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A genome-wide association study on confection consumption in a Japanese population: the Japan Multi-Institutional Collaborative Cohort Study

Published online by Cambridge University Press:  26 February 2021

Taro Suzuki
Affiliation:
Department of Food Science and Human Nutrition, Ryukoku University, Otsu, Japan
Yasuyuki Nakamura*
Affiliation:
Yamashina Racto Clinic and Medical Examination Center, Kyoto, Japan Department of Public Health, Shiga University of Medical Science, Otsu, Japan
Yukio Doi
Affiliation:
Department of Food Science and Human Nutrition, Ryukoku University, Otsu, Japan
Akira Narita
Affiliation:
Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
Atsushi Shimizu
Affiliation:
Division of Biomedical Information Analysis, Institute for Biomedical Sciences, Iwate Medical University, Shiwa-gun, Iwate, Japan
Nahomi Imaeda
Affiliation:
Department of Nutrition, Faculty of Wellness, Shigakkan University, Obu, Japan Department of Public Health, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
Chiho Goto
Affiliation:
Department of Public Health, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan Department of Health and Nutrition, School of Health and Human Life, Nagoya Bunri University, Inazawa, Japan
Kenji Matsui
Affiliation:
Division of Bioethics and Healthcare Law, Center for Public Health Sciences, the National Cancer Center, Tokyo, Japan
Aya Kadota
Affiliation:
Department of Public Health, Shiga University of Medical Science, Otsu, Japan Center for Epidemiologic Research in Asia, Shiga University of Medical Science, Otsu, Japan
Katsuyuki Miura
Affiliation:
Department of Public Health, Shiga University of Medical Science, Otsu, Japan Center for Epidemiologic Research in Asia, Shiga University of Medical Science, Otsu, Japan
Masahiro Nakatochi
Affiliation:
Public Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan
Keitaro Tanaka
Affiliation:
Department of Preventive Medicine, Faculty of Medicine, Saga University, Saga, Japan
Megumi Hara
Affiliation:
Department of Preventive Medicine, Faculty of Medicine, Saga University, Saga, Japan
Hiroaki Ikezaki
Affiliation:
Department of Comprehensive General Internal Medicine, Faculty of Medical Sciences, Kyushu University Graduate School, Fukuoka, Japan Department of General Internal Medicine, Kyushu University Hospital, Fukuoka, Japan
Masayuki Murata
Affiliation:
Department of General Internal Medicine, Kyushu University Hospital, Fukuoka, Japan
Toshiro Takezaki
Affiliation:
Department of International Island and Community Medicine, Kagoshima University Graduate School of Medical and Dental Sciences, Kagoshima, Japan
Daisaku Nishimoto
Affiliation:
School of Health Sciences, Faculty of Medicine, Kagoshima University, Kagoshima, Japan
Keitaro Matsuo
Affiliation:
Division of Cancer Epidemiology and Prevention, Aichi Cancer Center, Nagoya, Japan
Isao Oze
Affiliation:
Division of Cancer Epidemiology and Prevention, Aichi Cancer Center, Nagoya, Japan
Nagato Kuriyama
Affiliation:
Department of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine, Kyoto, Japan
Etsuko Ozaki
Affiliation:
Department of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine, Kyoto, Japan
Haruo Mikami
Affiliation:
Cancer Prevention Center, Chiba Cancer Center Research Institute, Chiba, Japan
Yohko Nakamura
Affiliation:
Cancer Prevention Center, Chiba Cancer Center Research Institute, Chiba, Japan
Miki Watanabe
Affiliation:
Department of Public Health, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
Sadao Suzuki
Affiliation:
Department of Public Health, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
Sakurako Katsuura-Kamano
Affiliation:
Department of Preventive Medicine, Institute of Biomedical Sciences, Tokushima University Graduate School, Tokushima, Japan
Kokichi Arisawa
Affiliation:
Department of Preventive Medicine, Institute of Biomedical Sciences, Tokushima University Graduate School, Tokushima, Japan
Kiyonori Kuriki
Affiliation:
Laboratory of Public Health, Division of Nutritional Sciences, School of Food and Nutritional Sciences, University of Shizuoka, Shizuoka, Japan
Yukihide Momozawa
Affiliation:
Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
Michiaki Kubo
Affiliation:
Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
Kenji Takeuchi
Affiliation:
Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
Yoshikuni Kita
Affiliation:
Department of Public Health, Shiga University of Medical Science, Otsu, Japan Faculty of Nursing Science, Tsuruga Nursing University, Tsuruga, Japan
Kenji Wakai
Affiliation:
Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
*
*Corresponding author: Yasuyuki Nakamura, Email nakamura@belle.shiga-med.ac.jp

