Food Liking-Based Diet Quality Indexes (DQI) Generated by Conceptual and Machine Learning Explained Variability in Cardiometabolic Risk Factors in Young Adults.

The overall pattern of a diet (diet quality) is recognized as more important to health and chronic disease risk than single foods or food groups. Indexes of diet quality can be derived theoretically from evidence-based recommendations, empirically from existing datasets, or a combination of the two. We used these methods to derive diet quality indexes (DQI), generated from a novel dietary assessment, and to evaluate relationships with cardiometabolic risk factors in young adults with (n = 106) or without (n = 106) diagnosed depression (62% female, mean age = 21). Participants completed a liking survey (proxy for usual dietary consumption). Principle component analysis of plasma (insulin, glucose, lipids) and adiposity (BMI, Waist-to-Hip ratio) measures formed a continuous cardiometabolic risk factor score (CRFS). DQIs were created: theoretically (food/beverages grouped, weighted conceptually), empirically (grouping by factor analysis, weights empirically-derived by ridge regression analysis of CRFS), and hybrid (food/beverages conceptually-grouped, weights empirically-derived). The out-of-sample CRFS predictability for the DQI was assessed by two-fold and five-fold cross validations. While moderate consistencies between theoretically- and empirically-generated weights existed, the hybrid outperformed theoretical and empirical DQIs in cross validations (five-fold showed DQI explained 2.6% theoretical, 2.7% empirical, and 6.5% hybrid of CRFS variance). These pilot data support a liking survey that can generate reliable/valid DQIs that are significantly associated with cardiometabolic risk factors, especially theoretically- plus empirically-derived DQI.

ANGPTL4 variants E40K and T266M are associated with lower fasting triglyceride levels in Non-Hispanic White Americans from the Look AHEAD Clinical Trial.

BACKGROUND: Elevated triglyceride levels are a risk factor for cardiovascular disease. Angiopoietin-like protein 4 (Angptl4) is a metabolic factor that raises plasma triglyceride levels by inhibiting lipoprotein lipase (LPL). In non-diabetic individuals, the ANGPTL4 coding variant E40K has been associated with lower plasma triglyceride levels while the T266M variant has been associated with more modest effects on triglyceride metabolism. The objective of this study was to determine whether ANGPTL4 E40K and T266M are associated with triglyceride levels in the setting of obesity and T2D, and whether modification of triglyceride levels by these genetic variants is altered by a lifestyle intervention designed to treat T2D. METHODS: The association of ANGPTL4 E40K and T266M with fasting triglyceride levels was investigated in 2,601 participants from the Look AHEAD Clinical Trial, all of whom had T2D and were at least overweight. Further, we tested for an interaction between genotype and treatment effects on triglyceride levels. RESULTS: Among non-Hispanic White Look AHEAD participants, ANGPTL4 K40 carriers had mean triglyceride levels of 1.61 ± 0.62 mmol/L, 0.33 mmol/L lower than E40 homozygotes (p = 0.001). Individuals homozygous for the minor M266 allele (MAF 30%) had triglyceride levels of 1.75 ± 0.58 mmol/L, 0.24 mmol/L lower than T266 homozygotes (p = 0.002). The association of the M266 with triglycerides remained significant even after removing K40 carriers from the analysis (p = 0.002). There was no interaction between the weight loss intervention and genotype on triglyceride levels. CONCLUSIONS: This is the first study to demonstrate that the ANGPTL4 E40K and T266M variants are associated with lower triglyceride levels in the setting of T2D. In addition, our findings demonstrate that ANGPTL4 genotype status does not alter triglyceride response to a lifestyle intervention in the Look AHEAD study.