Analyse intégrée des données omiques dans l'impact de l'alimentation sur la santé cardiométabolique

Au Canada, les maladies cardiovasculaires (MCV) sont la deuxième cause de mortalité après le cancer, et l'une des principales causes d'hospitalisation. La prise en charge des individus souffrant de MCV repose sur l'évaluation et le traitement de plusieurs facteurs de risque cardiométabolique, lesquels comprennent le syndrome métabolique, l'activité physique et l'alimentation. L'adoption de saines habitudes de vie, incluant notamment une alimentation équilibrée, demeure la pierre angulaire de la prévention des MCV. En effet, une alimentation riche en fruits et légumes est inversement reliée à l'incidence de MCV. Les biomarqueurs d'exposition à la diète permettent par ailleurs d'étudier l'impact des facteurs alimentaires sur le développement des MCV. Les caroténoïdes plasmatiques, qui sont des biomarqueurs de la consommation de fruits et de légumes, sont associés à la santé cardiométabolique. L'alimentation influence en plus une multitude de facteurs omiques, modulant ainsi le risque de MCV. Les sciences omiques étudient l'ensemble complexe des molécules qui composent le corps. Parmi ces sciences, la génomique, l'épigénomique, la transcriptomique et la métabolomique s'intéressent respectivement à l'étude à grande échelle des gènes, de la méthylation de l'ADN, de l'expression génique et des métabolites. Étant donné qu'un seul type de données omiques ne permet généralement pas de saisir la complexité des processus biologiques, une approche intégrative combinant plusieurs données omiques s'avère idéale afin de déchiffrer la physiopathologie des traits complexes. La biologie des systèmes étudie les interactions complexes des différentes données omiques entre elles, et avec l'environnement ainsi que leur influence sur un trait d'intérêt, tel que la santé. Il existe plusieurs méthodes pour analyser et intégrer des données omiques. La génétique quantitative permet d'estimer les contributions des effets génétiques et environnementaux dans la variance de traits complexes. L'analyse de réseaux de corrélations pondérées permet de mettre en relation un grand nombre de données omiques interreliées avec un trait, comme par exemple un ensemble de facteurs de risque de maladies complexes. L'objectif général de cette thèse est d'étudier l'impact des déterminants omiques sur la relation entre l'alimentation et la santé cardiométabolique. Le premier objectif spécifique, utilisant une approche de la génétique quantitative, est de caractériser l'héritabilité des données omiques et des caroténoïdes plasmatiques ainsi que de vérifier si le lien avec des facteurs de risque cardiométabolique peut être expliqué par des facteurs génétiques et environnementaux. Le deuxième objectif spécifique, utilisant une approche de réseaux de corrélations pondérées, est d'évaluer le rôle des données omiques individuelles et combinées dans la relation entre les caroténoïdes plasmatiques et le profil lipidique. Ce projet de doctorat repose sur l'étude observationnelle GENERATION qui comprend 48 sujets en bonne santé répartis en 16 familles. Toutes les données omiques étudiées et les caroténoïdes plasmatiques ont démontré iii des ressemblances familiales dues, à des degrés divers, à l'effet de la génétique et de l'environnement partagé. La génétique et l'environnement sont également impliqués dans le lien entre la méthylation de l'ADN et l'expression génique ainsi qu'entre les métabolites, les caroténoïdes et les facteurs de risque cardiométabolique. L'utilisation de réseaux de corrélations pondérées a en outre permis de mieux comprendre le système moléculaire interactif qui relie les caroténoïdes, la méthylation de l'ADN, l'expression génique et le profil lipidique. En conclusion, ces travaux basés sur des données omiques individuelles et combinées analysées dans des approches de la génétique quantitative et de réseaux de corrélations pondérées ont mis en lumière la relation entre l'alimentation et la santé cardiométabolique.After cancer, cardiovascular disease (CVD) is the second leading cause of death and one of the leading causes of hospitalization in Canada. CVD management is based on the assessment and treatment of several cardiometabolic risk factors, which include metabolic syndrome, physical activity, and diet. A healthy lifestyle, including a balanced diet, remains the key to prevent CVD. A diet rich in fruits and vegetables is inversely associated with CVD incidence. Biomarkers of exposure to diet are used to study the impact of dietary factors on the development of CVD. Plasma carotenoids, a biomarker of fruit and vegetable consumption, are associated with cardiometabolic health. Diet also influences a myriad of omics factors, thus modulating CVD risk. Omics sciences study the complex set of molecules that make up the body. Among these sciences, genomics, epigenomics, transcriptomics, and metabolomics consider the large-scale study of genes, DNA methylation, gene expression, and metabolites, respectively. Given that a single type of omics data usually does not capture the complexity of biological processes, an integrative approach combining multiple omics data proves ideal to elucidate the pathophysiology of diseases. Systems biology studies the complex interactions of different omics data among themselves and with the environment on a trait such as health. There are several methods for analyzing and integrating omics data. Quantitative genetics estimates the contributions of genetic and environmental effects to the variance of complex traits such as omics data. Weighted correlation network analysis allows the association of a large number of omics data with a trait such as risk factors for diseases. The general objective of this thesis is to study the impact of omics determinants in the link between diet and cardiometabolic health. The first specific objective, using a quantitative genetics approach, is to characterize the heritability of omics data and plasma carotenoids as well as to check if their link with cardiometabolic risk factors can be explained by genetic and environmental factors. The second specific objective, using a weighted correlation network approach, is to assess the role of individual and combined omics data in the relationship between plasma carotenoids and lipid profile. This project is based on the GENERATION observational study, which includes 48 healthy subjects from 16 families. All omics data studied showed familial resemblances due, to varying degrees, to genetic and common environmental effects. Genetics and environment are also involved in the link between DNA methylation and gene expression, as well as between metabolites, carotenoids, and cardiometabolic risk factors. Moreover, weighted correlation network analysis has provided insight into the interactive molecular system that links carotenoids, DNA methylation, gene expression, and lipid profile. In conclusion, the present study, using approaches from quantitative genetics and weighted correlation network analysis, brought to light the impact of some individual and combined omics data in the link between diet and cardiometabolic healt

