Genome‐Wide Interactions with Dairy Intake for Body Mass Index in Adults of European Descent

Smith, Caren E.; Follis, Jack L.; Dashti, Hassan S.; Tanaka, Toshiko; Graff, Mariaelisa; Fretts, Amanda M.; Kilpeläinen, Tuomas O.; Wojczynski, Mary K.; Richardson, Kris; Nalls, Mike A.; Schulz, Christina Alexandra; Liu, Yongmei; Frazier‐Wood, Alexis C.; Eekelen, Esther van; Wang, Carol; Vries, Paul S. de; Mikkilä, Vera; Rohde, Rebecca; Psaty, Bruce M.; Hansen, Torben; Feitosa, Mary F.; Lai, Chao‐Qiang; Houston, Denise K.; Ferruci, Luigi; Ericson, Ulrika; Wang, Zhe; Mutsert, Renée de; Oddy, Wendy H.; Jonge, Ester A.L. de; Seppälä, Ilkka; Justice, Anne E.; Lemaître, Rozenn N.; Sørensen, Thorkild I. A.; Province, Michael A.; Parnell, Laurence D.; García, Melissa; Bandinelli, Stefania; Orho‐Melander, Marju; Rich, Stephen S.; Rosendaal, Frits R.; Pennell, Craig E.; Jong, Jessica C. Kiefte‐de; Kähönen, Mika; Young, Kristin L.; Pedersen, Oluf; Aslibekyan, Stella; Rotter, Jerome I.; Mook‐Kanamori, Dennis O.; Zillikens, M. Carola; Raitakari, Olli T.; North, Kari E.; Overvad, Kim; Arnett, Donna K.; Hofman, Albert; Lehtimäki, Terho; Tjønneland, Anne; Uitterlinden, André G.; Rivadeneira, Fernando; Franco, Oscar H.; German, J. Bruce; Siscovick, David S.; Cupples, L. Adrienne; Ordovás, José M.

doi:10.1002/mnfr.201700347

Cited by 9 publications

(5 citation statements)

References 37 publications

(37 reference statements)

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“…As obesity is a complex, multifactorial condition, some GWAS have integrated demographic factors (such as sex and age 82 ) and environmental factors (such as physical activity 83 , diet 84 or smoking 85 ) into their analyses. Despite sample sizes of more than 200,000 individuals, these genome-wide gene-by-environment (G×E) interaction analyses remain challenging and so far only 12 loci have been identified, the effects of which on obesity are attenuated or exacerbated by non-genetic factors.…”

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confidence: 99%

The genetics of obesity: from discovery to biology

2021

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The prevalence of obesity has tripled over the past four decades, imposing an enormous burden on people's health. Polygenic (or common) obesity and rare, severe, early-onset monogenic obesity are often polarized as distinct diseases. However, gene discovery studies for both forms of obesity show that they have shared genetic and biological underpinnings, pointing to a key role for the brain in the control of body weight. Genome-wide association studies (GWAS) with increasing sample sizes and advances in sequencing technology are the main drivers behind a recent flurry of new discoveries. However, it is the post-GWAS, cross-disciplinary collaborations, which combine new omics technologies and analytical approaches, that have started to facilitate translation of genetic loci into meaningful biology and new avenues for treatment.

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confidence: 99%

The genetics of obesity: from discovery to biology

2021

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“…In traditional GWAS, apart from ignoring the influence of sex, gene-environment interactions were also commonly overlooked [15,16]. Thus, few studies analyzing gene-diet interactions at the GWAS level have been published [17,18,19]. This is, among other factors, due to the large sample size generally required.…”

Section: Introductionmentioning

confidence: 99%

Genome-Wide Association Study (GWAS) on Bilirubin Concentrations in Subjects with Metabolic Syndrome: Sex-Specific GWAS Analysis and Gene-Diet Interactions in a Mediterranean Population

