UvA-DARE is a service provided by the library of the University of Amsterdam (https://dare.uva.nl)
Towards virological monitoring of HIV-1 drug resistance in resource-limited
settings
Aitken, S.C.
Publication date
2014
Link to publication
Citation for published version (APA):
Aitken, S. C. (2014). Towards virological monitoring of HIV-1 drug resistance in
resource-limited settings.
General rights
It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons).
Disclaimer/Complaints regulations
If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: https://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible.
C
A
H
P
T
E
R
1
General introduction
S
ince the first recorded cases in 1981, human immunodeficiency virus (HIV) has spread globally, resulting in the death of over 35 million people(1). The global HIV-1 epidemic has been estimated to include 34.0 million (range 31.4-35.9 million) infected adults and children by the end of 2011. An alarming 69% (n= 23.5 million) of the total global infections are people residing in Sub-Saharan Africa. Prevalence is highest in adults aged 15-49, affecting 0.8% of the global adult population, and as high as 4.9% of adults residing in sub-Saharan Africa(2). People at greatest risk of being infected with HIV are homosexual and heterosexual people having unprotected sex, sex workers, people who inject drugs, and children born to HIV-infected mothers(2).HIV primarily infects CD4+ T-lymphocytes and macrophages, entering the body via mucous membranes or through blood-blood contact. After transmission, an acute infection ensues, characterised by rapid virus replication and immune activation(3-5). The infection then stabilises to a chronic condition, characterised by stable, continuous viral replication and a gradual decline in CD4+ T-lymphocytes(6). If not treated, the decline in CD4+ T-lymphocytes will continue until the immune system of the infected individual is compromised, thereby making them vulnerable to opportunistic infections leading to acquired immunodeficiency syndrome (AIDS) and eventually death.
The number of people dying from AIDS-related illnesses was estimated to be 1.7 million (range 1.5-1.9 million) worldwide in 2011. Compared to 2005, this is a 24% reduction. The primary reason for this reduction is the scale-up and success of antiretroviral treatment (ART) programs, which have resulted in a decrease of AIDs related deaths and a decline in the incidence of new HIV infections. Antiretroviral (ARV) access in resource-limited settings (RLS) has also improved the health of people infected with HIV, enabling them to lead relatively normal lives, including being able to work and providing an income for themselves and their families(2).
General introduction
|
131
Human immunodeficiency virus, HIV
HIV is an enveloped RNA virus belonging to the Family of the Retroviridae, genus lentiviridae. HIV-1 is the predominant global HIV species, with the less pathogenic HIV-2 found mostly in West Africa. HIV-1 is further divided into four groups, namely major (M), non-M/non-O (N), outlier (O) and pending the identification of further human cases (P), of which M is the primary contributor to the global HIV pandemic. Group M HIV-1 comprises of subtypes A- D, F-H, J and K, and numerous circulating recombinant forms (CRFs; currently n= 58), including common CRFs 01_AE and 02_AG(7, 8) (Figure 1). HIV-1 subtype C is responsible for the majority of global HIV-1 infections (48%), followed by subtypes A (12%) and B (11%). Evidence suggests that Central Africa is where the HIV epidemic originated and as such has the largest diversity of subtypes (Figure 1) (9-11). In sub-Saharan Africa infections are primarily caused by HIV-1 subtype C, whilst in Europe and North America HIV-1 subtype B predominates, although subtype diversity has increased over the last decade, particularly in Europe(7).
Overview of the replicative cycle of HIV
During infection, HIV first binds to the surface of target cells by interaction of the viral surface glycoprotein 120 (gp120) with the CD4 receptor on the cell surface(12, 13). This binding causes a conformational change in gp120(14, 15), allowing for an additional interaction of gp120 with either CC chemokine receptor 5 (CCR5)(16) or CxC chemokine receptor 4 (CXCR4)(17). This interaction triggers the viral transmembrane subunit gp41 to interact with the target cell, eventually leading to fusion of the virus envelope with the target cell(18) and internalization of the virus particle. The virus uncoats, releasing the genomic RNA into the cytoplasm of the cell. Once in the cytoplasm the genomic viral RNA is converted into double-stranded cDNA by the viral reverse transcriptase (RT), which is then complexed with integrase and other viral components to form the pre-integration complex(19) enabling entry into the cells’ nucleus. In the nucleus, the integrase enzyme mitigates the integration of the double-stranded viral DNA into the host cell genome. Once integration has occurred proviral DNA will be copied into each daughter cell with every division cycle of an infected cell, thereby achieving long-term presence in the host genome. Furthermore, the proviral DNA serves as a template for transcription to produce viral mRNA and genomic HIV-1 RNA molecules. In the cytoplasm, viral mRNA is translated into viral precursor polyproteins, which are cleaved by protease (PR), a process necessary to produce infectious viral progeny(20). Cleaved viral proteins are then assembled with RNA genomes into new virions on the cellular membranes(21), eventually being released as virus particles (Figure 2).
Cells that have productive HIV replication generally have a short life span, either being destroyed as a result of virus replication or by the host immune response. HIV infection is not always productive, which is the case when infection stops at the point of integration and the cell enters a resting state, referred to as latently infected resting CD4+ T cells(23). Integrated proviral DNA found in latently infected cells is referred to as archived virus, which can represent a viral population different to the currently circulating population.
