Appearing in Nature’s ‘Scientific Reports’ the research team reveal a new way of measuring patient intake of milk and dairy products, in which a novel nutritional biomarker was used.
This, the team said could be used to counter the bias found in traditional data collection techniques such as food questionnaires that rely on patient memory and recall.
Together with a series of biochemical, genetic and statistical analyses the team found no association between a greater dairy intake and increase in cardiovascular risk factors, such as raised cholesterol, triglyceride and glucose levels.
The issue has divided opinion with studies yielding mixed results. The accuracy of questionnaire and interview-based estimations in data gathering has been questioned.
It has led to a shift in the use of new biomarkers targeting different foodstuffs that are proving more insightful.
Previous studies using biomarkers of milk intake focused on a different polymorphism — MCM6-rs4988235. Although this biomarker works well in northern European populations, it has proved limited for Mediterranean and non-European populations.
This has meant the association of cardiovascular risk with milk intake is not as strong in these populations, as expressed in the variability of previous study findings.
The team, based at the Spanish Biomedical Research Networking Centre in Physiopathology of Obesity and Nutrition (CIBERobn) in Madrid, used another variation of the MCM6 gene — MCM6-rs3754686 SNP.
This biomarker has been identified as a reliable indicator of lactose tolerance, with strong links with milk intake in the European Mediterranean population, as well as in the white, Afro-American and Hispanic populations.
Food intake data was collated from a total of 20,089 subjects from a number of populations including the Boston Puerto Rican Health Study (BPRHS), and Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) Study.
One other population was included — the Prevention with Mediterranean Diet (PREDIMED) trial. Here a randomised, controlled clinical trial used 7,477 participants (4120 women and 3065 men) to investigate food intake data over five years. Critically, the genetic data of these subjects was available.
By conducting a meta-analysis of the masses of data obtained, along with designing computational methods, the researchers could reliably assess cardiovascular risk with milk intake in the general and sub-group populations.
Mechanism of action
“In this study, we have identified a good biomarker for milk intake in Mediterranean and American populations, the MCM6-rs3754686 SNP,” explained lead author Dr Dolores Corella, also based at CIBERobn.
“We tested the association between this biomarker with milk and dairy intake and found a strong association, mainly for milk, suggesting its suitability in assessing milk intake in Mediterranean and American populations.”
“We also measured milk intake with CVD incidence and total mortality in the PREDIMED study. We found no significant association for the whole population.”
The research referred to a previous study that found the MCM6-rs4988235 biomarker did not predict milk intake in all populations.
Whilst the new biomarker MCM6-rs3754686 greatly added to the study’s insights, the team were unable to explain the ambiguous relationship of the MCM6-rs3754686 biomarker with glucose and lipids.
This complexity was outlined in a Danish study that reported an interaction between milk intake and genes that promote continued digestion of lactose. The study believed these genes were protective against diabetes in milk consumers and tended to increase risk in non-milk consumers.
“In other words, the effect of the genotype depended directly on the intakes of the participants, complicating the reliance on the genotype as a determinant of dietary intake that can predict disease,” the study determined.
Source: Nature/Scientific Reports
Published online ahead of print, doi:10.1038/srep33188
“Associations of the MCM6-rs3754686 proxy for milk intake in Mediterranean and American populations with cardiovascular biomarkers, disease and mortality: Mendelian randomization.”
Authors: Dolores Corella et al.