GWAS for BMI: a treasure trove of fundamental insights into the genetic basis of obesity

J R Speakman* (Corresponding Author), R J F Loos, S O'Rahilly, J N Hirschhorn, D B Allison

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

43 Citations (Scopus)
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Abstract

Muller et al (1) have provided a strong critique of the Genome Wide Association Studies (GWAS) of body mass index (BMI), arguing that the GWAS approach for the study of BMI is flawed, and has provided us with few biological insights. They suggest that what is needed instead is a new start, involving GWAS for more complex energy balance related traits. In this invited counter-point, we highlight the substantial advances that have occurred in the obesity field, directly stimulated by the GWAS of BMI. We agree that GWAS for BMI is not perfect, but consider that the best route forward for additional discoveries will likely be to expand the search for common and rare variants linked to BMI and other easily obtained measures of obesity, rather than attempting to perform new, much smaller GWAS for energy balance traits that are complex and expensive to measure. For GWAS in general, we emphasise that the power from increasing the sample size of a crude but easily measured phenotype outweighs the benefits of better phenotyping.
Original languageEnglish
Pages (from-to)1524-1531
Number of pages8
JournalInternational Journal of Obesity
Volume42
Early online date6 Jul 2018
DOIs
Publication statusPublished - 2018

Bibliographical note

The authors declare no conflicts of interest. JRS is supported by a Wolfson merit professorship from the UK Royal Society and a grant from the National Science Foundation of China microevolution program (NSFC 91731303). RJFL is supported by the NIH (R01DK110113, U01HG007417, R01DK101855, R01DK107786). DBA is supported by NIH Grants R25DK099080 and R25HL124208. The opinions are those of the authors and not necessarily the NIH or any other orgnaization.

Keywords

  • biological techniques
  • genetics

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