General introduction
|
151
Latently infected, resting CD4+ T cells are the largest barrier to curing HIV as they are a source for reactivation of viral replication(24-26).
Figure 2. Replication cycle of HIV (adapted from Engelman et al. 2012(22))
HIV Therapy
There are currently six classes of FDA-approved ARV drugs that target different steps of the HIV replication cycle: Nucleoside reverse transcriptase inhibitors (NRTI), non-nucleoside reverse transcriptase inhibitors (NNRTI), protease inhibitors (PI), fusion inhibitors, integrase inhibitors, and entry inhibitors (CCR5)(27). All currently available drugs for the treatment of HIV are summarised with their introduction over time in Figure 3.
Initial treatment for HIV infection was based on the NRTI zidovudine (AZT) monotherapy. Although clinical benefit was demonstrated upon AZT treatment, the effect was rather temporal and lasted for only weeks to months(28, 29) due
Figure 3. Currently available FDA-approved antiretroviral drugs for HIV treatment, with their introduction over time.
Nucleoside reverse transcriptase inhibitors (NRTI; Black): Zidovudine azidothymidine (AZT,
ZDV), didanosine dideoxyinosine (ddI), stavudine (d4T), lamivudine (3TC), abacavir sulphate
(ABC), enteric coated didanosine (ddI EC), tenofovir disoproxil fumerate (TDF), emtricitabine
(FTC). Non-nucleoside reverse transcriptase inhibitors (NNRTI; Blue): Nevirapine (NVP),
delavirdine (DLV), efavirenz (EFV), etravarine (ETR), rilpivirine (RPV), nevirapine extended
release (NVP-XR). Protease inhibitor (PI; Red): Saquinavir mesylate (SQV), ritonavir
(RTV), indinavir (IDV), nelfinavir mesylate (NFV), lopinavir and ritonavir (LPV/r), atazanavir
sulphate (ATV), fosamprenavir calcium (FPV), tipranavir (TPV), darunavir (DRV). Fusion
inhibitors (Green): Enfuvirtide (T-20, ENF). Entry Inhibitor (CCR5; Purple): Maraviroc (MVC).
Integrase inhibitor (Orange): Raltegravir (RAL), Elvitegravir (EVG). Cobicistat (COBI; pink)
is a cytochrome P450 3A enzyme inhibitor. Combination regimens are underlined. Generic drugs are shown in italics.
1981 1987 1991 1994 1995 1996 1997 1998 2000 2001 2003 2004 2005 2006 2007 2008 201
1
1986
First reported AIDS case First virus isolated
First FDA-approved blood test
AZT ddI d4T 3TC, SQV RTV, IDV, NVP NFV, DLV, AZT/3TC EFV, ABC LPV/r, ddI-EC, AZT/3TC/ABC TDF ENF, ATV, FTC, FPV MVC, RAL 2012
ABC/3TC, TDF/FTC, ddI generic
TPV, AZT generic DRV, TDF/FTC/EFV ETR RPV, TDF/FTC/RPV, NVP-XR EVG/FTC/TDF/COBI 1985 HIV named
First FDA-approved antiretroviral
General introduction
|
171
to the emergence of viruses harbouring reduced susceptibility to the drug(30, 31). New drugs were developed, and in the early 1990s combination therapy was shown to have a greater success for long term HIV treatment(32, 33). The use of combination antiretroviral therapy (cART) was introduced in resource-rich settings (RRS) in the mid-1990s. With the introduction of cART, the number of people dying from AIDS-related illnesses substantially decreased (34-36).
Antiretroviral Therapy Roll-out
When introduced, the cost of cART was on average USD 10 000 to 15 000 per person per year, restricting access to RRS. International lobby by HIV/ AIDS activists put pressure on governments and branded pharmaceutical companies to reduce the cost. In 2000 the International Aids Society (IAS) conference was held for the first time on African soil in Durban, South Africa. The conference highlighted the need for improved HIV treatment in RLS, and subsequently the Accelerated Access Initiate (AAI) was undertaken by the WHO, lowering the costs of cART considerably. In 2002 a total of only 300 000 infected individuals in low- and middle-income countries were receiving the necessary ART(1). The WHO “3 by 5” initiative(37) was responsible for increasing access to cART to more than 6.6 million infected individuals in 2011(1). In 2011, a political declaration was made, the United Nations Political Declaration on HIV and AIDS, where countries pledged to intensify efforts to eliminate HIV and AIDS(38). One of the goals of this pledge is to provide antiretroviral therapy to 15 million people by 2015, and as a result just over 9.7 million infected individuals are currently receiving cART in low- and middle-income countries(39) (Figure 4 and 5).
The 2013 WHO guidelines on HIV treatment have greatly increased the number of people qualifying for treatment. People eligible for ART include all HIV infected adults and children older than five years of age presenting with stage 3 or 4 AIDS defining illnesses and/or with a CD4 count ≤500 (previously ≤350(41)) cells/mm3; with active TB infection; with HBV co-infection with
evidence of severe chronic liver disease; partners with HIV in serodiscordant couples to reduce HIV transmission (new); and pregnant and breastfeeding (new) women with HIV(40). For children younger than five years of age infected with HIV, ART should be given regardless of WHO clinical stage or CD4 count. With the introduction of the new staring criteria, an additional 9.2 million people qualify for ART compared to the 2010 guidelines(41).
