Proportions of trans fatty acids in erythrocytes of Canadian adults before the prohibition of partially hydrogenated oils in foods: results from the Canadian Health Measures Survey 2012-2015.

BACKGROUND: The partially hydrogenated oil (PHO) prohibition came into effect in Canada in September 2018 to reduce the intakes of total trans fatty acids (t-TFAs) and industrially produced TFAs (i-TFAs). OBJECTIVES: We aimed to estimate the red blood cell (RBC) proportions of t-TFA (primary objective) and total 18:1 TFA (secondary objective) of adults in Canada before the PHO prohibition and to identify the population subgroups at risk of higher TFA intakes. METHODS: We pooled data from 4025 adult participants of the cross-sectional Canadian Health Measures Survey cycles 3 and 4 (2012-2015). We estimated mean proportions, relative to total fatty acids (FAs), of RBC t-TFA and 18:1 TFA and their associations with sociodemographic, health, and lifestyle characteristics using multiple linear regression models. RESULTS: The nonadjusted mean RBC proportions of t-TFA and total 18:1 TFA were 0.59% (95% CI: 0.54, 0.63) and 0.27% (95% CI: 0.25, 0.29), respectively. In the adjusted models, the same participant characteristics were associated with t-TFA and 18:1 TFA but differences were generally smaller for 18:1 TFA than for t-TFA. Race, BMI, and alcohol intake were independently associated with RBC t-TFA and 18:1 TFA. Asian and Black participants had lower RBC t-TFA (-0.05% and -0.10% of total FA, respectively) than White participants. Obesity and high risk alcohol drinking were associated with slightly lower (≤0.06%) t-TFA proportions than lower adiposity and alcohol intake concentrations, respectively. CONCLUSIONS: Pre-PHO prohibition in food in Canada, t-TFA proportions were relatively low compared with a proposed threshold of 1% of total RBC FAs, over which cardiovascular disease risk may be higher. Previous voluntary initiatives to reduce i-TFA in the food supply may explain these relatively low RBC t-TFA concentrations. Some population subgroups had higher baseline RBC TFA than other subgroups, but the physiological implications of these small differences, at relatively low baseline RBC TFA proportions, remain to be determined.

Corrigendum: Revisiting multi-omics-based predictors of the plasma triglyceride response to an omega-3 fatty acid supplementation.

[This corrects the article DOI: 10.3389/fnut.2024.1327863.].

Revisiting multi-omics-based predictors of the plasma triglyceride response to an omega-3 fatty acid supplementation.

Background: The aim of the present study was to identify the metabolomic signature of responders and non-responders to an omega-3 fatty acid (n-3 FA) supplementation, and to test the ability of a multi-omics classifier combining genomic, lipidomic, and metabolomic features to discriminate plasma triglyceride (TG) response phenotypes. Methods: A total of 208 participants of the Fatty Acid Sensor (FAS). Study took 5 g per day of fish oil, providing 1.9-2.2 g eicosapentaenoic acid (EPA) and 1.1 g docosahexaenoic (DHA) daily over a 6-week period, and were further divided into two subgroups: responders and non-responders, according to the change in plasma TG levels after the supplementation. Changes in plasma levels of 6 short-chain fatty acids (SCFA) and 25 bile acids (BA) during the intervention were compared between subgroups using a linear mixed model, and the impact of SCFAs and BAs on the TG response was tested in a mediation analysis. Genotyping was conducted using the Illumina Human Omni-5 Quad BeadChip. Mass spectrometry was used to quantify plasma TG and cholesterol esters levels, as well as plasma SCFA and BA levels. A classifier was developed and tested within the DIABLO framework, which implements a partial least squares-discriminant analysis to multi-omics analysis. Different classifiers were developed by combining data from genomics, lipidomics, and metabolomics. Results: Plasma levels of none of the SCFAs or BAs measured before and after the n-3 FA supplementation were significantly different between responders and non-responders. SCFAs but not BAs were marginally relevant in the classification of plasma TG responses. A classifier built by adding plasma SCFAs and lipidomic layers to genomic data was able to even the accuracy of 85% shown by the genomic predictor alone. Conclusion: These results inform on the marginal relevance of SCFA and BA plasma levels as surrogate measures of gut microbiome in the assessment of the interindividual variability observed in the plasma TG response to an n-3 FA supplementation. Genomic data still represent the best predictor of plasma TG response, and the inclusion of metabolomic data added little to the ability to discriminate the plasma TG response phenotypes.