Host Genetic Factors Associated with Symptomatic
Primary HIV Infection and Disease Progression among
Argentinean Seroconverters
Romina Soledad Coloccini1, Dario Dilernia1, Yanina Ghiglione1, Gabriela Turk1, Natalia Laufer1,2,
Andrea Rubio1, Marı́a Eugenia Socı́as2,3, Marı́a Inés Figueroa2,3, Omar Sued2,3, Pedro Cahn2,3,
Horacio Salomón1, Andrea Mangano4, Marı́a Ángeles Pando1*
1 Instituto de Investigaciones Biomédicas en Retrovirus y SIDA (INBIRS), Universidad de Buenos Aires-CONICET, Buenos Aires, Argentina, 2 Hospital Juan A. Fernandez,
Buenos Aires, Argentina, 3 Fundación Huésped, Buenos Aires, Argentina, 4 Laboratorio de Biologı́a Celular y Retrovirus, CONICET, Hospital de Pediatrı́a ‘‘Prof. Dr. Juan P.
Garrahan’’, Buenos Aires, Argentina
Abstract
Background: Variants in HIV-coreceptor C-C chemokine receptor type 5 (CCR5) and Human leukocyte antigen (HLA) genes
are the most important host genetic factors associated with HIV infection and disease progression. Our aim was to analyze
the association of these genetic factors in the presence of clinical symptoms during Primary HIV Infection (PHI) and disease
progression within the first year.
Methods: Seventy subjects diagnosed during PHI were studied (55 symptomatic and 15 asymptomatic). Viral load (VL) and
CD4 T-cell count were evaluated. HIV progression was defined by presence of B or C events and/or CD4 T-cell counts ,
350 cell/mm3. CCR5 haplotypes were characterized by polymerase chain reaction and SDM-PCR-RFLP. HLA-I characterization
was performed by Sequencing.
Results: Symptoms during PHI were significantly associated with lower frequency of CCR5-CF1 (1.8% vs. 26.7%, p = 0.006).
Rapid progression was significantly associated with higher frequency of CCR5-CF2 (16.7% vs. 0%, p = 0.024) and HLA-A*11
(16.7% vs. 1.2%, p = 0.003) and lower frequency of HLA-C*3 (2.8% vs. 17.5%, p = 0.035). Higher baseline VL was significantly
associated with presence of HLA-A*11, HLA-A*24, and absence of HLA-A*31 and HLA-B*57. Higher 6-month VL was
significantly associated with presence of CCR5-HHE, HLA-A*24, HLA-B*53, and absence of HLA-A*31 and CCR5-CF1. Lower
baseline CD4 T-cell count was significantly associated with presence of HLA-A*24/*33, HLA-B*53, CCR5-CF2 and absence of
HLA-A*01/*23 and CCR5-HHA. Lower 6-month CD4 T-cell count was associated with presence of HLA-A*24 and HLA-B*53,
and absence of HLA-A*01 and HLA-B*07/*39. Moreover, lower 12-month CD4 T-cell count was significantly associated with
presence of HLA-A*33, HLA-B*14, HLA-C*08, CCR5-CF2, and absence of HLA-B*07 and HLA-C*07.
Conclusion: Several host factors were significantly associated with disease progression in PHI subjects. Most results agree
with previous studies performed in other groups. However, some genetic factor associations are being described for the first
time, highlighting the importance of genetic studies at a local level.
Citation: Coloccini RS, Dilernia D, Ghiglione Y, Turk G, Laufer N, et al. (2014) Host Genetic Factors Associated with Symptomatic Primary HIV Infection and Disease
Progression among Argentinean Seroconverters. PLoS ONE 9(11): e113146. doi:10.1371/journal.pone.0113146
Editor: Srinivas Mummidi, South Texas Veterans Health Care System and University of Texas Health Science Center at San Antonio, United States of America
Received July 3, 2014; Accepted October 20, 2014; Published November 18, 2014
Copyright: ß 2014 Coloccini et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The authors confirm that all data underlying the findings are fully available without restriction. All relevant data are within the paper and its
Supporting Information files.
Funding: This research was funded by grants from: Agencia Nacional de Promoción Cientı́fica y Tecnológica (grant number 2008-0559), ‘‘Fundación Florencio
Fiorini’’ (period: 2009–2010), UBACYT (period: 2010–2012) and CONICET (PIP 2011–2013). The funders had no role in study design, data collection and analysis,
decision to publish, or preparation of the manuscript.
Competing Interests: One of the authors, Dr. Omar Sued (Fundación Huesped) is a PLOS ONE Editorial Board member. This does not alter the authors’
adherence to PLOS ONE Editorial policies and criteria.
* Email: mpando@fmed.uba.ar
in the host, local studies are needed to better understand the
particular characteristics of HIV infection dynamics [1].
