Effect of antiviral treatment and host susceptibility on positive selection in hepatitis C virus (HCV)

Available online at www.sciencedirect.com

Virus Research 131 (2008) 224–232

Effect of antiviral treatment and host susceptibility on positive selection in hepatitis C virus (HCV) Nuria Jim´enez-Hern´andez a,b , Vicente Sentandreu a , Jos´e A. Castro c , Manuela Torres-Puente a , Alma Bracho a,b , Inmaculada Garc´ıa-Robles a , Enrique Ortega d , Juan del Olmo e , Fernando Carnicer f , Fernando Gonz´alez-Candelas a,b , Andr´es Moya a,b,∗ a

Instituto Cavanilles de Biodiversidad y Biolog´ıa Evolutiva, Universitat de Val`encia, Spain b CIBER de Epidemiolog´ıa y Salud P´ ublica (CIBERESP), Spain c Departamento de Biologia, Universidad de las Islas Baleares, Spain d Unidad Enfermedades Infecciosas, Hospital General de Val` encia, Spain e Servicio de Hepatolog´ıa, Hospital Cl´ınico, Universidad de Val` encia, Spain f Unidad de Hepatolog´ıa, Hospital General de Alicante, Spain

Received 7 May 2007; received in revised form 21 September 2007; accepted 22 September 2007 Available online 5 November 2007

Abstract We have conducted a large sequence study of the E1–E2 and NS5A regions of the HCV, subtypes 1a and b, both in patients previously treated with interferon, and untreated patients, who later responded, or not, to a combination therapy based on interferon plus ribavirin. We have examined the role played by the number of positively selected sites on disease progression and its relationship with several variables such as patients’ age, sex and their risk of acquiring the disease. We have detected three groups of patients that respond or not to combination therapy: responders of intermediate age, older non-responders and young non-responders, they possess an increasing average number of positively selected sites in the E1–E2 region, respectively. We conclude that the host’s genetic factors play an important role in whether the disease is contained or becomes chronic. © 2007 Elsevier B.V. All rights reserved. Keywords: Positive selection; HCV; E1–E2 region; NS5A region; Interferon treatment; Response to combination therapy based on interferon plus ribavirin; Host genetic factors

1. Introduction Hepatitis C virus (HCV) affects around 200 million people around the world. It has been grouped into six phylogenetically related genotypes and different subtypes (Simmonds, 2001). HCV is a single stranded RNA virus of about 10 kb, with positive polarity and with an open reading frame that is proteolitically processed, giving rise to four structural and six non-structural proteins. HCV disease diagnosis is not always easy because patients can remain asymptomatic for years after infection. Disease treatment with interferon and ribavirin (IFN + RIB) gives

∗ Corresponding author at: Instituto Cavanilles de Biodiversidad y Biolog´ıa Evolutiva, Universidad de Valencia, Apartado Postal 22085, 46071 Valencia, Spain. Tel.: +34 96 354 3480; fax: +34 96 354 3670. E-mail address: [email protected] (A. Moya).

0168-1702/$ – see front matter © 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.virusres.2007.09.012

good results in about 40% of patients (Zein and Zein, 2002; Zeuzem et al., 2000). HCV gives rise to persistent infection in 60% of patients; however, little is known about the factors responsible for the high viral persistence, nor regarding the unequal clinic progression observed. Two HCV genomic regions seem to play a key role in viral persistence and disease progression: the hypervariable region 1, HVR1 (Kato et al., 1994; Farci et al., 1996; Shimizu et al., 1994; Weiner et al., 1991; Zibert et al., 1997), and the interferon sensitivity determining region, ISDR (Enomoto et al., 1995, 1996; Kurosaki et al., 1997; Saiz et al., 1998). The HVR1 region might be one of the antigenic determinants against which host-neutralizing antibodies are directed. This fact could be responsible, in part, for generating the huge genetic variability that allows the virus to evade the immune response, thus driving the host towards chronic infection (Curran et al., 2002; Farci, 2001; Farci et al., 2000). On the other hand, ISDR, located

Table 1 Main features of the samples of subtypes 1a and b used in this study Host

Subtype 1b Patient

Subtype 1a

# Clones E1–E2

# Clones NS5A

Age

Sex

Risk practice

Rx

IFN + RIB

Patient

# Clones E1–E2

# Clones NS5A

Age

Sex

Risk practice

Rx

IFN + RIB

A03 A06 A14 A16 A25 A32 A35

100 100 100 100 101 100 110

38 96 58 52 70 75 27

? ? 35 ? 21 ? ?