Abstract

Differences in individual eating habits may be influenced by genetic factors, in addition to cultural, social or environmental factors. Previous studies suggested that genetic variants within sweet taste receptor genes family were associated with sweet taste perception and the intake of sweet foods. The aim of this study was to conduct a genome-wide association study (GWAS) to find genetic variations that affect confection consumption in a Japanese population. We analysed GWAS data on confection consumption using 14 073 participants from the Japan Multi-Institutional Collaborative Cohort study. We used a semi-quantitative FFQ to estimate food intake that was validated previously. Association of the imputed variants with confection consumption was performed by linear regression analysis with adjustments for age, sex, total energy intake and principal component analysis components 1–3. Furthermore, the analysis was repeated adjusting for alcohol intake (g/d) in addition to the above-described variables. We found 418 SNP located in 12q24 that were associated with confection consumption. SNP with the ten lowest P-values were located on nine genes including at the BRAP, ACAD10 and aldehyde dehydrogenase 2 regions on 12q24.12-13. After adjustment for alcohol intake, no variant was associated with confections intake with genome-wide significance. In conclusion, we found a significant number of SNP located on 12q24 genes that were associated with confections intake before adjustment for alcohol intake. However, all of them lost statistical significance after adjustment for alcohol intake.

Type
Full Papers
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of The Nutrition Society

