Evidence map›Paper›PMID 28384278›Full record

ArticlePloS one2017

A post-GWAS analysis of predicted regulatory variants and tuberculosis susceptibility.

Caitlin Uren, Brenna M Henn, Andre Franke, Michael Wittig, Paul D van Helden, Eileen G Hoal, Marlo Möller

Abstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Trial
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  9. Review
  10. Single Nucleotide Polymorphisms inJournal of immunology research · 2020
    Article
  11. Article
  12. Article
  13. Article
  14. Human Genomics ofCurrent genetic medicine reports · 2017
    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

7 authors.

Caitlin UrenSA MRC Centre for TB Research, DST/NRF Centre of Excellence for Biomedical TB Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.ORCID http://orcid.org/0000-0003-2358-0135
Brenna M HennDepartment of Ecology and Evolution, Stony Brook University, Stony Brook, New York, United States of America.
Andre FrankeInstitute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Rosalind-Franklin-Strasse Kiel, Germany.
Michael WittigInstitute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Rosalind-Franklin-Strasse Kiel, Germany.
Paul D van HeldenSA MRC Centre for TB Research, DST/NRF Centre of Excellence for Biomedical TB Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.
Eileen G HoalSA MRC Centre for TB Research, DST/NRF Centre of Excellence for Biomedical TB Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.
Marlo MöllerSA MRC Centre for TB Research, DST/NRF Centre of Excellence for Biomedical TB Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Utilizing data from published tuberculosis (TB) genome-wide association studies (GWAS), we use a bioinformatics pipeline to detect all polymorphisms in linkage disequilibrium (LD) with variants previously implicated in TB disease susceptibility. The probability that these variants had a predicted regulatory function was estimated using RegulomeDB and Ensembl's Variant Effect Predictor. Subsequent genotyping of these 133 predicted regulatory polymorphisms was performed in 400 admixed South African TB cases and 366 healthy controls in a population-based case-control association study to fine-map the causal variant. We detected associations between tuberculosis susceptibility and six intronic polymorphisms located in MARCO, IFNGR2, ASHAS2, ACACA, NISCH and TLR10. Our post-GWAS approach demonstrates the feasibility of combining multiple TB GWAS datasets with linkage information to identify regulatory variants associated with this infectious disease.

Indexed as

Genetic Predisposition to DiseaseGenome-Wide Association StudyAdultCase-Control StudiesEthnicityFemaleGenotypeHumansMaleMiddle AgedPolymorphism, Single NucleotideSouth AfricaTuberculosis

Identifiers

PMID28384278
PMCPMC5383035

What OpenQuestion holds

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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.