F F F ? F M ?

? ? Unk ? ? ? ?

NT NT NT NT NT NT ?

NR ? NR ? R R ?

A05 A09 A20 A26 A27 A34

100 100 112 100 100 100

25 32 67 62 73 29

25 35 21 28 27 ?

M M M F M ?

IDU Unk IDU IDU Unk ?

NT NT NT NT NT ?

NR NR NR NR NR ?

H2

C03 C04 C05 C08 C09 C10 C12 C13 C15 C16 C19 C23 C25 C27 C32

100 100 100 100 111 100 100 100 102 101 100 100 100 104 100

86 92 75 77 57 63 92 69 80 74 73 80 37 80 48

28 34 51 65 38 31 46 58 45 51 51 37 57 42 58

M M M M M M F F M M M F M M F

IDU Unk Unk Unk Donor Unk Unk Transf Unk IDU IDU ? Transf ? ?

T NT NT NT T T T NT NT T NT NT T T T

R R NR NR R NR R R NR R R R R NR NR

C01 C02 C06 C07 C11 C14 C17 C18 C20 C21 C22 C24 C28 C31 C33 C38

100 102 100 101 110 101 106 100 101 100 100 100 100 100 100 100

65 96 76 63 92 29 25 78 91 80 44 50 49 73 74 90

35 36 34 41 28 26 57 44 37 33 40 43 32 42 23 33

M M M M M M F F M F M M F M M F

Donor IDU Unk IDU IDU Outbreak Outbreak Unk Unk IDU IDU Unk IDU Unk Unk Outbreak

T T NT T NT NT NT NT T T T T T T T NT

R R R R R R R R NR R NR NR R R R R

H3

G02 G05 G06 G07 G09 G16 G17 G26

100 100 100 100 100 103 101 100

65 62 61 48 58 57 68 84

53 50 27 60 43 40 53 62

F M M M M M F F

Unk Unk Unk Unk Unk Unk Unk Unk

NT NT NT NT NT T NT NT

NR R NR NR NR NR NR NR

G10 G14 G19

100 100 100

28 84 52

? ? 33

M M F

IDU Unk IDU

NT NT NT

R NR NR

3033

2002

2533

1527

Total

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H1

The first column indicates sample source, the second gives the name of the sample, the third and fourth show the number of clones used for each sample and both regions E1–E2 and NS5A, respectively. The fifth, sixth and seventh columns indicate the age, sex and risk practice of each patient, respectively. The eighth column shows if patients were mono-treated or not with interferon before serum samples were collected. The ninth column gives the response to combination therapy IFN-RIB given to all patients. Abbreviations: H1, Hospital General de Alicante; H2, Hospital Cl´ınico de Valencia; H3, Hospital General de Valencia;?, unavailable details; Rx, mono-treatment with interferon; T, treated; NT, non-treated; IFN + RIB, combination therapy; R, responder; NR, non-responder; IDU, intravenous drug user; Transf, transfusion; Unk, unknown; M, male; F, female.

