The association of fish consumption and its urinary metabolites with cardiovascular risk factors: the International Study of Macro-/Micronutrients and Blood Pressure (INTERMAP)

Rachel Gibson, Chung-Ho E Lau, Ruey Leng Loo, Timothy M D Ebbels, Elena Chekmeneva, Alan R Dyer, Katsuyuki Miura, Hirotsugu Ueshima, Liancheng Zhao, Martha L Daviglus, Jeremiah Stamler, Linda Van Horn, Paul Elliott, Elaine Holmes, Queenie Chan, Rachel Gibson, Chung-Ho E Lau, Ruey Leng Loo, Timothy M D Ebbels, Elena Chekmeneva, Alan R Dyer, Katsuyuki Miura, Hirotsugu Ueshima, Liancheng Zhao, Martha L Daviglus, Jeremiah Stamler, Linda Van Horn, Paul Elliott, Elaine Holmes, Queenie Chan

Abstract

Background: Results from observational studies regarding associations between fish (including shellfish) intake and cardiovascular disease risk factors, including blood pressure (BP) and BMI, are inconsistent.

Objective: To investigate associations of fish consumption and associated urinary metabolites with BP and BMI in free-living populations.

Methods: We used cross-sectional data from the International Study of Macro-/Micronutrients and Blood Pressure (INTERMAP), including 4680 men and women (40-59 y) from Japan, China, the United Kingdom, and United States. Dietary intakes were assessed by four 24-h dietary recalls and BP from 8 measurements. Urinary metabolites (2 timed 24-h urinary samples) associated with fish intake acquired from NMR spectroscopy were identified. Linear models were used to estimate BP and BMI differences across categories of intake and per 2 SD higher intake of fish and its biomarkers.

Results: No significant associations were observed between fish intake and BP. There was a direct association with fish intake and BMI in the Japanese population sample (P trend = 0.03; fully adjusted model). In Japan, trimethylamine-N-oxide (TMAO) and taurine, respectively, demonstrated area under the receiver operating characteristic curve (AUC) values of 0.81 and 0.78 in discriminating high against low fish intake, whereas homarine (a metabolite found in shellfish muscle) demonstrated an AUC of 0.80 for high/nonshellfish intake. Direct associations were observed between urinary TMAO and BMI for all regions except Japan (P < 0.0001) and in Western populations between TMAO and BP (diastolic blood pressure: mean difference 1.28; 95% CI: 0.55, 2.02 mmHg; P = 0.0006, systolic blood pressure: mean difference 1.67; 95% CI: 0.60, 2.73 mmHg; P = 0.002).

Conclusions: Urinary TMAO showed a stronger association with fish intake in the Japanese compared with the Western population sample. Urinary TMAO was directly associated with BP in the Western but not the Japanese population sample. Associations between fish intake and its biomarkers and downstream associations with BP/BMI appear to be context specific. INTERMAP is registered at www.clinicaltrials.gov as NCT00005271.

Keywords: INTERMAP metabolomics; biomarkers; blood pressure; body mass index; fish; homarine; hypertension; metabonomics; seafood; shellfish.

Copyright © The Author(s) 2019.

Figures

FIGURE 1
FIGURE 1
NMR spectral variables correlating to fish intake. Partial correlation analyses of total fish intake were performed. Fish intake was correlated against each NMR intensity variable using the combined sample population from 4 countries and analyses were adjusted for age, sex, and center. Analyses were performed on first and repeat visit samples independently. Bonferroni threshold was used for multiple testing corrections (P threshold = 7×10−6) with repeat visit samples used as validation set. Upper panel: median spectrum of first visit samples with significantly correlated NMR variable annotated/highlighted in red. Lower panel: Manhattan plot showing signed -log10(P) indicates the level of significance of the correlating NMR variables. Significantly correlated NMR variables were annotated/highlighted in red. r: partial correlation coefficient. 1: 3-methyladipic acid; 2: 3-hydroxyisobutyrate; 3: ethyl glucuronide; 4: N-acetyl neuraminate; 5: pyroglutamate; 6: dimethylamine; 7: creatine; 8: trimethyllysine; 9: trimethylamine N-oxide; 10: taurine; 11: theophylline; 12: homarine.
FIGURE 2
FIGURE 2
Receiver operating characteristic (ROC) curves were used to assess the predictive ability of urinary metabolites of interest in discriminating total fish intake (including shellfish) and separately for shellfish only. A) Panels illustrate by country the ability of urinary metabolites of interest in discriminating high fish intake from nonfish consumers (China, USA, UK) and low fish intake from nonfish consumers (Japan) using samples from the first visit. N = 753 (Japan), N = 757 (China), N = 1777 (USA), N = 409 (UK). Japan: consumers of high fish intake N = 380, consumers of low fish intake N = 373; China: consumers of high fish intake N = 73, nonconsumers N = 684; USA: consumers of high fish intake N = 384, nonconsumers N = 1393; UK: consumers of high fish intake N = 72, nonconsumers N = 337. B) Panel illustrates the ability of urinary metabolites of interest in discriminating high shellfish intake from nonconsumers of shellfish (Japan only). Analysis was independently performed for first and repeat visit urine samples. TMAO, trimethylamine-N-oxide.

