Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2017 May 9;15(1):97.
doi: 10.1186/s12916-017-0862-0.

Habitual coffee consumption and genetic predisposition to obesity: gene-diet interaction analyses in three US prospective studies

Tiange Wang  1   2 , Tao Huang  1 , Jae H Kang  3 , Yan Zheng  4 , Majken K Jensen  4 , Janey L Wiggs  5 , Louis R Pasquale  3   5 , Charles S Fuchs  3   6 , Hannia Campos  4   7 , Eric B Rimm  3   4   8 , Walter C Willett  3   4   8 , Frank B Hu  3   4 , Lu Qi  9   10   11
Affiliations

Habitual coffee consumption and genetic predisposition to obesity: gene-diet interaction analyses in three US prospective studies

Tiange Wang et al. BMC Med. .

Abstract

Background: Whether habitual coffee consumption interacts with the genetic predisposition to obesity in relation to body mass index (BMI) and obesity is unknown.

Methods: We analyzed the interactions between genetic predisposition and habitual coffee consumption in relation to BMI and obesity risk in 5116 men from the Health Professionals Follow-up Study (HPFS), in 9841 women from the Nurses' Health Study (NHS), and in 5648 women from the Women's Health Initiative (WHI). The genetic risk score was calculated based on 77 BMI-associated loci. Coffee consumption was examined prospectively in relation to BMI.

Results: The genetic association with BMI was attenuated among participants with higher consumption of coffee than among those with lower consumption in the HPFS (P interaction = 0.023) and NHS (P interaction = 0.039); similar results were replicated in the WHI (P interaction = 0.044). In the combined data of all cohorts, differences in BMI per increment of 10-risk allele were 1.38 (standard error (SE), 0.28), 1.02 (SE, 0.10), and 0.95 (SE, 0.12) kg/m2 for coffee consumption of < 1, 1-3 and > 3 cup(s)/day, respectively (P interaction < 0.001). Such interaction was partly due to slightly higher BMI with higher coffee consumption among participants at lower genetic risk and slightly lower BMI with higher coffee consumption among those at higher genetic risk. Each increment of 10-risk allele was associated with 78% (95% confidence interval (CI), 59-99%), 48% (95% CI, 36-62%), and 43% (95% CI, 28-59%) increased risk for obesity across these subgroups of coffee consumption (P interaction = 0.008). From another perspective, differences in BMI per increment of 1 cup/day coffee consumption were 0.02 (SE, 0.09), -0.02 (SE, 0.04), and -0.14 (SE, 0.04) kg/m2 across tertiles of the genetic risk score.

Conclusions: Higher coffee consumption might attenuate the genetic associations with BMI and obesity risk, and individuals with greater genetic predisposition to obesity appeared to have lower BMI associated with higher coffee consumption.

Keywords: Body mass index; Coffee; Gene-diet interaction; Genetic predisposition; Obesity.

PubMed Disclaimer

Figures

Fig. 1
Fig. 1
Genetic associations with prevalent obesity, according to coffee consumption in the HPFS, NHS, and WHI. Data are odds ratios (95% CIs) for prevalent obesity. In the HPFS and NHS, data were derived from the repeated-measures analysis in men (three measures from 1986 to 1998) and women (three measures from 1986 to 1998); in the WHI, data were derived from the repeated-measures in women (two measures from 1993 to 2003). Data were adjusted for age, genotyping source, physical activity (<3, 3–8.9, 9–17.9, 18–26.9, ≥ 27 MET-h/wk), Alternative Healthy Eating Index score (quintiles), total energy intake (quintiles), smoking status (never, former, current), sugar-sweetened beverage consumption (quintiles), and alcohol consumption (0, 0.1–4.9, 5–9.9, 10–14.9, ≥ 15 g/day). Results for the three cohorts were pooled by means of inverse-variance-weighted random effects meta-analysis (if P < 0.05 for heterogeneity) or fixed effects meta-analysis (if P ≥ 0.05 for heterogeneity)
Fig. 2
Fig. 2
Differences in BMI per increment of 1 cup/day coffee consumption, according to tertiles of the genetic risk score in the HPFS, NHS, and WHI. Data are multivariable-adjusted β coefficients (SEs) of BMI (kg/m2). Data description and adjustment are the same as shown in Fig. 1
Fig. 3
Fig. 3
BMI according to joint categories of coffee consumption and the genetic risk score in combined data of the HPFS, NHS, and WHI. Data are multivariable-adjusted mean values of BMI (kg/m2). Data description and adjustment are the same as shown in Fig. 1
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Qi Q, Chu AY, Kang JH, et al. Sugar-sweetened beverages and genetic risk of obesity. N Engl J Med. 2012;367:1387–96. doi: 10.1056/NEJMoa1203039. - DOI - PMC - PubMed
    1. Qi Q, Chu AY, Kang JH, et al. Fried food consumption, genetic risk, and body mass index: gene-diet interaction analysis in three US cohort studies. BMJ. 2014;348:g1610. doi: 10.1136/bmj.g1610. - DOI - PMC - PubMed
    1. Greenberg JA, Axen KV, Schnoll R, Boozer CN. Coffee, tea and diabetes: the role of weight loss and caffeine. Int J Obes (Lond) 2005;29:1121–9. doi: 10.1038/sj.ijo.0802999. - DOI - PubMed
    1. Lopez-Garcia E, van Dam RM, Rajpathak S, Willett WC, Manson JE, Hu FB. Changes in caffeine intake and long-term weight change in men and women. Am J Clin Nutr. 2006;83:674–80. - PubMed
    1. Nordestgaard AT, Thomsen M, Nordestgaard BG. Coffee intake and risk of obesity, metabolic syndrome and type 2 diabetes: a Mendelian randomization study. Int J Epidemiol. 2015;44:551–65. doi: 10.1093/ije/dyv083. - DOI - PubMed