Secondary Logo

Journal Logo

Basic and Translational Science

Polymorphic Mutations Associated With the Emergence of the Multinucleoside/Tide Resistance Mutations 69 Insertion and Q151M

Scherrer, Alexandra U. PhD*; von Wyl, Viktor PhD; Götte, Matthias PhD; Klimkait, Thomas PhD§; Cellerai, Cristina MD; Yerly, Sabine MSc; Böni, Jürg DVM#; Held, Leonhard PhD**; Ledergerber, Bruno PhD*; Günthard, Huldrych F. MD*The Swiss HIV Cohort Study

Author Information
JAIDS Journal of Acquired Immune Deficiency Syndromes: February 1st, 2012 - Volume 59 - Issue 2 - p 105-112
doi: 10.1097/QAI.0b013e31823c8b69


The emergence of resistance mutations during antiretroviral therapy (ART) of HIV-1 infections is an important cause for treatment failure. The 69 insertion and the Q151M mutation are 2 rare drug-associated genotypic modifications causing multinucleoside/tide resistance (MNR).1–5 The prevalence among several European studies was <3.5%, but recent studies from resource-limited countries reported a higher prevalence.6–9 Among others, Marcelin et al, Cases-Gonzalez et al, and Masquelier et al10–12 showed that the 69 insertion often co-occurred with mutations from the thymidine analogue mutation (TAM) 1 pathway (M41L, L210W, and T215Y). Q151M has a completely different resistance pattern and is usually accompanied by 2 or more accessory mutations (A62V, V75I, F77L, and F116Y) that compensate the negative impact of Q151M on viral replication.1,13 There is no clear association described between Q151M and TAM pathways.10,14,15 In developed countries, MNR mutations mostly have occurred during outdated single-class nucleoside reverse transcriptase inhibitor therapy. In addition, the 69 insertion has been associated with didanosine exposure.5,16,17 Otherwise, very little is known about risk factors for the emergence of MNR, mostly due to the rare occurrence of MNR mutations and hence the limited sample size for analysis.15,16

Previous studies have already demonstrated the existence of polymorphic mutations that are strongly associated with the emergence of TAM 1 as opposed to TAM 2 (eg, F214L).18–20 Therefore, we hypothesized that, besides exposure to specific drugs, the emergence of the different MNR profiles, 69 insertion and Q151M, may also depend on particular genomic signatures of the virus in the polymerase region. We aimed to identify such mutations using data from the Swiss HIV Cohort study (SHCS) and the SHCS drug resistance database.


General Procedure

To identify mutations associated with the emergence of MNR, we proceeded as follows: first, we determined whether the emergence of the 2 MNR profiles, 69 insertion and Q151M, are linked to specific TAM patterns. In particular, we were interested in finding out whether the MNR mutations could occur independently from TAMs or whether they mark an endpoint of a specific TAM pathway (analysis step 1). The result from this analysis then allowed us to form appropriate groupings for MNR/TAM pathways to be used in subsequent analyses (henceforth named MNR/TAM groups). Next, we identified polymorphic mutations, which were not significantly more prevalent in patients with treatment exposure compared with individuals without treatment exposure. This initial set of polymorphic mutations was further restricted to mutations, which were present at significantly different proportions across the MNR/TAM groups defined in the first analysis, thus suggesting an accumulation of polymorphic mutations in certain MNR/TAM groups (analysis step 2). In a final analysis, the predictive values of the found polymorphic mutations were studied (analysis step 3).

Statistical analyses were performed with Stata 11 SE (StataCorp, College Station, TX). All confidence intervals (CIs) are 95% CI, and the level of significance was set at 0.05 unless indicated otherwise.

Data and Study Population

Data from the SHCS resistance database were analyzed, which contains all genotypic HIV resistance tests performed by the 4 authorized laboratories in Switzerland, stored in SmartGene's (Zug, Switzerland) Integrated Database Network System (version 3.5.7).21 Additionally, clinical data came from the SHCS, which is a nationwide, clinic-based cohort study with continuous enrollment and semiannual study visits.22,23 The SHCS has been approved by ethical committees of all participating institutions, and written informed consent has been obtained from participants. To avoid a potential bias caused by non–B subtypes, only sequences from therapy-exposed individuals infected with subtype B viruses were considered for analysis. The numbers of 69 insertion (n = 1) and Q151M (n = 5) among non–B strains were too low to perform a separate analysis.