References

    1. Weichselbaum E, Coe S, Buttriss J, Stanner S. Fish in the diet: a review. Nutr Bull. 2013;38:128–77.
    1. Trichopoulou A, Costacou T, Bamia C, Trichopoulos D. Adherence to a Mediterranean diet and survival in a Greek population. N Engl J Med. 2003;348(26):2599–608.
    1. Calton EK, James AP, Pannu PK, Soares MJ. Certain dietary patterns are beneficial for the metabolic syndrome: reviewing the evidence. Nutr Res. 2014;34(7):559–68.
    1. US Department of Health and Human Services and US Department of Agriculture. 2015–2020 Dietary Guidelines for Americans [Internet]. 8th ed December 2015. Available from: .
    1. Van Horn L, Carson JA, Appel LJ, Burke LE, Economos C, Karmally W, Lancaster K, Lichtenstein AH, Johnson RK, Thomas RJ et al. .. Recommended dietary pattern to achieve adherence to the American Heart Association/American College of Cardiology (AHA/ACC) guidelines: a scientific statement from the American Heart Association. Circulation. 2016;134(22):e505–e29.
    1. Pauletto P, Puato M, Caroli MG, Casiglia E, Munhambo AE, Cazzolato G, Bittolo Bon G, Angeli MT, Galli C, Pessina AC. Blood pressure and atherogenic lipoprotein profiles of fish-diet and vegetarian villagers in Tanzania: the Lugalawa study. Lancet. 1996;348(9030):784–8.
    1. Yang B, Shi MQ, Li ZH, Yang JJ, Li D. Fish, long-chain n-3 PUFA and incidence of elevated blood pressure: a meta-analysis of prospective cohort studies. Nutrients. 2016;8(1):58.
    1. Chowdhury R, Stevens S, Gorman D, Pan A, Warnakula S, Chowdhury S, Ward H, Johnson L, Crowe F, Hu FB et al. .. Association between fish consumption, long chain omega 3 fatty acids, and risk of cerebrovascular disease: systematic review and meta-analysis. BMJ. 2012;345:e6698.
    1. Schmedes M, Aadland EK, Sundekilde UK, Jacques H, Lavigne C, Graff IE, Eng O, Holthe A, Mellgren G, Young JF et al. .. Lean-seafood intake decreases urinary markers of mitochondrial lipid and energy metabolism in healthy subjects: metabolomics results from a randomized crossover intervention study. Mol Nutr Food Res. 2016;60(7):1661–72.
    1. Jakobsen MU, Dethlefsen C, Due KM, May AM, Romaguera D, Vergnaud AC, Norat T, Sorensen TI, Halkjaer J, Tjonneland A et al. .. Fish consumption and subsequent change in body weight in European women and men. Br J Nutr. 2013;109(2):353–62.
    1. Jakobsen MU, Due KM, Dethlefsen C, Halkjaer J, Holst C, Forouhi NG, Tjonneland A, Boeing H, Buijsse B, Palli D et al. .. Fish consumption does not prevent increase in waist circumference in European women and men. Br J Nutr. 2012;108(5):924–31.
    1. Jayedi A, Shab-Bidar S, Eimeri S, Djafarian K. Fish consumption and risk of all-cause and cardiovascular mortality: a dose-response meta-analysis of prospective observational studies. Public Health Nutr. 2018;21(7):1297–306.
    1. Mancano G, Mora-Ortiz M, Claus SP. Recent developments in nutrimetabolomics: from food characterisation to disease prevention. Curr Opin Food Sci. 2018;22:145–52.
    1. Brennan L. Metabolomics: a tool to aid dietary assessment in nutrition. Curr Opin Food Sci. 2017;16:96–9.
