Familial resemblances in blood leukocyte DNA methylation levels

Intergenerational association of DNA methylation between parents and offspring

Early patterning of DNA methylation (DNAm) may play an important role in later disease development. To better understand intergenerational epigenetic inheritance, we investigated the correlation between DNAm in blood in mother-newborn and in father-newborn pairs in the Isle of Wight (IoW) birth cohort. For parent-newborn pairs (n = 48), offspring DNAm was measured in cord blood and the parent's DNAm in whole blood. Mothers' DNAm was analyzed at birth (Guthrie card), age 18, early and late pregnancy respectively, and fathers' DNAm was measured during the mother's pregnancy. Linear regressions were applied to assess the intergenerational correlation of parental DNAm with that of offspring. Among various pairs of mother-newborn and father-newborn DNAm, the pairs where the mothers' DNAm was measured at age 18 years exhibited the highest number of CpGs with significant intergenerational correlation in DNAm, with 1829 CpGs (0.54%) of the 338,526 CpGs studied (FDR < 0.05). Amongst these 1829 CpGs, 986 (54%) are known quantitative trait loci (QTL) for CpG methylation (methQTL). When the mother's DNAm was assessed at early pregnancy, the number of CpGs showing intergenerational correlation was the smallest (384 CpGs, 0.11%). The second smallest number of such CpGs (559 CpGs, 0.17%) was found when investigating DNAm in offspring cord blood and father pairs. The low proportions of intergenerationally correlated CpGs suggest that epigenetic inheritance is limited.

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.

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.

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.

Electronic supplementary material

The online version of this article (10.1186/s12263-019-0639-5) contains supplementary material, which is available to authorized users.

Causes of blood methylomic variation for middle-aged women measured by the HumanMethylation450 array

To address the limitations in current classic twin/family research on the genetic and/or environmental causes of human methylomic variation, we measured blood DNA methylation for 479 women (mean age 56 years) including 66 monozygotic (MZ), 66 dizygotic (DZ) twin pairs and 215 sisters of twins, and 11 random technical duplicates using the HumanMethylation450 array. For each methylation site, we estimated the correlation for pairs of duplicates, MZ twins, DZ twins, and siblings, fitted variance component models by assuming the variation is explained by genetic factors, by shared and individual environmental factors, and by independent measurement error, and assessed the best fitting model. We found that the average (standard deviation) correlations for duplicate, MZ, DZ, and sibling pairs were 0.10 (0.35), 0.07 (0.21), -0.01 (0.14) and -0.04 (0.07). At the genome-wide significance level of 10^-7, 93.3% of sites had no familial correlation, and 5.6%, 0.1%, and 0.2% of sites were correlated for MZ, DZ, and sibling pairs. For 86.4%, 6.9%, and 7.1% of sites, the best fitting model included measurement error only, a genetic component, and at least one environmental component. For the 13.6% of sites influenced by genetic and/or environmental factors, the average proportion of variance explained by environmental factors was greater than that explained by genetic factors (0.41 vs. 0.37, P value <10^-15). Our results are consistent with, for middle-aged woman, blood methylomic variation measured by the HumanMethylation450 array being largely explained by measurement error, and more influenced by environmental factors than by genetic factors.

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.

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.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4698-6) contains supplementary material, which is available to authorized users.

Genetic regulation of differentially methylated genes in visceral adipose tissue of severely obese men discordant for the metabolic syndrome

A genetic influence on methylation levels has been reported and methylation quantitative trait loci (meQTL) have been identified in various tissues. The contribution of genetic and epigenetic factors in the development of the metabolic syndrome (MetS) has also been noted. To pinpoint candidate genes for testing the association of SNPs with MetS and its components, we aimed to evaluate the contribution of genetic variations to differentially methylated CpG sites in severely obese men discordant for MetS. A genome-wide differential methylation analysis was conducted in visceral adipose tissue (VAT) of 31 severely obese men discordant for MetS (16 with and 15 without MetS) and identified ∼17,800 variable CpG sites. The genome-wide association study conducted to identify the SNPs (meQTL) associated with methylation levels at variable CpG sites revealed 2292 significant associations (P < 2.22 × 10^-11) involving 2182 unique meQTLs regulating the methylation levels of 174 variable CpG sites. Two meQTLs disrupting CpG sites located within the collagen-encoding COL11A2 gene were tested for associations with MetS and its components in a cohort of 3021 obese individuals. Rare alleles of these meQTLs showed association with plasma fasting glucose levels. Further analysis conducted on these meQTL suggested a biological impact mediated through the disruption of transcription factor (TF)-binding sites based on the prediction of TF-binding affinities. The current study identified meQTL in the VAT of severely obese men and revealed associations of two COL11A2 meQTL with fasting glucose levels.