Familial resemblances in human whole blood transcriptome.

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.

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.

Integrative Network Analysis of Multi-Omics Data in the Link between Plasma Carotenoid Concentrations and Lipid Profile.

INTRODUCTION: Carotenoids, which are a reliable biomarker of fruit and vegetable consumption, are positively associated with the lipid profile. Circulating carotenoid concentrations may interact with several omics profiles including genome, transcriptome, and epigenome. Few studies have used multi-omics approaches, and they rarely include environmental factors, such as diet. OBJECTIVE: The objective of this observational study was to examine the potential role of multi-omics data in the interconnection between diet, represented by total carotenoids, and lipid profile using weighted gene correlation network analysis (WGCNA). METHODS: Blood leukocyte DNA methylation levels of 472,245 CpG sites and whole blood gene expression levels of 18,160 transcripts were tested for associations with total carotenoid concentrations using regressions in 48 healthy subjects. WGCNA was used to identify co-omics modules and hub genes related to the lipid profile. RESULTS: Among genes associated with total carotenoid concentrations, a total of 236 genes were identified at both DNA methylation and gene expression levels. Using WGCNA, six modules, consisting of groups of highly correlated genes represented by colors, were identified and linked to the lipid profile. Probes clustered in the turquoise and green modules correlated with plasma lipid concentrations. A total of 28 hub genes were identified. CONCLUSIONS: Genome-wide DNA methylation and gene expression levels were both associated with plasma total carotenoid concentrations. Several hub genes, mostly involved in lipid metabolism and inflammatory response with several genetic variants associated with plasma lipid concentrations, came out of the integrative analysis. This provides a comprehensive understanding of the interactive molecular system between carotenoids, omics, and plasma lipid profile.

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.

Familial resemblances in human plasma metabolites are attributable to both genetic and common environmental effects.

Metabolites are of great importance for understanding the pathogenesis of several diseases. Understanding the genetic contribution to metabolite concentrations may provide insights into mechanisms of complex diseases. Several studies have investigated heritability of metabolites but none investigated potential influences of genetic and environmental factors on the relationship between metabolites and cardiometabolic (CM) risk factors. Thus, we tested the hypothesis that both genetic and common environmental effects contribute to the variance of plasma metabolite concentrations and that shared genetic and environmental effects explain their phenotypic correlations with CM risk factors. To test this hypothesis, variance component method and bivariate genetic analysis were performed in a family-based sample of 48 French Canadians from 16 families. Familial resemblances were computed for all 147 detected metabolites and 9 (acetylornithine, acylcarnitine C9, arginine, phosphatidylcholine acyl-alkyl C36:4, serotonin, lysophosphatidylcholine acyl C20:4, citrulline, asymmetric dimethylarginine, phosphatidylcholine acyl-alkyl C36:5) showed a significant familial effect (55.7%, 18.7%, and 37.0% for maximal heritability, genetic heritability, and common environmental effect, respectively). Citrulline, phosphatidylcholine acyl-alkyl C36:4, phosphatidylcholine acyl-alkyl C36:5, and serotonin had significant phenotypic correlations with CM risk factors. Citrulline had a positive genetic correlation with apolipoprotein B100, while phosphatidylcholine acyl-alkyl C36:5 had a positive environmental correlation with total cholesterol. In conclusion, familial resemblances in metabolite concentrations were mainly attributable to common environmental effect when considering metabolites with a significant familial effect. Common genetic and environmental factors may also influence the relationship between metabolites and CM risk factors.

Network Analysis of the Potential Role of DNA Methylation in the Relationship between Plasma Carotenoids and Lipid Profile.

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.

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 ß-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, ß-carotene, ß-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 ß-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.

Nutrigenomic point of view on effects and mechanisms of action of ruminant trans fatty acids on insulin resistance and type 2 diabetes.

Evidence from observational studies suggests beneficial effects of ruminant trans fatty acids (rTFA) on insulin resistance (IR) and type 2 diabetes (T2D). However, beneficial effects of rTFA are not always observed in cell, animal, and human studies. This narrative review presents potential mechanisms of action of rTFA using nutrigenomics and microRNA results in an integrative model. In addition, the review presents factors, including measures of IR and T2D, dose and duration of studies, as well as health status, ethnicity, and genotypes of subjects, that may help explain the heterogeneity in response to rTFA supplementation. Future studies should consider these factors, as well as research in nutritional genomics, to better understand the effects of rTFA on IR and T2D.

Epigenetic changes in blood leukocytes following an omega-3 fatty acid supplementation.

BACKGROUND: Omega-3 polyunsaturated fatty acids (n-3 FAs) have several beneficial effects on cardiovascular (CV) disease risk factors. These effects on CV risk profile may be mediated by several factors, including epigenetic modifications. Our objective is to investigate, using genome-wide DNA methylation analyses, methylation changes following an n-3 FA supplementation in overweight and obese subjects and to identify specific biological pathways potentially altered by the supplementation. RESULTS: Blood leukocytes genome-wide DNA methylation profiles of 36 overweight and obese subjects before and after a 6-week supplementation with 3 g of n-3 FAs were compared using GenomeStudio software. After supplementation, 308 CpG sites, assigned to 231 genes, were differentially methylated (FDR-corrected Diffscore ≥│13│~ P ≤ 0.05). Using Ingenuity Pathway Analysis system, a total of 55 pathways were significantly overrepresented following supplementation. Among these pathways, 16 were related to inflammatory and immune response, lipid metabolism, type 2 diabetes, and cardiovascular signaling. Changes in methylation levels of CpG sites within AKT3, ATF1, HDAC4, and IGFBP5 were correlated with changes in plasma triglyceride and glucose levels as well as with changes in the ratio of total cholesterol/HDL-cholesterol following the supplementation. CONCLUSIONS: These data provide key differences in blood leukocytes DNA methylation profiles of subjects following an n-3 FA supplementation, which brings new, potential insights on metabolic pathways underlying the effects of n-3 FAs on CV health.

Familial resemblances in blood leukocyte DNA methylation levels.

Epigenetic factors such as DNA methylation are DNA alterations affecting gene expression that can convey environmental information through generations. Only a few studies have demonstrated epigenetic inheritance in humans. Our objective is to quantify genetic and common environmental determinants of familial resemblances in DNA methylation levels, using a family based sample. DNA methylation was measured in 48 French Canadians from 16 families as part of the GENERATION Study. We used the Illumina HumanMethylation450 BeadChip array to measure DNA methylation levels in blood leukocytes on 485,577 CpG sites. Heritability was assessed using the variance components method implemented in the QTDT software, which partitions the variance into polygenic (G), common environmental (C), and non-shared environmental (E) effects. We computed maximal heritability, genetic heritability, and common environmental effect for all probes (12.7%, 8.2%, and 4.5%, respectively) and for statistically significant probes (81.8%, 26.9%, and 54.9%, respectively). Higher maximal heritability was observed in the Major Histocompatibility Complex region on chromosome 6. In conclusion, familial resemblances in DNA methylation levels are mainly attributable to genetic factors when considering the average across the genome, but common environmental effect plays an important role when considering statistically significant probes. Further epigenome-wide studies on larger samples combined with genome-wide genotyping studies are needed to better understand the underlying mechanisms of DNA methylation heritability.