In Argentina, an estimated 110,000 persons live with HIV
(approximately 5,000 new cases per year) [2]. The first multicenter
follow-up study of PHI (Grupo Argentino de Seroconversión)
started in 2008. Retrospective and prospective data analyses
allowed identifying factors associated with disease progression
among untreated subjects. Symptomatic PHI, high VL ($100,000
Introduction
Research studies on primary HIV infection (PHI) are increasing
worldwide to better understand the natural history of HIV
infection and to identify the most important disease prognostic
markers. As most of these studies were performed in other
countries and due to genetic differences in the circulating virus and
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Host Genetic Factor Influence on HIV Infection
RNA copies/ml) or low CD4 T-cell count (#350 cell/mm3) at
baseline were identified as relevant factors for faster progression
during the first year follow-up [3]. Data comparisons with other
PHI cohorts revealed that VL at baseline in the Argentinean
cohort was higher than those found in developed countries [4–5],
closer to African and Asian levels [6–7]. Globally, 50–90% of
subjects diagnosed during PHI are symptomatic [8–10], reaching
74% in the mentioned Argentinean cohort [3].
Previous studies demonstrated extensive variability in host
susceptibility to HIV infection and disease progression [11–13].
Several host genetic factors affecting HIV infection and pathogenesis were identified, like chemokine receptors and HLA alleles
[14–17]. Multiple variations were described in the CCR5 gene, in
particular the 32 base-pair deletion (CCR5-D32). This deletion
provides protection against HIV-1 infection with CCR5 tropic
viruses in homozygotes and delays progression in heterozygous
subjects [16,18–19]. Seven Single Nucleotide Polymorphisms
(SNPs) were defined in the cis-regulatory region between 22761
and 21835 of the CCR5 gene: 22733, 22554, 22459, 22135,
22132, 22086 and 21835 (GenBank accession number
AF031236 and AF031237) [20]. Based on these variations and
on the CCR2-V64I polymorphism, nine polymorphisms, called
CCR5 Human Haplotypes (HH)-A, -B, -C, -D, -E, -F (F*1 and
F*2), and –G (G*1 and G*2) were defined [15,20–21]. One of the
largest studies in the subject demonstrated that the frequency and
effect of CCR5-HH differ among different ethnic groups. CCR5HHA was associated with disease retardation among AfricanAmericans, whereas CCR5-HHC did so among EuropeanAmericans. In the same study, specific sequences of CCR5-HHE
were associated with higher transcriptional activity, surface
expression and HIV/AIDS susceptibility [21]. Another factor
associated with disease progression is the dose of the gene
encoding CCL3L1 (MIP-1a), a natural ligand of CCR5. A
previous study found an association between lower gene dose and
disease progression, and this susceptibility is even greater in
individuals with CCR5 genotypes associated with disease progression [22].
The HLA system has an impact on several aspects of HIV
infection such as transmission, progression and therapeutic
response [23–24]. HLA class I molecules are involved in peptide
presentation to CD8 cytotoxic T lymphocytes (CTLs), which play
a key role in reducing viral replication. HIV specific CD8 T-cell
response emerges along with the control of viremia and resolution
of clinical symptoms, which varies from person to person and
constitutes a strong predictor of disease progression [25–26].
Heterozygosis at HLA class I region is considered to be a selective
advantage because those individuals are able to present a greater
range of antigenic peptides to CTLs than homozygotes, deferring
the emergence of escape mutants and prolonging the period before
the development of AIDS [18]. Even when several HLA alleles
were associated with disease progression, HLA-B*27 and HLAB*57 alleles showed a particularly strong association with delayed
progression [27] and HLA-B*35 and HLA-B*53 with acceleration
to AIDS [28].
Based on the effects of host genetic variations described on HIV
disease progression, our aim was to analyze the association of
CCR5/CCL3L1 system and HLA in the presence of clinical
symptoms during PHI and disease progression within the first year
post-infection.
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Materials and Methods
Study population
A group of 70 individuals recruited through 2008–2012 was
studied. Inclusion criteria for enrolment in the cohort were: .16
years old at first evaluation, PHI confirmed diagnosis, and first
medical and laboratory evaluation (i.e., CD4 T-cell count and
plasma HIV RNA) within six months of the probable date of
infection. Primary HIV infection is defined as: (1) detection of HIV
RNA or p24 antigen with a simultaneous negative or indeterminate Western blot assay [12]; or (2) positive Western blot with a
negative test within the previous six months. Hence, it includes
both acute and recently infected patients [3].
In this study, PHI was defined as symptomatic if one or more of
the following symptoms, associated with acute retroviral syndrome, were present: fever, rash, lymphadenopathy, headache,
oral ulcers, dysphagia or pharyngitis. Disease progression was
defined by clinical B or C events (according to the Centers for
Disease Control and Prevention 1993 classification [29]) and/or
CD4 T-cell count ,350 cells/mm3 within the first year of
infection [3].
Ethics Statement
International and national ethical guidelines for biomedical
research involving human subjects were followed. This research
study was reviewed and approved by a local Institutional Review
Board (IRB), ‘‘Fundación Huésped’’ and was conducted in
compliance with all federal regulations governing the protection
of human subjects. All potential participants signed an informed
consent prior to entering the study.