Association of the 69 Insertion and Q151M With TAMs (Analysis Step 1)

To start with, we built 4 groups representing the particular resistance pathways: (1) patients with the 69 insertion detected, (2) patients with the Q151M detected, (3) patients with ≥2 TAM 1 (M41L, L210W, T215Y), and (4) patients with ≥2 TAM 2 (D67N, K70R, T215F, K219K/E) detected. Sequences with both, TAM 1 and TAM 2, were excluded (n = 495). Sequences with 69 insertion and TAMs were allocated to the 69 insertion group and sequences with Q151M and TAMs to the Q151M group.

To assess whether MNR mutations can emerge independently of TAMs, the percentage of co-occurrence of the 69 insertion or Q151M with TAMs of group 1 or 2 was compared. In addition, we investigated the possible chronological order of the TAM and MNR mutations. For this purpose, the time from therapy initiation until detection of either TAMs or MNR mutations was compared between the different MNR profiles and the 2 TAM pathways. In particular, we aimed to study whether MNR mutations tended to follow TAMs, which would support the hypothesis that the MNR mutations emerge as the end point of the respective TAM pathway. The time until mutation detection (described by median and interquartile ranges) were compared by use of the Wilcoxon rank sum test. Based on these analyses, we regrouped the 4 initial MNR or TAM groups to represent possible pathways.

Identification of Polymorphic Mutations Associated With Different MNR/TAM Groups (Analysis Step 2)

To identify polymorphic mutations, we compared the frequency of all reverse transcriptase mutations between treatment-exposed patients (detected with 69 insertion, Q151M, ≥2 TAM 1 or ≥2 TAM 2) and an equal number of randomly selected sequences from treatment-naive patients. For the definition of a polymorphism, only amino acid changes with a prevalence of at least 3% among treatment-naive patients were considered. In addition, the prevalence of the respective mutation among treatment-experienced patients was not allowed to be significantly higher compared with the frequency among treatment-naive patients. Analogous to algorithms used in analyses of noninferiority clinical trials,24 an upper limit for an allowed difference in prevalence of specific mutations between treatment-naive and treatment-exposed individuals was determined to still be considered equivalent (or nonsuperior), which was set at 5% in this study. If the 95% CI of the difference in prevalence did not include this margin (ie, was superior), then this mutation was discarded from the list of potential polymorphisms, otherwise the mutation was included. To verify that the identification of polymorphisms were not influenced unduly by our dataset, we applied the same selection criteria (ie, >3% frequency among treatment naive and <5% difference) to genotypic data from the Stanford database by querying the Genotype-Treatment Correlations tool (

Of this initial set of polymorphic mutations, those were selected varied significantly across the MNR/TAM groups defined in step 1. Significance was assessed by use of Fisher exact tests and Benjamini-Hochberg correction with a false-discovery rate of 5% to adjust for multiple testing.

The associations of polymorphic mutations with specific MNR/TAM groups were checked further by use of multivariable logistic regression models adjusted for the exposure to specific nucleoside reverse transcriptase inhibitors (ever exposed). Variables (polymorphic mutations and treatment exposure) were included in the multivariable model if the P value in the univariable model was <0.1.

Predictive Values of Polymorphic Mutations (Analysis Step 3)

The predictive values of the identified polymorphic mutations were assessed by performing nonparametric receiver operating characteristic (ROC) analyses defining the sensitivity, specificity, number of correctly classified, and the area under ROC curve.

To further validate the predictive value of polymorphisms identified in analysis step 2, we queried the Stanford database Genotype-Treatment Correlations tool for sequence pairs consisting of 1 genotype performed before treatment exposure and 1 obtained after any exposure to zidovudine and/or stavudine (Results). Sequence pairs were included in the analysis if the sequence taken after treatment exposure either carried the 69 insertion, ≥2 TAM 1, ≥2 TAM 2, or Q151M, analogous to our initial selection criteria for sequences from the SHCS drug resistance database. The same analytic methods for prediction performance assessment were used as for the SHCS dataset.


