Hostname: page-component-8448b6f56d-42gr6 Total loading time: 0 Render date: 2024-04-24T17:20:48.228Z Has data issue: false hasContentIssue false
  • English
  • Français

Interaction of polygenetic variants related to inflammation with carbohydrate and vitamin D intakes in middle-aged and older adults in a large hospital-based cohort

Published online by Cambridge University Press:  10 May 2022

Sunmin Park Open the ORCID record for Sunmin Park [Opens in a new window]  and
Suna Kang
Sunmin Park*
Affiliation:
Food and Nutrition, Obesity/Diabetes Research Center, Hoseo University, Asan, Republic of Korea Department of Bio-Convergence System, Hoseo University, Asan 31499, Republic of Korea Yejunbio, Asan 31499, Republic of Korea
Suna Kang
Affiliation:
Food and Nutrition, Obesity/Diabetes Research Center, Hoseo University, Asan, Republic of Korea Yejunbio, Asan 31499, Republic of Korea
*
*Corresponding author: Sunmin Park, email: smpark@hoseo.edu
Get access Rights & Permissions [Opens in a new window]

Abstract

Low-grade subclinical inflammation is interrelated with metabolic diseases, and its susceptibility interacts with genetic and environmental factors. We aimed to examine genetic variants related to a high risk for inflammation using serum C-reactive protein (CRP) concentration, interactions among the genetic variants and the genetic variant interaction with dietary and lifestyle factors in adults. The participants were divided into case and control by serum CRP concentrations: ≥ 0·5 mg/dl (case; n 2018) and < 0·5 mg/dl (control; n 47 185). Genetic variants contributing to high inflammation risk were selected using GWAS after adjusting covariates to influence inflammation, and genetic variant–genetic variant interactions were identified by generalised multifactor dimensionality reduction analysis. Polygenetic-risk scores (PRS) were constructed from the selected genetic variants, and PRS–nutrient interactions for the high inflammation risk were determined. The PRS included CRP_rs1205, OASL_rs3213545, APOE_rs429358, HNF1A_rs1169286, APOC1_rs7256200 and SLC13A3_rs424697. The PRS was positively associated with serum CRP concentration by 2·0 times after adjusting for covariates. The PRS interacted with age: older participants with High-PRS had much higher serum CRP concentrations than those with Low-PRS. Intake of carbohydrates, MUFA and vitamin D exhibited an interaction with PRS for inflammation risk (P < 0·05). In participants with high-carbohydrate/low-fat diets and low vitamin D intakes, those with High-PRS had a higher risk of serum CRP concentrations than those with Low-PRS. In conclusion, the participants with inflammation-related PRS potentially worsened inflammation status, especially in diets with high carbohydrates, low fat (especially MUFA) and low vitamin D. These results can be applied to personalised nutrition to reduce inflammation risk.

Keywords

C-reactive proteinInflammationPolygenetic riskCarbohydratesVitamin D
Type
Research Article
Information
British Journal of Nutrition , Volume 130 , Issue 2 , 28 July 2023 , pp. 331 - 343
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

