Department of Pathology, Immunology, and Laboratory Medicine and Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA.
Received 5 January, 2011
Accepted 1 February, 2011
Correspondence to Marco Salemi, PhD, Department of Pathology, University of Florida School of Medicine, University of Florida, Gainesville, FL, USA. E-mail: firstname.lastname@example.org
Development of a vaccine that may significantly slow down the global HIV-1 epidemic is hindered, in large part, by the extensive genetic heterogeneity of the virus caused by lack of proofreading activity of the reverse transcriptase, coupled with high replication and recombination rate. Any effective large-scale immunization strategy will depend on the availability of robust molecular epidemiology data on HIV-1 subtype distribution. The work of Hemelaar et al. , which analyzed an impressive dataset of 65 913 samples from HIV-1-infected patients in 109 countries during 2000–2007, is a significant step forward in this direction.
The distribution of HIV-1 subtypes is usually inferred from meta-analysis of existing literature, an approach often hampered by publication bias and lack of standardization , as Hemelaar et al. rightly note. In contrast, the authors of the new study combined a thorough survey of the literature with subtype statistics from the WHO–UNAIDS Network for HIV Isolation and Characterisation. Moreover, their analysis took into account UNAIDS/WHO estimates of the average number of HIV-1 infections by country during 2000–2003 and 2004–2007 [3,4]. The result is a detailed series of maps (available in full in the supplemental data files of the paper) showing the worldwide prevalence of the nine HIV-1 subtypes, the three major circulating recombinant forms (CRF01_AE, CRF01_AG and CRF01_AB), as well as other CRFs and unique recombinant forms (URFs).
The Hemelaar et al. survey confirmed that HIV-1 is not a uniform pandemic but is characterized by a strong spatial structure more accurately described as a collection of regional epidemics with specific subtype distributions and dynamics. In agreement with previous reports, the authors found that subtype C is the most prevalent worldwide, accounting for almost half of the infections, followed by subtypes A and B and CFR02-AG.
Interestingly, the comparison of 2004–2007 data with the ones from the preceding 4 years showed that although global subtype distribution remained very similar overall, the number of infections caused by CRFs increased by at least 50%. In particular, CRF02_AG infections jumped from 5 to 8%, representing 900 000 additional cases. However, because subtyping is all too often based only on partial genome sequences, a systematic generation of full-genome data, which could be enhanced by pyrosequencing techniques in the near future, will be necessary to assess the actual spread of CRFs. In addition, the authors caution that their results are based on cross-sectional studies and estimates of people living with the virus, rather than new infections. Therefore, the observed trends may substantially predate the time interval under investigation. Such concerns highlight the urgent need to investigate subtype incidence in different geographic areas.
The recent clinical trials of ALVAC and AIDSVAX have renewed hope in the possibility to develop an actual HIV-1 vaccine [5,6], although it is still controversial whether a single vaccine protecting against the major subtypes and CRFs is in fact possible. It seems more plausible that region-specific vaccines will be required to protect populations infected by viral strains circulating in discrete geographic areas. The data of Hemelaar et al. underline the dynamic nature of the HIV-1 epidemic. If a successful vaccine against one or more subtype will be developed, the population immunized against the dominant subtypes may become a niche of susceptible hosts among which emergent CRFs or URFs, fostered by positive selection, could rapidly spread giving rise to entirely new epidemic waves.
Apart from the impact on vaccination strategies, building research programs to monitor subtype incidence and prevalence can provide important clues to the longstanding, and only partially answered, questions about whether specific subtypes are associated with different transmission rates and/or disease progression [7–9]. Moreover, even in the era of HAART, the occurrence of AIDS-related neurological disorders seems to be increasing in infected patients [10,11], and it is still unclear how different HIV-1 subtypes affect the development of HIV-associated dementia (HAD) . A robust and continuous monitoring of viral subtypes and HAD prevalence and incidence in different countries is essential for providing the necessary knowledge base to address this issue.
The molecular epidemiology of HIV-1 subtypes could also shed light on the evolutionary and population dynamics of the virus. The temporal and geographic origins of HIV-1 Group M have been well characterized [13–15] but the reasons for the uneven distribution of subtypes and prevalence rates remain unresolved. Recently, the use of phylogenetic and geographic information data has shown great potential in explaining the early spread of HIV-1 in east Africa . Such studies could benefit considerably from reliable data on country-specific subtype distributions.