Study Procedure
Once subjects were identified as PHI, they were included in the
cohort. Subjects were evaluated at the time of diagnosis (baseline),
at 6 months and at one year. On each visit, HIV plasma VL
(branched-DNA, Versant HIV-1 RNA 3.0 assay, Siemmens
Healthcare, USA), CD4 T-cell count (flow cytometry double
platform, BD FACSCanto, BD Biosciences, USA), and clinical
information were updated.
Study samples
Peripheral blood samples were obtained on each visit. Whole
blood samples or peripheral blood mononuclear cells (PBMC)
were used for DNA extraction using QIAmp DNA Blood Mini Kit
(QIAGEN GmbH, Hilden, Germany). Plasma samples from the
first visit after HIV diagnosis were used for lipopolysaccharide
(LPS) quantification (Limulus Amebocyte Lysate test, LAL assay,
QCL-1000, Lonza, DK). HIV tropism was determined by
sequencing a region of V3 loop from env gene (HXB2) [30].
Viral DNA was amplified in duplicate by nested PCR and
amplicons were sequenced by Big Dye Terminator Kit (Amersham, Sweden). Viral tropism was inferred from Geno2Pheno
algorithm
(http://coreceptor.bioinf.mpi-inf.mpg.de/index.php)
using a false positive rate of 10%.
CCR5 and CCL3L1 characterization
CCR5-D32 deletion was identified by differences in PCR
products size. CCR2 genotypes and Single Nucleotide Polymorphisms (SNPs) of the CCR5 gene corresponding to positions 29,
208, 627, 630, 676 and 927 (Genbank accession number:
AF031236 and AF031237) [31] were determined with Site
Directed Mutagenesis-PCR-Restriction Fragment Length Polymorphism (SDM-PCR-RFLP) assay. Primers used in each
determination, PCR cycling condition and RFLP assay were
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Host Genetic Factor Influence on HIV Infection
reported previously [15,21,32–33]. Haplotype classification
(HHA, HHB, HHC, HHD, HHE, HHF*1, HHF*2, HHG*1
and HHG*2) was determined as reported previously [15,20–21].
CCL3L1 Copy Number (CN) was determined by Taqman realtime PCR [22].
surrounding areas. The population of this area is mostly
descendent from South Europe [41]. Median HIV VL at diagnosis
was 61862 RNA copies/ml, whit significantly higher VL in those
who presented symptoms and those who progressed (Table 1).
The same trend was observed for VL at 6 months. Baseline CD4
T-cell count was 514 cells/mm3 without statistical differences
between symptomatic and asymptomatic subjects. Significantly
higher CD4 T-cell counts (baseline, 6 and 12 months) were
observed among subjects who did not progress to disease during
the first year (Table 1).
HLA characterization
HLA class I characterization was performed by sequencingbased typing (SBT). HLA-A exons 2 and 3 were amplified
together. HLA-B and HLA-C exons 2 and 3 were amplified
separately as reported in Table S1 and Figure S1 [34–36].
Amplicons were sequenced using the Big Dye Terminator
sequencing kit (Amersham, Sweden) [36]. Sequence interpretation
was performed using the NCBI SBT Interpretation software
(http://www.ncbi.nlm.nih.gov/gv/mhc/sbt.cgi?cmd=main).
Frequency of CCR5 haplotypes/genotypes and CCL3L1
Similar to the results found in Argentinean children exposed
perinatally to HIV (including both HIV infected and not infected)
[42] and blood donors [43], the most frequent CCR5 haplotypes
in the PHI group were HHE (36.4%) and HHC (30.7%).
Frequencies of all the other haplotypes were lower than 10%
(Figure 1; Table S2). Regarding CCR5 genotypes, HHC/HHE
(21.4%) and HHE/HHE (12.9%) were the most commonly found.
Other genotypes were present with frequencies lower than 10%
(Table 2 and Table S3). The CCL3L1 gene copy number, one of
the main ligands of CCR5, was evaluated in 50 PHI subjects with
a median of two copies (IQR25-75, 1–4), as reported in persons of
European origin [22].
Genetic score
Additive genetic score was used to compile host genetic
information [37]. In our model, alleles with a previous reported
protective effect were added, and risk alleles were subtracted. For
CCR5 polymorphisms, D32 and CCR2-64I alleles were considered as protective (1) [21]. Regarding CCR5 genotypes, HHC/
HHF*2 and HHC/HHG*2 were considered as protective (1),
HHC/HHE, HHE/HHE and HHE/HHG*2 as deleterious (–1),
and the others as neutral (0) [21,32]. Two CCL3L1 cpg (mean in
the Argentinean population) were considered as neutral (0). Lower
CCL3L1 CN than the mean was considered as deleterious (–1)
and higher CN as protective (1) [22]. HLA-A*02, HLA-A*32,
HLA-A*68, HLA-B*15, HLA-B*13, HLA-B*27, HLA-B*32,
HLA-B*39, HLA-B*44, HLA-B*51 and HLA-B*57 were considered as protective (1). HLA-A*11, HLA-A*23, HLA-A*24, HLAB*08, HLA-B*35, HLA-B*53, HLA-C*04 and HLA-C*07 were
considered as deleterious (–1). Other HLA alleles were considered
as neutral (0) [11–13,23–24,27–28,37–39]. Heterozygosis for HLA
was considered as protective (1) and homozygosis as deleterious
(–1) [18].
