Evaluating Fish and Cardiovascular Health Using 1H-NMR

It is commonly known that one of the healthiest foods is fish due to its high protein and the fact it contains numerous important nutrients, like iodine, selenium, and vitamin D. Additionally, it is a source of long-chain omega-3 polyunsaturated fatty acids (3-PUFAs) that are essential for brain function and cardiovascular health1.

It is recommended that fish should be frequently included in the diet to keep cardiovascular disease risk factors at a minimum2. Yet, observational study results do not offer an obvious association between fish intake and cardiovascular disease risk factors, like blood pressure and body mass index (BMI).

Further research is required for the accurate definition of the effect of dietary fish on cardiovascular risk.

Cardiovascular health and fish

The advantageous cardioprotective effects of a fish diet were initially described in a research study in Tanzania3. Results showed lower incidences of hypertension among subjects consuming 300–600 g of freshwater fish per day in comparison with those on a vegetarian diet.

However, meta-analyses of the data from prospective studies have shown varying results with regards to the cardiovascular advantages of dietary fish consumption. One study stated that dietary fish intake consistently lowered blood pressure4. Additional studies demonstrated that dietary fish did not affect blood pressure, although higher n–3 PUFA levels were related with reduced blood pressure5.

Further to this, mitochondrial efficiency has been indicated to increase with lean fish intake, which in turn has the potential to promote lipid catabolism6. However, no studies have been reported regarding the effects of fish consumption on body weight.

There are numerous data showing an advantageous effect of fish consumption on cardiovascular risk, but there is a requirement for objective biomarkers of fish intake to deliver consistency and allow comparison and consolidation of data between studies7.

Metabolic profiling

The method most frequently used to enable the identification of objective biomarkers for the effects of diet is called metabolic profiling8.

Defining metabolic markers of fish consumption could allow the collation of increasingly robust data with and without fish consumption, which has the potential to explain the underlying mechanisms leading to positive cardiovascular health outcomes. Specifically, it would be useful to have urinary biomarkers of fish consumption to allow non-invasive monitoring during observational studies.

Many serum biomarkers for fish consumption have been determined, with 3-PUFAs, polychlorinated biphenyls, and methyl mercury as metabolic markers9. However, additional research is required to verify urinary biomarkers. Some studies have suggested trimethylamine-N-oxide (TMAO), taurine, and 1-methylhistidine as possible urinary biomarkers of fish consumption, but further confirmatory data specifying the exact relationship are needed10,11.

NMR evaluation of the effects of fish intake

Recently, the associations between fish consumption, urinary metabolites and cardiovascular markers have been assessed in nearly 5000 men and women aged 40–59 years. They were participants in the International Study of Macro-/Micronutrients and Blood Pressure (INTERMAP) study (NCT00005271)12.

Proton nuclear magnetic spectroscopy (1H-NMR) was completed on 24-hour urine samples with a Bruker Avance IVDr system and after the standardized SOPs for urine analysis. Fish consumption was established from four 24-hour dietary diaries and blood pressure, height and weight were reported eight times.

Three major urinary metabolites linked with fish consumption were determined; TMAO, homarine, and taurine. Although the data gained in this research verify that TMAO is a urinary biomarker of fish consumption, it is important to be cautious because TMAO can also be an indirect urinary biomarker of red meat and egg intake. It is created through the oxidation of trimethylamine, which is released by gut microbiota throughout the metabolism of meat and eggs.

Fish consumption was not identified to have a significant effect on blood pressure. Body mass index (BMI) was revealed to have a direct link with fish consumption among participants from Japan. Remarkably, the opposite was seen for urinary TMAO, which was directly linked with BMI for participants from all regions apart from Japan.

Similar to this, a link between TMAO and diastolic blood pressure was identified among Western populations but not in Japan. Therefore, it is suggestive that links between fish consumption and its biomarkers and health outcomes, like blood pressure and BMI, seem to be context specific. Additional investigations are required into such region-specific differences in order to establish whether they arise because of variances in dietary patterns and/or gut microbiota.

The observed direct link between fish consumption and BMI in the Japanese population sample is in contrast to previous results from European studies and may exemplify an effect of ethnicity or regional differences in measurement methods.

Additionally,, the most recent research determined homarine as a new potential urinary biomarker of shellfish consumption. Homarine is a metabolite originating from the muscle of shellfish. This result needs further validation in future observational studies and controlled feeding studies. If this observation can be repeated and validated in upcoming studies, contributions will be made towards the progressive development in the detection of objective dietary biomarkers.

References

  1. Weichselbaum E, et al. Nutr Bull 2013;38:128–177.
  2. Van Horn L, et al. Circulation 2016;134(22):e505–e529.
  3. Pauletto P, et al. Lancet 1996;348(9030):784–788.
  4. Chowdhury R, et al. BMJ 2012;345:e6698
  5. Yang B, Shi MQ, Li ZH, Yang JJ, Li D. Nutrients 2016;8(1):58.
  6. Schmedes M, et al. Mol Nutr Food Res 2016;60(7):1661–1672.
  7. Jayedi A, et al. Public Health Nutr 2018;21(7):1297–1306.
  8. Mancano G, et al. Curr Opin Food Sci 2018;22:145–152.
  9. Guertin KA, et al. Am J Clin Nutr 2014;100(1):208–217.
  10. Sagara M, et al. Adv Exp Med Biol 2015;803:623–636.
  11. Manor O, et al. Cell Rep 2018;24(4):935–946.
  12. Gibson R, et al. Am J Clin Nutr 2020;111:280–290. https://academic.oup.com/ajcn/article/111/2/280/5645625

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Last updated: Jun 10, 2020 at 11:18 AM

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