Mendelian Randomization Identifies the Potential Causal Impact of Dietary Patterns on Circulating Blood Metabolites
Year: 2021
Type: article
Study design: Observational Study
Abstract: Nutrition plays an important role in the development and progress of several health conditions, but the exact mechanism is often still unclear. Blood metabolites are likely candidates to be mediating these relationships, as their levels are strongly dependent on the frequency of consumption of several foods/drinks. Understanding the causal effect of food on metabolites is thus of extreme importance. To establish these effects, we utilized two-sample Mendelian randomization using the genetic variants associated with dietary traits as instrumental variables. The estimates of single-nucleotide polymorphisms' effects on exposures were obtained from a recent genome-wide association study (GWAS) of 25 individual and 15 principal-component dietary traits, whereas the ones for outcomes were obtained from a GWAS of 123 blood metabolites measured by nuclear magnetic resonance spectroscopy. We identified 413 potentially causal links between food and metabolites, replicating previous findings, such as the association between increased oily fish consumption and higher DHA, and highlighting several novel associations. Most of the associations were related to very-low-density, intermediate-density (IDL), and low-density lipoproteins (LDL). For example, we found that constituents of IDL particles and large LDL particles were raised by coffee and alcohol while lowered by an overall healthier diet and fruit consumption. Our findings provide a strong base of evidence for planning future RCTs aimed at understanding the role of diet in determining blood metabolite levels.
Source: Frontiers in Genetics
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,950
Awards: G1408924007, G1888088267, G1953887145, G2975900969, Sytematic phenome-wide search for genetic modulators in health and disease, G3527974372, G391091299, G434337789, G4579096045, G5316693180, Quantitative Traits in Health and Disease, G6318795230, Genetic and epidemiological predictors for all-cause and cause-specific mortality in the Estonian population., G753227631, Utilising special human populations to quantify the impact of rare DNA sequence variants in human health, Improved Methods and Actionable Tools for Enhancing Health Technology Assessment, G8747799516
OpenAlex ID: W3209050786
