Evidence map›Paper›PMID 27139154›Full record

ArticleThe pharmacogenomics journal2017

Emergent biomarker derived from next-generation sequencing to identify pain patients requiring uncommonly high opioid doses.

D Kringel, A Ultsch, M Zimmermann, J-P Jansen, W Ilias, R Freynhagen, N Griessinger, A Kopf, C Stein, A Doehring and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in The pharmacogenomics journal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Pathology of pain and its implications for therapeutic interventions.Signal transduction and targeted therapy · 2024
    Review
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. Article
  9. Review
  10. Big Data's Role in Precision Public Health.Frontiers in public health · 2018
    Review
  11. Opioids and Chronic Pain: Where Is the Balance?Current oncology reports · 2016
    Review
  12. Article
  13. [Chronic pain care : Reality and entitlement].Schmerz (Berlin, Germany) · 2016
    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

12 authors.

D KringelInstitute of Clinical Pharmacology, Goethe-University, Frankfurt am Main, Germany.
A UltschDataBionics Research Group, University of Marburg, Marburg, Germany.
M ZimmermannDepartment of Anesthesiology, Intensive Care Medicine and Pain Therapy, University Hospital Frankfurt, Frankfurt am Main, Germany.
J-P JansenSchmerzzentrum Berlin, Berlin, Germany.
W IliasDepartment of Anaesthesiology and Intensive Care Medicine, Vienna, Austria.
R FreynhagenZentrum für Anästhesiologie, Intensivmedizin, Schmerztherapie &Palliativmedizin, Benedictus Krankenhaus Tutzing, Tutzing, Germany.
N GriessingerDepartment of Anesthesiology, University Hospital Erlangen, Erlangen, Germany.
A KopfDepartment of Anesthesiology and Critical Care Medicine, Freie Universität Berlin-Charité, Berlin, Germany.
C SteinDepartment of Anesthesiology and Critical Care Medicine, Freie Universität Berlin-Charité, Berlin, Germany.ORCID 0000-0001-5240-6836
A DoehringInstitute of Clinical Pharmacology, Goethe-University, Frankfurt am Main, Germany.
E ReschFraunhofer Institute for Molecular Biology and Applied Ecology IME, Project Group Translational Medicine and Pharmacology TMP, Frankfurt am Main, Germany.
J LötschInstitute of Clinical Pharmacology, Goethe-University, Frankfurt am Main, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Next-generation sequencing (NGS) provides unrestricted access to the genome, but it produces 'big data' exceeding in amount and complexity the classical analytical approaches. We introduce a bioinformatics-based classifying biomarker that uses emergent properties in genetics to separate pain patients requiring extremely high opioid doses from controls. Following precisely calculated selection of the 34 most informative markers in the OPRM1, OPRK1, OPRD1 and SIGMAR1 genes, pattern of genotypes belonging to either patient group could be derived using a k-nearest neighbor (kNN) classifier that provided a diagnostic accuracy of 80.6±4%. This outperformed alternative classifiers such as reportedly functional opioid receptor gene variants or complex biomarkers obtained via multiple regression or decision tree analysis. The accumulation of several genetic variants with only minor functional influences may result in a qualitative consequence affecting complex phenotypes, pointing at emergent properties in genetics.

Indexed as

Pharmacogenomic TestingPharmacogenomic VariantsAnalgesics, OpioidBiomarkers, PharmacologicalChronic PainDose-Response Relationship, DrugGenotypeHigh-Throughput Nucleotide SequencingHumansReceptors, OpioidReceptors, Opioid, deltaReceptors, Opioid, kappaReceptors, Opioid, muReceptors, sigmaSigma-1 ReceptorAnalgesics, OpioidBiomarkers, PharmacologicalOPRD1 protein, humanOPRK1 protein, humanOPRM1 protein, humanReceptors, OpioidReceptors, Opioid, deltaReceptors, Opioid, kappaReceptors, Opioid, muReceptors, sigmaSigma-1 Receptor

Identifiers

PMID27139154
PMCPMC5637232

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.