Transcript Incidence and Risk Factors of Rash from Efavirenz in HIV

Poster
M-105
Protease Polymorphisms in HIV-1 Subtype CRF01_AE Represent Selection by
Antiretroviral Therapy and Host Immune Pressure
Weerawat Manosuthi1,2, David M. Butler2, Josué Perez2, Art F. Y. Poon2, Sergei Kosakovsky Pond2, Satish K. Pillai3, Sanjay R. Mehta2, Mary E. Pacold2, Douglas D. Richman2,4, Davey M. Smith2,4 (Contact: [email protected])
1Bamrasnaradura
Infectious Diseases Institute, Ministry of Public Health, Thailand 2University of California San Diego, CA 3University of California San Francisco, CA 4Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
INTRODUCTION
RESULTS
▪ Resistance to protease inhibitors (PIs) develops with the acquisition of mutations in the
protease gene (pro). These resistance-associated mutations can be classified as either
major or accessory (Hammer 2008).
▪ 1,322 sequences between 1990 - 2007 were retrieved. 328 duplicated sequences and 6 nonCRF01_AE sequences were excluded. Analysis demonstrated that all remaining 988 sequences
were not hypermutated.
▪ 846 (86%) sequences were from Asian countries and 142 (14%) sequences came from non-Asian
countries. Asian countries included Thailand (22%), Vietnam (18%), China (17%), Cambodia (13%),
Singapore (10%), Japan (5%) and others (1%).
▪ Phylogenetic analysis demonstrated that the branch length between CRF01_AE pro sequences
revealed relatively low genetic diversity and overall percentage of pairwise similarity was 96%.
▪ The frequencies of major PRAMs and polymorphisms for the time periods of before and after the
introduction of PIs in the Asia region were also investigated (Figure 1).
▪ The correlation between each pair of polymorphisms was investigated (Table 1). There were
eight positive correlations and three negative correlations (all with P <0.05).
▪ Intersubtype genetic differences and the genetic background of the infected host
population can also influence PI susceptibility and viral replication capacity (Hirsch 2008).
OBJECTIVE
▪ To investigate how CRF01_AE protease polymorphisms and protease resistanceassociated mutations (PRAMs) have been affected by the introduction of antiretroviral
therapy and the frequency of HLA haplotypes in studied populations (Thai and Chinese).
METHODS
▪ All HIV-1 CRF01_AE pro sequences were downloaded from the Los Alamos National
Laboratory database on April 28, 2008.
▪ The recombinant identification program, RIP 3.0 (available at http://lanl.gov/), was used to
identify and confirm subtype and presence of recombination in retrieved sequences.
▪ The dataset was checked for uniqueness using the UNIX command “uniq” and
sequences were aligned using Multiple Sequence Comparison (Edgar 2004).
▪ Geneious Basic version 3.7.1 software (Biomatters Ltd., Auckland, NZ) was used to
construct a neighbor-joining tree using the Jukes-Cantor 69 method for phylogenetic
analysis.
▪ HYPERMUT 2.0 and Epitope Location Finder (available at http://lanl.gov/) were used to
detect APOBEC-induced hypermutation and searched CTL recognized epitopes from viral
amino acid sequences by using sequence code 01_AE.AU.X.CT1 as a reference sequence
(Rose and Korber 2000).
Figure 2. Logistic regression analysis of major PRAMs
and each polymorphism
Figure 1. Frequencies of major PRAMs and
polymorphisms by time period
1990-2000 (n=188)
L76V
2001-2007
V77I
No data (n=263)
D30N
P olymorphis ms
1990-2000
L33V
2001-2007 (n=537)
OR
No data
I62V
N88S
10.955 3.236-37.092
P = 0.031
2.6% 0.5%
D60E
I84V
V82I
I54VA
I93L
4.263 2.585-7.032
L10V
M46IL
4.8%
2.0%
P = 0.067
6.460 3.972-10.505
K20RMI
V82AFMS
I13V
85.6%
L90M
M36I
95.2%
0
10
20
30
40
Number
Frequencies of PRAMs
0
76.3%
87.1%
P = 0.007
Adjusted odds ratios
Unadjusted odds ratios
*
0
10
20
30
P <0.001
40
50
60
Odds ratio and 95% confidence interval (CI)
Number
Frequencies of polymorphisms
Figure 3. Associations between HLA haplotypes
and polymorphisms
Figure 4. Predicted fold changes of HLA class I
binding affinities from the eptiope of subtype B
consensus to CRF01_AE
B: E EM NLPGRW
AE: E DINLPGKW
Protease
Epitope position: 34-42
HLA Allele: B*4001
0
34-42
B*4430
34-42
34-42
30-38
30-38
11-20
12-20
B*4402
B*1801
A*6802
A*6801
A*0301
A*0301
3.0
2.4
4.9
4.1
-20
18.9
26.7
-30
-40
36.5
39.7
▪ There were no substantial differences in hydrophobicity or chemical classifications of these
residues between subtype B and CRF01_AE consensus sequences (Table 2).