Frequency of HLA variants
Given the essential role of CTL responses during PHI as well as
the description of a strong association among certain HLA-I alleles
with virus control, HLA-I frequencies were studied in this cohort
finding 17 HLA-A, 27 HLA-B and 14 HLA-C different alleles.
The HLA-A alleles most frequently found were HLA-A*02
(27.2%) and HLA-A*24 (12.5%). In HLA-B locus, HLA-B*35
(15.6%) and HLA-B*44 (12.9%) were the most frequent. In HLAC, HLA-C*07 (27.9%), HLA-C*04 (16.2%) and HLA-C*03
(11.8%) were the most frequent. Other HLA-A, B and C alleles
showed frequencies lower than 10% (Table S4). HLA class I alleles
were found in homozygosis in the following frequencies: 32.4% for
HLA-A, 3.0% for HLA-B and 17.6% for HLA-C (Table S5). The
most common combinations for HLA-A were A*02-A*02 (11.8%)
and A*02-A*68 (8.8%), for HLA-B were B*15-B*35 (4.5%) and
B*35-B*44 (4.5%), and for HLA-C, C*04-C*07 (8.8%), C*07C*07 (8.8%) and C*03-C*07 (7.4%) (data not shown).
Statistical analysis
Baseline characteristics were described using mean or medians
and standard deviation or interquartile ranges [IQRs] for
continuous variables respectively, and counts and percentages
for categorical data. Chi-square test or Fisher’s exact test were
used to compare proportions. Differences among continuous
variables were analyzed using Student’s t-test or Wilcoxon test.
Spearman correlation was calculated for genetic score and HIV
viral load and CD4 T-cell count (baseline and follow up). All p
values were two-sided; p values,0.05 were considered to be
statistically significant. Lack of complete data values in table is
expressed in numbers. Data analysis was performed using SPSS
15.0, 2007 (Chicago, Illinois).
Influence of CCR5 haplotypes/genotypes, CCL3L1 copy
number, and HLA variants on symptoms present during
acute HIV infection
In order to identify individual host genetic determinants of early
HIV disease progression, the PHI cohort was stratified according
to the presence/absence of symptoms during the seroconversion
period. Regarding the CCR5 coreceptor, HHC was overrepresented (40% vs. 28.2%) and HHE (23.3% vs. 40%) was less
frequent in asymptomatic as compared to symptomatic subjects,
however without statistical significance (Figure 1). Concerning
CCR5 genotypes, HHC/HHF*1 was detected in a significantly
higher percentage among asymptomatic subjects (26.7% vs. 1.8%,
p = 0.006). Even when it was not statistically significant, genotype
HHE/HHF*1 was only found among symptomatic subjects
(10.9%) (Table 2 and Table S3). No significant differences were
found in the CCL3L1 copy number, even when a higher copy
number was detected among asymptomatic (median (IQR25-75);
3 (2–3) and 2 (1–4), respectively). No influence of HLA-A, -B and C alleles was detected in the presence of symptoms during PHI
(Table S4). Likewise, no influence of HLA homozygosis was
Results
Characteristics of the study population
We studied 70 HIV-infected adults diagnosed during primary
HIV infection (PHI) (49 men and 21 women), 55 were
symptomatic and 15 asymptomatic. Sixty of them were also
classified according to disease progression within the first year post
diagnosis, 18 progressed and 42 did not. Most PHI subjects were
recruited during Fiebig stages V and VI [40]. Sexual transmission
was reported as the main route: all the women reported
heterosexual transmission whereas 82.2% of men reported sexual
relationship with other men as the probably route of acquisition of
the virus. All subjects were from Buenos Aires City and
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Table 1. HIV viral load and CD4 T-cell count of the study population diagnosed during primary HIV infection [PHI] (N = 70).
Symptomatic PHI
HIV RNA
median
copies/ml
(IQR)
Yes (N = 55)
No (N = 15)
77,080
7,024
(30,449–386,715)
(2,699–76,466)
66,002
9,018
(17.959–178.030)
(3,820–34,624)
Baseline
502
587
(356–649)
(416–876)
6 month
499
555
(356–665)
(424–665)
491
534
(389–615)
(436–672)
Baseline
6 month
CD4 T-cell
count
median
cells/mm3
(IQR)
p
12 month
0.003
0.004
0.322
0.694
0.296
Progressor at one year
4
Yes (N = 18)
No (N = 42)
193,601
41,402
(80,545–500,000)
(10,409–154,476)
166,812
33,508
(47,167–321,018)
(8,578–73,231)
306
602
(237–346)
(500–741)
323
602
(172–386)
(488–690)
330
534
(289–504)
(435–643)
p
All (N = 70)
0.003
61,862
(17,050–257,524)
0.001
40,231
(117,17–165,238)
,0.001
514
(387–671)
,0.001
503
(404–65)
0.001
501
(400–619)
PHI: primary HIV infection. IQR: interquartile range. Statistically significant p values are in bold.
doi:10.1371/journal.pone.0113146.t001
Host Genetic Factor Influence on HIV Infection
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Host Genetic Factor Influence on HIV Infection
Figure 1. Frequency of CCR5 haplotypes of the study population diagnosed during primary HIV infection [PHI] (N = 70). Full
information is available on supplementary material (Table S1).
doi:10.1371/journal.pone.0113146.g001
(66,001 copies/ml vs. 31,718 copies/ml, p = 0.039) and also higher
baseline VL (98,684 copies/ml vs. 41,402 copies/ml, p = 0.082).