Figure 4. Actual and projected number of people receiving antiretroviral therapy in low- and middle-income countries, by region, 2003-2015(39) (Source: 2013 Global AIDS Response Progress Reporting (WHO/UNICEF/UNAIDS)).
When first-line ARV treatment is no longer effective in suppressing viral replication, in most cases due to emerging drug resistance, switching to a second-line regimen is warranted. The WHO suggested second-line regimen consists of a boosted PI, preferably atazanavir/ritonavir (ATV/r) or lopinavir/ ritonavir (LPV/r), and two NRTIs, preferably AZT and 3TC, the choice of which is dependant on an infected individuals previous first-line regimen(40). In addition to use as a PI in second-line therapy, LPV/r and two NRTIs are also recommended in first-line treatment for HIV infected children younger
General introduction
|
191
than three years of age(40). In general, the availability of PI-based regimens varies largely between countries, mainly due to its much higher cost.
0 10 20 30 40 50 60 70 80 90 100 Angol a Botsw ana Burun di Cam eroon Chad Côte d 'Ivoir e Dem ocrat ic Repu blic of Cong o Ethiopi a Ghan a Keny a Lesotho Ma lawi Mozam bique Namib ia Nigeria Sout h Afric a Swa zilan d Ugand a* United Republ ic of Tanz ania Zam bia Zimbabw e
Figure 5. Antiretroviral therapy (ART) coverage among adults and children eligible for ART in 21 African countries with a high burden of HIV infection, 2012. Blue: Southern Africa; Green: East and Central Africa; Yellow: West Africa. (Adapted from: 2013 Global AIDS Response Progress Reporting (WHO/UNICEF/UNAIDS) and 2013 UNAIDS/WHO estimates)
Current cART regimens for the treatment of HIV-1 in adults and adolescents in RLS, as recommended by WHO guidelines, are a combination of two NRTIs and one NNRTI. As this is the starting therapy, it is commonly known as first-line treatment regimen. The preferred first-line regimen is comprised of tenofovir disoproxil fumerate (TDF), lamivudine (3TC) or emtricitabine (FTC), and efavirenz (EFV)(40). Alternative regimens allow for zidovudine (AZT) in place of TDF, and nevirapine (NVP) in place of EFV(40). For children three years of age and up, the recommenced first-line includes EFV, 3TC, and the NRTI abacavir (ABC). Until recently, regimens in RLS often contained stavudine (d4T), however as a result of high toxicity associated with its use, d4T use is declining.
HIV Drug Resistance
The reverse transcriptase enzyme, responsible for converting viral RNA into cDNA (Figure 1), lacks a proof-reading capability resulting in, on average, one mutation per genome per replication cycle(42). A lack of proof reading ability and frequent recombination events(43, 44), combined with the high turn-over of virus particles, on average 109 -1011 virus particles daily(45, 46), results in a multitude of different viruses within a population. This genetically diverse population of viruses is referred to as viral quasispecies(47), and can include viral variants containing drug resistance mutations (DRMs)(48, 49).
Mutations conferring drug resistance are introduced in the viral genome at reverse transcription, and the proviral DNA containing these mutations is subsequently integrated into the cellular genome. Even when viral replication is suppressed by effective treatment, integrated proviral DNA is still present in cells. Virus variants produced from proviral DNA encoding resistance often have a reduced replication capacity and are out competed by wild-type virus. However, incomplete suppression of viral replication due to suboptimal drug pressure as a result of poor adherence, treatment interruption, insufficient plasma drug concentrations, or the use of inferior drugs or drug combinations, may result in a selective replicative advantage for viral variants with resistance to that drug. In such a situation, resistance virus can rapidly become the dominant virus, decreasing efficacy of the particular ART regimen and resulting in ARV treatment failure. As such, sub-optimal bioavailability of the ARV leads to the acquisition of drug resistance. In addition, individuals harbouring drug resistant virus may transmit this virus to previously uninfected individuals, referred to as transmitted drug resistance (TDR).
DRMs are specific to the drug class they affect. Reduced NRTI susceptibility is associated with specific mutations at 16 amino acid positions in RT(50). Similarly, various mutations conferring reduced susceptibility to NNRTIs have been identified, as well as for PIs and inhibitors of the viral integrase enzyme.
General introduction
|
211
Within and between drug classes, those mutations can have either additive, synergistic or antagonistic cross-reactivities, which makes interpretation of mutational patterns for clinical drug efficacy purposes a rather complex and specialised matter.
The WHO established a global HIV Drug Resistance Network (HIVResNet) in order to monitor the emergence of HIVDR. Countries in Africa that are currently involved include Burundi, Cameroon, Kenya, Malawi, Mozambique, Nigeria, South Africa, Swaziland, Zambia, and Zimbabwe. In the 2012 report, results of the WHO survey of acquired drug resistance obtained between 2006 and 2010 have shown that of the individuals failing therapy (VL >1000 copies/ml) at 12 months, 72% had DRMs (Figure 6). The most common mutation observed is the NRTI mutation M184V followed by several NNRTI mutations, such as K103N, Y181C and V106M(51). Due to the limited use and later introduction of PI containing regimens, the occurrence of PI drug resistance is still low(51).
Figure 6. Prevalence of HIV drug resistance-associated mutations among people experiencing treatment failure at 12 months. Mutations were defined using the 2009 WHO surveillance resistance mutation list. (Source: WHO Resistance Report 2012(51)).
