Evidence map›Paper›PMID 36751652›Full record

ArticleOpen forum infectious diseases2023

Challenges in Harnessing Shared Within-Host Severe Acute Respiratory Syndrome Coronavirus 2 Variation for Transmission Inference.

Katharine S Walter, Eugene Kim, Renu Verma, Jonathan Altamirano, Sean Leary, Yuan J Carrington, Prasanna Jagannathan, Upinder Singh, Marisa Holubar, Aruna Subramanian and 3 more

Open access · goldAbstract read
In one paragraph

Article in Open forum infectious diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.0field-weighted citation impact, top 28% of its field
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

5 citing papers in PubMed, 6 citations in OpenAlex.

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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

13 authors at 2 institutions in 1 country.

Katharine S WalterDivision of Epidemiology, University of Utah, Salt Lake City, Utah, USA.ORCID https://orcid.org/0000-0003-0065-2204
Eugene KimDivision of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, California, USA.
Renu VermaDivision of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, California, USA.
Jonathan AltamiranoDepartment of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, California, USA.
Sean LearyDepartment of Pediatrics, Stanford University School of Medicine, Stanford, California, USA.
Yuan J CarringtonDepartment of Pediatrics, Stanford University School of Medicine, Stanford, California, USA.
Prasanna JagannathanDivision of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, California, USA.ORCID https://orcid.org/0000-0001-6305-758X
Upinder SinghDivision of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, California, USA.
Marisa HolubarDivision of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, California, USA.ORCID https://orcid.org/0000-0002-7585-1809
Aruna SubramanianDivision of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, California, USA.
Chaitan KhoslaStanford ChEM-H, Stanford University, Stanford, California, USA.
Yvonne MaldonadoDepartment of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, California, USA.
Jason R AndrewsDivision of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, Stanford, California, USA.ORCID https://orcid.org/0000-0002-5967-251X
Stanford University · USUniversity of Utah · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The limited variation observed among severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) consensus sequences makes it difficult to reconstruct transmission linkages in outbreak settings. Previous studies have recovered variation within individual SARS-CoV-2 infections but have not yet measured the informativeness of within-host variation for transmission inference. Methods: We performed tiled amplicon sequencing on 307 SARS-CoV-2 samples, including 130 samples from 32 individuals in 14 households and 47 longitudinally sampled individuals, from 4 prospective studies with household membership data, a proxy for transmission linkage. Results: Consensus sequences from households had limited diversity (mean pairwise distance, 3.06 single-nucleotide polymorphisms [SNPs]; range, 0-40). Most (83.1%, 255 of 307) samples harbored at least 1 intrahost single-nucleotide variant ([iSNV] median, 117; interquartile range [IQR], 17-208), above a minor allele frequency threshold of 0.2%. Pairs in the same household shared significantly more iSNVs (mean, 1.20 iSNVs; 95% confidence interval [CI], 1.02-1.39) than did pairs in different households infected with the same viral clade (mean, 0.31 iSNVs; 95% CI, .28-.34), a signal that decreases with increasingly stringent minor allele frequency thresholds. The number of shared iSNVs was significantly associated with an increased odds of household membership (adjusted odds ratio, 1.35; 95% CI, 1.23-1.49). However, the poor concordance of iSNVs detected across sequencing replicates (24.8% and 35.0% above a 0.2% and 1% threshold) confirms technical concerns that current sequencing and bioinformatic workflows do not consistently recover low-frequency within-host variants. Conclusions: Shared within-host variation may augment the information in consensus sequences for predicting transmission linkages. Improving sensitivity and specificity of within-host variant identification will improve the informativeness of within-host variation.

Indexed as

genomicsSARS-CoV-2transmissionviral evolutionwithin-host diversity

Identifiers

PMID36751652
PMCPMC9898879
OpenAlexW4313729248

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.