Slaats, J, Ten Oever, J, van de Veerdonk, FL, et al. (2016) IL-1β/IL-6/CRP and IL-18/ferritin: distinct inflammatory programs in infections. PLoS Pathog 12, e1005973.CrossRefGoogle ScholarPubMed
Toubi, E & Vadasz, Z (2019) Innate immune-responses and their role in driving autoimmunity. Autoimmun Rev 18, 306–311.CrossRefGoogle ScholarPubMed
Barbé-Tuana, F, Funchal, G, Schmitz, CRR, et al. (2020) The interplay between immunosenescence and age-related diseases. Semin Immunopathol 42, 545–557.CrossRefGoogle ScholarPubMed
Custodero, C, Mankowski, RT, Lee, SA, et al. (2018) Evidence-based nutritional and pharmacological interventions targeting chronic low-grade inflammation in middle-age and older adults: a systematic review and meta-analysis. Ageing Res Rev 46, 42–59.CrossRefGoogle ScholarPubMed
Capurso, C, Solfrizzi, V, D’Introno, A, et al. (2007) Interleukin 6 variable number of tandem repeats (VNTR) gene polymorphism in centenarians. Ann Hum Genet 71, 843–848.CrossRefGoogle ScholarPubMed
Nehring, SM, Goyal, A, Bansal, P, et al. (2020) C Reactive Protein (CRP). StatPearls. Treasure Island, FL: StatPearls Publishing.Google Scholar
Mantovani, A, Garlanda, C, Doni, A, et al. (2008) Pentraxins in innate immunity: from C-reactive protein to the long pentraxin PTX3. J Clin Immunol 28, 1–13.CrossRefGoogle Scholar
Koshikawa, M, Harada, M, Noyama, S, et al. (2020) Association between inflammation and skeletal muscle proteolysis, skeletal mass and strength in elderly heart failure patients and their prognostic implications. BMC Cardiovasc Disord 20, 228.CrossRefGoogle ScholarPubMed
Lee, JY, Kim, HA, Huh, K, et al. (2020) Risk factors for mortality and respiratory support in elderly patients hospitalized with COVID-19 in Korea. J na Med Sci 35, e223.Google ScholarPubMed
Best, LG, Balakrishnan, P, Cole, SA, et al. (2019) Genetic analysis of hsCRP in American Indians: the strong heart family study. PLOS ONE 14, e0223574.CrossRefGoogle ScholarPubMed
Dluzniewski, PJ, Wang, MH, Zheng, SL, et al. (2012) Variation in IL10 and other genes involved in the immune response and in oxidation and prostate cancer recurrence. Cancer Epidemiol Biomarkers Prev 21, 1774–1782.CrossRefGoogle ScholarPubMed
Lakoski, SG, Li, L, Langefeld, CD, et al. (2007) The association between innate immunity gene (IRAK1) and C-reactive protein in the Diabetes Heart Study. Exp Mol Pathol 82, 280–283.CrossRefGoogle ScholarPubMed
Ryu, J & Lee, C (2012) Association of glycosylated hemoglobin with the gene encoding CDKAL1 in the Korean Association Resource (KARE) study. Hum Mutat 33, 655–659.CrossRefGoogle ScholarPubMed
Park, S, Ahn, J & Lee, BK (2015) Self-rated subjective health status is strongly associated with sociodemographic factors, lifestyle, nutrient intakes, and biochemical indices, but not smoking status: KNHANES 2007–2012. J na Med Sci 30, 1279–1287.Google Scholar
Daily, JW & Park, S (2017) Interaction of BDNF rs6265 variants and energy and protein intake in the risk for glucose intolerance and type 2 diabetes in middle-aged adults. Nutrition 33, 187–194.CrossRefGoogle ScholarPubMed
Park, S, Daily, JW, Zhang, X, et al. (2016) Interactions with the MC4R rs17782313 variant, mental stress and energy intake and the risk of obesity in Genome Epidemiology Study. Nutr Metab 13, 38.CrossRefGoogle ScholarPubMed
Yoon, K, Ryu, S, Lee, J, et al. (2018) Higher and increased concentration of hs-CRP within the normal range can predict the incidence of metabolic syndrome in healthy men. Diab Metab Syndr 12, 977–983.CrossRefGoogle ScholarPubMed
Park, S, Zhang, X, Lee, NR, et al. (2016) TRPV1 gene polymorphisms are associated with type 2 diabetes by their interaction with fat consumption in the Korean genome epidemiology study. J Nutrigenet Nutrigenom 9, 47–61.Google ScholarPubMed
van Woudenbergh, GJ, Theofylaktopoulou, D, Kuijsten, A, et al. (2013) Adapted dietary inflammatory index and its association with a summary score for low-grade inflammation and markers of glucose metabolism: the Cohort study on Diabetes and Atherosclerosis Maastricht (CODAM) and the Hoorn study. Am J Clin Nutr 98, 1533–1542.CrossRefGoogle Scholar
Park, S & Kang, S (2021) Association between polygenetic risk scores of low immunity and interactions between these scores and moderate fat intake in a large cohort. Nutrients 13, 2849.CrossRefGoogle ScholarPubMed
Liu, M, Jin, HS & Park, S (2020) Protein and fat intake interacts with the haplotype of PTPN11_rs11066325, RPH3A_rs886477, and OAS3_rs2072134 to modulate serum HDL concentrations in middle-aged people. Clin Nutr 39, 942–949.CrossRefGoogle ScholarPubMed