According to the WHO resistance report for 2012, there has been an increase in TDR between 2004 and 2010 in RLS areas conducting HIVDR surveillance, either in published studies or as part of the WHO surveys(51). Of note was the increase and prevalence of NNRTI resistance. A slightly increased prevalence of HIVDR was seen in countries with high national ART coverage(51), with the level of TDR being linked to the duration of national roll-out programs(52, 53).
Treatment Monitoring
During the progression of HIV infection (Figure 7), an increase in viral replication generally precedes a decrease in CD4+ lymphocytes(54), which, in the long-term, is then followed by the presentation of AIDS-defining illnesses. VL monitoring is an effective tool to monitor for the first signs of treatment failure. The role of CD4+ lymphocyte counts is to gauge the state of the immune system to determine whether there is a risk for infection by opportunistic infections.
Figure 7. A generalised graph of the progression of HIV infection. (Adapted from Pantaleo et al., 1993(55)).
General introduction
|
231
In RRS, the standard of care for HIV treatment monitoring employs CD4+ counts and VL monitoring at entry into care and every three to six months thereafter. In addition to VL and CD4+ testing, resistance testing is often preformed prior to treatment initiation in order to ensure the most effective choice of therapy,as well as at virological failure in order to select an appropriate follow-up regimen(56).
By contrast, treatment monitoring in most RLS primarily involves clinical monitoring for stage 3 and 4 AIDS-defining illnesses and, if available, immunological monitoring using CD4+ counts(40). The inadequacies of CD4+ counts for determining treatment failure have been described on many occasions, either leading to unnecessary switching of regimens due to incorrectly diagnosed or presumed virological failure(57-61), or an accumulation of drug resistance mutations due to extended exposure to a failing regimen(62). Recently, the WHO added VL monitoring as a strong recommendation for diagnosis and confirmation of treatment failure in RLS(40), however its use is limited due to costs and lack of laboratory infrastructure. Similarly, the use of HIVDR genotyping for individual patient management in RLS is limited to clinical research studies, and for pre-authorized private medical care, or at the patients own expense. Limited routine resistance testing is performed due to high cost, infrastructure requirements, and complexity of available assays.
Logistics of Treatment Monitoring
Commercial VL and HIVDR genotyping assays are performed from plasma, which require cold-chain maintenance and biohazardous containment. This limits their use in RLS to collection sites with appropriate sample processing facilities and cold-storage, which are also within easy reach of reference laboratories for subsequent testing. The use of dried blood spot samples (DBS) is becoming increasingly popular for VL monitoring and HIVDR genotyping in RLS. Numerous studies have been conducted to determine potential application of DBS in various assays, reviewed by Hamers et al. (2009)(63)
and Bertagnolio et al. (2010)(64). Although initial data suggests application is feasible for VL and HIVDR genotyping, findings are inconsistent with respect to storage temperature and duration, and more detailed analysis on the effect of storage on sample degradation is necessary to ensure reliable results. Additionally, the sampling technique has numerous drawbacks: small sample volumes decrease analytical sensitivity, impaired nucleic acid integrity when stored in sub-optimal conditions, laborious nucleic acid isolation procedures limiting high throughput capacity, and potential interference of archived proviral DNA.
Treatment Challenges in RLS
The majority of HIV-infected individuals reside in Africa. Whilst access to treatment is increasing, there are still logistical hurdles to prevent HIVDR and maintain long-term treatment success. The largest risk factor associated with the development of HIVDR is adherence. The recent introduction of once-daily fixed dose cART greatly decreased pill burden and should improve patient adherence; however, adherence is still hindered by drug stock outs due to poor supply and procurement management, as well as limited supportive care, including VL and CD4 testing, resulting in extended exposure to failing regimens.
In addition to logistical hurdles, the vast array of subtypes found in Africa add an additional challenge to treatment and testing. Some resistance mutations are more prevalent in certain subtypes due to differences in the genetic make-up between subtypes thereby facilitating the emergence of some mutations over others. For example, studies have shown that the prevalence of K65R, conferring reduced susceptibility to d4T, ddI, ddC, 3TC, FTC, ABC, and TDF(50), is higher in nonsubtype-B clades(65-69). Similarly, a higher prevalence of the V106M mutation over the V106A is observed in subtype C viruses, which is associated with high-level EFV resistance(70, 71). Whilst individual patient management is currently not feasible in RLS due to costs, population-based surveillance for HIVDR mutations prevalence and subtype distribution
General introduction
|
251
is necessary in order to make the most effective choice of ARV therapy for national guidelines.
Scope of This Thesis
Affordable Resistance Test for Africa: ARTA
Established in 2008, the ARTA project is a private-public consortium headed up by the PharmAccess Foundation, a non-profit organisation affiliated with the Center for Poverty-related Communicable Diseases of the Academic Medical Centre (AMC) in Amsterdam. The collaborators involved in the project include the University Medical Centre Utrecht (UMCU) in the Netherlands, the Centre de Recherche Public de la Santé in Luxembourg, the University of the Witwatersrand and Contract Laboratory Services in Johannesburg, South Africa, and Janssen Diagnostics BVBA (formerly Virco BVBA) in Belgium. The ARTA project aimed to develop more affordable HIV-1 treatment monitoring applications, including VL monitoring and HIVDR genotyping, which can be universally applied in RLS. The specific requirements are given in Box 1.
