HIV-1C in-House RNA-Based Genotyping Assay for Detection of Drug Resistance Mutations in Samples with Low-Level Viral Loads.

HIV-1C drug resistance testing in-house genotyping low-level viremia samples

Journal

Infection and drug resistance
ISSN: 1178-6973
Titre abrégé: Infect Drug Resist
Pays: New Zealand
ID NLM: 101550216

Informations de publication

Date de publication:
2022
Historique:
received: 19 09 2022
accepted: 08 11 2022
entrez: 30 12 2022
pubmed: 31 12 2022
medline: 31 12 2022
Statut: epublish

Résumé

Monitoring HIV-1 drug resistance mutations (DRM) in treated patients on combination antiretroviral therapy (cART) with a detectable HIV-1 viral load (VL) is important for the selection of appropriate cART. Currently, there is limited data on HIV DRM at low-level viremia (LLV) (VL 401-999 copies/mL) due to the use of a threshold of VL ≥1000 copies/mL for HIV DRM testing. We here assess the performance of an in-house HIV drug resistance genotyping assay using plasma for the detection of DRM at LLV. We used a total of 96 HIV plasma samples from the population-based Botswana Combination Prevention Project (BCPP). The samples were stratified by VL groups: 50 samples had LLV, defined as 401-999 copies/mL, and 46 had ≥1000 copies/mL. HIV pol (PR and RT) region was amplified and sequenced using an in-house genotyping assay with BigDye sequencing chemistry. Known HIV DRMs were identified using the Stanford HIV Drug Resistance Database. Genotyping success rate between the two groups was estimated and compared using the comparison of proportions test. The overall genotyping success rate was 79% (76/96). For VL groups, the genotyping success was 72% (36/50) at LLV and 87% (40/46) at VL ≥1000 copies/mL. Among generated sequences, the overall prevalence of individuals with at least 1 major or intermediate-associated DRM was 24% (18/76). The proportions of NNRTI-, NRTI- and PI-associated resistance mutations were 28%, 24%, and 0%, respectively. The most predominant mutations detected were K103N (18%) and M184V (12%) in NNRTI- and NRTI-associated mutations, respectively. The prevalence of DRM was 17% (6/36) at LLV and 30% (12/40) at VL ≥1000 copies/mL. The in-house HIV genotyping assay successfully genotyped 72% of LLV samples and was able to detect 17% of DRM amongst them. Our results highlight the possibility and clinical significance of genotyping HIV among individuals with LLV.

Identifiants

pubmed: 36582452
doi: 10.2147/IDR.S388816
pii: 388816
pmc: PMC9792565
doi:

Types de publication

Journal Article

Langues

eng

Pagination

7565-7576

Subventions

Organisme : FIC NIH HHS
ID : K43 TW012350
Pays : United States
Organisme : Bill & Melinda Gates Foundation
ID : INV-033558
Pays : United States
Organisme : CGH CDC HHS
ID : U01 GH000447
Pays : United States
Organisme : NHGRI NIH HHS
ID : U41 HG006941
Pays : United States
Organisme : FIC NIH HHS
ID : D43 TW009610
Pays : United States
Organisme : CGH CDC HHS
ID : U2G GH001911
Pays : United States

Informations de copyright

© 2022 Bareng et al.

Déclaration de conflit d'intérêts

The authors report no conflicts of interest in relation to this work.

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Auteurs

Ontlametse T Bareng (OT)

Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana.
School of Allied Health Professions, Faculty of Health Sciences, University of Botswana, Gaborone, Botswana.

Wonderful T Choga (WT)

Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana.
School of Allied Health Professions, Faculty of Health Sciences, University of Botswana, Gaborone, Botswana.

Segomotso T Maphorisa (ST)

Ministry of Health and Wellness, Republic of Botswana, Gaborone, Botswana.

Sekgabo Seselamarumo (S)

Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana.

Kaelo K Seatla (KK)

Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana.

Patrick T Mokgethi (PT)

Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana.
Department of Biological Sciences, Faculty of Science, University of Botswana, Gaborone, Botswana.

Dorcas Maruapula (D)

Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana.
Department of Biological Sciences, Faculty of Science, University of Botswana, Gaborone, Botswana.

Mompati L Mogwele (ML)

Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana.

Doreen Ditshwanelo (D)

Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana.
Department of Biological Science and Biotechnology, Botswana International University of Science and Technology, Palapye, Botswana.

Natasha O Moraka (NO)

Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana.

Irene Gobe (I)

School of Allied Health Professions, Faculty of Health Sciences, University of Botswana, Gaborone, Botswana.

Modisa S Motswaledi (MS)

School of Allied Health Professions, Faculty of Health Sciences, University of Botswana, Gaborone, Botswana.

Joseph M Makhema (JM)

Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana.
Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Rosemary Musonda (R)

Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana.

Roger Shapiro (R)

Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana.
Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Max Essex (M)

Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana.
Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Vlad Novitsky (V)

Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana.

Sikhulile Moyo (S)

Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana.
School of Allied Health Professions, Faculty of Health Sciences, University of Botswana, Gaborone, Botswana.
Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Simani Gaseitsiwe (S)

Botswana Harvard AIDS Institute Partnership, Gaborone, Botswana.
Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA.

Classifications MeSH