On the other hand, HHA was found to be associated with higher
baseline CD4 T-cell levels (656 cells/mm3 vs. 499 cells/mm3,
p = 0.044). Regarding CCR5 genotypes, HHC/HHF*1 was
associated with lower VL (6,243 copies/ml vs. 53,997 copies/ml,
p = 0.027) and HHC/HHF*2 with lower CD4 T-cell levels at
baseline (379 cells/mm3 vs. 545 cells/mm3, p = 0.046), at 6
months (355 cells/mm3 vs. 531 cells/mm3, p = 0.024) and at 12
months (290 cells/mm3 vs. 510 cells/mm3, p = 0.034).
Concerning the HLA influence on CD4 T-cell count and HIV
plasma VL, the presence of several alleles was found to be
beneficial for HIV subjects, with an association with higher CD4
T-cell count (HLA-A*01, HLA-A*23, HLA-B*07, HLA-B*39 and
HLA-C*07) or lower HIV plasma VL (HLA-A*31 and HLAB*57). Conversely, some alleles were found to be detrimental for
subjects, with an association with higher HIV plasma VL (HLAA*11, HLA-A*24 and HLA-B*53) or lower CD4 T-cell count
(HLA-A*24, HLA-A*33, HLA-B*14, HLA-B*53 and HLA-C*08)
(Table 3).
observed in the presence of symptoms during seroconversion
(Table S5). When HLA pairs were compared, HLA-B*35-B*44
was found in a significantly higher frequency among asymptomatic
subjects (21.4% vs. 0%, p = 0.007) (data not shown).
Only CCR5 genotypes with a frequency higher than 10% in
some of the study groups were included in the table. No significant
differences were observed among CCR5 genotypes with frequencies lower than 10%. Full information is on supplementary
material (Table S2).
Influence of CCR5 haplotypes/genotypes, CCL3L1 and
HLA variants on disease progression within the first year
Additionally, the PHI group was analyzed in order to identify
possible genetic factors that might influence the rate of progression
within the first year. Several CCR5 haplotypes were most
frequently detected in individuals who did not progress (e.g.
HHA, HHF*1 and HHG*2) and HHF*2 was most represented in
subjects who progressed to disease (Table S2), without statistical
differences. Regarding CCR5 genotypes, HHC/HHF*2 was
significantly associated with progression (p = 0.024) and a higher,
but not significant proportion of subject who progress had HHE/
HHE also as compared with those who do not progress (22.2% vs.
7.1%) (Table S3). Regarding HLA alleles, a strong association was
found between disease progression and higher frequency of HLAA*11 (16.7% vs. 1.2%, p = 0.003) and lower frequency of HLAC*03 (17.5% vs. 2.8%, p = 0.035) (Table S4). No influence of HLA
homozygosis was observed in disease progression (Table S5).
Additive genetic score
Additive genetic score was calculated for each subject and
average values were calculated considering symptoms during PHI
(2.6 for asymptomatic and 1.4 for symptomatic subjects) and
disease progression within the first year (1.8 for those who did not
progress and 0.6 for those who progressed). Subjects were grouped
according to both characteristics: Group 1: Asymptomatic/Nonprogressors, Group 2: Asymptomatic/Progressors and Symptomatic/Non-progressors, and Group 3: Symptomatic/Progressors.
Mean genetic score was: 2.8, 1.6 and 0.5 for groups 1, 2 and 3,
respectively. Correlation analyses revealed a significant negative
correlation between genetic score and HIV viral load at baseline
(p = 0.008) (Figure 2). No significant association was observed
between genetic score and CD4 T-cells count.
Influence of CCR5 haplotypes/genotypes, CCL3L1 and
HLA variants on plasma HIV viral load and CD4 T-cell
count
As the CD4 T-cell count and HIV plasma VL are good
predictors of disease progression [3], the association of these
parameters with host genetic factors was also analyzed. Subjects
with CCR5 HHE haplotype had higher VL after 6 months
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Host Genetic Factor Influence on HIV Infection
9 (12.9)
6 (8.6)
0.220
1.000
3 (7.1)
4 (9.5)
4 (5.7)
0.658
5 (11.9)
6 (8.6)
0.024
0
5 (7.1)
1.000
4 (9.5)
3 (4.3)
0.212
1.000
1 (2.4)
9 (21.4)
p
No (N = 42)*
*Data are no. (%) of CCR5 haplotypes.
doi:10.1371/journal.pone.0113146.t002
4 (22.2)
0.672
1 (5.6)
0
8 (14.5)
6 (10.9)
HHE/HHF*1
1 (6.7)
Other countries reported associations between human genes
and HIV susceptibility. However, local studies are needed
considering differences in genetic background [14,17,19]. In line
with this, for the first time in Argentina, this study reports several
human genes associated with early HIV disease progression
among adults.