Box 1. Specific requirements for ARTA assays:
Simplified sample collection and transport (DBS) Optimized nucleic acid elution methodologies for DBS HIV subtype-independent assays nucleic acid amplification Pragmatic genotyping methods
Commercial VL assays provide precise measurement of viral RNA copies found in a sample, but generally require large equipment designed for high-throughput to ensure cost effectiveness, which is not always ideal for small- and medium-throughput facilities. However, in many cases exact VL quantitation is not required to determine treatment failure. Therefore, an assay that classifies a sample as either above or below a treatment success threshold could have wide application. As such, a simple virological failure (VF) screening assay that is compatible for application with DBS was
developed, validated and transferred to three laboratories in Uganda with various levels of experience on application of molecular monitoring methods (Chapter 2).
A recent review of ARV treatment programs in sub-Saharan Africa has shown that 94% of treatment is first-line based, and effective virological suppression is achieved for approximately 80% of these patients(72). Similarly, in the 2012 WHO survey of acquired drug resistance, 76% of patients achieved virological suppression at 12-months after initiation of a standard first-line regimen(51). However, 20-24% of patients failing cART did not have DRM, and would have had unnecessary treatment switching without access to HIVDR genotyping results. Taking into consideration that the majority of HIV infected individuals receive first-line cART, a low cost HIVDR genotyping assay targeting the region of RT harbouring all major RT inhibitor resistance mutation positions was developed and applied clinically for HIVDR determination in first-line therapy failure (Chapter 3). Further, evaluation of the application of newly
developed VL and HIVDR genotyping assays in RLS is shown to demonstrate feasibility in a South African laboratory (Chapter 4).
For more in depth studies on first- and second-line drug resistance, an alternative to commercial PR-RT based HIVDR genotyping assays is described (Chapter 5), and is integrated application in RLS-related studies is
shown (Chapters 6, and 7). Lastly, the stability of DBS samples is important
to ensure reliable results using DBS sampling, and a further understanding of the effect of storage conditions On DBS sample integrity is explored (Chapter 8). A final discussion (Chapter 9) concludes the relevance of the
described research.
References
1. WHO/UNAIDS/UNICEF. 2011. Progress report 2011: Global HIV/AIDS response. http://www.who.int/hiv/pub/progress_report2011/en/index.html. 2. UNAIDS. 2012. Global report: UNAIDS report in the global AIDS epidemic
General introduction
|
271
2012. http://www.unaids.org/en/media/unaids/contentassets/documents/ epidemiology/2012/gr2012/20121120_UNAIDS_Global_Report_2012_ with_annexes_en.pdf.
3. Borrow P, Lewicki H, Hahn BH, Shaw GM, Oldstone MB. 1994.
Virus-specific CD8+ cytotoxic T-lymphocyte activity associated with control of viremia in primary human immunodeficiency virus type 1 infection. J Virol 68:6103-6110.
4. Daar ES, Moudgil T, Meyer RD, Ho DD. 1991. Transient high levels of
viremia in patients with primary human immunodeficiency virus type 1 infection. N Engl J Med 324:961-964.
5. Koup RA, Safrit JT, Cao Y, Andrews CA, McLeod G, Borkowsky W,
Farthing C, Ho DD. 1994. Temporal association of cellular immune responses with the initial control of viremia in primary human immunodeficiency virus type 1 syndrome. J Virol 68:4650-4655.
6. Dewhurst SL, da Cruz RL, Whetter L. 2000. Pathogenesis and treatment of HIV-1 infection: recent developments (Y2K update). Front Biosci 5:D30-49.
7. Hemelaar J. 2012. The origin and diversity of the HIV-1 pandemic. Trends Mol Med 18:182-192.
8. LANL. 2013. Los Alamos HIV Database: HIV Circulating Recombinant
Forms (CRFs). http://www.hiv.lanl.gov/content/sequence/HIV/CRFs/CRFs. html.
9. Kalish ML, Robbins KE, Pieniazek D, Schaefer A, Nzilambi N, Quinn
TC, St Louis ME, Youngpairoj AS, Phillips J, Jaffe HW, Folks TM. 2004. Recombinant viruses and early global HIV-1 epidemic. Emerg Infect Dis 10:1227-1234.
10. Rambaut A, Robertson DL, Pybus OG, Peeters M, Holmes EC. 2001.
Human immunodeficiency virus. Phylogeny and the origin of HIV-1. Nature 410:1047-1048.
11. Vidal N, Peeters M, Mulanga-Kabeya C, Nzilambi N, Robertson D, Ilunga W, Sema H, Tshimanga K, Bongo B, Delaporte E. 2000. Unprecedented degree of human immunodeficiency virus type 1 (HIV-1) group M genetic diversity in the Democratic Republic of Congo suggests that the HIV-1 pandemic originated in Central Africa. J Virol 74:10498-10507.
the human immunodeficiency virus binds to the immunoglobulin-like domain of CD4. Nature 334:159-162.
13. Maddon PJ, Dalgleish AG, McDougal JS, Clapham PR, Weiss RA, Axel
R. 1986. The T4 gene encodes the AIDS virus receptor and is expressed in the immune system and the brain. Cell 47:333-348.
14. Trkola A, Dragic T, Arthos J, Binley JM, Olson WC, Allaway GP, Cheng-Mayer C, Robinson J, Maddon PJ, Moore JP. 1996. CD4-dependent, antibody-sensitive interactions between HIV-1 and its co-receptor CCR-5. Nature 384:184-187.