Genetic and common environmental contributions to familial resemblances in plasma carotenoid concentrations in healthy families

Carotenoids have shown an interindividual variability that may be due to genetic factors. The only study that has reported heritability of serum α- and β-carotene has not considered the environmental component. This study aimed to estimate the contribution of both genetic and common environmental effects to the variance of carotenoid concentrations and to test whether their phenotypic correlations with cardiometabolic risk factors are explained by shared genetic and environmental effects. Plasma carotenoid concentrations (α-carotene, β-carotene, β-cryptoxanthin, lutein, lycopene, zeaxanthin, and total carotenoids) of 48 healthy subjects were measured. Heritability estimates of carotenoid concentrations were calculated using the variance component method. Lutein and lycopene showed a significant familial effect (p = 6 × 10−6 and 0.0043, respectively). Maximal heritability, genetic heritability, and common environmental effect were computed for lutein (88.3%, 43.8%, and 44.5%, respectively) and lycopene (45.2%, 0%, and 45.2%, respectively). Significant phenotypic correlations between carotenoid concentrations and cardiometabolic risk factors were obtained for β-cryptoxanthin, lycopene, and zeaxanthin. Familial resemblances in lycopene concentrations were mainly attributable to common environmental effects, while for lutein concentrations they were attributable to genetic and common environmental effects. Common genetic and environmental factors may influence carotenoids and cardiometabolic risk factors, but further studies are needed to better understand the potential impact on disease development

Network Analysis of the potential role of DNA methylation in the relationship between plasma carotenoids and lipid profile

Abstract: Variability in plasma carotenoids may be attributable to several factors including genetic variants and lipid profile. Until now, the impact of DNA methylation on this variability has not been widely studied. Weighted gene correlation network analysis (WGCNA) is a systems biology method used for finding gene clusters (modules) with highly correlated methylation levels and for relating them to phenotypic traits. The objective of the present study was to examine the role of DNA methylation in the relationship between plasma total carotenoid concentrations and lipid profile using WGCNA in 48 healthy subjects. Genome-wide DNA methylation levels of 20,687 out of 472,245 CpG sites in blood leukocytes were associated with total carotenoid concentrations. Using WGCNA, nine co-methylation modules were identified. A total of 2734 hub genes (17 unique top hub genes) were potentially related to lipid profile. This study provides evidence for the potential implications of gene co-methylation in the relationship between plasma carotenoids and lipid profile. Further studies and validation of the hub genes are needed