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in the NS5A region, might interact with an interferon-induced intracellular protein kinase (PKR). PKR prevents the synthesis of viral proteins and, consequently, viral replication (Kauffman, 2000; Polyak et al., 2001; Tan and Katze, 2001). Nevertheless, some recent experiments have cast doubt on the existence of this region (Brillet et al., 2007). To understand HCV infection progression, it is important to gain insight into factors associated with immune escape. For instance, as mentioned before, HCV envelope glycoproteins E1 and E2 are exposed to antibody attack before entry into the host cell. Although the viral population within individual patients exhibits considerable diversity in these proteins, this in itself is not indicative of adaptation to the immune system. The absence of well-established in vitro neutralization assays for HCV make it difficult to prove immune escape; however, this could be clarified by identifying selected sites in regions that interact with the host, either through the immune response or via cell surface receptors. The presence of positively selected amino-acid sites indicates mutants have a selective advantage, allowing them to escape from the immune response. In this work, we carried out a systematic analysis of what type of selection forces are at work in the two HCV genome regions where HVR1 and ISDR are located. Several factors were taken into account to gain a better understanding of disease progression by identifying footprints left by selection and/or associated with several other factors. Firstly, we considered patients infected with HCV-1a and b. Secondly, we tested whether there are a priori differences among viral sequences, which can help predict the response or lack of response to antiviral treatment. Finally, we looked for the effects of previous treatment with interferon on those viral regions, as well as certain patient variables to explain the outcome in a later response, or not to IFN + RIBbased treatments. 2. Materials and methods 2.1. Study population Serum samples from 55 patients (30 infected with HCV-1b, and 25 with HCV-1a) were chosen for this study (Table 1). The patients were unrelated and not infected with HIV. Serum samples were obtained before the patients were subjected to a combination therapy with IFN + RIB. Some patients had previously been mono-treated with interferon (see Table 1). Two genomic regions were used in this study. The first, referred to as E1–E2 region measuring 472 bp in length (from nucleotide 1310 to 1781 in the reference HCV genome sequence, accession number D50481), contains a fragment spanning the genes coding for E1 and E2 proteins, and includes the HVR1 (from nucleotide 1478 to 1558), the HVR3 (from nucleotide 1619 to 1726) and HVR2 (from 1748 to 1774). The second one corresponds to a 743 bp fragment of the NS5A (from nucleotide 6742 to 7484) coding gene that includes the ISDR (from 6954 to 7073) and also the V3 variable region (from 7396 to 7466). In the case of the E1–E2 region, one hundred clones were sequenced per patient, and a number varying between 25 and 100 in the case of the NS5A region.

2.2. Viral RNA extraction and amplification Viral RNA was extracted from 140 ␮l of serum using High Pure Viral RNA Kit (Roche). We carried out all reverse transcription with random hexadeoxynucleotides. Reverse transcription was performed on a 20 ␮l volume containing 5 ␮l of eluted RNA, 4 ␮l of 5× RT buffer, 0.5 mM of each deoxynucleotide, 0.5 ␮g of random hexamers, 100 U of MMLV reverse transcriptase (Promega), and 20 U of RNasin Ribonuclease Inhibitor (Promega). The reaction was incubated at 42 ◦ C for 45 min, followed by 3 min at 95 ◦ C. Then, a first round of PCR was carried out in a 100 ␮l volume containing 10 ␮l of the reverse transcription product, 0.2 mM of each dNTP, 400 nM of genomic primer and 400 nM of antigenomic primer and 1.25 units of Pfu DNA polymerase (Promega). The set of primers used are described in (Jim´enez-Hern´andez et al., 2007). PCRs were performed according to the following profile: initial denaturation at 94 ◦ C for 1 min; 5× (94 ◦ C for 30 s, 55 ◦ C 30 s, 72 ◦ C 3 min); then 35× (94 ◦ C 30 s, 52 ◦ C 30 s, 72 ◦ C 3 min) and a final extension for 10 min at 72 ◦ C. A single amplified product was observed after electrophoresis on 1.4% agarose gels stained with ethidium bromide. 2.3. Cloning and sequencing of viral populations DNA products for both regions were purified with a purification kit (Roche) and directly cloned into EcoRV-digested pBluescript II SK(+) phagemid (Stratagene). Plasmid DNA was purified with an isolation kit (Roche). Cloned products were sequenced using vector-based primers KS and SK (Stratagene). Sequencing was carried out using BigDye Terminator v3.0 kit (Applied Biosystems) on an ABI 3700 automated sequencer. Sequences were verified and both strands assembled using the Staden package (Staden et al., 2000). The accession numbers are AM271041–AM275326 and AM279768–AM282548 for regions E1–E2 and NS5A, respectively. 2.4. Sequences analysis and statistics Sequence alignments were obtained using CLUSTALX v1.81 (Thompson et al., 1997). In order to identify the mechanisms underlying the diversification of viral strains within patients, evidence of positive selection was sought using a codon-based approach as implemented in DATAMONKEY (Kosakovsky and Frost, 2005). These offer several advantages over previously described methods, including not needing to assume equal synonymous substitution rates throughout the sequence and allowing the user to choose the most appropriate model for nucleotide substitution from the original data set. We use the GTR model of substitution and a fixed effects likelihood approach (IFEL), where selection is only tested for along internal branches of the phylogeny, using a P value 0.1. We chose this test because it enables us to investigate whether sequences sampled from a population have been subject to selective pressure at the population level.

