HIV-1 pol gene variation is sufficient for reconstruction of transmissions in the era of antiretroviral therapy

Hué, Stéphane; Clewley, Jonathan P.; Cane, Patricia A.; Pillay, Deenan

doi:10.1097/00002030-200403260-00002

Cited by 195 publications

(124 citation statements)

References 29 publications

Supporting

Mentioning

116

Contrasting

Unclassified

Order By: Relevance

“…Clearly, the optimal threshold for detecting clusters defined here of 5.3% may not be appropriate for all datasets, for example, the pol region, which is used by many studies for drug resistance screening and public health surveillance. On the other hand, pol and env have been shown to produce identical phylogenetic clustering patterns with similar statistical support, 1,25 suggesting that branch support thresholds are consistent across genes. Our data were collected from stable epidemic in Uganda in which genetic diversity has accumulated over time, whereas other clustering studies have examined more recent and localized HIV outbreaks 6,26,27 or epidemics 10 in which less diversity is present.…”

Section: Identifying Transmission Clustersmentioning

confidence: 99%

“…We refer to the couples and individuals collectively as ''pairs.' ' We also created two additional unlinked datasets by randomly shuffling the couples in dataset (1), and the individuals in dataset (2), while maintaining the same HIV subtype. The goal was to establish genetic distance threshold cut off values that best distinguish unrelated from related sequences.…”

Section: Hiv-1 Sequence Datasetsmentioning

confidence: 99%

“…[1][2][3][4][5][6] The identification of transmission clusters can support epidemiologically linked transmission events, 7 identify putative transmission chains, 8 and reveal mixing between key risk groups and geographic subpopulations. 9 Transmission clusters of HIV infections are typically defined using either genetic distances among sequences 4 or genetic distances in addition to branch support values (e.g., bootstrap values).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Identifying Transmission Clusters with Cluster Picker and HIV-TRACE

Rose¹,

Lamers²,

Dollar³

et al. 2017

AIDS Research and Human Retroviruses

View full text Add to dashboard Cite

We compared the behavior of two approaches (Cluster Picker and HIV-TRACE) at varying genetic distances to identify transmission clusters. We used three HIV gp41 sequence datasets originating from the Rakai Community Cohort Study: (1) next-generation sequence (NGS) data from nine linked couples; (2) NGS data from longitudinal sampling of 14 individuals; and (3) Sanger consensus sequences from a cross-sectional dataset (n = 1,022) containing 91 epidemiologically linked heterosexual couples. We calculated the optimal genetic distance threshold to separate linked versus unlinked NGS datasets using a receiver operating curve analysis. We evaluated the number, size, and composition of clusters detected by Cluster Picker and HIV-TRACE at six genetic distance thresholds (1%-5.3%) on all three datasets. We further tested the effect of using all NGS, versus only a single variant for each patient/time point, for datasets (1) and (2). The optimal gp41 genetic distance threshold to distinguish linked and unlinked couples and individuals was 5.3% and 4%, respectively. HIV-TRACE tended to detect larger and fewer clusters, whereas Cluster Picker detected more clusters containing only two sequences. For NGS datasets (1) and (2), HIV-TRACE and Cluster Picker detected all linked pairs at 3% and 4% genetic distances, respectively. However, at 5.3% genetic distance, 20% of couples in dataset (3) did not cluster using either program, and for >1/3 of couples cluster assignment were discordant. We suggest caution in choosing thresholds for clustering analyses in a generalized epidemic.

show abstract

Section: Identifying Transmission Clustersmentioning

confidence: 99%

Section: Hiv-1 Sequence Datasetsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Identifying Transmission Clusters with Cluster Picker and HIV-TRACE

Rose¹,

Lamers²,

Dollar³

et al. 2017

AIDS Research and Human Retroviruses

View full text Add to dashboard Cite

show abstract

“…HIV pol sequences contain enough genetic diversity to reconstruct phylogenetic clusters, 14,33 however, they cannot and do not intend to reflect epidemiologic linkages and do not necessarily indicate direct HIV transmission among its members. Evaluation of transmission clusters within our patient sample demonstrated some clustering, similar to our prior study in 2007.…”

Section: Chan Et Almentioning

confidence: 99%

Short Communication: New HIV Infections at Southern New England Academic Institutions: Implications for Prevention