15. Wu L, Gerard NP, Wyatt R, Choe H, Parolin C, Ruffing N, Borsetti A, Cardoso AA, Desjardin E, Newman W, Gerard C, Sodroski J. 1996. CD4-induced interaction of primary HIV-1 gp120 glycoproteins with the chemokine receptor CCR-5. Nature 384:179-183.
16. Deng H, Liu R, Ellmeier W, Choe S, Unutmaz D, Burkhart M, Di Marzio P, Marmon S, Sutton RE, Hill CM, Davis CB, Peiper SC, Schall TJ, Littman DR, Landau NR. 1996. Identification of a major co-receptor for primary isolates of HIV-1. Nature 381:661-666.
17. Feng Y, Broder CC, Kennedy PE, Berger EA. 1996. HIV-1 entry cofactor: functional cDNA cloning of a seven-transmembrane, G protein-coupled receptor. Science 272:872-877.
18. Chan DC, Kim PS. 1998. HIV entry and its inhibition. Cell 93:681-684. 19. Miller MD, Farnet CM, Bushman FD. 1997. Human immunodeficiency virus
type 1 preintegration complexes: studies of organization and composition. J Virol 71:5382-5390.
20. Kohl NE, Emini EA, Schleif WA, Davis LJ, Heimbach JC, Dixon RA,
Scolnick EM, Sigal IS. 1988. Active human immunodeficiency virus protease is required for viral infectivity. Proc Natl Acad Sci U S A 85:4686-4690.
21. Nguyen DH, Hildreth JE. 2000. Evidence for budding of human
immunodeficiency virus type 1 selectively from glycolipid-enriched membrane lipid rafts. J Virol 74:3264-3272.
22. Engelman A, Cherepanov P. 2012. The structural biology of HIV-1:
mechanistic and therapeutic insights. Nat Rev Microbiol 10:279-290.
23. Garcia-Blanco MA, Cullen BR. 1991. Molecular basis of latency in
General introduction
|
291
24. Chun TW, Stuyver L, Mizell SB, Ehler LA, Mican JA, Baseler M, Lloyd AL, Nowak MA, Fauci AS. 1997. Presence of an inducible HIV-1 latent reservoir during highly active antiretroviral therapy. Proc Natl Acad Sci U S A 94:13193-13197.
25. Finzi D, Hermankova M, Pierson T, Carruth LM, Buck C, Chaisson
RE, Quinn TC, Chadwick K, Margolick J, Brookmeyer R, Gallant J, Markowitz M, Ho DD, Richman DD, Siliciano RF. 1997. Identification of a reservoir for HIV-1 in patients on highly active antiretroviral therapy. Science 278:1295-1300.
26. Wong JK, Hezareh M, Gunthard HF, Havlir DV, Ignacio CC, Spina
CA, Richman DD. 1997. Recovery of replication-competent HIV despite prolonged suppression of plasma viremia. Science 278:1291-1295.
27. FDA. 2013. U.S. Food and Drug Administration: Antiretroviral drugs used in the treatment of HIV infection, http://www.fda.gov/ForConsumers/ byAudience/ForPatientAdvocates/HIVandAIDSActivities/ucm118915.htm. 28. Fischl MA, Richman DD, Hansen N, Collier AC, Carey JT, Para MF, Hardy
WD, Dolin R, Powderly WG, Allan JD, et al. 1990. The safety and efficacy of zidovudine (AZT) in the treatment of subjects with mildly symptomatic human immunodeficiency virus type 1 (HIV) infection. A double-blind, placebo-controlled trial. The AIDS Clinical Trials Group. Ann Intern Med 112:727-737.
29. Volberding PA, Lagakos SW, Koch MA, Pettinelli C, Myers MW, Booth
DK, Balfour HH, Jr., Reichman RC, Bartlett JA, Hirsch MS, et al. 1990. Zidovudine in asymptomatic human immunodeficiency virus infection. A controlled trial in persons with fewer than 500 CD4-positive cells per cubic millimeter. The AIDS Clinical Trials Group of the National Institute of Allergy and Infectious Diseases. N Engl J Med 322:941-949.
30. Larder BA, Darby G, Richman DD. 1989. HIV with reduced sensitivity to zidovudine (AZT) isolated during prolonged therapy. Science 243:1731-1734.
31. Larder BA, Kemp SD. 1989. Multiple mutations in HIV-1 reverse transcriptase confer high-level resistance to zidovudine (AZT). Science 246:1155-1158. 32. Johnson VA, Hirsch MS. 1990. New developments in antiretroviral drug
therapy for human immunodeficiency virus infections. AIDS Clin Rev :235-272.
33. Johnson VA, Hirsch MS. 1990. New developments in combination chemotherapy of anti-human immunodeficiency virus drugs. Ann N Y Acad Sci 616:318-327.
34. Collier AC, Coombs RW, Schoenfeld DA, Bassett RL, Timpone J,
Baruch A, Jones M, Facey K, Whitacre C, McAuliffe VJ, Friedman HM, Merigan TC, Reichman RC, Hooper C, Corey L. 1996. Treatment of human immunodeficiency virus infection with saquinavir, zidovudine, and zalcitabine. AIDS Clinical Trials Group. N Engl J Med 334:1011-1017.
