Evidence map›Paper›PMID 30818878›Full record

ArticleGenes2019

Single Nucleotide Polymorphisms in

Gabrielle Bradshaw, Larisa M Haupt, Eunise M Aquino, Rodney A Lea, Heidi G Sutherland, Lyn R Griffiths

Open access · goldAbstract read
In one paragraph

Article in Genes, 2019. 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
0.9field-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, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. 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

6 authors at 1 institution in 1 country.

Gabrielle BradshawGenomics Research Centre, School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia. lyn.griffiths@qut.edu.au.
Larisa M HauptGenomics Research Centre, School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia. lyn.griffiths@qut.edu.au.
Eunise M AquinoGenomics Research Centre, School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia. lyn.griffiths@qut.edu.au.
Rodney A LeaGenomics Research Centre, School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia. lyn.griffiths@qut.edu.au.
Heidi G SutherlandGenomics Research Centre, School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia. lyn.griffiths@qut.edu.au.
Lyn R GriffithsGenomics Research Centre, School of Biomedical Sciences, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia. lyn.griffiths@qut.edu.au.
Queensland University of Technology · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent studies show an association of microRNA (miRNA) polymorphisms (miRSNPs) in different cancer types, including non-Hodgkin lymphoma (NHL). The identification of miRSNPs that are associated with NHL susceptibility may provide biomarkers for early diagnosis and prognosis for patients who may not respond well to current treatment options, including the immunochemotherapy drug combination that includes rituximab, cyclophosphamide, doxorubicin, vincristine and prednisome (R-CHOP). We developed a panel of miRSNPs for genotyping while using multiplex PCR and chip-based mass spectrometry analysis in an Australian NHL case-control population (300 cases, 140 controls). Statistical association with NHL susceptibility was performed while using Chi-square (χ²) and logistic regression analysis. We identified three SNPs in MIR143 that are to be significantly associated with reduced risk of NHL: rs3733846 (odds ratio (OR) [95% confidence interval (CI)] = 0.54 [0.33 ⁻ 0.86], p = 0.010), rs41291957 (OR [95% CI] = 0.61 [0.39 ⁻ 0.94], p = 0.024), and rs17723799 (OR [95% CI] = 0.43 [0.26 ⁻ 0.71], p = 0.0009). One SNP, rs17723799, remained significant after correction for multiple testing (p = 0.015). Subsequently, we investigated an association between the rs17723799 genotype and phenotype by measuring target gene Hexokinase 2 (HKII) expression in cancer cell lines and controls. Our study is the first to report a correlation between miRSNPs in MIR143 and a reduced risk of NHL in Caucasians, and it is supported by significant SNPs in high linkage disequilibrium (LD) in a large European NHL genome wide association study (GWAS) meta-analysis.

Indexed as

Polymorphism, Single NucleotideAgedCase-Control StudiesCell Line, TumorFemaleGenetic Predisposition to DiseaseGenome-Wide Association StudyHexokinaseHumansLogistic ModelsLymphoma, Non-HodgkinMaleMicroRNAsMiddle AgedWhite PeopleHexokinaseHK2 protein, humanMicroRNAsMIRN143 microRNA, humanbiomarkercancerHKIIMIR143miRSNPnon-Hodgkin lymphomars17723799, Hexokinase 2

Identifiers

PMID30818878
PMCPMC6471575
OpenAlexW2915136486

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.