Buenos Aires population is mainly descendant of Southern
Europe. The frequency of CCR5 haplotypes reported here
correlates with reports in Hispanic and other Argentinean groups
[21,43], with HHE and HHC being the most common haplotypes.
Regarding CCR5 genotypes, the most common were HHC/HHE
and HHE/HHE, with other genotypes having frequencies lower
than 10%. In comparison with blood donors, PHI individuals were
found to have a higher but not significant frequency of HHE/
HHE genotype (5.9% vs. 12.9% respectively). This result is
consistent with previous reports evidencing an association between
presence of HHE/HHE genotype and enhancement of HIV
infection [21,42]. Even when the HHE haplotype and the HHE/
HHE genotype were overrepresented among symptomatic subjects
and those who progressed, no significant associations were
observed, maybe due to sample size. Data on HIV VL also
supports the same trend with significantly higher VL at 6 months
among subjects carrying HHE. This trend is in line with previous
studies that associated disease progression with HHE [21,42].
However, this disease-modified effect was not observed among
other ethnic groups (i.e., Africans) where the frequency of HHE
haplotype was much lower (<18%) [21]. As HHE is the most
frequent CCR5 haplotype in our cohort, the potential adverse
effect of this haplotype deserves special attention.
HHC/HHF*1 genotype was associated with asymptomatic PHI
and HHC/HHF*2 with disease progression. In line with these
results, we found that the HHC/HHF*1 genotype was associated
with lower levels of VL and HHC/HHF*2, with lower CD4 T-cell
levels at baseline and during one-year follow-up. Only few studies
support these findings, maybe due to the fact that these genotypes
were found in low frequency in most cohorts [21,42]. One of the
most important studies in the subject found a disease accelerating
effect for HHC/HHF*1 among African Americans [21]. However, this study also reports that the effect of HHC haplotypes on
HIV disease differed among ethnic groups. While the HHC
0.329
1 (5.6)
HHE/HHE
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1 (6.7)
5 (9.1)
HHC/HHG*1
1.000
3 (16.7)
1 (5.6)
0.006
HHC/HHF*2
1.000
4 (26.7)
1 (6.7)
1 (1.8)
3 (5.5)
HHC/HHF*1
4 (22.2)
2 (11.1)
0.521
1.000
12 (21.8)
HHC/HHE
1 (6.7)
2 (3.6)
HHC/HHC
No (N = 15)*
Yes (N = 55)*
3 (20)
Yes (N = 18)*
Progressor at one year
HIV infection has been associated with disruption of mucosal
barrier and CD4 T-cell depletion in the gastrointestinal tract. This
damage is caused, at least in part, by increased translocation of
microbial products, mainly lipopolysaccharides (LPS), a major
component of gram-negative bacterial cell walls [44–46]. Since
immune activation is a good predictor of disease progression,
plasma LPS levels were determined in the baseline sample of 65
individuals finding a median of 39.0 pg/ml (IQR25-75, 26.7–56.8)
with significantly higher levels in the symptomatic than the
asymptomatic group (43.5 pg/ml vs. 29.0 pg/ml, p = 0.040). No
association was found among LPS levels, disease progression, CD4
T-cell count, HIV VL or host genetic factors. HIV tropism was
determined given that the presence of X4 tropic viruses was
associated with a more rapid disease progression (data not shown).
Fourteen out of 59 (23.7%) PHI subjects presented X4 tropic HIV
variants. Even when no statistically significant differences were
observed, X4 tropic HIV variants were overrepresented among
symptomatic subjects (26.1% vs. 15.4%, p = 0.713). No differences
were observed among HIV tropism, disease progression, CD4 Tcell count or HIV VL.
Discussion
p
Symptomatic PHI
Genotype
Table 2. Frequency of CCR5 human genotypes of the study population diagnosed during primary HIV infection [PHI] (N = 70).
15 (21.4)
All (N = 70)
Complementary studies
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November 2014 | Volume 9 | Issue 11 | e113146
Host Genetic Factor Influence on HIV Infection
Table 3. HIV viral load and CD4 T-cell count of the study population diagnosed during primary HIV infection [PHI] according to
HLA alleles (N = 70).
