Near Real-Time Identification of Recent Human Immunodeficiency Virus Transmissions, Transmitted Drug Resistance Mutations, and Transmission Networks by Multiplexed Primer ID-Next-Generation Sequencing in North Carolina.
drug resistance mutations
next-generation sequencing
recency
transmission network
Journal
The Journal of infectious diseases
ISSN: 1537-6613
Titre abrégé: J Infect Dis
Pays: United States
ID NLM: 0413675
Informations de publication
Date de publication:
03 03 2021
03 03 2021
Historique:
received:
03
04
2020
accepted:
13
07
2020
pubmed:
15
7
2020
medline:
2
2
2022
entrez:
15
7
2020
Statut:
ppublish
Résumé
The identification of recent human immunodeficiency virus (HIV) 1 infections among people with new HIV diagnoses is important to both tailoring and assessing the impact of HIV-1 prevention strategies. We developed a multiplexed Primer ID-next-generation sequencing approach to identify recent infections by measuring the intrahost viral diversity over multiple regions of the HIV-1 genome, in addition to detecting drug resistance mutations (DRMs) and phylogenetically linked clusters. We summarize the field implementation of this all-in-one platform among persons with newly diagnosed HIV-1 by the North Carolina State Laboratory of Public Health in 2018. Overall, recent infection was identified in 94 (35%) of 268 patients with new HIV diagnoses. People <30 years old, and people who inject drugs were more likely to have diagnoses of recent infection. The reverse-transcriptase region K103N was the most commonly detected DRM (prevalence, approximately 15%). We found a total of 28 clusters, and persons with recent infection were more likely to be cluster members than were those with chronic infections (P = .03). We demonstrate the rapid identification of recent infection and pretreatment DRMs coupled with cluster analysis that will allow prioritization of linkage to care, treatment, and prevention interventions to those at highest risk of onward transmission.
Sections du résumé
BACKGROUND
The identification of recent human immunodeficiency virus (HIV) 1 infections among people with new HIV diagnoses is important to both tailoring and assessing the impact of HIV-1 prevention strategies.
METHODS
We developed a multiplexed Primer ID-next-generation sequencing approach to identify recent infections by measuring the intrahost viral diversity over multiple regions of the HIV-1 genome, in addition to detecting drug resistance mutations (DRMs) and phylogenetically linked clusters. We summarize the field implementation of this all-in-one platform among persons with newly diagnosed HIV-1 by the North Carolina State Laboratory of Public Health in 2018.
RESULTS
Overall, recent infection was identified in 94 (35%) of 268 patients with new HIV diagnoses. People <30 years old, and people who inject drugs were more likely to have diagnoses of recent infection. The reverse-transcriptase region K103N was the most commonly detected DRM (prevalence, approximately 15%). We found a total of 28 clusters, and persons with recent infection were more likely to be cluster members than were those with chronic infections (P = .03).
CONCLUSIONS
We demonstrate the rapid identification of recent infection and pretreatment DRMs coupled with cluster analysis that will allow prioritization of linkage to care, treatment, and prevention interventions to those at highest risk of onward transmission.
Identifiants
pubmed: 32663847
pii: 5871442
doi: 10.1093/infdis/jiaa417
pmc: PMC7938176
doi:
Substances chimiques
Anti-HIV Agents
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
876-884Subventions
Organisme : NIAID NIH HHS
ID : P30 AI050410
Pays : United States
Organisme : NIAID NIH HHS
ID : R01 AI135970
Pays : United States
Organisme : NIAID NIH HHS
ID : R01 AI140970
Pays : United States
Informations de copyright
© The Author(s) 2020. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.
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