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References

Dias, AG, Eny, KM, Cockburn, M, et al. (2015) Variation in the TAS1R2 gene, sweet taste perception and intake of sugars. J Nutrigenet Nutrigenom 8, 8190.CrossRefGoogle ScholarPubMed
Fushan, AA, Simons, CT, Slack, JP, et al. (2009) Allelic polymorphism within the TAS1R3 promoter is associated with human taste sensitivity to sucrose. Curr Biol 19, 12881293.CrossRefGoogle Scholar
Han, P, Keast, RSJ & Roura, E (2017) Salivary leptin and TAS1R2/TAS1R3 polymorphisms are related to sweet taste sensitivity and carbohydrate intake from a buffet meal in healthy young adults. Br J Nutr 118, 763770.CrossRefGoogle ScholarPubMed
Chamoun, E, Hutchinson, JM, Krystia, O, et al. (2018) Single nucleotide polymorphisms in taste receptor genes are associated with snacking patterns of preschool-aged children in the Guelph Family Health Study: a pilot study. Nutrients 10, 153.CrossRefGoogle Scholar
Knaapila, A, Hwang, LD, Lysenko, A, et al. (2012) Genetic analysis of chemosensory traits in human twins. Chem Senses 37, 869881.CrossRefGoogle ScholarPubMed
Eny, KM, Wolever, TM, Corey, PN, et al. (2010) Genetic variation in TAS1R2 (Ile191Val) is associated with consumption of sugars in overweight and obese individuals in 2 distinct populations. Am J Clin Nutr 92, 15011510.CrossRefGoogle ScholarPubMed
Fushan, AA, Simons, CT, Slack, JP, et al. (2010) Association between common variation in genes encoding sweet taste signaling components and human sucrose perception. Chem Senses 35, 579592.CrossRefGoogle ScholarPubMed
Eny, KM, Wolever, TM, Fontaine-Bisson, B, et al. (2008) Genetic variant in the glucose transporter type 2 is associated with higher intakes of sugars in two distinct populations. Physiol Genomics 33, 355360.CrossRefGoogle ScholarPubMed
Chu, AY, Workalemahu, T, Paynter, NP, et al. (2013) Novel locus including FGF21 is associated with dietary macronutrient intake. Hum Mol Genet 22, 18951902.CrossRefGoogle ScholarPubMed
Holstein-Rathlou, S, Grevengoed, TJ, Christensen, KB, et al. (2017) FGF21 is a sugar-induced hormone associated with sweet intake and preference in humans. Cell Metab 25, 10451053.Google Scholar
Hwang, LD, Lin, C, Gharahkhani, P, et al. (2019) New insight into human sweet taste: a genome-wide association study of the perception and intake of sweet substances. Am J Clin Nutr 109, 17241737.CrossRefGoogle ScholarPubMed
Kawafune, K, Hachiya, T, Nogawa, S, et al. (2020) Strong association between the 12q24 locus and sweet taste preference in the Japanese population revealed by genome-wide meta-analysis. J Hum Genet 65, 939947.CrossRefGoogle ScholarPubMed
Suzuki, T, Nakamura, Y, Matsuo, K, et al. (2020) A genome-wide association study on fish consumption in a Japanese population-the Japan Multi-Institutional Collaborative Cohort study. Eur J Clin Nutr Published online: 07 September 2020. doi: 10.1038/s41430-020-00702-7.Google Scholar
Nakagawa-Senda, H, Hachiya, T, Shimizu, A, et al. (2018) A genome-wide association study in the Japanese population identifies the 12q24 locus for habitual coffee consumption: the J-MICC Study. Sci Rep 8, 1493.CrossRefGoogle ScholarPubMed
Igarashi, M, Nogawa, S, Kawafune, K, et al. (2019) Identification of the 12q24 locus associated with fish intake frequency by genome-wide meta-analysis in Japanese populations. Genes Nutr 14, 21.CrossRefGoogle ScholarPubMed
Hamajima, N (2007) The Japan Multi-Institutional Collaborative Cohort Study (J-MICC Study) to detect gene–environment interactions for cancer. Asian Pac J Cancer Prev 8, 317323.Google ScholarPubMed
Tokudome, S, Goto, C, Imaeda, N, et al. (2004) Development of a data-based short food frequency questionnaire for assessing nutrient intake by middle-aged Japanese. Asian Pac J Cancer Prev 5, 4043.Google ScholarPubMed
Imaeda, N, Fujiwara, N, Tokudome, Y, et al. (2002) Reproducibility of a semi-quantitative food frequency questionnaire in Japanese female dietitians. J Epidemiol 12, 4553.CrossRefGoogle ScholarPubMed
Goto, C, Tokudome, Y, Imaeda, N, et al. (2006) Validation study of fatty acid consumption assessed with a short food frequency questionnaire against plasma concentration in middle-aged Japanese. Scand J Nutr 2, 7782.CrossRefGoogle Scholar
Tokudome, Y, Goto, C, Imaeda, N, et al. (2005) Relative validity of a short food frequency questionnaire for assessing nutrient intake versus three-day weighed diet records in middle-aged Japanese. J Epidemiol 15, 135145.CrossRefGoogle Scholar
Wakai, K (2009) A review of food frequency questionnaires developed and validated in Japan. J Epidemiol 19, 111.CrossRefGoogle ScholarPubMed
Purcell, S, Neale, B, Todd-Brown, K, et al. (2007) PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 81, 559575.CrossRefGoogle ScholarPubMed
Chang, CC, Chow, CC, Tellier, LC, et al. (2015) Second-generation PLINK: rising to the challenge of larger, richer datasets. Gigascience 4, 7.CrossRefGoogle ScholarPubMed
Price, AL, Patterson, NJ, Plenge, RM, et al. (2006) Principal components analysis corrects for stratification in genome-wide association studies. Nature Genet 38, 904909.CrossRefGoogle ScholarPubMed