Hwang, J-Y, Lee, HJ, Go, MJ, et al. (2016) An integrative study identifies KCNC2 as a novel predisposing factor for childhood obesity and the risk of diabetes in the Korean population. Sci Rep 6, 33043.CrossRefGoogle ScholarPubMed
Rabbee, N & Speed, TP (2006) A genotype calling algorithm for affymetrix SNP arrays. Bioinf 22, 7–12.Google ScholarPubMed
Uma Jyothi, K & Reddy, BM (2015) Gene-gene and gene–environment interactions in the etiology of type 2 diabetes mellitus in the population of Hyderabad, India. Meta Gene 5, 9–20.CrossRefGoogle ScholarPubMed
Hong, KW, Kim, SH, Zhang, X, et al. (2018) Interactions among the variants of insulin-related genes and nutrients increase the risk of type 2 diabetes. Nutr Res 51, 82–92.CrossRefGoogle ScholarPubMed
Sproston, NR & Ashworth, JJ (2018) Role of C-reactive protein at sites of inflammation and infection. Front Immunol 9, 754–754.CrossRefGoogle ScholarPubMed
Shen, J, Arnett, DK, Parnell, LD, et al. (2008) Association of common C-reactive protein (CRP) gene polymorphisms with baseline plasma CRP levels and fenofibrate response: the GOLDN study. Diabetes Care 31, 910–915.CrossRefGoogle ScholarPubMed
Sheu, WH-H, Wang, W-C, Wu, K-D, et al. (2017) CRP-level-associated polymorphism rs1205 within the CRP gene is associated with 2-hour glucose level: the SAPPHIRE study. Sci Rep 7, 7987.CrossRefGoogle ScholarPubMed
Wypasek, E, Potaczek, DP & Undas, A (2015) Association of the C-Reactive Protein Gene (CRP) rs1205 C > T polymorphism with aortic valve calcification in patients with aortic stenosis. Int J Mol Sci 16, 23745–23759.CrossRefGoogle Scholar
Ali, N (2020) Elevated level of C-reactive protein may be an early marker to predict risk for severity of COVID-19. J Med Virol 92, 2409–2411.CrossRefGoogle ScholarPubMed
Heng, EC, Karsani, SA, Abdul Rahman, M, et al. (2013) Supplementation with tocotrienol-rich fraction alters the plasma levels of Apolipoprotein A-I precursor, Apolipoprotein E precursor, and C-reactive protein precursor from young and old individuals. Eur J Nutr 52, 1811–1820.CrossRefGoogle Scholar
Vuoristo, M, Färkkilä, M, Gylling, H, et al. (1997) Expression and therapeutic response related to apolipoprotein E polymorphism in primary biliary cirrhosis. J Hepatol 27, 136–142.CrossRefGoogle ScholarPubMed
Egert, S, Boesch-Saadatmandi, C, Wolffram, S, et al. (2010) Serum lipid and blood pressure responses to quercetin vary in overweight patients by apolipoprotein E genotype. J Nutr 140, 278–284.CrossRefGoogle ScholarPubMed
Kashima, S, Inoue, K, Matsumoto, M, et al. (2019) White blood cell count and C-reactive protein independently predicted incident diabetes: Yuport medical checkup center study. Endocr Res 44, 127–137.CrossRefGoogle ScholarPubMed
Li, H, Manwani, B & Leng, SX (2011) Frailty, inflammation, and immunity. Aging Dis 2, 466–473.Google ScholarPubMed
Du Clos, TW & Mold, C (2004) C-reactive protein: an activator of innate immunity and a modulator of adaptive immunity. Immunol Res 30, 261–277.CrossRefGoogle Scholar
Park, S, Ahn, J & Lee, BK (2016) Very-low-fat diets may be associated with increased risk of metabolic syndrome in the adult population. Clin Nutr 35, 1159–1167.CrossRefGoogle ScholarPubMed
Park, S & Kang, S (2020) High carbohydrate and noodle/meat-rich dietary patterns interact with the minor haplotype in the 22q13 loci to increase its association with non-alcoholic fatty liver disease risk in Koreans. Nutr Res 82, 88–98.CrossRefGoogle ScholarPubMed
Park, S, Kim, DS & Kang, S (2019) Carrying minor alleles of FADS1 and haplotype of FADS1 and FADS2 increased the risk of metabolic syndrome and moderate but not low-fat diets lowered the risk in two Korean cohorts. Eur J Nutr 58, 831–842.CrossRefGoogle Scholar
Park, S, Ahn, J, Kim, NS, et al. (2017) High carbohydrate diets are positively associated with the risk of metabolic syndrome irrespective to fatty acid composition in women: the KNHANES 2007–2014. Int J Food Sci Nutr 68, 479–487.CrossRefGoogle ScholarPubMed
Park, S, Ham, JO & Lee, BK (2014) A positive association of vitamin D deficiency and sarcopenia in 50 year old women, but not men. Clin Nutr 33, 900–905.CrossRefGoogle Scholar
Siddiqui, M, Manansala, JS, Abdulrahman, HA, et al. (2020) Immune modulatory effects of vitamin D on viral infections. Nutrients 12, 2879.CrossRefGoogle ScholarPubMed
Attaway, AH, Welch, N, Hatipoğlu, U, et al. (2020) Muscle loss contributes to higher morbidity and mortality in COPD: an analysis of national trends. Respirology 26, 62–71.CrossRefGoogle ScholarPubMed
Livshits, G & Kalinkovich, A (2019) Inflammaging as a common ground for the development and maintenance of sarcopenia, obesity, cardiomyopathy, and dysbiosis. Ageing Res Rev 56, 100980.CrossRefGoogle 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.CrossRefGoogle ScholarPubMed