Association of TAM 1, TAM 2, 69 Insertion, and Q151M (Analysis Step 1)

The SHCS was screened for genotypic resistance tests from treatment-experienced patients. A total of 3335 subtype B sequences were selected. The 69 insertion and the Q151M mutation occurred very rarely, the prevalence was 0.5% (n = 17/3335) and 0.9% (n = 29/3335), respectively (Genbank accession no. JN991203-JN991248) (see Table, Supplemental Digital Content 1,

Previous studies suggested an association of the 69 insertion with the TAM 1 pathway. This finding was confirmed in our study. As shown in (Table 1), the 69 insertion co-occurred in 16 of 17 cases (94.1%) with ≥1 TAM 1 and rarely with ≥1 TAM 2 (2 of 17, 11.8%). In contrast to the 69 insertion, the Q151M mutation co-occurred very rarely with ≥1 TAM 1 (5 of 29, 17.2%), whereas TAM 2 were found frequently (16 of 29, 55.2%). These impressions were reinforced when checking the actual nucleotide sequences for ambiguous base calls at positions associated with TAM, 69 insertion, and Q151M.25 The presence of both wild-type and mutant virus is suggestive for the presence of separate viral strains, which has been described previously for incompatible mutations such as TAM 1 and K65R.26 Indeed, 2 of 5 patients with Q151M and TAM 1 also harbored virus with wild type at these amino acid positions. The infrequent co-occurrence of Q151M and TAM 1 on the same strain (3 of 29, 10%) may indicate fitness interactions between these mutations. For the sequences containing the 69 insertion, no ambiguous base calls were detected at relevant positions. Of further note, although the 69 insertion only once occurred in the absence of TAM 1, there were 12 (41%) cases of Q151M without the presence of any TAMs (and TAM 2 in particular). This finding indicates that Q151M emergence may be independent of the TAM 2 pathway.

Co-occurrence and Association of the 69 Insertion, Q151M, and TAM 1 and TAM 2

Next, to better understand the chronological order of the emergence of resistance mutations, the time until detection of MNR and ≥2 TAMs was analyzed. Given the results from above, we hypothesized that the 69 insertions may result from the TAM 1 pathway after prolonged exposure to ART. As shown in (Figure 1A), the overall time on ART until detection of 69 insertion {median [interquartile range (IQR)]: 6.8 years (4.7–9.4)} was longer compared with ≥2 TAM 1 [median (IQR): 4.4 years (2.3–6.9), P Wilcoxon = 0.009]. These findings support the notion that the 69 insertion results out of the TAM 1 pathway. The same type of analysis however showed no time-dependent difference between the occurrence of Q151M and TAM 2 mutations: 5.5 years (IQR: 3.9–6.4) and 5.1 years (IQR: 2.9–7.0, P = 0.566), respectively (Fig. 1B). Additionally, no difference was found between patients detected exclusively with mutations from the Q151M pattern [median years (IQR): 5.0 (1.9–6.1)] and patients detected with a combination of the Q151M and TAM 2 mutations [median years (IQR): 5.9 (4.5–8.8, P Wilcoxon = 0.136].

Time on antiretroviral treatment until the detection of 69 insertion (n = 17) and ≥2 TAM 1 (n = 400) (A) or Q151M (n = 29) and ≥2 TAMs 2 (n = 249) (B).

On the basis of these results, we established the following hypotheses for the dependencies between TAM and MNR. The 69 insertion emerges out of the TAM 1 pathway and is strongly discriminated against by TAM 2 mutations. In contrast, Q151M is selected against by TAM 1 mutations, but there is no strict association with TAM 2 mutations. Thus, in the following analyses, we considered TAM 2 and Q151M as separate MNR/TAM categories and a third group consisting of TAM 1 and 69 insertion.

Polymorphic Mutations Associated With the Emergence of MNR Mutations (Analysis Step 2)

To identify polymorphic mutations associated with the emergence of MNR mutations, we screened all reverse transcriptase mutations and compared their frequencies between treatment-naive individuals and all treatment-experienced individuals from the 3 MNR/TAM groups combined.