    1. Guertin KA, Moore SC, Sampson JN, Huang WY, Xiao Q, Stolzenberg-Solomon RZ, Sinha R, Cross AJ. Metabolomics in nutritional epidemiology: identifying metabolites associated with diet and quantifying their potential to uncover diet-disease relations in populations. Am J Clin Nutr. 2014;100(1):208–17.
    1. Turunen AW, Mannisto S, Kiviranta H, Marniemi J, Jula A, Tiittanen P, Suominen-Taipale L, Vartiainen T, Verkasalo PK. Dioxins, polychlorinated biphenyls, methyl mercury and omega-3 polyunsaturated fatty acids as biomarkers of fish consumption. Eur J Clin Nutr. 2010;64(3):313–23.
    1. Mori M, Mori H, Hamada A, Yamori Y. Taurine in morning spot urine for the useful assessment of dietary seafood intake in Japanese children and adolescents. J Biomed Sci. 2010;17(Suppl 1):S43.
    1. Kruger R, Merz B, Rist MJ, Ferrario PG, Bub A, Kulling SE, Watzl B. Associations of current diet with plasma and urine TMAO in the KarMeN study: direct and indirect contributions. Mol Nutr Food Res. 2017;61(11). doi:10.1002/mnfr.201700363.
    1. Lloyd AJ, Fave G, Beckmann M, Lin W, Tailliart K, Xie L, Mathers JC, Draper J. Use of mass spectrometry fingerprinting to identify urinary metabolites after consumption of specific foods. Am J Clin Nutr. 2011;94(4):981–91.
    1. Cheung W, Keski-Rahkonen P, Assi N, Ferrari P, Freisling H, Rinaldi S, Slimani N, Zamora-Ros R, Rundle M, Frost G et al. .. A metabolomic study of biomarkers of meat and fish intake. Am J Clin Nutr. 2017;105(3):600–8.
    1. Kohashi N, Katori R.. Decrease of urinary taurine in essential-hypertension. Jpn Heart J. 1983;24(1):91–102.
    1. Mizushima S, Moriguchi EH, Ishikawa P, Hekman P, Nara Y, Mimura G, Moriguchi Y, Yamori Y. Fish intake and cardiovascular risk among middle-aged Japanese in Japan and Brazil. J Cardiovasc Risk. 1997;4(3):191–9.
    1. Sagara M, Murakami S, Mizushima S, Liu LJ, Mori M, Ikeda K, Nara Y, Yamori Y. Taurine in 24-h urine samples is inversely related to cardiovascular risks of middle aged subjects in 50 populations of the world. Adv Exp Med Biol. 2015;803:623–36.
    1. Manor O, Zubair N, Conomos MP, Xu X, Rohwer JE, Krafft CE, Lovejoy JC, Magis AT. A multi-omic association study of trimethylamine N-oxide. Cell Rep. 2018;24(4):935–46.
    1. Papandreou C, Bullo M, Zheng Y, Ruiz-Canela M, Yu E, Guasch-Ferre M, Toledo E, Clish C, Corella D, Estruch R et al. .. Plasma trimethylamine-N-oxide and related metabolites are associated with type 2 diabetes risk in the Prevencion con Dieta Mediterranea (PREDIMED) trial. Am J Clin Nutr. 2018;108(1):163–73.
    1. Stamler J, Elliott P, Dennis B, Dyer AR, Kesteloot H, Liu K, Ueshima H, Zhou BF. INTERMAP: background, aims, design, methods, and descriptive statistics (nondietary). J Hum Hypertens. 2003;17(9):591–608.
    1. Dennis B, Stamler J, Buzzard M, Conway R, Elliott P, Moag-Stahlberg A, Okayama A, Okuda N, Robertson C, Robinson F et al. .. INTERMAP: the dietary data – process and quality control. J Hum Hypertens. 2003;17(9):609–22.
    1. Willett WC, Howe GR, Kushi LH. Adjustment for total energy intake in epidemiologic studies. Am J Clin Nutr. 1997;65(4 Suppl):1220S–8S.
    1. Dyer AR, Elliott P, Shipley M. Urinary electrolyte excretion in 24 hours and blood pressure in the INTERSALT Study: II. Estimates of electrolyte-blood pressure associations corrected for regression dilution bias. Am J Epidemiol. 1994;139(9):940–51.
