Morin-Bernier Josiane, de Toro-Martín Juan, Barbe Valentin, San-Cristobal Rodrigo, Lemieux Simone, Rudkowska Iwona, Couture Patrick, Barbier Olivier, Vohl Marie-Claude
Centre Nutrition, santé et société (NUTRISS)-Institut sur la nutrition et les aliments fonctionnels (INAF), Université Laval, Québec, QC, Canada.
School of Nutrition, Université Laval, Québec, QC, Canada.
Front Nutr. 2024 Feb 13;11:1327863. doi: 10.3389/fnut.2024.1327863. eCollection 2024.
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.
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.
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.
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.
本研究的目的是确定对ω-3脂肪酸（n-3 FA）补充剂有反应者和无反应者的代谢组学特征，并测试一种结合基因组、脂质组和代谢组特征的多组学分类器区分血浆甘油三酯（TG）反应表型的能力。
共有208名脂肪酸传感器（FAS）研究的参与者。每天服用5克鱼油，在6周内每天提供1.9 - 2.2克二十碳五烯酸（EPA）和1.1克二十二碳六烯酸（DHA），并根据补充后血浆TG水平的变化进一步分为两个亚组：反应者和无反应者。使用线性混合模型比较干预期间两个亚组之间6种短链脂肪酸（SCFA）和25种胆汁酸（BA）的血浆水平变化，并在中介分析中测试SCFA和BA对TG反应的影响。使用Illumina Human Omni-5 Quad BeadChip进行基因分型。采用质谱法定量血浆TG和胆固醇酯水平，以及血浆SCFA和BA水平。在DIABLO框架内开发并测试了一个分类器，该框架对多组学分析实施偏最小二乘判别分析。通过组合来自基因组学、脂质组学和代谢组学的数据开发了不同的分类器。
在n-3 FA补充前后测量的SCFA或BA中，反应者和无反应者之间的血浆水平均无显著差异。SCFA而非BA在血浆TG反应分类中具有微弱相关性。通过将血浆SCFA和脂质组层添加到基因组数据构建的分类器，能够将仅基因组预测器显示的85%的准确率提高。
这些结果说明了SCFA和BA血浆水平作为肠道微生物群替代指标在评估n-3 FA补充剂血浆TG反应中个体间变异性方面的微弱相关性。基因组数据仍然是血浆TG反应的最佳预测指标，纳入代谢组学数据对区分血浆TG反应表型的能力提升不大。