As Hemelaar et al. poignantly remarked in their conclusion, an improved and continuous global monitoring of HIV-1 genetic diversity has to be a major focus of twenty-first century molecular epidemiology. This will only happen through adequate investment of funds for national surveys based on statistically sound criteria, conducted as part of a highly coordinated worldwide effort.
1. Hemelaar J, Gouws E, Ghys PD, Osmanov S, WHO-AIDS Network for HIV Isolation and Characterisation. Global trends in molecular epidemiology of HIV-1 during 2000–2007. AIDS
2. Arien KK, Vanham G, Arts EJ. Is HIV-1 evolving to a less virulent form in humans? Nat Rev Microbiol 2007; 5:141–151.
3. Brown T, Salomon JA, Alkema L, Raftery AE, Gouws E. Progress and challenges in modelling country-level HIV/AIDS epidemics: the UNAIDS Estimation and Projection Package 2007. Sex Transm Infect 2008; 84(Suppl 1):i5–i10.
4. Stover J, Johnson P, Zaba B, Zwahlen M, Dabis F, Ekpini RE. The Spectrum projection package: improvements in estimating mortality, ART needs, PMTCT impact and uncertainty bounds. Sex Transm Infect 2008; 84(Suppl 1):i24–i30.
5. Rerks-Ngarm S, Pitisuttithum P, Nitayaphan S, Kaewkungwal J, Chiu J, Paris R, et al
. Vaccination with ALVAC and AIDSVAX to prevent HIV-1 infection in Thailand. N Engl J Med 2009; 361:2209–2220.
6. Bansal GP, Malaspina A, Flores J. Future paths for HIV vaccine research: exploiting results from recent clinical trials and current scientific advances. Curr Opin Mol Ther 2010; 12:39–46.
7. Lutalo T, Gray RH, Wawer M, Sewankambo N, Serwadda D, Laeyendecker O, et al
. Survival of HIV-infected treatment-naive individuals with documented dates of seroconversion in Rakai, Uganda. AIDS 2007; 21(Suppl 6):S15–S19.
8. Vasan A, Renjifo B, Hertzmark E, Chaplin B, Msamanga G, Essex M, et al
. Different rates of disease progression of HIV type 1 infection in Tanzania based on infecting subtype. Clin Infect Dis 2006; 42:843–852.
9. Kiwanuka N, Laeyendecker O, Quinn TC, Wawer MJ, Shepherd J, Robb M, et al
. HIV-1 subtypes and differences in heterosexual HIV transmission among HIV-discordant couples in Rakai, Uganda. AIDS 2009; 23:2479–2484.
10. Anthony I, Ramage S, Carnie F, Simmonds P, Bell J. Influence of HAART on HIV-related CNS disease and neuroinflammation. J Neuropathol Exp Neurol 2005; 64:529–536.
11. Bell J. An update on the neuropathology of HIV in the HAART era. Histopathology 2004; 45:549–559.
12. Liner KJ 2nd, Hall CD, Robertson KR. Impact of human immunodeficiency virus (HIV) subtypes on HIV-associated neurological disease. J Neurovirol 2007; 13:291–304.
13. Korber B, Muldoon M, Theiler J, Gao F, Gupta R, Lapedes A, et al
. Timing the ancestor of the HIV-1 pandemic strains. Science 2000; 288:1789–1796.
14. Salemi M, Strimmer K, Hall WW, Duffy M, Delaporte E, Mboup S, et al
. Dating the common ancestor of SIVcpz and HIV-1 group M and the origin of HIV-1 subtypes using a new method to uncover clock-like molecular evolution. FASEB J 2001; 15:276–278.
15. Worobey M, Gemmel M, Teuwen DE, Haselkorn T, Kunstman K, Bunce M, et al
. Direct evidence of extensive diversity of HIV-1 in Kinshasa by 1960. Nature 2008; 455:661–664.
16. Gray RR, Tatem AJ, Lamers SL, Hou W, Laeyendecker O, Serwadda D, et al
. Spatial phylodynamics of HIV-1 epidemic emergence in east Africa. AIDS 2009; 23:F9–F17.