Weighted gene co-expression network analysis to explain the relationship between plasma total carotenoids and lipid profile

Background: Variability in circulating carotenoids may be attributable to several factors including, among others, genetic variants and lipid profile. However, relatively few studies have considered the impact of gene expression in the inter-individual variability in circulating carotenoids. Most studies considered expression of genes individually and ignored their high degree of interconnection. Weighted gene co-expression network analysis (WGCNA) is a systems biology method used for finding gene clusters with highly correlated expression levels and for relating them to phenotypic traits. The objective of the present observational study is to examine the relationship between plasma total carotenoid concentrations and lipid profile using WGCNA. Results: Whole blood expression levels of 533 probes were associated with plasma total carotenoids. Among the four WGCNA distinct modules identified, turquoise, blue, and brown modules correlated with plasma high-density lipoprotein cholesterol (HDL-C) and total cholesterol. Probes showing a strong association with HDL-C and total cholesterol were also the most important elements of the brown and blue modules. A total of four and 29 hub genes associated with total carotenoids were potentially related to HDL-C and total cholesterol, respectively. Conclusions: Expression levels of 533 probes were associated with plasma total carotenoid concentrations. Using WGCNA, four modules and several hub genes related to lipid and carotenoid metabolism were identified. This integrative analysis provides evidence for the potential role of gene co-expression in the relationship between carotenoids and lipid concentrations. Further studies and validation of the hub genes are needed

Association between polymorphisms in phospholipase A2 genes and the plasma triglyceride response to an n-3 PUFA supplementation : a clinical trial

Background: Fish oil-derived long-chain omega-3 (n-3) polyunsaturated fatty acids (PUFAs), including eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), reduce plasma triglyceride (TG) levels. Genetic factors such as single-nucleotide polymorphisms (SNPs) found in genes involved in metabolic pathways of n-3 PUFA could be responsible for well-recognized heterogeneity in plasma TG response to n-3 PUFA supplementation. Previous studies have shown that genes in the glycerophospholipid metabolism such as phospholipase A2 (PLA2) group II, IV, and VI, demonstrate changes in their expression levels in peripheral blood mononuclear cells (PBMCs) after n-3 PUFA supplementation. Methods: A total of 208 subjects consumed 3 g/day of n-3 PUFA for 6 weeks. Plasma lipids were measured before and after the supplementation period. Five SNPs in PLA2G2A, six in PLA2G2C, eight in PLA2G2D, six in PLA2G2F, 22 in PLA2G4A, five in PLA2G6, and nine in PLA2G7 were genotyped. The MIXED Procedure for repeated measures adjusted for age, sex, BMI, and energy intake was used in order to test whether the genotype, supplementation or interaction (genotype by supplementation) were associated with plasma TG levels. Results: The n-3 PUFA supplementation had an independent effect on plasma TG levels. Genotype effects on plasma TG levels were observed for rs2301475 in PLA2G2C, rs818571 in PLA2G2F, and rs1569480 in PLA2G4A. Genotype x supplementation interaction effects on plasma TG levels were observed for rs1805018 in PLA2G7 as well as for rs10752979, rs10737277, rs7540602, and rs3820185 in PLA2G4A. Conclusion: These results suggest that, SNPs in PLA2 genes may influence plasma TG levels during a supplementation with n-3 PUFA. This trial was registered at clinicaltrials.gov as NCT01343342

Muscle Dystroglycan Organizes the Postsynapse and Regulates Presynaptic Neurotransmitter Release at the Drosophila Neuromuscular Junction

