Poster # 388 CROI 2009

8-11 FebMontreal, Canada

Association of HIV-1 Co-receptor Tropism with Immunologic and Virologic Parameters in HIV-1 infected, Treatment-Naïve Subjects in ACTG 384

G Skowron1, E Chan2, J Weidler3, G Robbins4, V Johnson5, J Spritzler2, D Asmuth6, R Gandhi4, Y Lie3, E Coakley3, R Pollard6, for the AIDS Clinical Trials Group 384 protocol team. 1 Roger Williams Medical Center/The Miriam Hospital ACTU, Providence, RI, and Boston Univ School of Medicine, Boston, MA, USA, 2 Harvard School of Public Health, Boston, MA, USA, 3 Monogram Biosciences, Inc., South San Francisco, CA, USA, 4 Massachusetts General Hospital, Boston, CA, USA, 5 Birmingham VA Medical Center and University of Alabama at Birmingham School of Medicine, Birmingham, AL, USA, 6 University of California Davis Medical School, Sacramento, CA, USA

Gail Skowron, M.D.Division of Infectious DiseasesRoger Williams Medical Center825 Chalkstone Ave, Providence, RI 02908gail_skowron@brown.edutelephone: 401-456-2437 FAX 401-456-6839

BackgroundViral co-receptor tropism is associated with disease progression in untreated chronic HIV-1 infection. The relationships between tropism and other pre-treatment factors, such as replication capacity and lymphocyte subsets, have not been described. Higher baseline (BL) viral replication capacity (RC) has previously been associated with higher HIV-1 RNA and CD4 activation %, and lower CD4 and CD4 memory counts.

Methods

Results Discussion

1. In this analysis of selected treatment-naive subjects participating in ACTG 384, BL DM/X4 tropism was associated with lower BL memory, naive and total CD4 count, higher BL HIV-1 RNA, higher replication capacity, and higher CD4 and CD8 percent activation (Table 2).

2. We previously demonstrated, in an analysis of a larger subset of subjects participating in ACTG 384, that higher baseline RC was significantly associated with higher HIV-1 RNA, higher CD4 cell activation, lower CD4 cell count, and lower CD4 memory cell count (Skowron, 2009).

3. In a linear regression model (Table 3), higher baseline CD8 activation percent was significantly associated with higher baseline viral load (RNA), controlling for tropism, CD4 cell count and replication capacity at baseline.

4. In a linear regression model (Table 4), higher baseline CD4 activation percent was significantly associated with non-R5 tropism, lower baseline CD4 cell count, and higher baseline replication capacity (RC), adjusted for BL RNA. We had previously noted an association between higher baseline RC and higher baseline CD4 activation percent (r = 0.23, p < 0.0001).

5. In our previous analysis, we constructed a multivariable model, demonstrating that an increase in CD4 cell count from baseline to week 48 was associated with lower baseline CD4 memory count and higher baseline CD4 naive percent (p=0.004, p=0.015, respectively), adjusting for baseline RC, baseline CD4 and CD8 count, baseline RNA, and the interaction between baseline CD4 and baseline RC. The current analysis adds baseline tropism to this model (Table 5), but only CD4 naive percent remains significant, i.e., an increase in CD4 cell count is associated with higher baseline CD4 naive percent, controlling for the above baseline covariates and tropism.

6. These data raise provocative questions regarding the interplay between RC and DM/X4 tropism, in depleting naive and memory CD4 cells and increasing CD4 activation, and the resultant effect on CD4 recovery in patients on effective ART.

Using Monogram’s original Trofile Assay, we determined HIV-1 co-receptor tropism on pre-treatment plasma samples from 230 HIV-infected, treatment-naive subjects enrolled in ACTG 384 and selected on CD4 and viral response status (a subset of subjects with sample available from the group described in Skowron, 2009). Of these, 210 had undetectable HIV-1 RNA (50) at week 48. HIV-1 RNA, CD4 and CD8 subsets and RC were used to investigate BL and week 48 associations with tropism. Continuous outcomes were compared between R5 vs. DM/X4 groups with Wilcoxon Rank Sum tests. Linear and logistic regression models were also applied when controlling for BL covariates.

Table 1. Baseline Characteristics

This project was supported by SBIR Grant Number R44AI050321 from the National Institute of Allergy and Infectious Diseases (NIAID) to Monogram Biosciences and NIAID grant numbers AI38855, AI27659, AI38858, AI25879, AI27666. The ACTG 384 study was also supported in part by Agouron/Pfizer, Bristol Myers Squibb, and GlaxoSmithKline.

