Dietary long-chain fatty acids and carbohydrate biomarker evaluation in a controlled feeding study in participants from the Women’s Health Initiative cohort ,

Abstract

Biomarkers of macronutrient intake are lacking. Controlled human feeding studies that preserve the normal variation in nutrient and food consumption are necessary for the development and validation of robust nutritional biomarkers. We aimed to assess the utility of serum phospholipid fatty acids (PLFAs) as biomarkers of dietary intakes of fatty acids, total fat, and carbohydrate. We used an individualized controlled feeding study in which 153 postmenopausal women from the Women's Health Initiative (WHI) were provided with a 2-wk controlled diet that mimicked each individual's habitual food intake. A total of 41 PLFAs were measured with the use of gas chromatography in end-of-feeding-period fasting serum samples and expressed in both relative and absolute concentrations. values (percentages of variation explained) from linear regressions of (ln-transformed) consumed fatty acids (individual, groups, and broad categories) on (ln-transformed) corresponding measures of serum PLFAs alone and together with selected participant-related variables (age, race/ethnicity, body mass index, season of study participation, education level, and estimated energy intake from doubly labeled water) were used for evaluation against established urinary recovery biomarkers of energy and protein intake as benchmarks. Models to predict intakes of other nutrients were also explored. Intakes of eicosapentaenoic acid and docosahexaenoic acid achieved the benchmark of > 36% with or without covariates. When all 41 serum PLFAs and participant-related covariates were initially included in the model for selection, cross-validated achieved>36% for consumed total carbohydrate (grams per day), total saturated fatty acids (SFAs), percentage of energy from SFAs, and total fatty acids with serum PLFAs in both relative and absolute concentrations. Serum PLFA biomarkers perform similarly to established energy and protein urinary recovery biomarkers in describing intake variations for several nutrients and, thus, appear suitable for application in this population of postmenopausal women. This approach represents an important methodologic contribution toward the utilization of nutritional biomarkers to assess macronutrient intake. This trial was registered at clinicaltrials.gov as NCT00000611.

Palmitic Acid: Physiological Role, Metabolism and Nutritional Implications

“…Association between PA levels in blood fraction in relation to breast cancer risk has been reported in a meta-analysis (Saadatian-Elahi et al, 2004 ) and a prospective study (Bassett et al, 2016 ), whereas another prospective study conducted in northern Italy found no association between saturated fatty acids and breast cancer risk (Pala et al, 2001 ). Since changes in PA intake do not influence significantly its tissue concentration (Innis and Dyer, 1997 ; Song et al, 2017 ), it implies that DNL has a central role in cancerogenesis.…”

“…The liver plays a central role in regulating body concentration of PA, through its desaturation to POA or elongation to SA and further desaturated to OA. As a matter of fact, its plasma concentrations, in physiological conditions, are not significantly influenced by PA dietary intake (Innis and Dyer, 1997 ; Song et al, 2017 ), suggesting that the homeostatic control of PA concentration in the liver is regulated by its production via DNL on one side and its desaturation on the other.…”

“…The average intake of PA is around 20–30 g/d representing about 8–10 en% (Sette et al, 2011 ). PA tissue content seems to be controlled around a well-defined concentration, since changes in its intake do not influence significantly its tissue concentration (Innis and Dyer, 1997 ; Song et al, 2017 ), because the intake is counterbalanced by PA endogenous biosynthesis via de novo lipogenesis (DNL). Particular physiopathological conditions and nutritional factors may strongly induce DNL, resulting in increased tissue content of PA and disrupted homeostatic control of its tissue concentration (Wilke et al, 2009 ).…”

Fatty acids in the de novo lipogenesis pathway and incidence of type 2 diabetes: A pooled analysis of prospective cohort studies

“…Other modifiable factors that may influence DNL include sleeping behavior and meal frequency [39]. Dietary intakes of saturated and monounsaturated fatty acids directly influence 16:0, 16:1n7, 18:0, and 18:1n9 [38,40,41], but it remains unclear whether these effects are similar or even smaller than the influence of endogenous synthesis and metabolism in long-term settings [42][43][44]. For example, limited evidence from Swedish cohorts suggests the negative or null association of carbohydrate intake with concentrations of DNL-related fatty acids in adipose tissue and phospholipids and highlight a role of saturated fat or alcohol as determining DNL fatty acids [45,46].…”

Nutritional epidemiology methods and related statistical challenges and opportunities

“…Prominent examples of nutritional biomarkers include a doubly-labeled water (DLW) biomarker of energy intake (Schoeller, 1999), a urinary nitrogen biomarker of protein intake (Bingham, 2003), and 24-hour urine-based measures of sodium and potassium intake (Luft, Fineberg, & Sloan, 1982; Rakova et al, 2013). Additionally, our research group, using data from a 153-woman human feeding study, has recently proposed novel biomarkers for the intake of several carotenoids and tocopherols using blood serum concentrations measurements (Lampe et al, 2017), and a carbohydrate biomarker using plasma fatty acid profiles (Song et al, 2017). These latter biomarkers required the inclusion of certain study subject variables for (1) to be plausible.…”