We identified 95 mutations which fulfilled the criteria for a polymorphic mutation, meaning that the frequency among treatment-naive patients was >3% and the 95% CI of the difference between treatment-exposed and treatment-naive patients did not contain the 5% margin. Of these 95 mutations, 8 (8.4%) showed statistically significant differences in proportions across the 3 MNR/TAM groups after adjustment for multiple testing as follows: K43E, V60I, S68G, S162C, T165I, I202V, R211K, and F214L (Table 2). We checked these findings with data from the Stanford database, which included 12,172 sequences from treatment-naive and 9101 sequences from treatment-experienced patients. With the exception of K43E, all mutations classified as polymorphisms by our algorithm were confirmed, meaning that they showed a prevalence of >3% among treatment-naive patients, and the differences in prevalence relative to treatment-exposed sequences was <5%.

Polymorphic Mutations Associated With the 69 Insertion/TAM 1, Q151M, or TAM 2

The polymorphism F214L showed the most pronounced difference between the MNR/TAM groups. It occurred very rarely (2.2%) in the 69 insertion/TAM 1 group, but frequently in the Q151M (27.6%) or TAM 2 group (30.9%), which provides evidence that F214L might direct viral evolution toward the Q151M and TAM 2 pathways as opposed to the TAM 1 pathway. Compared with the 69 insertion/TAM 1 and the TAM 2 groups, S68G and I202V co-occurred frequently with Q151M in 27.6% and 41.4% of cases, but only at 6.7% and 7.2% in the 69 insertion/TAM 1 group and at 1.6% and 14.5% in the TAM 2 group, respectively. From these comparisons and the results shown in Table 1, we inferred that there may exist a similarity between the Q151M and the TAM 2 group, but a pronounced dissimilarity between these 2 groups with the 69 insertion/TAM 1 group in terms of polymorphism profiles. We hypothesized that there may exist an early split in pathways between TAM 1 and the other 2 MNR/TAM groups, and a later split between TAM 2 and Q151M, as outlined graphically in (Figure 2). Accordingly, modelling was performed in 2 sequential steps. The first step consisted of a multivariable comparison of the 69 insertion group with a pooled group of TAM 2 and Q151M with respect to polymorphisms and therapy exposures. Subsequently, factors separating the TAM 2 and Q151M groups were identified by repeating the multivariable modelling analysis on these 2 groups only.

Polymorphic mutations associated with different resistance pathways.

The first logistic regression comparing the pooled 69 insertion/TAM 1 groups with the pooled Q151M/TAM 2 groups (Table 3, first logistic regression) confirmed the strong association of the polymorphic mutation F214L with the emergence of Q151M and or ≥2 TAM 2 [univariable odds ratio (OR): 20.0, 95% CI: 9.8 to 40.5, P < 0.001; multivariable OR: 19.0, 95% CI: 9.0 to 40.1, P < 0.001]. Moreover, V60I and I202V were also associated with the emergence of Q151M/ ≥2 TAM 2, whereas K43E and R211K were negatively associated. In the second step aiming at finding polymorphisms, which may influence the emergence of Q151M as opposed to TAM 2 mutations, S68G was strongly associated with the occurrence of Q151M (univariable OR: 23.2, 95% CI: 6.5 to 83.9, P < 0.001; multivariable OR: 18.1, 95% CI: 4.0 to 81.3, P < 0.001). Additionally, T165I and I202V were positively associated with the occurrence of Q151M. Of note, this analysis also suggests a role of stavudine use and possibly also zalcitabine in the emergence of the MNR mutation Q151M (Table 3, second logistic regression).

Univariable and Multivariable Logistic Regressions Comparing Patients Detected With 69 Insertion/≥2 TAM 1 (Reference) and Q151M/ ≥2 TAM 2 (First Logistic Regression) and Patients Detected With ≥2 TAM 2 (Reference) and Q151M (Second Logistic Regression)

Predictive Values of Polymorphic Mutations (Analysis Step 3)

The polymorphism with the highest sensitivity (30.6%) and specificity (97.8%) to predict Q151M/TAM 2 as opposed to 69 insertion/TAM 1 was F214L, with an area under the curve of 0.64. Having this mutation predicted the correct pathway (ie, Q151M/TAM 2) in 71.0% of cases. The sensitivity, specificity, and the percentage of correctly classified V60I and I202V were 17.3% and 25.2%; 92.8% and 85.4%; and 62.6% and 61.3%, respectively.