N 230

CD4 count (cells/mm3) median (Q1, Q3) 350 (119, 478)

HIV-1 RNA (log10copies/mL) median (Q1, Q3) 4.9 (4.4, 5.4)

Tropism

R5 (%) 173 (75%)

Dual-Mixed (%) 56* (24%)

X4 (%) 1* (<1%)

Table 5. Linear Regression Model of Change in CD4 cell count from BL to wk 48*

Figure 1. Baseline Immunologic and Virologic Parameters by Baseline Tropism

VariableParameter Estimate

Standard Error

t value Pr > |t |

Intercept 36.97 10.55 3.50 0.0006

BL Tropism R5 -1.37 2.75 -0.05 0.62

BL log10 RNA 4.02 1.86 2.15 0.033

BL CD4 cell count -0.010 0.0067 -1.52 0.13

BL RC -0.019 0.020 -0.95 0.34

Table 4. Linear Regression Model of Baseline CD4 activation percent*

VariableParameter Estimate

Standard Error

t value Pr > |t |

Intercept 30.51 9.19 3.32 0.0011

BL Tropism R5 -9.98 2.39 -4.17 < 0.0001

BL log10 RNA 0.71 1.62 0.44 0.66

BL CD4 cell count -0.030 0.0058 -5.14 < 0.0001

BL RC 0.039 0.018 2.19 0.0296

*restricted to 210 subjects who had virologic suppression (RNA 50) at wk 48

Results

BL covariates           Tropism  Median (Q1, Q3) P (Wilcoxon) P (adj. for RC)*

BL CD4 Cell Count(cells/mm3)                              

R5    385 (220, 525) <0.0001 <0.0001

DM or X4  138 (24, 311) 

BL Memory CD4 Count (cells/mm3)CD4+/CD45RO+/CD45RA- 

R5 192 (116, 271) <0.0001 0.0001

DM/X4 70 (16, 173) 

BL Naive CD4 Count(cells/mm3)CD4+/CD45RA+/CD62L+

R5 130 (49, 219) <0.0001 <0.0001

DM/X4  19 (3, 99)

BL CD4 Activation Percent (%)CD4+/CD38+/HLA-DR+

R5    12 ( 7, 19) <0.0001 <0.0001

DM/X4  33 (13, 48)   

BL CD8 Activation Percent (%)CD8+/CD38+/HLA-DR+

R5 48 (37, 60) 0.046 0.047

DM/X4 53 (41, 62)    

BL log 10 RNA (log10 copies/ml)

R5 4.8 (4.3, 5.3) <0.0001 0.0004

DM/X4 5.3 (4.9, 5.6)

BL Replication Capacity (BL RC)

R5 89 (53, 124) 0.0014 N/A

DM/X4 118 (82, 153)

Table 3. Linear Regression Model of Baseline CD8 activation percent*

Variable             Parameter Estimate  

Standard Error  

t value    Pr > |t|

Intercept           114.75      111.02       1.03      0.30

BL Tropism R5        11.99      27.65       0.43      0.66

BL RC                -0.43        0.28 -1.55      0.12

BL CD4 cell count   -0.16       0.15   -1.03      0.30

BL CD8 cell count -0.037    0.022    -1.67      0.097

BL log10 RNA         24.63  18.60      1.32      0.19

BL CD4 Memory count  -0.12     0.18     -0.66      0.51

BL CD4 Naive percent  1.42     0.72     1.98      0.049

Bl CD4 x BL RC             0.0018  0.00087  2.02      0.045*DM and X4 subsets combined in this analysis (DM/X4)

R5 vs DM/X4 virus

192

130

12

48

4.8

89

138

70

1933

53

5.3

118

385

0

50

100

150

200

250

300

350

400

450

CD4 cellcount

CD4memory

count

CD4 naivecount

CD4activation

%

CD8activation

%

HIV-1 RNA RC

Me

dia

n (

se

e T

ab

le 2

fo

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nit

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R5

DM or X4

*in a linear regression model adjusting for BL RC

References1. Skowron G, Spritzler JG, Weidler J, et al. Replication Capacity in Relation to

Immunologic and Virologic Outcomes in HIV-1 infected, Treatment-Naïve Subjects, J Acquir Immune Defic Syndr, 2009, in press.

Table 2. Baseline Immunologic and Virologic Parameters by Baseline Tropism