Evidence map›Paper›PMID 31427879›Full record

SynthesisJournal of sports science & medicine2019

Genes and Elite Marathon Running Performance: A Systematic Review.

Hannah J Moir, Rachael Kemp, Dirk Folkerts, Owen Spendiff, Cristina Pavlidis, Elizabeth Opara

Abstract readSystematic Review
In one paragraph

Synthesis in Journal of sports science & medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 4 pooled it
–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

12 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Review
  6. Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Predictive Performance Models in Long-Distance Runners: A Narrative Review.International journal of environmental research and public health · 2020
    Review
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.

Hannah J MoirSchool of Life Sciences, Pharmacy & Chemistry, Faculty of Science, Engineering and Computing, Kingston University, London, UK.
Rachael KempSchool of Life Sciences, Pharmacy & Chemistry, Faculty of Science, Engineering and Computing, Kingston University, London, UK.
Dirk FolkertsSchool of Life Sciences, Pharmacy & Chemistry, Faculty of Science, Engineering and Computing, Kingston University, London, UK.
Owen SpendiffSchool of Life Sciences, Pharmacy & Chemistry, Faculty of Science, Engineering and Computing, Kingston University, London, UK.
Cristina PavlidisDepartment of Pharmacy, University of Patras, Pátra, Greece.
Elizabeth OparaSchool of Life Sciences, Pharmacy & Chemistry, Faculty of Science, Engineering and Computing, Kingston University, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genetics has long been considered to associate with many exercise-related traits and sport performance phenotypes. A genetic basis for elite international marathon running performance exists due to the heritability of endurance-related traits. This has prompted a generation of genomic study to identify marathon success. The aim of this study was to systematically review the evidence of genes, and their polymorphisms, that may play a role in marathon running performance. A search strategy was implemented on systematic databases following PRISMA guidelines. Studies were case-control, cohort or genome-wide association designs and provided data on the genotypes associated with elite marathon athlete status and/or marathon running performance. The search identified 241 studies, from which, 14 studies were deemed suitable for inclusion. A total of 160 different polymorphisms in 27 genes were identified in 10,442 participants, of which 2,984 were marathon distance runners. The review identified a possible 16 single nucleotide polymorphisms (SNPs) in 14 genes associated with marathon running performance. While multiple genes and their polymorphisms have been associated with marathon running performance, predicting future marathon success based on genomic data is premature due to the lack of replicated studies. There is limited replication of genotype-phenotype associations and there is possible publication bias, thus, further studies are required to strengthen our understanding of the genes involved in marathon running. Future research utilising genome-wide technologies in large cohorts is required to elucidate the multiple genetic factors that govern complex endurance-related traits and the impact of epigenetics should be considered.

Indexed as

GenotypeHumansPhenotypePhysical EndurancePolymorphism, Single NucleotideRunningenduranceexerciseGeneticsgenotypeperformance

Identifiers

PMID31427879
PMCPMC6683622

What OpenQuestion holds

Textmetadata
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.