Evidence map›Paper›PMID 40706602›Full record

ArticleThe Lancet. Microbe2025

Characterisation of a persistent SARS-CoV-2 infection lasting more than 750 days in a person living with HIV: a genomic analysis.

Joseline M Velasquez-Reyes, Beau Schaeffer, Scott R Curry, Victoria Overbeck, Cole Sher-Jan, Bradford P Taylor, Jacquelyn Turcinovic, Krutika Kuppalli, John H Connor, William P Hanage

Abstract read
In one paragraph

Article in The Lancet. Microbe, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Joseline M Velasquez-ReyesProgram in Bioinformatics, Boston University, Boston, MA, USA; Department of Virology, Immunology, and Microbiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA; National Emerging Infectious Diseases Laboratories, Boston University, Boston, MA, USA.
Beau SchaefferCenter for Communicable Disease Dynamics, Department of Epidemiology, Harvard T H Chan School of Public Health, Boston, MA, USA.
Scott R CurryDivision of Infectious Diseases, Department of Medicine, Medical University of South Carolina, Charleston, SC, USA.
Victoria OverbeckDepartment of Epidemiology, Boston University School of Public Health, Boston, MA, USA; Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
Cole Sher-JanDepartment of Virology, Immunology, and Microbiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA; National Emerging Infectious Diseases Laboratories, Boston University, Boston, MA, USA.
Bradford P TaylorCenter for Communicable Disease Dynamics, Department of Epidemiology, Harvard T H Chan School of Public Health, Boston, MA, USA.
Jacquelyn TurcinovicProgram in Bioinformatics, Boston University, Boston, MA, USA; Department of Virology, Immunology, and Microbiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA; National Emerging Infectious Diseases Laboratories, Boston University, Boston, MA, USA.
Krutika KuppalliDepartment of Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA; O'Donnell School of Public Health, University of Texas Southwestern Medical Center, Dallas, TX, USA.
John H ConnorProgram in Bioinformatics, Boston University, Boston, MA, USA; Department of Virology, Immunology, and Microbiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA; National Emerging Infectious Diseases Laboratories, Boston University, Boston, MA, USA.
William P HanageCenter for Communicable Disease Dynamics, Department of Epidemiology, Harvard T H Chan School of Public Health, Boston, MA, USA. Electronic address: whanage@hsph.harvard.edu.

Funding

ChimeraX -- Next Generation Visualization and Analysis Software for Multiscale ModelingR01GM129325 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI FERRIN, THOMAS E · 2018 to 2025
$5.2M
Deep sequencing of pathogens to precisely define transmission networks using rare variantsR01AI128344 · NIAID · HARVARD SCHOOL OF PUBLIC HEALTH · PI HANAGE, WILLIAM · 2017 to 2021
$3.4M
Predoctoral Training in Bioinformatics and Computational BiologyT32GM100842 · NIGMS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI TULLIUS, THOMAS D · 2012 to 2022
$2.8M
CDC HHS HHSD200201691779INCEZID CDC HHS NU50CK000629NIAID NIH HHS R01 AI128344NIGMS NIH HHS R01 GM129325NIGMS NIH HHS T32 GM100842
6 · The paper itself

Abstract

backgroundPeople who are immunocompromised can develop persistent SARS-CoV-2 infections. Several viral mutations accumulated during the course of such persistent infections have also been observed in prominent variants of concern (VOCs). Here, we characterise persistent infection and viral evolution of SARS-CoV-2 lasting more than 750 days in a person with advanced HIV-1 infection.

methodsBetween March, 2021, and July, 2022, eight clinical specimens were collected from a person living with HIV, neither receiving antiretroviral therapy nor virally suppressed, and presumed to have been initially infected with SARS-CoV-2 in mid-May, 2020. Viral RNA was extracted from each swab and an amplicon-based sequencing approach was used for genomic analysis of SARS-CoV-2. Variable sites were characterised at the consensus and subconsensus levels, and phylogenetic tools were applied to analyse viral evolution. Publicly available SARS-CoV-2 sequences from GenBank were leveraged to contextualise our sequenced samples and identify any potential evidence of transmission.

findingsGenomes formed a monophyletic cluster in the B.1 lineage. 68 consensus and 67 subconsensus single nucleotide variants were observed over the course of infection. The intrahost clock rate remained similar to that of the interhost rate in contemporaneous community sequences (6·74 × 10

interpretationConvergent SARS-CoV-2 evolution, both in and outside the spike protein, observed in this study suggests parallels with the evolutionary process leading to emergence of the omicron VOC. The inferred absence of onward infections might indicate a loss of transmissibility during adaptation to a single host. Our results underscore the importance of appropriate treatment to cure persistent SARS-CoV-2 infections and monitoring them to understand how mutations contribute to viral adaptation.

fundingNational Institute of General Medical Sciences of the National Institutes of Health, Centers for Disease Control and Prevention, the National Institute of Allergy and Infectious Diseases, MassCPR, and Morris Singer Foundation.

Indexed as

COVID-19HIV InfectionsPersistent InfectionSARS-CoV-2Evolution, MolecularFemaleGenome, ViralGenomicsHumansMaleMiddle AgedMutationPhylogenyRNA, ViralRNA, Viral

Identifiers

PMID40706602
PMCPMC12633830

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.