Evidence map›Paper›PMID 31875229›Full record

ArticleThe Journal of infectious diseases2020

Correlates of Nonrandom Patterns of Serotype Switching in Pneumococcus.

Shreyas S Joshi, Mohammad A Al-Mamun, Daniel M Weinberger

Abstract read
In one paragraph

Article in The Journal of infectious diseases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

3 authors.

Shreyas S JoshiDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, USA.
Mohammad A Al-MamunDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, USA.
Daniel M WeinbergerDepartment of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut, USA.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Forecasting pneumococcal serotype frequencies to develop adult-specific vaccinesR01AI123208 · NIAID · YALE UNIVERSITY · PI WEINBERGER, DANIEL MARTIN · 2016 to 2019
$2.5M
NCATS NIH HHS UL1 TR001863NIAID NIH HHS R01 AI123208
6 · The paper itself

Abstract

backgroundPneumococcus is a diverse pathogen, with >90 serotypes, each of which has a distinct polysaccharide capsule. Pneumococci can switch capsules, evading vaccine pressure. Certain serotype pairs are more likely to occur on the same genetic background as a results of serotype switching, but the drivers of these patterns are not well understood.

methodsWe used the PubMLST and Global Pneumococcal Sequencing Project databases to quantify the number of genetic lineages on which different serotype pairs occur together. We also quantified the genetic diversity of each serotype. Regression model were used to evaluate the relationship between shared polysaccharide components and the frequency of serotype co-occurrence and diversity.

resultsA number of serotype pairs occurred together on the same genetic lineage more commonly than expected. Co-occurrence of between-serogroup pairs was more common when both serotypes had glucose as a component of the capsule (and, potentially, glucuronic acid, any-N-acetylated sugar, or ribitol). Diversity also varied markedly by serotype and was associated with the presence of specific sugars in the capsule.

conclusionsCertain pairs of serotypes are more likely to co-occur on the same genetic background. These patterns were correlated with shared polysaccharide components. This might reflect adaptation of strains to produce capsules with specific characteristics.

Indexed as

Databases, GeneticHumansPneumococcal InfectionsSerogroupSerotypingStreptococcus pneumoniaePneumococcuspolysaccharide capsuleserotype switchingvaccination

Identifiers

PMID31875229
PMCPMC7184915

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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.