Alleles
HLA-A*01
HLA-A*11
HLA-A*23
HLA-A*24
HLA-A*31
HLA-A*33
HLA-B*07
HLA-B*14
HLA-B*39
HLA-B*53
HLA-B*57
HLA-C*07
HLA-C*08
CD4 T-cell count
HIV RNA
median cells/mm3
median copies/ml
Baseline
6 months
12 months
Baseline
6 months
Yes
902
810
716
5160
4298
No
500
499
491
64045
40083
p
0.022
0.019
0.112
0.241
0.317
Yes
347
344
475
477708
166930
No
525
517
492
52352
38270
p
0.070
0.071
0.447
0.020
0.059
Yes
736
637
534
36101
24322
No
499
497
475
61862
40232
p
0.038
0.072
0.195
0.374
0.290
Yes
393
403
483
500000
89517
No
576
545
500
41402
30591
p
0.049
0.048
0.371
0.001
0.004
Yes
602
563
612
24654
19603
No
502
502
491
67397
56594
p
0.494
0.616
0.883
0.032
0.038
Yes
387
387
347
67660
67660
No
535
528
515
55276
39484
p
0.046
0.100
0.021
0.818
1.00
Yes
535
818
679
378025
133268
No
525
499
474
52352
38720
p
0.972
0.015
0.005
0.177
0.280
Yes
466
485
410
213099
117061
No
575
542
534
52352
37506
p
0.167
0.135
0.002
0.229
0.260
Yes
644
780
573
4383
18062
No
509
497
483
62679
42753
p
0.098
0.027
0.175
0.073
0.085
Yes
288
248
286
500000
349244
No
545
531
509
54286
39033
p
0.046
0.036
0.117
0.058
0.028
Yes
525
495
654
16926
12971
No
529
528
492
66821
47077
p
0.819
0.865
0.272
0.046
0.058
Yes
525
527
534
66821
60546
No
497
491
449
62679
40083
p
0.738
0.527
0.038
0.584
0.563
Yes
437
499
409
184000
163664
No
519
499
533
61045
40083
p
0.290
0.200
0.001
0.443
0.286
doi:10.1371/journal.pone.0113146.t003
haplotype in African Americans was associated with disease
acceleration, in Caucasians and Hispanics it was associated with
disease retardation. Regarding the HHF*2 haplotype, a previous
report found similar results in individuals carrying the allele with
lower CD4 T-cell counts during follow-up [47]. However, these
PLOS ONE | www.plosone.org
results disagree with previous studies that observed a protective
effect against disease progression among subjects carrying the
CCR2-64I allele [33]. HHC/HHF*2 genotype was also associated
with disease retardation among Argentinean children [42]. Even
when no statistically significant association was established, the
7
November 2014 | Volume 9 | Issue 11 | e113146
Host Genetic Factor Influence on HIV Infection
Figure 2. Correlation between baseline HIV viral load and additive genetic score on the study population diagnosed during
primary HIV infection [PHI] (N = 70).
doi:10.1371/journal.pone.0113146.g002
lower CD4 T-cell counts at baseline and during follow-up. These
results agree with a previous study that found a higher frequency
of HLA-A*1101 among subjects with AIDS compared with other
HIV subjects who did not progress [51]. Even when this study
performed high resolution HLA-typing, in contrast to our low
resolution data, it is important to mention that typing studies
reported that most of the typed HLA-A*11 are HLA-A*1101
[41,52].
HLA-B*53 was associated with lower CD4 T-cell counts and
higher HIV VL levels, even when only two subjects carried that
allele. Elevated VL levels among subjects with HLA-B*53 were
previously observed among African seroconverters [53]. Although
only few subjects carried the HLA-B*53, the potential impact of
this allele on disease progression may deserve more investigation.
Another interesting allele is HLA-A*24, associated with lower
CD4 T-cell counts and higher VL levels at baseline and during
follow-up. This allele frequency was also higher (but not
significant) among subjects who presented symptoms during
seroconversion as compared with those without them. Previous
studies also found a deleterious effect of this allele, enhancing HIV
infection [54], showing rapid decline in CD4 T-cells [27] and
favouring disease progression [55]. HLA-B*39 confers a beneficial
effect on disease evolution yielding high CD4 T-cell counts and
low VL levels [16,55]. We also observed a trend in higher
frequency of HLA-B*39 among asymptomatic vs. symptomatic
(10.7% vs. 2.9%) subjects. Controversial results were found in
other alleles. While our study suggests that subjects with HLAB*14 (with significantly lower CD4 T-cell counts at 12 months and
a trend of lower levels of CD4 T-cells at baseline and at 6 months
and higher VL) progressed faster to disease, others found
significant associations between allele and low disease progression
[56] and that the allele had enhanced HIV infection [57].
Previous studies showed that plasma LPS levels among subjects
with acute HIV infection were similar to non-infected subjects
[58]. In fact, our study found similar levels in the PHI group (39.0
pg/ml) and a group of HIV-negative subjects (37.4 pg/ml, data
not shown). However, we found that higher plasma LPS levels are
significantly associated with presence of symptoms during PHI.
CCR5 genotype HHE/HHF*1 was only detected among symptomatic subjects in more than 10% of the group. CCL3L1 copy
number distribution in PHI population was similar to that
observed in the European population [22] with a median of two
copies. Even when no significant differences were observed,
asymptomatic individuals had a higher copy number, maybe
suggesting that CCL3L1 would have an impact since the HIV
infection onset.
Identifying HLA alleles associations with HIV disease progression is complex due to the extreme variability of the loci. In fact,
this study identifies 17, 27 and 14 HLA-A, B and C alleles,
respectively. Coincident with previous reports, including our blood
donors group, the alleles most frequently reported here were HLAA*02 and HLA-*24, HLA-B*35 and HLA-B*44, and HLA-C*07,
HLA-C*04 and HLA-C*03 [41]. Even when it was proposed that
heterozygosis on HLA confers advantages on disease progression
revealing a greater variety of the immune response [18,48–49], no
significant differences in disease progression were detected
between heterozygotes and homozygotes at any individual HLA
locus or homozygosis at one, two, or all three class I loci.