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3. Results 3.1. Detecting codon sites under positive selection The number of codons detected under positive selection for E1–E2 and NS5A regions are shown in Tables 2 and 3, respectively. Fig. 1(a–d) shows the corresponding location of such sites and the most frequent amino-acid change for each particular site. As one can observe, the majority of codon sites under positive selection are around the middle of the E1–E2 region, where the HVR1 region is located and, to a lower extent, in the second half of the E1–E2 region, preferentially in the HVR3 and HVR2 regions (Fig. 1(a and b)). Fig. 1(c and d) shows the distribution of positively selected codon sites for the NS5A region. One can observe the average number of positively selected sites in this region is lower and more spread out than in the E1–E2 region. Another interesting feature is the different number of patients showing evidence of positive selection for each one of the two regions. The E1–E2 region shows 44 patients out of 55 with one or more positively selected codons (Table 2), whereas in the case of the NS5A only 31 out of 55 patients showed one or

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more positively selected sites (Table 3), which is a statistically significant difference (Chi-square test = 20.69, 1 d.f.; P < 0.05). It seems then than positive selection is more present in E1–E2 than in NS5A region. 3.2. Positive selection and viral subtypes We compared the number of positively selected sites per patient for both E1–E2 and NS5A regions. As shown in Fig. 2(a), subtypes 1a and b did not reveal statistically significant differences for either region, although they clearly did so on comparing E1–E2 (4.12 ± 0.47, see Table 2) versus NS5A (0.98 ± 0.16, see Table 3) (t-test = 10.83, 108 d.f.; P < 0.05). We have also examined the number of positively selected sites throughout the two regions and tested for differences between viral subtypes. In the E1–E2 region we considered the following five sub-regions: (i) the region belonging to the gene coding for E1 protein; (ii) the HVR1 hypervariable region; (iii) the region belonging to the gene coding for E2 protein (excluding the HVR1, HVR3 and HVR2 regions); (iv) the HVR3 region and (v) the HVR2 region. In all five cases there were no statistically

Table 2 Codons under positive selection in the E1–E2 region Patient 1b

Number of positively selected sites

Codons under positive selection

Patient 1a

Number of positively selected sites 0 0 7 12

A03 A06 A14 A16

2 0 7 6

63, 73 3, 57, 68, 69, 70, 76, 78 3, 18, 28, 57, 137, 152

A05 A09 A20 A26

A25 A32 A35

3 8 1

70, 77, 78 38, 67, 68, 70, 81, 118, 134, 148 59

A27 A34 C01

2 8 12

C03 C04 C05 C08

0 0 8 10

C02 C06 C07 C11

1 0 5 3

C09 C10 C12 C13 C15 C16 C19

3 4 3 3 8 4 13

C14 C17 C18 C20 C21 C22 C24

1 5 8 7 6 6 1

C23

0

C28

10

C25 C27 C32 G02 G05 G06 G07 G09 G16 G17 G26

0 5 7 3 4 5 4 6 0 3 0

C31 C33 C38 G10 G14 G19

2 2 1 0 4 4

57, 60, 61, 72, 83, 105, 117, 118 57, 59, 60, 67, 70, 71, 77, 78, 112, 115 57, 59, 81 38, 84, 148, 153 57, 59, 153 59, 109, 151 78, 95, 99, 107, 126, 139, 148, 151 60, 70, 71, 72 18, 59, 61, 69, 74, 77, 81, 83, 117, 118, 119, 139, 144

59, 64, 65, 152, 153 72, 77, 117, 118, 126, 134, 148 28, 72, 78 64, 65, 81, 139 5, 59, 143, 152, 156 59, 111, 118, 151 70, 78, 107, 118, 136, 152 81, 134, 151

The second and third columns give the number and positions of positively selected sites for each patient, respectively.

