Evidence map›Paper›PMID 19604093›Full record

ArticlePharmacogenomics2009

Genetic polymorphisms, their allele combinations and IFN-beta treatment response in Irish multiple sclerosis patients.

Catherine O'Doherty, Alexander Favorov, Shirley Heggarty, Colin Graham, Olga Favorova, Michael Ochs, Stanley Hawkins, Michael Hutchinson, Killian O'Rourke, Koen Vandenbroeck

Abstract readComparative Study
In one paragraph

Article in Pharmacogenomics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Combinations of Genetic Variants Occurring Exclusively in Patients.Computational and structural biotechnology journal · 2017
    Review
  8. Review
  9. Article
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  11. Article
  12. Article
  13. Article
  14. Review
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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

10 authors.

Catherine O'DohertyUniversity of South Australia, Adelaide, Australia.
Alexander Favorov
Shirley Heggarty
Colin Graham
Olga Favorova
Michael Ochs
Stanley Hawkins
Michael Hutchinson
Killian O'Rourke
Koen Vandenbroeck

Funding

Identifying Genetic Factors for Predisposition in Polygenic DiseasesR03LM008932 · NLM · JOHNS HOPKINS UNIVERSITY · PI OCHS, MICHAEL F · 2006 to 2008
$248k
NLM NIH HHS LM008932NLM NIH HHS R03 LM008932
6 · The paper itself

Abstract

introductionIFN-beta is widely used as first-line immunomodulatory treatment for multiple sclerosis. Response to treatment is variable (30-50% of patients are nonresponders) and requires a long treatment duration for accurate assessment to be possible. Information about genetic variations that predict responsiveness would allow appropriate treatment selection early after diagnosis, improve patient care, with time saving consequences and more efficient use of resources. MATERIALS &

methodsWe analyzed 61 SNPs in 34 candidate genes as possible determinants of IFN-beta response in Irish multiple sclerosis patients. Particular emphasis was placed on the exploration of combinations of allelic variants associated with response to therapy by means of a Markov chain Monte Carlo-based approach (APSampler).

resultsThe most significant allelic combinations, which differed in frequency between responders and nonresponders, included JAK2-IL10RB-GBP1-PIAS1 (permutation p-value was p(perm) = 0.0008), followed by JAK2-IL10-CASP3 (p(perm) = 0.001). DISCUSSION: The genetic mechanism of response to IFN-beta is complex and as yet poorly understood. Data mining algorithms may help in uncovering hidden allele combinations involved in drug response versus nonresponse.

Indexed as

FemaleGene FrequencyHumansInterferon-betaIrelandMaleMultiple SclerosisPolymorphism, GeneticWhite PeopleInterferon-beta

Identifiers

PMID19604093
PMCPMC2727921

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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.