A Dietary Biomarker Approach Captures Compliance and Cardiometabolic Effects of a Healthy Nordic Diet in Individuals with Metabolic Syndrome

Abstract

Assessment of compliance with dietary interventions is necessary to understand the observed magnitude of the health effects of the diet per se. To avoid reporting bias, different dietary biomarkers (DBs) could be used instead of self-reported data. However, few studies investigated a combination of DBs to assess compliance and its influence on cardiometabolic risk factors. The objectives of this study were to use a combination of DBs to assess compliance and to investigate how a healthy Nordic diet (ND) influences cardiometabolic risk factors in participants with high apparent compliance compared with the whole study population. From a recently conducted isocaloric randomized trial, SYSDIET (Systems Biology in Controlled Dietary Interventions and Cohort Studies), in 166 individuals with metabolic syndrome, several DBs were assessed to reflect different key components of the ND: canola oil (serum phospholipid α-linolenic acid), fatty fish [eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA)], vegetables (plasma β-carotene), and whole grains (plasma alkylresorcinols). High-fat dairy intake (expectedly low in the ND) was reflected by serum pentadecanoic acid. All participants with biomarker data (n = 154) were included in the analyses. Biomarkers were combined by using a biomarker rank score (DB score) and principal component analysis (PCA). The DB score was then used to assess compliance. During the intervention, median concentrations of alkylresorcinols, α-linolenic acid, EPA, and DHA were >25% higher in the ND individuals than in the controls (P < 0.05), whereas median concentrations of pentadecanoic acid were 14% higher in controls (P < 0.05). Median DB score was 57% higher in the ND than in controls (P < 0.001) during the intervention, and participants were ranked similarly by DB score and PCA score. Overall, estimates of group difference in cardiometabolic effects generally appeared to be greater among compliant participants than in the whole study population (e.g., estimates of treatment effects on blood pressure and lipoproteins were ∼1.5- to 2-fold greater in the most compliant participants), suggesting that poor compliance attenuated the dietary effects. With adequate consideration of their limitations, DB combinations (e.g., DB score) could be useful for assessing compliance in intervention studies investigating cardiometabolic effects of healthy dietary patterns. The study was registered at clinicaltrials.gov as NCT00992641.

Healthy Nordic diet and cardiovascular disease

“…apples), vegetables, root vegetables and legumes . Controlled trials conducted in various Nordic populations have shown that healthy Nordic diets cause reduction in several key cardiovascular disease (CVD) risk factors . Overall, the reductions in risk factors were of similar magnitude as those previously reported for, for example, Mediterranean and dietary approach to stop hypertension (DASH) diets .…”

Milk fat biomarkers and cardiometabolic disease

“…For example, when butter and other dairy products are iso-calorically replaced with vegetable fats, there is a reduction of 15 : 0 and 17 : 0 in circulating lipids [25–29]. In addition, in mixed diets, which either increase or decrease of dairy fats, such intake variations are reflected by changes in circulating OCFAs [30–32]. Although these results support the use of 15 : 0 as dairy fat biomarker, the precise dose–response association between dairy fat intake and circulating 15 : 0 can only be obtained by strictly controlled feeding studies in which the quantity and quality of the dairy products are monitored and known [33].…”

Discovery of urinary biomarkers of whole grain rye intake in free‐living subjects using nontargeted LC‐MS metabolite profiling

“…Unfortunately, there are very few valid biomarkers available and putative biomarkers identified are typically concentration biomarkers, i.e. biomarkers where the concentrations are correlated with the intake, but where other determinates also may affect the intake‐biomarker relationship . In most cases, only a small proportion of the variation of these markers is explained by direct intake with other determinants typically being unknown.…”