In the second analysis comparing only the TAM 2 and Q151M groups, the sensitivity and specificity of S68G to predict the TAM 2 pathway was 27.6% and 98.4%, respectively. The percentage of correctly classified was 91.0% and the area under ROC curve 0.74. For T165I and I202V were sensitivity: 17.2% and 41.4%, specificity: 98.0% and 85.5%, and percentage of correctly classified: 89.6% and 80.9%, respectively.

For the external validation, 36 sequence pairs from the Stanford database could be included, of which 8 had the Q151M mutation, 21 had ≥2 TAM 1, 22 ≥2 TAM 2. The 69 insertion was not observed. Interestingly, the polymorphisms F214L and V60I also showed the best prediction performance in this new sample for Q151M/TAM 2 (see Table, Supplemental Digital Content 2,, with 64% and 67% of samples correctly classified, respectively. Due to the very small numbers of S68G (n = 1), T165I (n = 1), and I202V (n = 0) mutations in treatment-naive samples, no meaningful comparisons could be performed between the Q151M and the TAM 2 group.


The present study aimed to better characterize possible viral genetic signatures associated with the emergence of MNR profiles. Specifically, it was investigated whether particular polymorphic mutations are associated with the occurrence of 69 insertion and Q151M. The study confirmed the cluster of the 69 insertion with the TAM 1 pathway. The polymorphisms K43E, S162C, and R211K were associated with the emergence of this cluster, but no polymorphism was shown to be solely associated with the 69 insertion. Among others, the polymorphism F214L was found to be strongly positively associated with the Q151M/TAM 2 pathway, but negatively with the 69 insertion/TAM 1 pathway. S68G, T165I, and I202V were specifically associated with Q151M in contrast to TAM 2. We summarized the suggested resistance pathways in Figure 2.

Q151M co-occurred more often with TAM 2 than with TAM 1. In the absence of crystallographic data, it is difficult to explain why Q151M and TAM 1 are apparently less compatible than Q151M and TAM 2. It is, however, conceivable that Q151M/TAM 1 show greater fitness deficits than the Q151M/TAM 2 combination. The 69 insertion most often emerges in the presence of TAM 1, therefore, it is important to change the ART immediately after the detection of TAM 1 to lower the risk for a 69 insertion.

F214L is a polymorphism known to direct resistance pathways.18,27 This is the first study showing an association with the emergence of Q151M. The high percentage of F214L in samples detected with the Q151M mutation is probably due to the negative association with the TAM 1 pathway. On a structural level, F214L is too far away from the Q151M pattern to interact directly. However, indirect effects via other amino acids can not formally be excluded. S68G was commonly observed together with Q151M. S68G is known to partially compensate the negative impact on the viral replication of Q151L that is a potential intermediate of the Q151M mutation with a strongly decreased viral replication capacity.15,28–30 The polymorphic mutation I202V was found to be positively associated with the Q151M pathway. T165I and I202V might be an important factor directing viral evolution toward Q151M in contrast to TAM 2. I202V was described to co-occur with several drug resistance mutations (eg, at position 41, 214, and 215).31 K43E was previously described to be associated with the TAM 1 pathway, which was confirmed in our study.18,32,33 V60I was found to be associated with the occurrence of TAMs, and a poor virological response to zidovudine was described together with T215Y.31,34

In principle, structural analysis could give evidence if the described polymorphic mutations energetically favor the appearance of 69 insertion and Q151M. However, in the absence of crystal structures of 69 insertion and Q151M mutants in our view, it would be too speculative to draw any meaningful conclusions given that the dipeptide insertions are part of a flexible loop and Q151M likely affects the positioning of R72 that interacts with the phosphate moieties of the bound nucleotide.