International audienceBACKGROUND: The Dystrophin-glycoprotein complex (DGC) comprises dystrophin, dystroglycan, sarcoglycan, dystrobrevin and syntrophin subunits. In muscle fibers, it is thought to provide an essential mechanical link between the intracellular cytoskeleton and the extracellular matrix and to protect the sarcolemma during muscle contraction. Mutations affecting the DGC cause muscular dystrophies. Most members of the DGC are also concentrated at the neuromuscular junction (NMJ), where their deficiency is often associated with NMJ structural defects. Hence, synaptic dysfunction may also intervene in the pathology of dystrophic muscles. Dystroglycan is a central component of the DGC because it establishes a link between the extracellular matrix and Dystrophin. In this study, we focused on the synaptic role of Dystroglycan (Dg) in Drosophila. METHODOLOGY/PRINCIPAL FINDINGS: We show that Dg was concentrated postsynaptically at the glutamatergic NMJ, where, like in vertebrates, it controls the concentration of synaptic Laminin and Dystrophin homologues. We also found that synaptic Dg controlled the amount of postsynaptic 4.1 protein Coracle and alpha-Spectrin, as well as the relative subunit composition of glutamate receptors. In addition, both Dystrophin and Coracle were required for normal Dg concentration at the synapse. In electrophysiological recordings, loss of postsynaptic Dg did not affect postsynaptic response, but, surprisingly, led to a decrease in glutamate release from the presynaptic site. CONCLUSION/SIGNIFICANCE: Altogether, our study illustrates a conservation of DGC composition and interactions between Drosophila and vertebrates at the synapse, highlights new proteins associated with this complex and suggests an unsuspected trans-synaptic function of Dg

Effet des polymorphismes des gènes des phospholipases A2 sur la variabilité interindividuelle des facteurs de risque cardiométaboliques suite à une supplémentation en acides gras oméga-3 d'origine marine

Tableau d'honneur de la Faculté des études supérieures et postdorales, 2015-2016Les acides gras polyinsaturés oméga-3 (AGPI n-3), plus spécifiquement l’acide eicosapentaénoïque (AEP) et l’acide docosahexaénoïque (ADH), abaissent le risque de maladies cardiovasculaires (MCV) en agissant sur différents facteurs de risque dont une diminution des triglycérides (TG) plasmatiques et de l’inflammation. Toutefois, une grande variabilité interindividuelle dans la réponse cardiométabolique à la supplémentation en AGPI n-3 est observée et elle serait en partie reliée à des facteurs génétiques. Les gènes du métabolisme des lipides, dont les phospholipases A2 (PLA2), ont été modulés suite à la supplémentation de 3 g d’AEP et d’ADH/jour pendant six semaines. Des effets de génotype*supplémentation ont été observés avec des variations des gènes des PLA2 sur les niveaux de TG et de protéine C-réactive (CRP). Les résultats suggèrent que des variations sur les gènes de PLA2 expliquent en partie la variabilité interindividuelle de la réponse des TG et de la CRP à la supplémentation en AGPI n-3.Fish oil-derived long-chain omega-3 (n-3) polyunsaturated fatty acids (PUFAs), including eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), reduce the risk of cardiovascular disease by lowering plasma triglyceride (TG) and inflammation levels. However, a large inter-individual variability is observed, which could be explained by genetic factors. Genes involved in metabolic pathways of n-3 PUFA, including phospholipases A2 (PLA2) had changes in their expression in individuals who consumed 3 g/day of EPA and DHA for 6 weeks. Genotype by supplementation interaction effect on TG and C-reactive protein (CRP) levels were observed for PLA2 variations. These results suggest that variations in PLA2 genes may influence plasma TG and CRP levels during a supplementation with n-3 PUFA

Familial resemblances in human whole blood transcriptome

Abstract Background Considering the implication of gene expression in the susceptibility of chronic diseases and the familial clustering of chronic diseases, the study of familial resemblances in gene expression levels is then highly relevant. Few studies have considered the contribution of both genetic and common environmental effects to familial resemblances in whole blood gene expression levels. The objective is to quantify the contribution of genetic and common environmental effects in the familial resemblances of whole blood genome-wide gene expression levels. We also make comparisons with familial resemblances in blood leukocytes genome-wide DNA methylation levels in the same cohort in order to further investigate biological mechanisms. Results Maximal heritability, genetic heritability, and common environmental effect were computed for all probes (20.6%, 15.6%, and 5.0% respectively) and for probes showing a significant familial effect (78.1%, 60.1%, and 18.0% respectively). Pairwise phenotypic correlations between gene expression and DNA methylation levels adjusted for blood cell heterogeneity were computed for probes showing significant familial effect. A total of 78 probe pairs among the 7,618,401 possible pairs passed Bonferroni correction (corrected P-value = 6.56 × 10− 9). Significant genetic correlations between gene expression and DNA methylation levels were found for 25 probe pairs (absolute genetic correlation of 0.97). Conclusions Familial resemblances in gene expression levels were mainly attributable to genetic factors, but common environmental effect also played a role especially in probes showing a significant familial effect. Probes and CpG sites with familial effect seem to be under a strong shared genetic control