Codons under positive selection

64, 67, 78, 115, 123, 146, 150 69, 70, 78, 80, 81, 83, 104, 107, 115, 118, 133, 136 78, 116 68, 72, 74, 77, 78, 81, 116, 117 68, 70, 73, 74, 77, 87, 89, 115, 117, 118, 123, 153 144 72, 89, 108, 111, 136 64, 66, 122 57 59, 70, 73, 74, 126 57, 59, 65, 67, 70, 74, 77, 150 13, 57, 64, 71, 73, 77, 107 57, 60, 64, 115, 139, 148 68, 78, 80, 107, 117, 119 74 64, 70, 73, 74, 78, 111, 115, 123, 126, 146 71, 115 74, 106 70 78, 119, 126, 137 18, 70, 139, 148

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Table 3 Codons under positive selection in the NS5A region Patient 1b

Number of positively selected sites

Codons under positive selection

Patient 1a

Number of positively selected sites

A03 A06 A14 A16 A25 A32 A35 C03 C04 C05 C08 C09 C10 C12 C13 C15 C16 C19 C23 C25 C27 C32 G02 G05 G06 G07 G09 G16 G17 G26

1 2 1 0 2 1 1 0 0 1 2 0 1 2 3 0 1 4 1 0 1 0 0 2 5 1 1 0 0 0

142 97, 233 234

A05 A09 A20 A26 A27 A34 C01 C02 C06 C07 C11 C14 C17 C18 C20 C21 C22 C24 C28 C31 C33 C38 G10 G14 G19

0 0 0 3 0 2 1 0 0 4 1 0 0 0 0 1 2 1 3 1 0 0 0 1 1

127, 238 8 160

31 240, 244 145 149, 240 86, 105, 222 213 10, 80, 165, 140 31 17

31, 211 15, 122, 139, 149, 165 167 122

Codons under positive selection

37, 65, 229 90, 239 15

162, 226, 233, 237 114

222 53, 114 127 144, 230, 238 244

114 229

The second and third columns give the number and positions of positively selected sites for each patient, respectively.

significant differences between subtypes 1a and b. Analogously, NS5A was divided into the three following sub-regions: (i) the region belonging to the NS5A coding gene (excluding ISDR and V3 region); (ii) the ISDR region and (iii) the V3 region (Fig. 2(b)). In these three cases there were no statistically significant differences between subtypes 1a and b. Given these results, we combined data regarding viral subtypes. 3.3. Studying association between positive selection and patient variables As in the previous section we have examined whether there was statistical evidence of the differential presence of positive selection in variables like sex, age, mono-treatment, risk and later response to combination therapy. We carried out this task following two different procedures. The first one involved performing statistical tests to check the differences between the average number of positively selected sites for both regions (Tables 2 and 3) according to the different states of the variables mentioned (i.e., regarding sex, male or female; in mono-treatment if the patient was treated or untreated, etc.). The second one involved performing contingency tables for the same state variables by simply counting either the number of patients with zero sites versus those with at least one positively selected site. In both approaches and for the two regions no evi-

