Hostname: page-component-8448b6f56d-tj2md Total loading time: 0 Render date: 2024-04-24T16:37:50.770Z Has data issue: false hasContentIssue false
  • English
  • Français

Interactive effect of the empirical lifestyle index for insulin resistance with the common genetic susceptibility locus rs2423279 for colorectal cancer

Published online by Cambridge University Press:  13 April 2022

Jimi Kim ,
Jeonghee Lee ,
Jae Hwan Oh ,
Hee Jin Chang ,
Dae Kyung Sohn ,
Aesun Shin  and
Jeongseon Kim Open the ORCID record for Jeongseon Kim [Opens in a new window]
Jimi Kim
Affiliation:
Department of Cancer Biomedical Science, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang-Si, Gyeonggi-Do, Goyang 10408, South Korea
Jeonghee Lee
Affiliation:
Department of Cancer Biomedical Science, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang-Si, Gyeonggi-Do, Goyang 10408, South Korea
Jae Hwan Oh
Affiliation:
Center for Colorectal Cancer, National Cancer Center Hospital, National Cancer Center, Goyang-Si, Gyeonggi-Do, South Korea
Hee Jin Chang
Affiliation:
Division of Precision Medicine, Research Institute, Department of Pathology, National Cancer Center Hospital, National Cancer Center, Goyang-Si, Gyeonggi-Do, South Korea
Dae Kyung Sohn
Affiliation:
Center for Colorectal Cancer, National Cancer Center Hospital, National Cancer Center, Goyang-Si, Gyeonggi-Do, South Korea
Aesun Shin
Affiliation:
Department of Preventive Medicine, Seoul National University, College of Medicine, Jongno-Gu, Seoul, South Korea Cancer Research Institute, Seoul National University, Jongno-Gu, Seoul, South Korea
Jeongseon Kim*
Affiliation:
Department of Cancer Biomedical Science, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang-Si, Gyeonggi-Do, Goyang 10408, South Korea
*
*Corresponding author: Dr J. Kim, fax +82 31 920 2576, email jskim@ncc.re.kr
Get access Rights & Permissions [Opens in a new window]

Abstract

The aim of this study is to examine the empirical insulinemic potential consisting of dietary and lifestyle factors and the interactive effect with the common genetic susceptibility locus rs2423279 on the risk of colorectal cancer (CRC). This case–control study was conducted with 923 CRC patients and 1846 controls. The empirical measures for assessing the insulinemic potential, namely, the empirical dietary index for hyperinsulinemia (EDIH), for insulin resistance (EDIR), the empirical lifestyle index for hyperinsulinemia (ELIH), and for insulin resistance (ELIR), were calculated based on semiquantitative food frequency questionnaire and lifestyle questionnaire. A genetic variant of rs2423279 was genotyped. The CRC patients were more likely to score in the highest quartile for the ELIH (OR 2·90, Q4 v. Q1, 95 % CI (2·01, 4·19), P for trend < 0·001), EDIR (OR 3·32, Q4 v. Q1, 95 % CI (2·32, 4·74), P < 0·001) and ELIR (OR 2·79, Q4 v. Q1, 95 % CI (1·96, 3·97), P < 0·001) than the controls. The significant effect between the ELIR, which assesses dietary and lifestyle patterns related to insulin resistance, and C allele carriers of rs2423279 was stronger than that for homozygous T allele carriers (OR 2·50, 95 % CI (1·78, 3·51), P for interaction = 0·034). The empirical insulinemic potential for insulin resistance might have interactive effects with the rs2423279 polymorphism on the risk of CRC. The results of this study suggest the basis of the metabolic impact of the insulin response on colorectal carcinogenesis.

