Abstract
Recent studies have identified genetic markers associated with risk for certain sports-related injuries and performance-related conditions, with the hope that these markers could be used by individual athletes to personalize their training and diet regimens. We found that we could greatly expand the knowledge base of sports genetic information by using published data originally found in health and disease studies. For example, the results from large genome-wide association studies for low bone mineral density in elderly women can be re-purposed for low bone mineral density in young endurance athletes. In total, we found 124 single-nucleotide polymorphisms associated with: anterior cruciate ligament tear, Achilles tendon injury, low bone mineral density and stress fracture, osteoarthritis, vitamin/mineral deficiencies, and sickle cell trait. Of these single nucleotide polymorphisms, 91% have not previously been used in sports genetics.
We conducted a pilot program on fourteen triathletes using this expanded knowledge base of genetic variants associated with sports injury. These athletes were genotyped and educated about how their individual genetic make-up affected their personal risk profile during an hour-long personal consultation. Overall, participants were favorable of the program, found it informative, and most acted upon their genetic results.
This pilot program shows that recent genetic research provides valuable information to help reduce sports injuries and to optimize nutrition. There are many genetic studies for health and disease that can be mined to provide useful information to athletes about their individual risk for relevant injuries.
Citation: Goodlin GT, Roos AK, Roos TR, Hawkins C, Beache S, Baur S, et al. (2015) Applying Personal Genetic Data to Injury Risk Assessment in Athletes. PLoS ONE 10(4):
e0122676.
https://doi.org/10.1371/journal.pone.0122676
Academic Editor: Alejandro Lucia, Universidad Europea de Madrid, SPAIN
Received: May 2, 2014; Accepted: February 24, 2015; Published: April 28, 2015
Copyright: © 2015 Goodlin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Data Availability: All relevant data is available upon request from Stanford University School of Medicine Department of Genetics; please contact Dr. Stuart Kim: Beckman Center B300 279 Campus Drive Stanford, CA 94309 t:(650) 725-7671 f:(650) 725-7739 stuartkm@stanford.edu
Funding: This work was supported by a Spectrum grant from NIH/Stanford University (#S13-064). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Description
This study explores the use of genetic data to assess injury risk in athletes.