    1. Grandits GA, Bartsch GE, Stamler J. Method issues in dietary data analyses in the Multiple Risk Factor Intervention Trial. Am J Clin Nutr. 1997;65(1):211S–27S.
    1. Holmes E, Loo RL, Stamler J, Bictash M, Yap IKS, Chan Q, Ebbels T, De Iorio M, Brown IJ, Veselkov KA et al. .. Human metabolic phenotype diversity and its association with diet and blood pressure. Nature. 2008;453(7193):396–400.
    1. Loo RL, Coen M, Ebbels T, Cloarec O, Maibaum E, Bictash M, Yap I, Elliott P, Stamler J, Nicholson JK et al. .. Metabolic profiling and population screening of analgesic usage in nuclear magnetic resonance spectroscopy-based large-scale epidemiologic studies. Anal Chem. 2009;81(13):5119–29.
    1. Dumas M, Maibaum EC, Teague C, Ueshima H, Zhou B, Lindon JC, Nicholson JK, Stamler J, Elliott P, Chan Q et al. .. Assessment of analytical reproducibility of 1H NMR spectroscopy based metabonomics for large-scale epidemiological research: the INTERMAP Study. Anal Chem. 2006;78(7):2199–208.
    1. Elliott P, Posma JM, Chan Q, Garcia-Perez I, Wijeyesekera A, Bictash M, Ebbels TMD, Ueshima H, Zhao L, van Horn L et al. .. Urinary metabolic signatures of human adiposity. Sci Transl Med. 2015;7(285):285ra62.
    1. Robin X, Turck N, Hainard A, Tiberti N, Lisacek F, Sanchez J-C, Müller M. pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics. 2011;12(77).
    1. Tobin MD, Sheehan NA, Scurrah KJ, Burton PR. Adjusting for treatment effects in studies of quantitative traits: antihypertensive therapy and systolic blood pressure. Stat Med. 2005;24(19):2911–35.
    1. Alhassan A, Young J, Lean MEJ, Lara J. Consumption of fish and vascular risk factors: a systematic review and meta-analysis of intervention studies. Atherosclerosis. 2017;266:87–94.
    1. Lara JJ, Economou M, Wallace AM, Rumley A, Lowe G, Slater C, Caslake M, Sattar N, Lean ME. Benefits of salmon eating on traditional and novel vascular risk factors in young, non-obese healthy subjects. Atherosclerosis. 2007;193(1):213–21.
    1. Cottin SC, Sanders TA, Hall WL. The differential effects of EPA and DHA on cardiovascular risk factors. Proc Nutr Soc. 2011;70(2):215–31.
    1. Sakurai M, Stamler J, Miura K, Brown IJ, Nakagawa H, Elliott P, Ueshima H, Chan Q, Tzoulaki I, Dyer AR et al. .. Relationship of dietary cholesterol to blood pressure: the INTERMAP study. J Hypertens. 2011;29(2):222–8.
    1. Lin MH, Lu SC, Huang PC, Liu YC, Liu SY. The amount of dietary cholesterol changes the mode of effects of (n-3) polyunsaturated fatty acid on lipoprotein cholesterol in hamsters. Ann Nutr Metab. 2004;48(5):321–8.
    1. Nishimura T, Murakami K, Livingstone MB, Sasaki S, Uenishi K. Japan Dietetic Students' Study for N, Biomarkers G. Adherence to the food-based Japanese dietary guidelines in relation to metabolic risk factors in young Japanese women. Br J Nutr. 2015;114(4):645–53.
    1. Wang SS, Lay S, Yu HN, Shen SR. Dietary guidelines for Chinese residents (2016): comments and comparisons. J Zhejiang Univ Sci B. 2016;17(9):649–56.
    1. Public Health England. The Eatwell Guide. Version 28 January2019; [Internet]. Available from: (accessed 1 May 2019).
