A Generalized Entropy Measure of Within-Host Viral Diversity for Identifying Recent HIV-1 Infections.
There is a need for incidence assays that accurately estimate HIV incidence based on cross-sectional specimens. Viral diversity-based assays have shown promises but are not particularly accurate. We hypothesize that certain viral genetic regions are more predictive of recent infection than others an...
| Publicado en: | Medicine Vol. 94; no. 42; pp. 1 - 9 |
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| Autores principales: | , , , , , |
| Formato: | Journal Article |
| Publicado: |
Lippincott Williams & Wilkins
Oct2015
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=110664561&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 110664561 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00257974 2S6 jtl: Medicine issn: 00257974 maglogo: N pubinfo: dt: Oct2015 vid: 94 iid: 42 pid: 433 pub: Lippincott Williams & Wilkins place: Baltimore, Maryland artinfo: ui: 110664561 110664561 NLM26496342 10.1097/MD.0000000000001865 NLM26496342 PMC4620842 110664561 ppf: 1 ppct: 8 formats: tig: atl: A Generalized Entropy Measure of Within-Host Viral Diversity for Identifying Recent HIV-1 Infections. aug: au: Wei Wu, Julia Patterson-Lomba, Oscar Novitsky, Vladimir Pagano, Marcello Wei, Julia Wu Wu, Julia Wei affil: Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA sug: subj: HIV Infections Physics HIV-1 HIV-1 Classification Adult Cross Sectional Studies Female Male Adult: 19-44 years Female Male ab: There is a need for incidence assays that accurately estimate HIV incidence based on cross-sectional specimens. Viral diversity-based assays have shown promises but are not particularly accurate. We hypothesize that certain viral genetic regions are more predictive of recent infection than others and aim to improve assay accuracy by using classification algorithms that focus on highly informative regions (HIRs).We analyzed HIV gag sequences from a cohort in Botswana. Forty-two subjects newly infected by HIV-1 Subtype C were followed through 500 days post-seroconversion. Using sliding window analysis, we screened for genetic regions within gag that best differentiate recent versus chronic infections. We used both nonparametric and parametric approaches to evaluate the discriminatory abilities of sequence regions. Segmented Shannon Entropy measures of HIRs were aggregated to develop generalized entropy measures to improve prediction of recency. Using logistic regression as the basis for our classification algorithm, we evaluated the predictive power of these novel biomarkers and compared them with recently reported viral diversity measures using area under the curve (AUC) analysis.Change of diversity over time varied across different sequence regions within gag. We identified the top 50% of the most informative regions by both nonparametric and parametric approaches. In both cases, HIRs were in more variable regions of gag and less likely in the p24 coding region. Entropy measures based on HIRs outperformed previously reported viral-diversity-based biomarkers. These methods are better suited for population-level estimation of HIV recency.The patterns of diversification of certain regions within the gag gene are more predictive of recency of infection than others. We expect this result to apply in other HIV genetic regions as well. Focusing on these informative regions, our generalized entropy measure of viral diversity demonstrates the potential for improving accuracy when identifying recent HIV-1 infections. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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