Our study is limited by the small sample size, but to date, it is the largest study addressing the topic of MNR.15,16 With our definition for a polymorphic mutation, we can not fully exclude false-positive or false-negative classifications, previous studies showed evidence, for example, for a treatment association of S68G.35 Overall, the predictive values of polymorphisms for the emergence of specific pathways were quite low. This is not so surprising, given that the emergence or resistance mutations is also strongly influenced by ART which was difficult to adjust for in this analysis. It should be noted however that we have been able to reproduce some of our main findings in an independent strictly selected dataset namely the negative associations of the polymorphisms F214L and V60I with the TAM 1/69 insertion pathway. Whether polymorphic mutations can favor the emergence of Q151M mutation is less clear from this analysis. Although we found solid evidence for a distinct 69 insertion/TAM 1 pathway, there was no clear separation between Q151M and TAM 2 mutations. Although Q151M and TAM 2 can occur independently, these mutations do not seem mutually exclusive, and the emergence of Q151M may largely be driven by factors like treatment.

To conclude, this is the first study, which found evidence for a dependency of MNR emergence on the genomic background of the HIV polymerase. The polymorphisms F214L and V60I were found to direct viral evolution toward Q151M pathway and TAM 2 pathway in contrast to the 69 insertion/TAM 1 pathway. Other genotypic changes, such as S68G, T165I, and I202V, were strongly associated with the emergence of Q151M, but their role was less clear. Nevertheless, a better understanding of the processes leading up to the emergence of MNR mutations is of great relevance in light of their negative clinical impact and the increasing MNR prevalence in resource-limited settings.36,37 Similar studies in less developed settings and with subtypes other than subtype B are clearly warranted.


We thank the patients who participate in the SHCS; the physicians and study nurses for excellent patient care; the resistance laboratories for high quality genotypic drug resistance testing; SmartGene, Zug, Switzerland, for technical support; Brigitte Remy, Martin Rickenbach, MD, F. Schöni-Affolter, and Yannick Vallet from the SHCS Data Center in Lausanne for the data management and Marie-Christine Francioli for administrative assistance. The members of theSHCS are Battegay M, Bernasconi E, Böni J, Bucher H. C, Bürgisser P, Calmy A, Cattacin S, Cavassini M, Dubs R, Egger M, Elzi L, Fischer M, Flepp M, Fontana A, Francioli P (President of the SHCS), Furrer H (Chairman of the Clinical and Laboratory Committee), Fux C. A, Gorgievski M, Günthard H (Chairman of the Scientific Board), Hirsch H. H, Hirschel B, Hösli I, Kahlert C, Kaiser L, Karrer U, Kind C, Klimkait T, Ledergerber B, Martinetti G, Müller N, Nadal D, Paccaud F, Pantaleo G, Rauch A, Regenass S, Rickenbach M (Head of Data Center), Rudin C (Chairman of the Mother & Child Substudy), Schmid P, Schultze D, Schüpbach J, Speck R, de Tejada B. M, Taffé P, Telenti A, Trkola A, Vernazza P, Weber R, and Yerly S.