dence of differential positive selection was obtained (results not shown). 3.4. Analysis of the response to combination therapy Based on the previous results it is not difficult to see that the response to combination therapy (i.e., IFN + RIB, see Table 1) or the lack of it is a complex issue involving factors like patient susceptibility to the disease, viral variability, previous antiviral treatments, etc. By mean of contingency tables we have tested whether there is any particular association between the response to combination therapy and any of the variables chosen (age, sex, viral subtype, mono-treatment and risk practice; see Table 1). It should be mentioned, again, that serum samples were obtained before treatment with combination therapy. The results are shown in Table 4. Four of the variables, age, sex, viral subtype and mono-treatment did not show any significant association with response to IFN + RIB. The opposite was observed, however, when considering risk practice, which deserves our attention. The tendency shown by patients who acquired HCV of unknown origin, probably many years ago (29.2% responders, 7 out of 24), was opposite to that for the other types of risk (76.2% responders, 16 out of 21; see Table 4). We have further explored the different outcomes for both types of patients by considering the average age of the groups

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Fig. 1. Codon sites under positive selection (black square around the amino acid), in the region E1–E2 for patients of subtypes 1b (a) and 1a (b) and in the NS5A region for subtypes 1a (c) and 1b (d). The first row indicates the locations of HVR1 (within amino acids 384–410), HVR3 (within amino acids 431–449), HVR2 (within amino acids 474–482), ISDR (within amino acids 2209–2248) and V3 (within amino acids 2356–2379) regions.

formed by patients that acquired HCV from a known source (grouped together and labeled ‘rest’ in Table 5) and patients that acquired it from an unknown source, probably many years ago. As one can observe, both groups of non-responders are formed by older and younger patients, with statistical dif-

ferences (t-test = 3.70, 19 d.f.; P < 0.05). On the other hand, the average age of both groups of responders is intermediate, falling between the average ages of the non-responders; furthermore, there are no statistical differences between these two groups.

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Fig. 2. Average number (±standard error) of positively selected sites for subtypes 1a and b. (a) In the case of the entire E1–E2 and NS5A regions. (b) Sub-regions E1 coding gene (E1), HVR1, E2 coding gene except HVR1, HVR3 and HVR2 (E2), HVR3 and HVR2 from E1–E2 region, and NS5A coding gene excluding ISDR (NS), ISDR and V3 regions from NS5A region. Table 4 Contingency tables of the different variables with respect to combination therapy (responders versus non-responders) Variable

States

Responders

Nonresponders

d.f.

Chi-square test

Age

<35 35–44 45–65

10 7 7

7 8 8

2

0.75ns

Sex

M F

17 9

7 8

1

0.03ns

Mono-treatment

T NT

12 14

7 18

1

1.78ns

Risk practice

IDU Donor Transf Outbreak Unk

9 2 2 3 7

5 0 0 0 17

4

15.21*

Viral subtype

1a 1b

14 12

10 15

1

1.02ns

Abbreviations used are shown in Table 1. Age has been grouped in three intervals; ns: not significant. * P < 0.05.

Therefore, it seems that there are three different groups formed by non-responders of older and younger ages as well as responders of intermediate age. One final result that reinforces the likelihood of these groupings has been obtained when averaging those patients with a number of positively selected sites in E1–E2 region equal to or higher than one (Table 2). The results Table 5 Average age (±standard error) of responders and non-responders to combination therapy when the risk practice has been grouped into patients infected with HCV from unknown origin and remaining risk practices Group

n

Non-responders

Unknown, all Unknown, positively selected Rest Rest, positively selected

16 13 5 4

44.2 43.8 29.4 30.5

± ± ± ±

2.4 3.4 3.3 4.0

n

Responders

7 5 15 13

39.0 41.0 38.6 39.9

± ± ± ±

3.5 4.7 2.7 3.0

Similarly, the same two categories are shown but only for patients showing at least one positively selected site. See Section 3 for more details; n is the sample size for each group.