Several HLA alleles identified in our study were associated with
disease progression. Our results adds more evidence to the
protective effect of HLA-B*57 allele on disease progression [23],
with significantly lower VL at baseline and also lower, but not
significant, VL at 6 months. Moreover, the allele was only found
among those who did not progress. Even when HLA-B*57 was
previously associated with the absence of symptoms during
seroconversion, our study failed to confirm these findings [50].
Regarding HLA-B*27, reported as a protective allele [50], we did
not observe this trend or evidence, likely due to the low frequency
found (1.5% among HIV positive and 2.0% among blood donors).
Another HLA allele, several times associated with disease
progression is HLA-B*35 [18,23]. However, our study did not
find any statistical association or trend even when the frequency of
the allele was around 15% in the overall group.
HLA-A*11 was associated with disease progression during the
first year and with higher VL at baseline. We also found a trend in
the presence of the allele and higher HIV VL at 6 months and
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8
November 2014 | Volume 9 | Issue 11 | e113146
Host Genetic Factor Influence on HIV Infection
Table S1 Sequences of primers used for HLA class I
characterization.
(DOC)
These results suggest higher immune activation in symptomatic
subjects since the establishment of infection.
An important limitation of the current research was the low
frequency of asymptomatic subjects included due to the difficulty
in identifying them during the seroconversion period. The lack of
progression data in a group of patients also influenced the
possibility of finding significant associations. It is also important to
note the difficulty in finding associations when genetic variants are
in low frequency. Given these limitations, a score was constructed
in order to combine some of the most important human genetic
factors previously associated with HIV/AIDS and to look for
associations with presence of symptoms, disease progression and
other progression markers like HIV viral load and CD4 T-cell
count. Results reveal a higher score in asymptomatic and those
who did not progress, revealing the presence of more protective
genetic factors in these groups. Even more, when data were
analysed considering both variables (symptoms and progression) a
higher score was observed for those who did not present symptoms
during PHI and did not progress at one year. As described by
other authors, the genetic score was a useful tool to evaluate the
additive influence of human genetic factors with high variability on
small groups [37].
Table S2 Frequency of CCR5 haplotypes of the study
population diagnosed during primary HIV infection
[PHI] (N = 70).
(DOC)
Table S3 Frequency of CCR5 human genotypes among
the study population diagnosed during primary HIV
infection [PHI] (N = 70).
(DOC)
Table S4 Frequency of HLA class I alleles among the
study population diagnosed during primary HIV infection [PHI].
(DOC)
Table S5 Frequency of HLA class I alleles homozygosis
among the study population diagnosed during primary
HIV infection [PHI].
(DOC)
Acknowledgments
Conclusions
We thank all the physicians of the ‘‘Grupo Argentino de Seroconversión’’
Study Group: Lorena Abusamra, Marcela Acosta, Carolina Acuipil,
Viviana Alonso, Liliana Amante, Graciela Ben, M. Belén Bouzas, Ariel
Braverman, Mercedes Cabrini, Pedro Cahn, Osvaldo Cando, Cecilia
Cánepa, Daniel Cangelosi, Juan Castelli, Mariana Ceriotto, Carina Cesar,
Marı́a Collins, Fabio Crudo, Darı́o Dilernia, Andrea Duarte, Gustavo
Echenique, Marı́a I. Figueroa, Valeria Fink, Claudia Galloso, Palmira
Garda, Manuel Gómez Carrillo, Ana Gun, Alejandro Krolewiecki, Natalia
Laufer, Marı́a E. Lázaro, Alberto Leoni, Eliana Loiza, Patricia
Maldonado, Horacio Mingrone, Marcela Ortiz, Patricia Patterson, Héctor
Pérez, Norma Porteiro, Daniel Pryluka, Carlos Remondegui, Raúl Román,
Horacio Salomón, M. Eugenia Socı́as, Omar Sued, J. Gonzalo Tomás,
Gabriela Turk, Javier Yave, Carlos Zala, Inés Zapiola. Authors also thank
Sergio Mazzini for assistance during manuscript preparation.
This study reveals that some host genetic variants identified
previously as disease-modificating factors influence disease progression from the very beginning of the HIV infection. However,
here we also described some associations for the first time.
Variability of host genetic factors as well as their association with
HIV infection and/or disease progression relies strongly on the
ethnic population background. Therefore, the population ethnicities are growing it is becoming increasingly difficult to extrapolate
results from one study to other populations. In this context, it is
important to highlight the need to perform studies at a in this
setting not only these genetic differences in the population but also
the environmental variance and the circulating virus.
Author Contributions
Supporting Information
Conceived and designed the experiments: RSC AM HS MAP. Performed
the experiments: RSC DD YG GT AR. Analyzed the data: MAP RSC.
Contributed to the writing of the manuscript: MAP AM RSC. Participants’
recruitment: NL MES MIF OS PC.
Figure S1 PCR Cycle conditions for HLA class I
characterization.
(DOC)
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