Non-B variants of HIV-1 in San Francisco, California

O’Keefe, Kara J.; Pipkin, Sharon; Fatch, Robin; Scheer, Susan; Liegler, Teri; McFarland, Willi; Grant, Robert M.; Truong, Hong‐Ha M.

doi:10.1016/j.meegid.2020.104677

Cited by 2 publications

(2 citation statements)

References 42 publications

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“…Our results among blood donors are consistent with the known epidemiology and genetic diversity of HIV infections reported in specific areas of the country. For example, our findings parallel those recently reported for San Francisco, California, where non-B and CRF variants remain a small proportion (3%) of all HIV [ 21 ]. In addition, among HIV subtype B, we found evidence of strong HIV genetic similarity within small clusters of specific demographic groups.…”

Section: Discussionsupporting

confidence: 91%

HIV Subtypes and Drug-resistance-associated Mutations in US Blood Donors, 2015–2020

Custer,

Altan,

Montalvo

et al. 2024

Open Forum Infectious Diseases

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Background Monitoring genotypes of HIV infections in blood donors may provide insights into infection trends in the general population. Methods HIV RNA was extracted from plasma samples of blood donors confirmed as HIV-positive by blood screening nucleic acid and antibody tests. HIV genome target regions were amplified using nested real time-polymerase chain reaction followed by next generation sequencing. Sequences were compared to those in the Los Alamos National Laboratory (LANL) database. Sequences were also assessed for drug resistance mutations (DRM) using the Stanford HIV DRM Database. Results From available HIV-positive donations collected between September 1, 2015, and December 31, 2020, 563 of 743 (75.8%) were successfully sequenced; 4 were subtype A, 543 subtype B, 5 subtype C, 1 subtype G, 5 circulating recombinant forms (CRF), and 2 were subtype B and D recombinants. Overall, no significant differences between blood donor and available LANL genotypes were found, and the genotypes of newly acquired versus prevalent HIV infections in donors were similar. The proportion of non-B subtypes and CRF remained a small fraction, with no other subtype or CRF representing more than 1% of the total. DRM were identified in 122 (21.6%) samples with protease inhibitor, nucleoside reverse transcriptase inhibitor (NRTI) and non-NRTI DRMs identified in 4.9, 4.6 and 14.0% of samples, respectively. Conclusions HIV genetic diversity and DRM in blood donors appear representative of circulating HIV infections in the US general population and may provide more information on infection diversity than sequences reported to LANL, particularly for recently transmitted infections.

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Section: Discussionsupporting

confidence: 91%

HIV Subtypes and Drug-resistance-associated Mutations in US Blood Donors, 2015–2020

Custer,

Altan,

Montalvo

et al. 2024

Open Forum Infectious Diseases

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“…Identifying and Selecting Clusters. The parameters used for identifying transmission clusters have been described previously (O'Keefe et al, 2021;Truong et al, 2015). In brief, HIV transmission cluster membership was based on full protease and partial reverse transcriptase sequences.…”

Section: Overviewmentioning

confidence: 99%

Integrating Phylogenetic Biomarker Data and Qualitative Approaches: An Example of HIV Transmission Clusters as a Sampling Frame for Semistructured Interviews and Implications for the COVID-19 Era

Hughes

Woods

O’Keefe

et al. 2021

Journal of Mixed Methods Research

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Mixed methods studies of human disease that combine surveillance, biomarker, and qualitative data can help elucidate what drives epidemiological trends. Viral genetic data are rarely coupled with other types of data due to legal and ethical concerns about patient privacy. We developed a novel approach to integrate phylogenetic and qualitative methods in order to better target HIV prevention efforts. The overall aim of our mixed methods study was to characterize HIV transmission clusters. We combined surveillance data with HIV genomic data to identify cases whose viruses share enough similarities to suggest a recent common source of infection or participation in linked transmission chains. Cases were recruited through a multi-phase process to obtain consent for recruitment to semi-structured interviews. Through linkage of viral genetic sequences with epidemiological data, we identified individuals in large transmission clusters, which then served as a sampling frame for the interviews. In this article, we describe the multi-phase process and the limitations and challenges encountered. Our approach contributes to the mixed methods research field by demonstrating that phylogenetic analysis and surveillance data can be harnessed to generate a sampling frame for subsequent qualitative data collection, using an explanatory sequential design. The process we developed also respected protections of patient confidentiality. The novel method we devised may offer an opportunity to implement a sampling frame that allows for the recruitment and interview of individuals in high-transmission clusters to better understand what contributes to spread of other infectious diseases, including COVID-19.

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Non-B variants of HIV-1 in San Francisco, California

Cited by 2 publications

References 42 publications

HIV Subtypes and Drug-resistance-associated Mutations in US Blood Donors, 2015–2020

HIV Subtypes and Drug-resistance-associated Mutations in US Blood Donors, 2015–2020

Integrating Phylogenetic Biomarker Data and Qualitative Approaches: An Example of HIV Transmission Clusters as a Sampling Frame for Semistructured Interviews and Implications for the COVID-19 Era

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