1. Shirasaka T, Kavlick MF, Ueno T, et al.. Emergence of human immunodeficiency virus type 1 variants with resistance to multiple dideoxynucleosides in patients receiving therapy with dideoxynucleosides. Proc Natl Acad Sci U S A. 1995;92:2398–2402.
2. De Antoni A, Foli A, Lisziewicz J, et al.. Mutations in the pol gene of human immunodeficiency virus type 1 in infected patients receiving didanosine and hydroxyurea combination therapy. J Infect Dis. 1997;176:899–903.
3. de Jong JJ, Goudsmit J, Lukashov VV, et al.. Insertion of two amino acids combined with changes in reverse transcriptase containing tyrosine-215 of HIV-1 resistant to multiple nucleoside analogs. AIDS. 1999;13:75–80.
4. Gunthard HF, Wong JK, Ignacio CC, et al.. Comparative performance of high-density oligonucleotide sequencing and dideoxynucleotide sequencing of HIV type 1 pol from clinical samples. AIDS Res Hum Retroviruses. 1998;14:869–876.
5. Winters MA, Coolley KL, Girard YA, et al.. A 6-basepair insert in the reverse transcriptase gene of human immunodeficiency virus type 1 confers resistance to multiple nucleoside inhibitors. J Clin Invest. 1998;102:1769–1775.
6. Gomez-Cano M, Rubio A, Puig T, et al.. Prevalence of genotypic resistance to nucleoside analogues in antiretroviral-naive and antiretroviral-experienced HIV-infected patients in Spain. AIDS. 1998;12:1015–1020.
7. Re MC, Borderi M, Monari P, et al.. Prevalence of multiple dideoxynucleoside analogue resistance (MddNR) in a cohort of Italian HIV-1 seropositive patients extensively treated with antiretroviral drugs. Int J Antimicrob Agents. 2001;18:519–523.
8. Truong Giang L, Thu Thuy H, Tuyet Nhung V, et al.. ARV restistance in patients with treatment failure to first-line regimens in Ho Chi Minh city, Vietnam. Presented at: XVII International AIDS Conference; August 3-8, 2008; Mexico City, Mexico.
9. Harrigan PR, Mo T, Hirsch J, et al.. 21-base pair insertion/duplication at codon 69 of the HIV type 1 reverse transcriptase in a patient undergoing multiple nucleoside therapy. AIDS Res Hum Retroviruses. 2007;23:895–899.
10. Marcelin AG, Delaugerre C, Wirden M, et al.. Thymidine analogue reverse transcriptase inhibitors resistance mutations profiles and association to other nucleoside reverse transcriptase inhibitors resistance mutations observed in the context of virological failure. J Med Virol. 2004;72:162–165.
11. Cases-Gonzalez CE, Franco S, Martinez MA, et al.. Mutational patterns associated with the 69 insertion complex in multi-drug-resistant HIV-1 reverse transcriptase that confer increased excision activity and high-level resistance to zidovudine. J Mol Biol. 2007;365:298–309.
12. Masquelier B, Race E, Tamalet C, et al.. Genotypic and phenotypic resistance patterns of human immunodeficiency virus type 1 variants with insertions or deletions in the reverse transcriptase (RT): multicenter study of patients treated with RT inhibitors. Antimicrob Agents Chemother. 2001;45:1836–1842.
13. Rhee SY, Liu TF, Holmes SP, et al.. HIV-1 subtype B protease and reverse transcriptase amino acid covariation. PLoS Comput Biol. 2007;3:e87.
14. Cozzi-Lepri A, Ruiz L, Loveday C, et al.. Thymidine analogue mutation profiles: factors associated with acquiring specific profiles and their impact on the virological response to therapy. Antivir Ther. 2005;10:791–802.
15. Schmit JC, Van Laethem K, Ruiz L, et al.. Multiple dideoxynucleoside analogue-resistant (MddNR) HIV-1 strains isolated from patients from different European countries. AIDS. 1998;12:2007–2015.
16. Zaccarelli M, Perno CF, Forbici F, et al.. Q151M-mediated multinucleoside resistance: prevalence, risk factors, and response to salvage therapy. Clin Infect Dis. 2004;38:433–437.
17. Scherrer AU, von Wyl V, Joos B, et al.. Predictors for the emergence of the 2 multi-nucleoside/nucleotide resistance mutations 69 insertion and Q151M and their impact on clinical outcome in the Swiss HIV Cohort Study. J Infect Dis. 2011;203:791–797.
18. Svicher V, Sing T, Santoro MM, et al.. Involvement of novel human immunodeficiency virus type 1 reverse transcriptase mutations in the regulation of resistance to nucleoside inhibitors. J Virol. 2006;80:7186–7198.