Keywords

Colorectal cancerEmpirical index of insulinemic potentialInsulin resistanceCommon variant for colorectal cancerrs2423279 polymorphism
Type
Research Article
Information
British Journal of Nutrition , Volume 129 , Issue 9 , 14 May 2023 , pp. 1563 - 1573
Check for updates
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of The Nutrition Society

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Sung, H, Ferlay, J, Siegel, RL, et al. (2021) Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 71, 209–249.10.3322/caac.21660CrossRefGoogle ScholarPubMed
Hong, S, Won, YJ, Lee, JJ, et al. (2021) Cancer statistics in Korea: incidence, mortality, survival, and prevalence in 2018. Cancer Res Treat 53, 301–315.10.4143/crt.2021.291CrossRefGoogle ScholarPubMed
Jung, KW, Won, YJ, Hong, S, et al. (2021) Prediction of cancer incidence and mortality in Korea, 2021. Cancer Res Treat 53, 316–322.10.4143/crt.2021.290CrossRefGoogle ScholarPubMed
Clinton, SK, Giovannucci, EL & Hursting, SD (2020) The world cancer research fund/American institute for cancer research third expert report on diet, nutrition, physical activity, and cancer: impact and future directions. J Nutr 150, 663–671.10.1093/jn/nxz268CrossRefGoogle ScholarPubMed
Orgel, E & Mittelman, SD (2013) The links between insulin resistance, diabetes, and cancer. Curr Diab Rep 13, 213–222.10.1007/s11892-012-0356-6CrossRefGoogle ScholarPubMed
Inoue, M & Tsugane, S (2012) Insulin resistance and cancer: epidemiological evidence. Endocr Relat Cancer 19, F1–F8.10.1530/ERC-12-0142CrossRefGoogle ScholarPubMed
Godsland, IF (2009) Insulin resistance and hyperinsulinaemia in the development and progression of cancer. Clin Sci 118, 315–332.CrossRefGoogle ScholarPubMed
Tabung, FK, Wang, W, Fung, TT, et al. (2016) Development and validation of empirical indices to assess the insulinaemic potential of diet and lifestyle. Br J Nutr 116, 1787–1798.10.1017/S0007114516003755CrossRefGoogle ScholarPubMed
Kantor, ED, Hutter, CM, Minnier, J, et al. (2014) Gene–environment interaction involving recently identified colorectal cancer susceptibility Loci. Cancer Epidemiol Biomarkers Prev 23, 1824–1833.10.1158/1055-9965.EPI-14-0062CrossRefGoogle ScholarPubMed
Jia, WH, Zhang, B, Matsuo, K, et al. (2013) Genome-wide association analyses in East Asians identify new susceptibility loci for colorectal cancer. Nat Genet 45, 191–196.10.1038/ng.2505CrossRefGoogle ScholarPubMed
Song, S (2000) Can the glyoxylate pathway contribute to fat-induced hepatic insulin resistance? Med Hypotheses 54, 739–747.10.1054/mehy.1999.0943CrossRefGoogle ScholarPubMed
Nikiforova, VJ, Giesbertz, P, Wiemer, J, et al. (2014) Glyoxylate, a new marker metabolite of type 2 diabetes. J Diabetes Res 2014, 685204.10.1155/2014/685204CrossRefGoogle ScholarPubMed
Ahn, Y, Kwon, E, Shim, JE, et al. (2007) Validation and reproducibility of food frequency questionnaire for Korean genome epidemiologic study. Eur J Clin Nutr 61, 1435–1441.10.1038/sj.ejcn.1602657CrossRefGoogle ScholarPubMed
Willett, WC, Howe, GR & Kushi, LH (1997) Adjustment for total energy intake in epidemiologic studies. Am J Clin Nutr 65, 1220S–1228S.10.1093/ajcn/65.4.1220SCrossRefGoogle ScholarPubMed
Fernandez, CJ, George, AS, Subrahmanyan, NA, et al. (2021) Epidemiological link between obesity, type 2 diabetes mellitus and cancer. World J Methodol 11, 23–45.10.5662/wjm.v11.i3.23CrossRefGoogle ScholarPubMed
