Intake and metabolism of omega-3 and omega-6 polyunsaturated fatty acids: nutritional implications for cardiometabolic diseases
Abstract
Prospective observational studies support the use of long-chain omega-3 polyunsaturated fatty acids (PUFAs) in the primary prevention of atherosclerotic cardiovascular disease; however, randomised controlled trials, have often reported neutral findings. There is a long history of debate about the potential harmful effects of a high intake of omega-6 PUFAs, although this idea is not supported by prospective observational studies or randomised controlled trials. Health effects of PUFAs might be influenced by Δ-5 and Δ-6 desaturases, the key enzymes in the metabolism of PUFAs. The activity of these enzymes and modulation by variants in encoding genes (FADS1-2-3 gene cluster) are linked to several cardiometabolic traits. This Review will further consider non-genetic determinants of desaturase activity, which have the potential to modify the availability of PUFAs to tissues. Finally, we discuss the consequences of altered desaturase activity in the context of PUFA intake, that is, gene-diet interactions and their clinical and public health implications.
Read the paper
Related studies
- eggNOG 5.0: a hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses
- Online Survival Analysis Software to Assess the Prognostic Value of Biomarkers Using Transcriptomic Data in Non-Small-Cell Lung Cancer
- OptiType: precision HLA typing from next-generation sequencing data
- Nicotinic Cholinergic System and COVID-19: In Silico Identification of an Interaction between SARS-CoV-2 and Nicotinic Receptors with Potential Therapeutic Targeting Implications
- Saccharomyces cerevisiae cells have three Omega class glutathione S-transferases acting as 1-Cys thiol transferases
- Hemolysis at low blood flow rates: in-vitro and in-silico evaluation of a centrifugal blood pump
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.