1000 Genomes Project Consortium, Auton, A, Brooks, LD, et al. (2015) A global reference for human genetic variation. Nature 526, 6874.Google ScholarPubMed
Yamaguchi-Kabata, Y, Nakazono, K, Takahashi, A, et al. (2008) Japanese population structure, based on SNP genotypes from 7003 individuals compared to other ethnic groups: effects on population-based association studies. Am J Hum Genet 83, 445456.CrossRefGoogle ScholarPubMed
Delaneau, O, Marchini, J & Zagury, J (2011) A linear complexity phasing method for thousands of genomes. Nat Methods 9, 179181.CrossRefGoogle Scholar
Das, S, Forer, L, Schnherr, S, et al. (2016) Next-generation genotype imputation service, methods. Nature Genet 48, 12841287.CrossRefGoogle ScholarPubMed
Das, S (2017) DosageConvertor. https://genome.sph.umich.edu/wiki/DosageConvertor (accessed March 2021).Google Scholar
Delongchamp, R, Faramawi, MF, Feingold, E, et al. (2018) The association between SNPs and a quantitative trait: power calculation. Eur J Environ Public Health 2, 17.Google Scholar
Visscher, PM, Wray, NR, Zhang, Q, et al. (2017) 10 years of GWAS discovery: biology, function, and translation. Am J Hum Genet 101, 522.CrossRefGoogle Scholar
Gogarten, SM, Bhangale, T, Conomos, MP, et al. (2012) GWAS Tools: an R/Bioconductor package for quality control and analysis of genome-wide association studies. Bioinformatics 28, 33293331.CrossRefGoogle Scholar
Turner, SD (2014) qqman: an R package for visualizing GWAS results using Q-Q and Manhattan plots. BiorXiv Published online: 14 May 2014. doi: 10.1101/005165.Google Scholar
Pruim, RJ, Welch, RP, Sanna, S, et al. (2010) LocusZoom: regional visualization of genome-wide association scan results. Bioinformatics 26, 23362337.CrossRefGoogle ScholarPubMed
Li, H, Borinskaya, S, Yoshimura, K, et al. (2009) Refined geographic distribution of the oriental ALDH2 × 504Lys (nee 487Lys) Variant. Ann Hum Gen 73, 335345.CrossRefGoogle Scholar
Koganebuchi, K, Haneji, K, Toma, T, et al. (2017) The allele frequency of ALDH2 Glu504Lys and ADH1B Arg47His for the Ryukyu islanders and their history of expansion among East Asians. Am J Hum Biol 29, e22933.CrossRefGoogle ScholarPubMed
Cui, R, Kamatani, Y, Takahashi, A, et al. (2009) Functional variants in ADH1B and ALDH2 coupled with alcohol and smoking synergistically enhance esophageal cancer risk. Gastroenterology 137, 17681775.CrossRefGoogle ScholarPubMed
Takeuchi, F, Isono, M, Nabika, T, et al. (2011) Confirmation of ALDH2 as a major locus of drinking behavior and of its variants regulating multiple metabolic phenotypes in a Japanese population. Circ J 75, 911918.CrossRefGoogle Scholar
Matsuo, K, Hamajima, N, Shinoda, M, et al. (2001) Gene–environment interaction between an aldehyde dehydrogenase-2 (ALDH2) polymorphism, alcohol consumption for the risk of esophageal cancer. Carcinogenesis 22, 913916.CrossRefGoogle ScholarPubMed
NINDS Stroke Genetics Network (SiGN), International Stroke Genetics Consortium (ISGC), Pulit, SL, et al. (2016) The NINDS Stroke Genetics Network: a genome-wide association study of ischemic stroke, its subtypes. Lancet Neurol 15, 174184.CrossRefGoogle Scholar
Lee, J, Lee, Y, Park, B, et al. (2018) Genome-wide association analysis identifies multiple loci associated with kidney disease-related traits in Korean populations. PLoS One 13, e0194044.CrossRefGoogle ScholarPubMed
Kato, N, Loh, M, Takeuchi, F, et al. (2015) Trans-ancestry genome-wide association study identifies 12 genetic loci influencing blood pressure, implicates a role for DNA methylation. Nature Genetics 47, 12821293.CrossRefGoogle ScholarPubMed
Cordell, HJ, Han, Y, Mells, GF, et al. (2015) International genome-wide meta-analysis identifies new primary biliary cirrhosis risk loci and targetable pathogenic pathways. Nat Commun 6, 8019.CrossRefGoogle ScholarPubMed
Takeshima, K, Nishiwaki, Y, Suda, Y, et al. (2017) A missense single nucleotide polymorphism in the ALDH2 gene, rs671, is associated with hip fracture. Sci Rep 7, 428.CrossRefGoogle ScholarPubMed
Kesse, E, Clavel-Chapelon, F, Slimani, N, et al. (2001) Do eating habits differ according to alcohol consumption? Results of a study of the French cohort of the European Prospective Investigation into Cancer and Nutrition (E3N-EPIC). Am J Clin Nutr 74, 322327.CrossRefGoogle Scholar
Okada, Y, Momozawa, Y, Sakaue, S, et al. (2018) Deep whole-genome sequencing reveals recent selection signatures linked to evolution and disease risk of Japanese. Nat Commun 9, 1631.CrossRefGoogle ScholarPubMed
Wang, X, Ouyang, Y, Liu, J, et al. (2014) Fruit and vegetable consumption and mortality from all causes, cardiovascular disease, and cancer: systematic review and dose-response meta-analysis of prospective cohort studies. BMJ 349, 114.CrossRefGoogle ScholarPubMed
Aune, D, Giovannucci, E, Boffetta, P, et al. (2017) Fruit and vegetable intake and the risk of cardiovascular disease, total cancer and all-cause mortality-a systematic review and dose-response meta-analysis of prospective studies. Int J Epidemiol 46, 10291056.CrossRefGoogle ScholarPubMed
Malik, VS, Popkin, BM, Bray, GA, et al. (2010) Sugar-sweetened beverages, risk of metabolic syndrome, type 2 diabetes: a meta-analysis. Diabetes Care 33, 24772483.CrossRefGoogle ScholarPubMed
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