Lega, IC & Lipscombe, LL (2020) Review: diabetes, obesity, and cancer-pathophysiology and clinical implications. Endocr Rev 41, bnz014.10.1210/endrev/bnz014CrossRefGoogle ScholarPubMed
Sacerdote, C & Ricceri, F (2018) Epidemiological dimensions of the association between type 2 diabetes and cancer: a review of observational studies. Diabetes Res Clin Pract 143, 369–377.10.1016/j.diabres.2018.03.002CrossRefGoogle Scholar
Ma, Y, Yang, W, Song, M, et al. (2018) Type 2 diabetes and risk of colorectal cancer in two large U.S. prospective cohorts. Br J Cancer 119, 1436–1442.10.1038/s41416-018-0314-4CrossRefGoogle ScholarPubMed
Ali Khan, U, Fallah, M, Sundquist, K, et al. (2020) Risk of colorectal cancer in patients with diabetes mellitus: a Swedish nationwide cohort study. PLoS Med 17, e1003431.10.1371/journal.pmed.1003431CrossRefGoogle ScholarPubMed
Giovannucci, E (2001) Insulin, insulin-like growth factors and colon cancer: a review of the evidence. J Nutr 131, 3109s–3120s.10.1093/jn/131.11.3109SCrossRefGoogle ScholarPubMed
Ma, J, Giovannucci, E, Pollak, M, et al. (2004) A prospective study of plasma C-peptide and colorectal cancer risk in men. J Natl Cancer Inst 96, 546–553.10.1093/jnci/djh082CrossRefGoogle ScholarPubMed
Jenab, M, Riboli, E, Cleveland, RJ, et al. (2007) Serum C-peptide, IGFBP-1 and IGFBP-2 and risk of colon and rectal cancers in the European prospective investigation into cancer and nutrition. Int J Cancer 121, 368–376.10.1002/ijc.22697CrossRefGoogle ScholarPubMed
Farahani, H, Mahmoudi, T, Asadi, A, et al. (2020) Insulin resistance and colorectal cancer risk: the role of elevated plasma resistin levels. J Gastrointest Cancer 51, 478–483.10.1007/s12029-019-00260-7CrossRefGoogle ScholarPubMed
Lee, DH, Li, J, Li, Y, et al. (2020) Dietary inflammatory and insulinemic potential and risk of type 2 diabetes: results from three prospective U.S. cohort studies. Diabetes Care 43, 2675–2683.10.2337/dc20-0815CrossRefGoogle ScholarPubMed
Aroke, D, Folefac, E, Shi, N, et al. (2020) Inflammatory and insulinemic dietary patterns: influence on circulating biomarkers and prostate cancer risk. Cancer Prev Res 13, 841–852.10.1158/1940-6207.CAPR-20-0236CrossRefGoogle ScholarPubMed
Tabung, FK, Noonan, A, Lee, DH, et al. (2020) Post-diagnosis dietary insulinemic potential and survival outcomes among colorectal cancer patients. BMC Cancer 20, 817.CrossRefGoogle ScholarPubMed
Lee, DH, Fung, TT, Tabung, FK, et al. (2019) Dietary pattern and risk of multiple myeloma in two large prospective US cohort studies. JNCI Cancer Spectr 3, pkz025.10.1093/jncics/pkz025CrossRefGoogle ScholarPubMed
Farhadnejad, H, Mokhtari, E, Teymoori, F, et al. (2021) Association of the insulinemic potential of diet and lifestyle with risk of diabetes incident in Tehranian adults: a population based cohort study. Nutr J 20, 39.CrossRefGoogle ScholarPubMed
Yang, W, Sui, J, Zhao, L, et al. (2021) Association of inflammatory and insulinemic potential of diet and lifestyle with risk of hepatocellular carcinoma. Cancer Epidemiol Biomarkers Prev 30, 789–796.10.1158/1055-9965.EPI-20-1329CrossRefGoogle ScholarPubMed
Yue, Y, Hur, J, Cao, Y, et al. (2021) Prospective evaluation of dietary and lifestyle pattern indices with risk of colorectal cancer in a cohort of younger women. Ann Oncol 32, 778–786.CrossRefGoogle Scholar
Steck, SE & Murphy, EA (2020) Dietary patterns and cancer risk. Nat Rev Cancer 20, 125–138.10.1038/s41568-019-0227-4CrossRefGoogle ScholarPubMed
