Evidence map›Paper›PMID 29253674›Full record

ArticleInfection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases2018

Complex patterns of Hepatitis-C virus longitudinal clustering in a high-risk population.

Rebecca Rose, Susanna L Lamers, Guido Massaccesi, William Osburn, Stuart C Ray, David L Thomas, Andrea L Cox, Oliver Laeyendecker

Abstract read
In one paragraph

Article in Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Molecular source attribution.PLoS computational biology · 2022
    Article
  4. Article
  5. Article
  6. Article
  7. Correlates of hepatitis C viral clustering among people who inject drugs in Baltimore.Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2020
    Article
  8. Article
  9. Article
  10. Inconsistent temporal patterns of genetic variation of HCV among high-risk subjects may impact inference of transmission networks.Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2019
    Article
  11. Article
  12. Article
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

8 authors.

Rebecca RoseBioInfoExperts LLC, Thibodaux, LA, United States.
Susanna L LamersBioInfoExperts LLC, Thibodaux, LA, United States.
Guido MassaccesiDepartment of Medicine, Johns Hopkins University, Baltimore, MD, United States.
William OsburnDepartment of Medicine, Johns Hopkins University, Baltimore, MD, United States.
Stuart C RayDepartment of Medicine, Johns Hopkins University, Baltimore, MD, United States.
David L ThomasDepartment of Medicine, Johns Hopkins University, Baltimore, MD, United States.
Andrea L CoxDepartment of Medicine, Johns Hopkins University, Baltimore, MD, United States.
Oliver LaeyendeckerDepartment of Medicine, Johns Hopkins University, Baltimore, MD, United States; NIAID, NIH, Baltimore, MD, United States. Electronic address: olaeyen1@jhmi.edu.

Funding

LC: HIV Prevention Trials Network - Laboratory Support for the SARS-CoV-2 Seroprevalence Study (CoVPN 5002)UM1AI068613 · NIAID · JOHNS HOPKINS UNIVERSITY · PI SUSAN H ESHLEMAN, Mark A Marzinke · 2011 to 2026
$100.2M
International Studies of the Acquired Immune Deficiency Syndrome (AIDS)ZIAAI000361 · NIAID · NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES · PI REDD, ANDREW · 2009 to 2025
$15.8M
Scientific CoreU19AI088791 · NIAID · JOHNS HOPKINS UNIVERSITY · PI COX, ANDREA L · 2010 to 2020
$8.2M
Intramural NIH HHS Z99 AI999999NIAID NIH HHS U19 AI088791NIAID NIH HHS UM1 AI068613
6 · The paper itself

Abstract

We investigated longitudinal viral clustering among and within subjects in a highly networked cohort of people who inject drugs (PWID). All subjects had estimated dates of infection and two or more E1 sequences (bp 943-1288 relative to H77) with 1 to 14years of follow up. Two methods (HIV-TRACE and PhyloPart) were used to determine clusters. Genetic distance thresholds were determined by comparing intra-and inter-host distances. Additional phylogenetic analysis was performed on subjects with complicated viral histories. At the optimal threshold of 3.9%, HIV-TRACE found 77 clusters and PhyloPart found 63 clusters, of which 27 and 32 contained multiple subjects, respectively. Furthermore, 1/3 of the subjects had sequences in different clusters over the course of the study, including some cases in which a later-sampled sequence matched a cluster detected much earlier in the infection, despite being separated by RNA-negative lab visit and detection of sequences in different clusters. A detailed phylogenetic analysis of four subjects with such patterns showed that in all four cases, the earlier and later variants grouped closely on the tree, and did not group with concurrent sequences from any other subject. These observations suggest that subjects are either experiencing rapid and recurring infection-clearance-reinfection cycles from the same source, or a single transmission event produces a chronic infection that may go undetected and/or co-circulate with different viruses from separate transmission events. Furthermore, our results show the utility of using longitudinal sampling to obtain a more comprehensive view of the viral linkages in high-risk populations.

Indexed as

HepacivirusCluster AnalysisEvolution, MolecularGenotypeHepatitis CHumansPhylogenyRisk AssessmentRisk FactorsRNA, ViralROC CurveViral LoadRNA, ViralClusteringEpidemiologyHCVLinkagePhylogenetic

Identifiers

PMID29253674
PMCPMC5807204

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Registered trials

None linked

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.