    1. Oude Griep LM, Seferidi P, Stamler J, Van Horn L, Chan Q, Tzoulaki I, Steffen LM, Miura K, Ueshima H, Okuda N et al. .. Relation of unprocessed, processed red meat and poultry consumption to blood pressure in East Asian and Western adults. J Hypertens. 2016;34(9):1721–9.
    1. Netherton JC 3rd, Gurin S. Biosynthesis and physiological role of homarine in marine shrimp. J Biol Chem. 1982;257(20):11971–5.
    1. Polychronopoulos P, Magiatis P, Skaltsounis A-L, Tillequin F, Vardala-Theodorou E, Tsarbopoulos A. Hormarine, a common metabolite in edible Mediterranean molluscs: occurrence, spectral data and revision of related structure. Natural Product Letters. 2001;15(6):411–8.
    1. Wojcik OP, Koenig KL, Zeleniuch-Jacquotte A, Costa M, Chen Y. The potential protective effects of taurine on coronary heart disease. Atherosclerosis. 2010;208(1):19–25.
    1. Waldron M, Patterson SD, Tallent J, Jeffries O. The effects of oral taurine on resting blood pressure in humans: a meta-analysis. Curr Hypertens Rep. 2018;20(9):81.
    1. Kim KS, Jang MJ, Fang S, Yoon SG, Kim IY, Seong JK, Yang HI, Hahm DH. Anti-obesity effect of taurine through inhibition of adipogenesis in white fat tissue but not in brown fat tissue in a high-fat diet-induced obese mouse model. Amino Acids. 2019;51(2):245–54.
    1. Svensson BG, Akesson B, Nilsson A, Paulsson K. Urinary excretion of methylamines in men with varying intake of fish from the Baltic Sea. J Toxicol Environ Health. 1994;41(4):411–20.
    1. Rath S, Heidrich B, Pieper DH, Vital M. Uncovering the trimethylamine-producing bacteria of the human gut microbiota. Microbiome. 2017;5(1):54.
    1. Cho CE, Taesuwan S, Malysheva OV, Bender E, Tulchinsky NF, Yan J, Sutter JL, Caudill MA. Trimethylamine-N-oxide (TMAO) response to animal source foods varies among healthy young men and is influenced by their gut microbiota composition: a randomized controlled trial. Mol Nutr Food Res. 2017;61(1). doi: 10.1002/mnfr.201600324.
    1. Koliada A, Syzenko G, Moseiko V, Budovska L, Puchkov K, Perederiy V, Gavalko Y, Dorofeyev A, Romanenko M, Tkach S et al. .. Association between body mass index and Firmicutes/Bacteroidetes ratio in an adult Ukrainian population. BMC Microbiol. 2017;17(1):120.
    1. Conlon MA, Bird AR.. The impact of diet and lifestyle on gut microbiota and human health. Nutrients. 2014;7(1):17–44.
    1. Elliott P, Posma JM, Chan Q, Garcia-Perez I, Wijeyesekera A, Bictash M, Ebbels TM, Ueshima H, Zhao L, van Horn L et al. .. Urinary metabolic signatures of human adiposity. Sci Transl Med. 2015;7(285):285ra62.
    1. Yu D, Shu XO, Rivera ES, Zhang X, Cai Q, Calcutt MW, Xiang YB, Li H, Gao YT, Wang TJ et al. .. Urinary levels of trimethylamine-N-oxide and incident coronary heart disease: a prospective investigation among urban Chinese adults. J Am Heart Assoc. 2019;8(1):e010606.
    1. Kelly RH, Yancey PH. High contents of trimethylamine oxide correlating with depth in deep-sea teleost fishes, skates, and decapod crustaceans. Biol Bull. 1999;196(1):18–25.
    1. Kim YS, Xun P, Iribarren C, Van Horn L, Steffen L, Daviglus ML et al. .. Intake of fish and long-chain omega-3 polyunsaturated fatty acids and incidence of metabolic syndrome among American young adults: a 25-year follow-up study. Eur J Nutr. 2016;55(4):1707–16.

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