Sieri, S, Krogh, V, Agnoli, C, et al. (2015) Dietary glycemic index and glycemic load and risk of colorectal cancer: results from the EPIC-Italy study. Int J Cancer 136, 2923–2931.10.1002/ijc.29341CrossRefGoogle ScholarPubMed
Shivappa, N, Godos, J, Hébert, JR, et al. (2017) Dietary inflammatory index and colorectal cancer risk-a meta-analysis. Nutrients 9, 1043.CrossRefGoogle ScholarPubMed
Frishberg, Y, Zeharia, A, Lyakhovetsky, R, et al. (2014) Mutations in HAO1 encoding glycolate oxidase cause isolated glycolic aciduria. J Med Genet 51, 526–529.10.1136/jmedgenet-2014-102529CrossRefGoogle ScholarPubMed
Caricasole, A, Sala, C, Roncarati, R, et al. (2000) Cloning and characterization of the human phosphoinositide-specific phospholipase C-β 1 (PLC β 1). Biochim Biophys Acta 1517, 63–72.10.1016/S0167-4781(00)00260-8CrossRefGoogle ScholarPubMed
Komninou, D, Ayonote, A, Richie, JP, et al. (2003) Insulin resistance and its contribution to colon carcinogenesis. Exp Biol Med 228, 396–405.10.1177/153537020322800410CrossRefGoogle ScholarPubMed
Arcidiacono, B, Iiritano, S, Nocera, A, et al. (2012) Insulin resistance and cancer risk: an overview of the pathogenetic mechanisms. Exp Diabetes Res 2012, 789174.CrossRefGoogle ScholarPubMed
Calle, EE & Kaaks, R (2004) Overweight, obesity and cancer: epidemiological evidence and proposed mechanisms. Nat Rev Cancer 4, 579–591.CrossRefGoogle ScholarPubMed
Uzunlulu, M, Caklili, OT & Oguz, A (2016) Association between metabolic syndrome and cancer. Ann Nutr Metab 68, 173–179.10.1159/000443743CrossRefGoogle ScholarPubMed
Obi, K, Ramsey, M, Hinton, A, et al. (2018) Insights into insulin resistance, lifestyle, and anthropometric measures of patients with prior colorectal cancer compared to controls: a national health and nutrition examination survey (NHANES) study. Curr Probl Cancer 42, 276–285.CrossRefGoogle ScholarPubMed
Cowey, S & Hardy, RW (2006) The metabolic syndrome: a high-risk state for cancer? Am J Pathol 169, 1505–1522.CrossRefGoogle ScholarPubMed
Arima, K, Lau, MC, Zhao, M, et al. (2020) Metabolic profiling of formalin-fixed paraffin-embedded tissues discriminates normal colon from colorectal cancer. Mol Cancer Res 18, 883–890.CrossRefGoogle ScholarPubMed
Patra, T, Ghosh, P, Alam, N, et al. (2018) Supra-physiological concentration of glyoxylate inhibits proliferation of human colon cancer cells through oxidative stress. Life Sci 207, 80–89.10.1016/j.lfs.2018.05.047CrossRefGoogle ScholarPubMed
Gaesser, GA (2020) Whole grains, refined grains, and cancer risk: a systematic review of meta-analyses of observational studies. Nutrients 12, 3756.10.3390/nu12123756CrossRefGoogle Scholar
Zhang, X-F, Wang, X-K, Tang, Y-J, et al. (2020) Association of whole grains intake and the risk of digestive tract cancer: a systematic review and meta-analysis. Nutr J 19, 52.10.1186/s12937-020-00556-6CrossRefGoogle Scholar
Park, Y, Subar, AF, Kipnis, V, et al. (2007) Fruit and vegetable intakes and risk of colorectal cancer in the NIH–AARP diet and health study. Am J Epidemiol 166, 170–180.CrossRefGoogle ScholarPubMed
Frugé, AD, Smith, KS, Riviere, AJ, et al. (2021) A dietary intervention high in green leafy vegetables reduces oxidative DNA damage in adults at increased risk of colorectal cancer: biological outcomes of the randomized controlled meat and three greens (M3G) feasibility trial. Nutrients 13, 1220.10.3390/nu13041220CrossRefGoogle ScholarPubMed
Supplementary material: File

Kim et al. supplementary material

Tables S1-S5

Download Kim et al. supplementary material(File)
File 48.8 KB