et al. 2019

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Although, for decades, increased serum bilirubin concentrations were considered a threatening sign of underlying liver disease and had been associated with neonatal jaundice, data from recent years show that bilirubin is a powerful antioxidant and suggest that slightly increased serum bilirubin concentrations are protective against oxidative stress-related diseases, such as cardiovascular diseases. Therefore, a better understanding of the gene-diet interactions in determining serum bilirubin concentrations is needed. None of the previous genome-wide association studies (GWAS) on bilirubin concentrations has been stratified by sex. Therefore, considering the increasing interest in incorporating the gender perspective into nutritional genomics, our main aim was to carry out a GWAS on total serum bilirubin concentrations in a Mediterranean population with metabolic syndrome, stratified by sex. Our secondary aim was to explore, as a pilot study, the presence of gene-diet interactions at the GWAS level. We included 430 participants (188 men and 242 women, aged 55–75 years, and with metabolic syndrome) in the PREDIMED Plus-Valencia study. Global and sex-specific GWAS were undertaken to analyze associations and gene-diet interaction on total serum bilirubin. Adherence (low and high) to the Mediterranean diet (MedDiet) was analyzed as the dietary modulator. In the GWAS, we detected more than 55 SNPs associated with serum bilirubin at p < 5 × 10−8 (GWAS level). The top-ranked were four SNPs (rs4148325 (p = 9.25 × 10−24), rs4148324 (p = 9.48 × 10−24), rs6742078 (p = 1.29 × 10−23), rs887829 (p = 1.39 × 10−23), and the rs4148324 (p = 9.48 × 10−24)) in the UGT1A1 (UDP glucuronosyltransferase family 1 member A1) gene, which replicated previous findings revealing the UGT1A1 as the major locus. In the sex-specific GWAS, the top-ranked SNPs at the GWAS level were similar in men and women (the lead SNP was the rs4148324-UGT1A1 in both men (p = 4.77 × 10−11) and women (p = 2.15 × 10−14), which shows homogeneous genetic results for the major locus. There was more sex-specific heterogeneity for other minor genes associated at the suggestive level of GWAS significance (p < 1 × 10−5). We did not detect any gene-MedDiet interaction at p < 1 × 10−5 for the major genetic locus, but we detected some gene-MedDiet interactions with other genes at p < 1 × 10−5, and even at the GWAS level for the IL17B gene (p = 3.14 × 10−8). These interaction results, however, should be interpreted with caution due to our small sample size. In conclusion, our study provides new data, with a gender perspective, on genes associated with total serum bilirubin concentrations in men and women, and suggests possible additional modulations by adherence to MedDiet.

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“…The associations between milk and dairy intake and cardiometabolic health outcomes have been assessed in cohort [ 7 , 8 , 9 ] and cohort meta-analysis [ 10 , 11 , 12 , 13 , 14 , 15 , 16 ] studies and in Mendelian randomization evaluations using SNPs of the MCM6 gene [ 17 , 18 , 19 ]. The results are inconsistent, with some protective associations [ 8 , 13 , 14 , 15 , 16 ], many null-associations [ 10 , 11 , 12 ], and some inverse association [ 9 ] when events, such as total and cause-specific mortality and incident development of various cardiovascular events, were targeted [ 17 ].…”

Section: Introductionmentioning

confidence: 99%

Dairy Product Intake and Cardiometabolic Diseases in Northern Sweden: A 33-Year Prospective Cohort Study

et al. 2019

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Dairy products are important constituents of most diets, and their association with adverse health outcomes remains a focus. We characterized dairy food intake and examined associations with the incidence of type 2 diabetes (T2D), myocardial infarction (MI) or stroke among 108,065 Swedish men and women. Hazard ratios (HRs) and 95% CIs were estimated using the multivariable Cox proportional hazards models in a population characterized by high milk tolerance. During a mean follow-up of 14.2 years, 11,641 first-time events occurred. Non-fermented milk intake decreased, whereas butter intake increased over the period. For high intake of non-fermented milk, the HR (95% CI) for developing T2D and MI was 1.17 (1.03, 1.34) and 1.23 (1.10, 1.37), respectively, in men. A greater intake of butter, fermented milk, and cheese tended to be associated with a reduced risk of T2D and/or MI. Non-consumers and those who chose low-fat variants of the targeted dairy products had increased risk for T2D, MI, or stroke compared to those in the non-case group. Generally, effect-sizes were small. This prospective study found that non-fermented milk was associated with an increased risk for developing T2D and MI and that subjects abstaining from dairy products or choosing low-fat variants were at greater risk. However, the overall cardiometabolic risk of non-fermented milk intake was judged as low, since the effect sizes were small.

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Genome‐Wide Interactions with Dairy Intake for Body Mass Index in Adults of European Descent

Cited by 9 publications

References 37 publications

The genetics of obesity: from discovery to biology

The genetics of obesity: from discovery to biology

Genome-Wide Association Study (GWAS) on Bilirubin Concentrations in Subjects with Metabolic Syndrome: Sex-Specific GWAS Analysis and Gene-Diet Interactions in a Mediterranean Population

Dairy Product Intake and Cardiometabolic Diseases in Northern Sweden: A 33-Year Prospective Cohort Study

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