Evidence map›Paper›PMID 25239152›Full record

ArticleInternational journal of epidemiology2015

Reproducibility of telomere length assessment: an international collaborative study.

Carmen M Martin-Ruiz, Duncan Baird, Laureline Roger, Petra Boukamp, Damir Krunic, Richard Cawthon, Martin M Dokter, Pim van der Harst, Sofie Bekaert, Tim de Meyer and 12 more

Erratum issuedOpen access · hybridAbstract read
In one paragraph

Article in International journal of epidemiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 101 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
101citing papers in PubMed, 3 pooled it
12.8field-weighted citation impact, top 1% 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

101 citing papers in PubMed, 3 syntheses or guidelines pooled it, 185 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Best practices for using biological data in psychological research.Journal of mood and anxiety disorders · 2026
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41 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

22 authors at 14 institutions in 7 countries.

Carmen M Martin-RuizNewcastle University Institute for Ageing, Newcastle University, Newcastle, UK.
Duncan BairdInstitute of Cancer and Genetics, Cardiff University, Cardiff, UK.
Laureline RogerInstitute of Cancer and Genetics, Cardiff University, Cardiff, UK.
Petra BoukampDeutsches Krebsforschungszentrum (DKFZ), Heidelberg, Germany.
Damir KrunicDeutsches Krebsforschungszentrum (DKFZ), Heidelberg, Germany.
Richard CawthonDepartment of Human Genetics, University of Utah, Salt Lake City, UT, USA.
Martin M DokterDepartment of Cardiology, University of Groningen, Groningen, The Netherlands.
Pim van der HarstDepartment of Cardiology, University of Groningen, Groningen, The Netherlands.
Sofie BekaertBimetra, Clinical Research Center, Ghent University Hospital, Ghent, Belgium.
Tim de MeyerDepartment of Mathematical Modelling, Statistics and Bioinformatics, Ghent University, Ghent, Belgium.
Goran RoosDepartment of Medical Biosciences, Umeå University, Umeå, Sweden.
Ulrika SvensonDepartment of Medical Biosciences, Umeå University, Umeå, Sweden.
Veryan CoddDepartment of Cardiovascular Sciences, University of Leicester, Leicester, UK.
Nilesh J SamaniDepartment of Cardiovascular Sciences, University of Leicester, Leicester, UK.
Liane McGlynnInstitute of Cancer Sciences, University of Glasgow, Glasgow, UK.
Paul G ShielsInstitute of Cancer Sciences, University of Glasgow, Glasgow, UK.
Karen A PooleyDepartment of Public Health and Primary Care.
Alison M DunningDepartment of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK and.
Rachel CooperMRC Unit for Lifelong Health and Ageing at UCL, London, UK.
Andrew WongMRC Unit for Lifelong Health and Ageing at UCL, London, UK.
Andrew KingstonNewcastle University Institute for Ageing, Newcastle University, Newcastle, UK.
Thomas von ZglinickiNewcastle University Institute for Ageing, Newcastle University, Newcastle, UK, t.vonzglinicki@newcastle.ac.uk.
Newcastle University · GBCardiff University · GBMRC Unit for Lifelong Health and Ageing · GBUmeå University · SEUniversity of Glasgow · GBUniversity of Groningen · NLUniversity of Leicester · GBGerman Cancer Research Center · DEGhent University · BEGhent University Hospital · BEHeidelberg University · DEPrimary Health Care · QAUniversity of Cambridge · GBUniversity of Utah · US

Funding

Biotechnology and Biological Sciences Research Council BB/F010966/1Biotechnology and Biological Sciences Research Council BB/I020748/1Cancer Research UK 16565Medical Research Council G0500997Medical Research Council G0601333Medical Research Council MC_UU_12019/1Worldwide Cancer Research 10-0021
6 · The paper itself

Abstract

backgroundTelomere length is a putative biomarker of ageing, morbidity and mortality. Its application is hampered by lack of widely applicable reference ranges and uncertainty regarding the present limits of measurement reproducibility within and between laboratories.

methodsWe instigated an international collaborative study of telomere length assessment: 10 different laboratories, employing 3 different techniques [Southern blotting, single telomere length analysis (STELA) and real-time quantitative PCR (qPCR)] performed two rounds of fully blinded measurements on 10 human DNA samples per round to enable unbiased assessment of intra- and inter-batch variation between laboratories and techniques.

resultsAbsolute results from different laboratories differed widely and could thus not be compared directly, but rankings of relative telomere lengths were highly correlated (correlation coefficients of 0.63-0.99). Intra-technique correlations were similar for Southern blotting and qPCR and were stronger than inter-technique ones. However, inter-laboratory coefficients of variation (CVs) averaged about 10% for Southern blotting and STELA and more than 20% for qPCR. This difference was compensated for by a higher dynamic range for the qPCR method as shown by equal variance after z-scoring. Technical variation per laboratory, measured as median of intra- and inter-batch CVs, ranged from 1.4% to 9.5%, with differences between laboratories only marginally significant (P = 0.06). Gel-based and PCR-based techniques were not different in accuracy.

conclusionsIntra- and inter-laboratory technical variation severely limits the usefulness of data pooling and excludes sharing of reference ranges between laboratories. We propose to establish a common set of physical telomere length standards to improve comparability of telomere length estimates between laboratories.

Indexed as

AgingBiomarkersBlotting, SouthernDNAHumansInternational CooperationReal-Time Polymerase Chain ReactionReproducibility of ResultsTelomereBiomarkersDNAAgeingbiomarkerhumantelomeresvariation

Identifiers

PMID25239152
PMCPMC4681105
OpenAlexW2130688853

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.