Evidence map›Paper›PMID 40155671›Full record

ArticleScientific reports2025

Phylodynamic assessment of SNP distances from whole genome sequencing for determining Mycobacterium tuberculosis transmission.

Bastiaan R Van der Roest, Martin C J Bootsma, Egil A J Fischer, Matthias I Gröschel, Richard M Anthony, Rina de Zwaan, Mirjam E E Kretzschmar, Don Klinkenberg

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 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

8 authors.

Bastiaan R Van der RoestJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, P.O.Box 85500, Utrecht, The Netherlands. b.r.vanderroest-2@umcutrecht.nl.ORCID http://orcid.org/0000-0002-8985-8964
Martin C J BootsmaJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, P.O.Box 85500, Utrecht, The Netherlands.ORCID http://orcid.org/0000-0003-3005-0255
Egil A J FischerPopulation Health Sciences, Faculty of Veterinary Medicine, University Utrecht, Utrecht, The Netherlands.ORCID http://orcid.org/0000-0002-0599-701X
Matthias I GröschelDepartment of Infectious Diseases, Respiratory and Critical Care Medicine, Charité- Universitätsmedizin Berlin, Berlin, Germany.ORCID http://orcid.org/0000-0002-2509-3034
Richard M AnthonyTuberculosis Reference Laboratory, Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands.ORCID http://orcid.org/0000-0002-0550-5273
Rina de ZwaanTuberculosis Reference Laboratory, Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands.
Mirjam E E KretzschmarJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, P.O.Box 85500, Utrecht, The Netherlands.ORCID http://orcid.org/0000-0002-4394-7697
Don KlinkenbergNational Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands.ORCID http://orcid.org/0000-0002-9449-6873

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The global tuberculosis (TB) epidemic is driven by primary transmission. Pathogen genome sequencing is increasingly used in molecular epidemiology and outbreak investigations. Based on contact tracing and epidemiological links, Single Nucleotide Polymorphism (SNP) cut-offs, ranging from 3 to 12 SNPs, identify probable transmission clusters or exclude direct transmission. However, contact tracing can be limited by recall bias and inconsistent methodologies across TB settings. We propose phylodynamic models, i.e. methods to infer transmission processes from pathogen genomes and associated epidemiological data, as an alternative reference to infer transmission events. We analyzed 2,008 whole-genome sequences from Dutch TB patients collected from 2015 to 2019. Genetic clusters were defined within a 20-SNP range, and the phylodynamic model phybreak was employed to infer transmission. Probable transmission SNP cut-offs were assessed by the proportion of inferred transmission events with a SNP distance below these cut-offs. A total of 79 clusters were identified, with a median size of 4 isolates (IQR = 3-8). A SNP cut-off of 4 captured 98% of inferred transmission events while reducing pairs without transmission links. A cut-off beyond 12 SNPs effectively excluded transmission. Phylodynamic approaches provide a valuable alternative to contact tracing for defining SNP cut-offs, allowing for a more precise assessment of transmission events.

Indexed as

Mycobacterium tuberculosisPolymorphism, Single NucleotideTuberculosisWhole Genome SequencingContact TracingGenome, BacterialHumansMaleMolecular EpidemiologyNetherlandsPhylogenyPhylodynamic modelingSNP cut-off assessmentTransmissionTuberculosisWhole Genome Sequencing

Identifiers

PMID40155671
PMCPMC11953417

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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.