Table 6 Average number (±standard error) of positively selected sites and statistical testing for differences among older non-responders (ONR), younger non-responders (YNR) and responders (R) to combination therapy IFN + RIB Grouping

Selected sites

n

Comparison

d.f.

t-Test

Responders Old non-responders Young non-responders

4.78 ± 0.87 5.23 ± 0.74 7.25 ± 1.70

18 13 4

R vs. ONR R vs. YNR ONR vs. YNR

29 20 15

0.69ns 2.34* 2.10*

ns: Not significant. * P < 0.05.

of testing for differences in such a number are given in Table 6. As it can be observed, young non-responders show a higher and statistically significant number of positively selected sites than older non-responders and responders. Although responders display fewer positively selected sites than older non-responders, the difference is not statistically significant. It should be mentioned (see Table 5) that the average age of the three groups (only considering those individuals with positive selection in the E1–E2 region) maintained the same pattern when the groups were established without taking into account whether patients displayed positively selected sites or not. 4. Discussion Three main conclusions can be drawn from this study. Firstly, although the two HCV regions studied are subjected to strong purifying selection, a purely neutral model does not provide an adequate model of the selection forces acting on these viral genome regions in most of the patients studied. On the contrary, most viral populations, regardless of the genome region analyzed or the viral subtype, show the presence of positive selection acting on a number of sites. Secondly, we have found no statistical differences between viral subtypes 1a and b. Specific analyses of the different outcomes observed for viral subtypes 1a and b have been reported elsewhere (Jim´enez-Hern´andez et al., 2007), indicating that results for risk practice suggest the transmission route may be the most important factor influencing the observed difference. Thirdly, there are adaptive responses of HCV viral populations against human selective forces, such as immune system and genetic susceptibility, a response apparently involving

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more E1–E2 than NS5A regions, and sites preferentially located on hypervariable regions. Several molecular features are indicative of the relevance of the E1–E2 region in relation to responses against antiviral treatments and the immune system. This region is known to contain epitopes against B cells (Bartosch et al., 2003; Zibert et al., 1999); consequently, the presence of sites under positive selection suggests that this region is under high immune pressure, and that the eventual fixation of positively selected sites may be a way to escape from it. Otherwise, E2 binding sites for specific virus-cell receptors may, therefore, be under selection pressure (Sheridan et al., 2004) to optimize binding affinity and so facilitate immunomodulation and cell entry (Crotta et al., 2002; Flint and McKeating, 1999; Pileri et al., 1998; Tseng and Klimpel, 2002; Wack et al., 2001; Yagnik et al., 2000). On the other hand, a correlation between the number of mutations in the HVR2 region and response to treatment has been reported (Hofmann et al., 2003), i.e., patients responding to treatment had a higher number of mutations (not necessarily a high number of positively selected sites). With respect to the NS5A region, this region presents fewer positively selected sites than the E1–E2 region. In particular, ISDR does not concentrate the highest number of positively selective sites, but they are rather uniformly distributed along the full region. It has been postulated that the binding of ISDR to the PKR host protein inhibits the antiviral host response. The presence of mutations in the ISDR region is also reported to be associated with lack of response to treatment (Enomoto et al., 1995, 1996; Kurosaki et al., 1997; Saiz et al., 1998); however, these reports are contradicted by others where no such correlation was found (Chung et al., 1999; Durvelie et al., 1998; Gerotto et al., 1999; Polyak et al., 1998). Furthermore, in some cases, this region was reported not to exist, as indicated by Brillet et al. (2007). We recall that samples were taken before patients were treated with the combination therapy, and that the variable response must be interpreted as the capacity to respond to disease. In general, non-responders accumulate a higher number of positively selected sites (Table 6), and this can be interpreted as a reduced capacity of the human host against the virus when compared with responders. HCV isolated from nonresponders is able to overcome the immune system more easily. Although not primarily studied, we do believe that the typical outcome for non-responders indicates that their disposition to disease differs from that of responders. The relative high proportion of positively selected sites in non-responders probably reflects indirect evidence that there are additional host factors, which can be generically described as genetic susceptibility to disease that could account for disease progression in those patients. There are well-documented cases, however, of successful immune response against HCV at the beginning of infection (Lechner et al., 2000; Thimme et al., 2001), and the importance of the vigor and quality of the antiviral immune response in determining the outcome of HCV infection (Aberle et al., 2006). Meanwhile, the disease progresses unchecked in other cases. We sustain the hypothesis that genetic susceptibility of the host differs in responders and non-responders to antiviral treat-

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