CONCLUSION
Polymorphisms in CRF01_AE protease gene are common with M36I being the most frequent.
Polymorphisms at residue 10, 20 and 62 were associated with major PRAMs and therefore PI
use, while R41K and H69K variants are more likely attributable to recognition of epitopes by
the HLA haplotypes in the population. Additionally, protease function most likely requires
maintaining the same biochemical properties at these residues.
Negative correlation
Polymorphic mutation
Correlation coefficient
P value
Polymorphic mutation
Correlation coefficient
P value
10 and 62
0.154
<0.001
20 and 36
-1.333
<0.001
20 and 62
0.140
<0.001
13 and 93
-0.400
<0.001
20 and 93
0.125
<0.001
10 and 93
-0.089
0.005
60 and 93
0.104
0.001
10 and 20
0.095
0.003
77 and 93
0.094
0.003
10 and 13
0.004
0.093
13 and 82
0.069
0.030
Table 2. Hydrophobicity and chemical classifications of six different residues
Residue
Subtype B
Hydrophobicity*
Chemical classifications
Subtype AE
Hydrophobicity*
Chemical classifications
13
I
1
Aliphatic group
V
1
Aliphatic group
35
E
4
Negative charge
D
4
Negative charge
A*0101
36
M
2
Sulphur containing group
I
1
Aliphatic group
1.1
41
R
5
Positive charge
K
4
Positive charge
69
H
4
Positive charge
K
4
Positive charge
89
L
1
Aliphatic group
M
2
Sulphur containing group
B: DTVLEE M NL
AE: DTVLEE INL
-10
A positive HLA-polymorphism association was defined as expression of a subtype B
consensus residue that would be expected during CTL escape with the HLA allele
expression in the study population.
A negative HLA-polymorphism association was defined when expression of the
CRF01_AE consensus residue was associated with HLA expression and CTL escape.
▪ The nine HLA-polymorphism associations with the largest changes in predicted binding
affinity are presented in Figure 4.
Positive correlation
100 200 300 400 500 600 700 800 900
▪ The prevalence of specific HLA alleles in the populations studied (Thai and Chinese) were
obtained from the dbMHC database of the National Center for Biotechnology Information
(http://www.ncbi.nlm.nih.gov/projects/gv/mhc).
▪ Spearman correlations and logistic regression models were used for further analyses.
-10
▪ At five residue sites, 30 HLA-polymorphism associations were found, distributed among 11
(37%) HLA-A, 17 (56%) HLA-B and 2 (7%) HLA-C haplotypes (Figure 3). Of these associations, 24
(80%) were positive correlations (i.e. the subtype B consensus amino acid was favored) and 6
(20%) were negative correlations.
Table 1. Correlations among each pair of polymorphisms
P = 0.002
▪ PRAMs and polymorphisms were identified based on data derived from clade B virus
using the Stanford Resistance Database (http://hivdb.stanford.edu/).
▪ HLA binding affinities were determined using the Immune Epitope Database and Analysis
resource (IEDB, www.immuneepitope.org) by stabilized matrix method.
I93L
V82I
V77I
*I62V
I62V
D60E
M36I
M36I
L33V
*K20RMI
K20RMI
I13V
*L10V
L10V
95%CI
Fold changes
▪ Continued viral replication in the setting of PIs allows for the development and
accumulation of accessory mutations in HIV pro, which can compensate for impaired
fitness conferred by other mutations or can increase the level of phenotypic resistance
(Hirsch 2008; Johnson 2008).
▪ 4 polymorphisms had an association with a PRAM with P values <0.2 in Fisher’s exact test
univariate analysis. In multivariate analysis, three of four polymorphisms were associated with
the presence of a major PRAM (P <0.05) (Figure 2).
7-15
* Hydrophobicity 1 to 5 = from the highest hydrophobicity to the least hydrophobicity
Acknowledgement: The authors would like to thank The University of California, San Diego Center for AIDS Research
(UCSD CFAR) for their support. This work was supported by grants AI69432 (ACTG), AI043638 (AIEDRP), MH62512
(HNRC), MH083552 (Clade), AI077304 (Dual Infection), AI36214 (the Viral Pathogenesis Core of the UCSD Center for
AIDS Research), AI047745 (Dynamics), AI74621 (Transmission) from the National Institutes of Health and the California
HIV/AIDS Research Program RN07-SD-702.