Chan

Kazi²,

Rana³

et al. 2013

AIDS Research and Human Retroviruses

View full text Add to dashboard Cite

New HIV infections among younger men who have sex with men (MSM) in the United States are escalating. Data on HIV infections in college students are limited. In 2010, three MSM college students presented to our clinic with primary HIV infection (PHI) in a single month. To determine the number of college students among new HIV diagnoses, we reviewed clinical characteristics and molecular epidemiology of HIV-diagnosed individuals from January to December 2010 at the largest HIV clinic in Southern New England. PHI was defined as acute HIV infection or seroconversion within the last 6 months. Of 66 individuals diagnosed with HIV in 2010, 62% were MSM and 17% were academic students (12% college or university, 5% other). Seventy-three percent of students were MSM. Compared to nonstudents, students were more likely to be younger (24 versus 39 years), born in the United States (91% versus 56%), have another sexually transmitted disease (45% versus 11%), and present with PHI (73% versus 16%, all p-values < 0.05). Thirty percent of individuals formed eight transmission clusters including four students. MSM were more likely to be part of clusters. Department of Health contact tracing of cluster participants allowed further identification of epidemiological linkages. Given these high rates of PHI in recently diagnosed students, institutions of higher education should be aware of acute HIV presentation and the need for rapid diagnosis. Prevention strategies should focus on younger MSM, specifically collegeage students who may be at increased risk of HIV infection.

show abstract

“…Owing to rapid errorprone replication, HIV-1 transmitting through a network of individuals acquires a genetic signature allowing the sequences to serve as proxies for epidemiological links among these individuals. 4 While not providing information on routes or direction of transmission, the phylogenetic relationships can be used to infer an association within a transmission chain. Two examples of the insights obtained through HIV phylogenetics in public health are the paradigm that primary HIV infections play a disproportionate role in driving the epidemic, 5 and that drug-resistant HIV is capable of being transmitted and of establishing infection.…”

mentioning

confidence: 99%

The Power and Pitfalls of HIV Phylogenetics in Public Health

Brooks

Sandstrom

2013

Can J Public Health

View full text Add to dashboard Cite

C lassification of living organisms, and the relationship among species, is one of the most enduring pursuits in human beings' efforts to understand their place in the world. Formalized in the early 18 th century by Carl Linnaeus, the phylogeny, or relationship of plant and animals has historically been based upon morphological features. With the advent of rapid and inexpensive DNA sequencing and the development of bioinformatics tools for comparing the genetic sequences from different organisms, we are now in the era of molecular phylogeny. Molecular characterization of both the relationship between species, and among organisms within the same species, has significant implications for public health.Phylogenetic analysis employs the cumulative similarities and weighted polymorphisms found in collections of sequences to build a graphical representation of genetic relatedness. An illustrative example of how a phylogenetic analysis can be shown to infer relationships is presented in Figure 1. Suppose that viral sequences from seven different infected individuals are aligned on the right. One can easily observe that while all seven viruses are identical at the majority of base-pair positions, single nucleotide differences occurring at two positions allow grouping into three phylogenetically related clusters. Each of these monophyletic clusters is in turn linked through an inferred "most recent common ancestors" at the branch points between clusters. In order to accurately resolve the relative relatedness of sequences under investigation, it is critical that care is taken when selecting a suitable set of background sequences for inclusion in the analysis. Similar to the way in which using cats as a reference for comparing different dogs would highlight only the similarities in all canine breeds, using only distantly related reference sequences may cause investigational sequences to appear more highly related. While the basic methods of comparing genetic sequences and quantifying the certainty of the predicted relationships was developed in the 1960s, with the advent of widely available DNA sequencing, ever more sophisticated methods were developed. In the past few years, powerful desktop computers and freely available bioinformatics programs have allowed phylogenetics to become an important tool in increasing our understanding of the epidemiology of infections. 1Application of phylogenetic tools in the context of epidemiology have led to startling revelations and helped to answer and illuminate previously unanswerable questions. The paradigm of the management of TB changed after the publication of an article in the Lancet in 1999.2 It was traditionally assumed that people with TB disease who had no organisms seen on a sputum smear were relatively non-infectious. In this report, Behr and colleagues used DNA fingerprinting on all of the TB cases in San Francisco between 1991 and 1996, to identify clusters of related infections. Through the use of molecular epidemiology, the authors determined that nearly 20% of all TB ...

show abstract

HIV-1 pol gene variation is sufficient for reconstruction of transmissions in the era of antiretroviral therapy

Cited by 195 publications

References 29 publications

Identifying Transmission Clusters with Cluster Picker and HIV-TRACE

Identifying Transmission Clusters with Cluster Picker and HIV-TRACE

Short Communication: New HIV Infections at Southern New England Academic Institutions: Implications for Prevention

The Power and Pitfalls of HIV Phylogenetics in Public Health

Contact Info

Product

Resources

About