for subtype

D as described before confirmed

 For subtype C R5 prediction rate similar

to subtype B

 Contradictory publications available  Limitations:  no further laboratory parameters and no

clinical data available

 Short sequence length may influence

subtyping performance (use of additional subtyping tools)

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HIV-GRADE association

 Thomas Berg, Medizinisches Labor Dr. Berg, Berlin  Patrick Braun, PZB, Aachen  Martin Däumer, Institut für Virologie, Köln  Josef Eberle, Pettenkofer-Institut, München  Robert Ehret, PZB Aachen  Rolf Kaiser, Institut für Virologie, Köln  Klaus Korn, NRZ für Retroviren, Erlangen  Claudia Kücherer, Robert Koch Institut, Berlin  Harm Müller,Labor Fenner, Hamburg  Christian Noah, Labor Lademannbogen, Hamburg  Martin Stürmer, Institut für Medizinische Virologie, Frankfurt  Alexander Thielen, Max Planck Institut Saarbrücken  Hauke Walter, NRZ für Retroviren, Erlangen