Caren E. Smith, USDA Human Nutrition Research
Jack L. Follis, University of St. Thomas
Hassan S. Dashti, Massachusetts General Hospital
Toshiko Tanaka, National Institute on Aging
Mariaelisa Graff, The University of North Carolina at Chapel Hill
Amanda M. Fretts, University of Washington
Tuomas O. Kilpeläinen, University of Copenhagen, Denmark
Mary K. Wojczynski, Washington University in St. Louis
Kris Richardson, USDA Human Nutrition Research Center on Aging
Mike A. Nalls, National Institute on Aging
Christina-Alexandra Schulz, Lund University, Sweden
Yongmei Liu, Wake Forest University
Alexis C. Frazier-Wood, USDA Agricultural Research Service
Esther van Eekelen, Leiden University, The Netherlands
Carol Wang, University of Western Australia, Australia
Paul S. de Vries, University of Texas Health Science Center at Houston
Vera Mikkilä, University of Helsinki, Finland
Rebecca Rohde, The University of North Carolina at Chapel Hill
Bruce M. Psaty, University of Washington
Torben Hansen, University of Copenhagen, Denmark
Mary F. Feitosa, Washington University in St. Louis
Chao-Qiang Lai, USDA Agricultural Research Service
Denise K. Houston, Wake Forest University
Luigi Ferruci, National Institute on Aging
Ulrika Ericson, Lund University, Sweden
Zhe Wang, University of Texas Health Science Center at Houston
Renée de Mutsert, Leiden University, The Netherlands
Wendy H. Oddy, University of Tasmania, Australia
Ester A. L. de Jonge, University Medical Center, The Netherlands
Ilkka Seppälä, Tampere University, Finland
Donna K. Arnett, University of KentuckyFollow


Scope: Body weight responds variably to the intake of dairy foods. Genetic variation may contribute to inter‐individual variability in associations between body weight and dairy consumption.

Methods and results: A genome‐wide interaction study to discover genetic variants that account for variation in BMI in the context of low‐fat, high‐fat and total dairy intake in cross‐sectional analysis was conducted. Data from nine discovery studies (up to 25 513 European descent individuals) were meta‐analyzed. Twenty‐six genetic variants reached the selected significance threshold (p‐interaction <10−7), and six independent variants (LINC01512‐rs7751666, PALM2/AKAP2‐rs914359, ACTA2‐rs1388, PPP1R12A‐rs7961195, LINC00333‐rs9635058, AC098847.1‐rs1791355) were evaluated meta‐analytically for replication of interaction in up to 17 675 individuals. Variant rs9635058 (128 kb 3’ of LINC00333) was replicated (p‐interaction = 0.004). In the discovery cohorts, rs9635058 interacted with dairy (p‐interaction = 7.36 × 10−8) such that each serving of low‐fat dairy was associated with 0.225 kg m−2 lower BMI per each additional copy of the effect allele (A). A second genetic variant (ACTA2‐rs1388) approached interaction replication significance for low‐fat dairy exposure.

Conclusion: Body weight responses to dairy intake may be modified by genotype, in that greater dairy intake may protect a genetic subgroup from higher body weight.

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Notes/Citation Information

Published in Molecular Nutrition & Food Research, v. 62, issue 3, 1700347, p. 1-27.

© 2017 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim

The copyright holder has granted the permission for posting the article here.

This is the peer reviewed version of the following article: Smith, C. E., Follis, J. L., Dashti, H. S., Tanaka, T., Graff, M., Fretts, A. M., ... Ordovás, J. M. (2018). Genome-wide interactions with dairy intake for body mass index in adults of European descent. Molecular Nutrition & Food Research, 62(3), 1700347, which has been published in final form at This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.

Due to the large number of authors, only the first 30 and the authors affiliated with the University of Kentucky are listed in the author section above. For the complete list of authors, please download this article or visit:

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Funding Information

Complete funding information is located in the Supporting Information, Table 8. B. P. serves on the DSMB of a clinical trial funded by the manufacturer (Zoll LifeCor) and on the Steering Committee of the Yale Open Data Access Project funded by Johnson & Johnson. M. N.’ participation is supported by a consulting contract between Kelly Services and the National Institute on Aging, NIH, Bethesda, MD, USA.

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Supporting Information is available from the Wiley Online Library or from the author.

mnfr3043-sup-0001-tables-s1.doc (9416 kB)
Supporting Information