35. D’Aquila RT, Hughes MD, Johnson VA, Fischl MA, Sommadossi JP, Liou
SH, Timpone J, Myers M, Basgoz N, Niu M, Hirsch MS. 1996. Nevirapine, zidovudine, and didanosine compared with zidovudine and didanosine in patients with HIV-1 infection. A randomized, double-blind, placebo-controlled trial. National Institute of Allergy and Infectious Diseases AIDS Clinical Trials Group Protocol 241 Investigators. Ann Intern Med 124:1019-1030.
36. Palella FJ, Jr., Delaney KM, Moorman AC, Loveless MO, Fuhrer J,
Satten GA, Aschman DJ, Holmberg SD. 1998. Declining morbidity and mortality among patients with advanced human immunodeficiency virus infection. HIV Outpatient Study Investigators. N Engl J Med 338:853-860. 37. WHO/UNAIDS. 2003. Treat 3 million by 2005 initiative. http://www.who.
int/3by5/publications/documents/en/3by5StrategyMakingItHappen.pdf. 38. United Nations General Assembly 2011 Political Declaration on HIV and
AIDS: Intensidying Our Efforts to Eliminate HIV and AIDS. New York, United Nations, 2011.
39. WHO/UNAIDS/UNICEF. 2013. Global update on HIV treatment 2013:
results, impact and opportunities http://www.unaids.org/en/media/unaids/ contentassets/documents/unaidspublication/2013/20130630_treatment_ report_en.pdf.
40. WHO. 2013. Consolidated guidelines on the use of antiretroviral drugs for treating and preventing HIV infection: recommendations fora public health approach. http://apps.who.int/iris/bitstream/10665/85321/1/9789241505727_eng.pdf. 41. WHO. 2010. Antiretroviral therapy for HIV infection in adults and adolescents:
recommendations for a public health approach 2010 revision. http:// whqlibdoc.who.int/publications/2010/9789241599764_eng.pdf.
42. Drake JW, Holland JJ. 1999. Mutation rates among RNA viruses. Proc Natl Acad Sci U S A 96:13910-13913.
General introduction
|
311
43. Onafuwa-Nuga A, Telesnitsky A. 2009. The remarkable frequency of
human immunodeficiency virus type 1 genetic recombination. Microbiol Mol Biol Rev 73:451-480, Table of Contents.
44. Ramirez BC, Simon-Loriere E, Galetto R, Negroni M. 2008. Implications of recombination for HIV diversity. Virus Res 134:64-73.
45. Ho DD, Neumann AU, Perelson AS, Chen W, Leonard JM, Markowitz
M. 1995. Rapid turnover of plasma virions and CD4 lymphocytes in HIV-1 infection. Nature 373:123-126.
46. Perelson AS, Neumann AU, Markowitz M, Leonard JM, Ho DD. 1996.
HIV-1 dynamics in vivo: virion clearance rate, infected cell life-span, and viral generation time. Science 271:1582-1586.
47. Eigen M. 1993. Viral quasispecies. Sci Am 269:42-49.
48. Kearney M, Palmer S, Maldarelli F, Shao W, Polis MA, Mican J,
Rock-Kress D, Margolick JB, Coffin JM, Mellors JW. 2008. Frequent polymorphism at drug resistance sites in HIV-1 protease and reverse transcriptase. Aids 22:497-501.
49. Ribeiro RM, Bonhoeffer S, Nowak MA. 1998. The frequency of resistant mutant virus before antiviral therapy. Aids 12:461-465.
50. Johnson VA, Calvez V, Gunthard HF, Paredes R, Pillay D, Shafer R,
Wensing AM, Richman DD. 2013. Update of the drug resistance mutations in HIV-1: March 2013. Top HIV Med 21:6-14.
51. WHO. 2012. WHO HIV drug resistance report 2012. http://apps.who.int/iris/ bitstream/10665/75183/1/9789241503938_eng.pdf.
52. Hamers RL, Wallis CL, Kityo C, Siwale M, Mandaliya K, Conradie
F, Botes ME, Wellington M, Osibogun A, Sigaloff KCE, Nankya I, Schuurman R, Wit FW, Stevens W, van Vugt M, Rinke de Wit TF. 2011. HIV-1 drug resistance among antiretroviral-naive individuals in sub-Saharan Africa after rollout of antiretroviral therapy: multicentre observational study. Lancet Infect Dis 11:750-759.
53. Price MA, Wallis CL, Lakhi S, Karita E, Kamali A, Anzala O, Sanders EJ, Bekker LG, Twesigye R, Hunter E, Kaleebu P, Kayitenkore K, Allen S, Ruzagira E, Mwangome M, Mutua G, Amornkul PN, Stevens G, Pond SL, Schaefer M, Papathanasopoulos MA, Stevens W, Gilmour J. 2011. Transmitted HIV type 1 drug resistance among individuals with recent HIV infection in East and Southern Africa. AIDS Res Hum Retroviruses 27:5-12.
54. Deeks SG, Barbour JD, Grant RM, Martin JN. 2002. Duration and predictors of CD4 T-cell gains in patients who continue combination therapy despite detectable plasma viremia. Aids 16:201-207.
55. Pantaleo G, Graziosi C, Fauci AS. 1993. New concepts in the
immunopathogenesis of human immunodeficiency virus infection. N Engl J Med 328:327-335.
