KeywordsTCF7L2; type-2 diabetes; obesity; T2D-genetic risk scores; TCF7L2-predictive value; PREDIMED study; eicosapentaenoic acid (EPA)/docosahexaenoic acid (DHA); spleen transcriptomics; inflammation and immunity; NF-κB; arachidonic acid; specialty oil; fatty acids; grapeseed oil; antioxidant; HDL; coconut oil; corn oil; lipoproteins; phytosterols; zinc requirements; SNPs; nutrigenetics; nutritional genomics; omega-3 fats; nutrigenomics; personalized nutrition; eicosapentaenoic acid; EPA; docosahexaenoic acid; DHA; single nucleotide polymorphisms; SNPs; fatty acid desaturase 1; genetic polymorphisms; absorption; bioavailability; β-carotene; retinyl palmitate; retinol; nutrigenetics; blood concentration; provitamin A; carotenoids; β-cryptoxanthin; α-carotene; postprandial; genetics; cycling; ergogenic aid; side effects; performance; clock gene; developmental origins of health and disease (DOHaD); high-fat diet; hypertension; next generation sequencing; nitric oxide; kidney disease; oxidative stress; renin-angiotensin system; nutrigenetics; nutritional genomics; dietetics; best-practice; children; exome-seq; food allergy; genetic variants; refractory esophageal stricture; one-carbon metabolism; folic acid fortification; genetic variants; homocysteine; polymorphisms; IL-6; rs1800795; diet intervention; BMI; walnut; association study; dietary patterns; food preferences; Prudent; Western; calcium; intake; ovarian cancer; meta-analysis; nutrigenetics; gene–diet interactions; precision nutrition; polymorphisms; inter-individual response; dairy; milk; lactase persistence; obesity; cardiometabolic disease; SNPs; polymorphisms; microarray; transcriptomics; micronutrient