19. Parikh UM, Barnas DC, Faruki H, et al.. Antagonism between the HIV-1 reverse-transcriptase mutation K65R and thymidine-analogue mutations at the genomic level. J Infect Dis. 2006;194:651–660.
20. Ceccherini-Silberstein F, Svicher V, Sing T, et al.. Characterization and structural analysis of novel mutations in human immunodeficiency virus type 1 reverse transcriptase involved in the regulation of resistance to nonnucleoside inhibitors. J Virol. 2007;81:11507–11519.
21. von Wyl V, Yerly S, Burgisser P, et al.. Long-term trends of HIV type 1 drug resistance prevalence among antiretroviral treatment-experienced patients in Switzerland. Clin Infect Dis. 2009;48:979–987.
22. Ledergerber B, Egger M, Opravil M, et al.. Clinical progression and virological failure on highly active antiretroviral therapy in HIV-1 patients: a prospective cohort study. Swiss HIV Cohort Study. Lancet. 1999;353:863–868.
23. Schoeni-Affolter F, Ledergerber B, Rickenbach M, et al.. Cohort profile: the Swiss HIV Cohort study. Int J Epidemiol. 2010;39:1179–1189.
24. Hill A, Sabin C. Designing and interpreting HIV noninferiority trials in naive and experienced patients. AIDS. 2008;22:913–921.
25. Kouyos RD, von Wyl V, Yerly S, et al.. Ambiguous nucleotide calls from population-based sequencing of HIV-1 are a marker for viral diversity and the age of infection. Clin Infect Dis. 2011;52:532–539.
26. von Wyl V, Yerly S, Boni J, et al.. Factors associated with the emergence of K65R in patients with HIV-1 infection treated with combination antiretroviral therapy containing tenofovir. Clin Infect Dis. 2008;46:1299–1309.
27. Ceccherini-Silberstein F, Cozzi-Lepri A, Ruiz L, et al.. Impact of HIV-1 reverse transcriptase polymorphism F214L on virological response to thymidine analogue-based regimens in antiretroviral therapy (ART)-naive and ART-experienced patients. J Infect Dis. 2007;196:1180–1190.
28. Monno L, Scudeller L, Brindicci G, et al.. Genotypic analysis of the protease and reverse transcriptase of non-B HIV type 1 clinical isolates from naive and treated subjects. Antiviral Res. 2009;83:118–126.
29. Garcia-Lerma JG, Gerrish PJ, Wright AC, et al.. Evidence of a role for the Q151L mutation and the viral background in development of multiple dideoxynucleoside-resistant human immunodeficiency virus type 1. J Virol. 2000;74:9339–9346.
30. Matsumi S, Kosalaraksa P, Tsang H, et al.. Pathways for the emergence of multi-dideoxynucleoside-resistant HIV-1 variants. AIDS. 2003;17:1127–1137.
31. Precious HM, Gunthard HF, Wong JK, et al.. Multiple sites in HIV-1 reverse transcriptase associated with virological response to combination therapy. AIDS. 2000;14:31–36.
32. Huigen MC, van Ham PM, de Graaf L, et al.. Identification of a novel resistance (E40F) and compensatory (K43E) substitution in HIV-1 reverse transcriptase. Retrovirology. 2008;5:20.
33. Saracino A, Monno L, Scudeller L, et al.. Impact of unreported HIV-1 reverse transcriptase mutations on phenotypic resistance to nucleoside and non-nucleoside inhibitors. J Med Virol. 2006;78:9–17.
34. Cane PA, Green H, Fearnhill E, et al.. Identification of accessory mutations associated with high-level resistance in HIV-1 reverse transcriptase. AIDS. 2007;21:447–455.
35. Roge BT, Katzenstein TL, Obel N, et al.. K65R with and without S68: a new resistance profile in vivo detected in most patients failing abacavir, didanosine and stavudine. Antivir Ther. 2003;8:173–182.
36. Hosseinipour MC, van Oosterhout JJ, Weigel R, et al.. The public health approach to identify antiretroviral therapy failure: high-level nucleoside reverse transcriptase inhibitor resistance among Malawians failing first-line antiretroviral therapy. AIDS. 2009;23:1127–1134.
37. Sungkanuparph S, Manosuthi W, Kiertiburanakul S, et al.. Options for a second-line antiretroviral regimen for HIV type 1-infected patients whose initial regimen of a fixed-dose combination of stavudine, lamivudine, and nevirapine fails. Clin Infect Dis. 2007;44:447–452.

HIV-1; 69 insertion; multinucleoside resistance; Q151M; subtype B; thymidine analogue mutation

Supplemental Digital Content

© 2012 Lippincott Williams & Wilkins, Inc.