56. 2012. Panel on Antiretroviral Guidelines for Adults and Adolescents. Guidelines for the use of antiretroviral agents in HIV-1-infected adults and adolescents. Department of Health and Human Services. 1-239. Available from: <http://www.aidsinfo.nih.gov/ContentFiles/AdultandAdolescentGL. pdf>.
57. Mee P, Fielding KL, Charalambous S, Churchyard GJ, Grant AD. 2008.
Evaluation of the WHO criteria for antiretroviral treatment failure among adults in South Africa. Aids 22:1971-1977.
58. Moore DM, Awor A, Downing R, Kaplan J, Montaner JS, Hancock J,
Were W, Mermin J. 2008. CD4+ T-cell count monitoring does not accurately identify HIV-infected adults with virologic failure receiving antiretroviral therapy. J Acquir Immune Defic Syndr 49:477-484.
59. Reynolds SJ, Nakigozi G, Newell K, Ndyanabo A, Galiwongo R, Boaz I, Quinn TC, Gray R, Wawer M, Serwadda D. 2009. Failure of immunologic criteria to appropriately identify antiretroviral treatment failure in Uganda. Aids 23:697-700.
60. Sigaloff KC, Hamers RL, Wallis CL, Kityo C, Siwale M, Ive P, Botes
ME, Mandaliya K, Wellington M, Osibogun A, Stevens WS, van Vugt M, de Wit TF. 2011. Unnecessary antiretroviral treatment switches and accumulation of HIV resistance mutations; two arguments for viral load monitoring in Africa. J Acquir Immune Defic Syndr 58:23-31.
61. van Oosterhout JJ, Brown L, Weigel R, Kumwenda JJ, Mzinganjira
D, Saukila N, Mhango B, Hartung T, Phiri S, Hosseinipour MC. 2009. Diagnosis of antiretroviral therapy failure in Malawi: poor performance of clinical and immunological WHO criteria. Trop Med Int Health 14:856-861. 62. Gupta RK, Jordan MR, Sultan BJ, Hill A, Davis DH, Gregson J, Sawyer
AW, Hamers RL, Ndembi N, Pillay D, Bertagnolio S. 2012. Global trends in antiretroviral resistance in treatment-naive individuals with HIV after rollout of antiretroviral treatment in resource-limited settings: a global collaborative
General introduction
|
331
study and meta-regression analysis. Lancet 380:1250-1258.
63. Hamers RL, Smit PW, Stevens W, Schuurman R, Rinke de Wit TF. 2009.
Dried fluid spots for HIV type-1 viral load and resistance genotyping: a systematic review. Antivir Ther 14:619-629.
64. Bertagnolio S, Soto-Ramirez L, Pilon R, Rodriguez R, Viveros M,
Fuentes L, Harrigan PR, Mo T, Sutherland D, Sandstrom P. 2007. HIV-1 drug resistance surveillance using dried whole blood spots. Antivir Ther 12:107-113.
65. Harrigan PR, Stone C, Griffin P, Najera I, Bloor S, Kemp S, Tisdale M, Larder B. 2000. Resistance profile of the human immunodeficiency virus type 1 reverse transcriptase inhibitor abacavir (1592U89) after monotherapy and combination therapy. CNA2001 Investigative Group. J Infect Dis 181:912-920.
66. Hawkins CA, Chaplin B, Idoko J, Ekong E, Adewole I, Gashau W, Murphy RL, Kanki P. 2009. Clinical and genotypic findings in HIV-infected patients with the K65R mutation failing first-line antiretroviral therapy in Nigeria. J Acquir Immune Defic Syndr 52:228-234.
67. Svarovskaia ES, Margot NA, Bae AS, Waters JM, Goodman D, Zhong
L, Borroto-Esoda K, Miller MD. 2007. Low-level K65R mutation in HIV-1 reverse transcriptase of treatment-experienced patients exposed to abacavir or didanosine. J Acquir Immune Defic Syndr 46:174-180.
68. Wallis CL, Mellors JW, Venter WD, Sanne I, Stevens W. 2010. Varied
patterns of HIV-1 drug resistance on failing first-line antiretroviral therapy in South Africa. J Acquir Immune Defic Syndr 53:480-484.
69. Winters MA, Shafer RW, Jellinger RA, Mamtora G, Gingeras T, Merigan TC. 1997. Human immunodeficiency virus type 1 reverse transcriptase genotype and drug susceptibility changes in infected individuals receiving dideoxyinosine monotherapy for 1 to 2 years. Antimicrob Agents Chemother 41:757-762.
70. Brenner B, Turner D, Oliveira M, Moisi D, Detorio M, Carobene M,
Marlink RG, Schapiro J, Roger M, Wainberg MA. 2003. A V106M mutation in HIV-1 clade C viruses exposed to efavirenz confers cross-resistance to non-nucleoside reverse transcriptase inhibitors. Aids 17:F1-5.
71. Grossman Z, Istomin V, Averbuch D, Lorber M, Risenberg K, Levi I,
variation at NNRTI resistance-associated positions in patients infected with HIV-1 subtype C. Aids 18:909-915.
72. Barth RE, van der Loeff MF, Schuurman R, Hoepelman AI, Wensing
AM. 2010. Virological follow-up of adult patients in antiretroviral treatment programmes in sub-Saharan Africa: a systematic review. Lancet Infect Dis 10:155-166.
