Associations of measured and genetically predicted leukocyte telomere length with vascular phenotypes: a population-based study

Shorter leukocyte telomere length (LTL) is associated with cardiovascular dysfunction. Whether this association differs between measured and genetically predicted LTL is still unclear. Moreover, the molecular processes underlying the association remain largely unknown. We used baseline data of the Rhineland Study, an ongoing population-based cohort study in Bonn, Germany [56.2% women, age: 55.5 ± 14.0 years (range 30 - 95 years)]. We calculated genetically predicted LTL in 4180 participants and measured LTL in a subset of 1828 participants with qPCR. Using multivariable regression, we examined the association of measured and genetically predicted LTL, and the difference between measured and genetically predicted LTL (ΔLTL), with four vascular functional domains and the overall vascular health. Moreover, we performed epigenome-wide association studies of three LTL measures. Longer measured LTL was associated with better microvascular and cardiac function. Longer predicted LTL was associated with better cardiac function. Larger ΔLTL was associated with better microvascular and cardiac function and overall vascular health, independent of genetically predicted LTL. Several CpGs were associated (p < 1e-05) with measured LTL (n = 5), genetically predicted LTL (n = 8), and ΔLTL (n = 27). Genes whose methylation status was associated with ΔLTL were enriched in vascular endothelial signaling pathways and have been linked to environmental exposures, cardiovascular diseases, and mortality. Our findings suggest that non-genetic causes of LTL contribute to microvascular and cardiac function and overall vascular health, through an effect on the vascular endothelial signaling pathway. Interventions that counteract LTL may thus improve vascular function.

Epigenome wide association study in peripheral blood of pregnant women identifies potential metabolic pathways related to gestational diabetes

Gestational diabetes mellitus (GDM) increases the risk of developing metabolic disorders in both pregnant women and their offspring. Factors such as nutrition or the intrauterine environment may play an important role, through epigenetic mechanisms, in the development of GDM. The aim of this work is to identify epigenetic marks involved in the mechanisms or pathways related to gestational diabetes. A total of 32 pregnant women were selected, 16 of them with GDM and 16 non-GDM. DNA methylation pattern was obtained from Illumina Methylation Epic BeadChip, from peripheral blood samples at the diagnostic visit (26-28 weeks). Differential methylated positions (DMPs) were extracted using ChAMP and limma package in R 2.9.10, with a threshold of FDR <0.05, deltabeta >|5|% and B >0. A total of 1.141 DMPs were found, and 714 were annotated in genes. A functional analysis was performed, and we found 23 genes significantly related to carbohydrate metabolism. Finally, a total of 27 DMPs were correlated with biochemical variables such as glucose levels at different points of oral glucose tolerance test, fasting glucose, cholesterol, HOMAIR and HbA1c, at different visits during pregnancy and postpartum. Our results show that there is a differentiated methylation pattern between GDM and non-GDM. Furthermore, the genes annotated to the DMPs could be implicated in the development of GDM as well as in alterations in related metabolic variables.

Exposure to polycyclic aromatic hydrocarbons, DNA methylation and heart rate variability among non-current smokers

Polycyclic aromatic hydrocarbons (PAHs) exposure is associated with heart rate variability (HRV) reduction, a widely used marker of cardiovascular autonomic dysfunction. The role of DNA methylation in the relationship between PAHs exposure and decreased HRV is largely unknown. This study aims to explore epigenome-wide DNA methylation changes associated with PAHs exposure and further evaluate their associations with HRV alternations among non-current smokers. We measured 10 mono-hydroxylated PAHs (OH-PAHs) in urine and DNA methylation levels in blood leukocytes among participants from three panels of Chinese non-current smokers (152 in WHZH, 99 in SY, and 53 in COW). We conducted linear regression analyses between DNA methylation and OH-PAHs metabolites with adjustment for age, gender, body mass index, drinking, blood cell counts, and surrogate variables in each panel separately, and combined the results by using inverse-variance weighted fixed-effect meta-analysis to obtain estimates of effect size. The median value of total OH-PAHs ranged from 0.92 × 10^-2 in SY panel (62.6% men) to 13.82 × 10^-2 μmol/mmol creatinine in COW panel (43.4% men). The results showed that methylation levels of cg18223625 (COL20A1) and cg07805771 (SLC16A1) were significantly or marginally significantly associated with urinary 2-hydroxynaphthalene [β(SE) = 0.431(0.074) and 0.354(0.068), FDR = 0.016 and 0.056, respectively], while methylation level of cg09235308 (PLEC1) was positively associated with urinary total OH-PAHs [β(SE) = 0.478(0.079), FDR = 0.004]. Hypermethylations of cg18223625, cg07805771, and cg09235308 were inversely associated with HRV indices among the WHZH and COW non-current smokers. However, we did not observe significant epigenome-wide associations for the other 9 urinary OH-PAHs. These findings provide new evidence that PAHs exposure is linked to differential DNA methylation, which may help better understand the influences of PAHs exposure on HRV alternations.

Evidence for the placenta-brain axis: multi-omic kernel aggregation predicts intellectual and social impairment in children born extremely preterm

BACKGROUND

Children born extremely preterm are at heightened risk for intellectual and social impairment, including Autism Spectrum Disorder (ASD). There is increasing evidence for a key role of the placenta in prenatal developmental programming, suggesting that the placenta may, in part, contribute to origins of neurodevelopmental outcomes.

METHODS

We examined associations between placental transcriptomic and epigenomic profiles and assessed their ability to predict intellectual and social impairment at age 10 years in 379 children from the Extremely Low Gestational Age Newborn (ELGAN) cohort. Assessment of intellectual ability (IQ) and social function was completed with the Differential Ability Scales-II and Social Responsiveness Scale (SRS), respectively. Examining IQ and SRS allows for studying ASD risk beyond the diagnostic criteria, as IQ and SRS are continuous measures strongly correlated with ASD. Genome-wide mRNA, CpG methylation and miRNA were assayeds with the Illumina Hiseq 2500, HTG EdgeSeq miRNA Whole Transcriptome Assay, and Illumina EPIC/850 K array, respectively. We conducted genome-wide differential analyses of placental mRNA, miRNA, and CpG methylation data. These molecular features were then integrated for a predictive analysis of IQ and SRS outcomes using kernel aggregation regression. We lastly examined associations between ASD and the multi-omic-predicted component of IQ and SRS.

RESULTS

Genes with important roles in neurodevelopment and placental tissue organization were associated with intellectual and social impairment. Kernel aggregations of placental multi-omics strongly predicted intellectual and social function, explaining approximately 8% and 12% of variance in SRS and IQ scores via cross-validation, respectively. Predicted in-sample SRS and IQ showed significant positive and negative associations with ASD case-control status.

LIMITATIONS

The ELGAN cohort comprises children born pre-term, and generalization may be affected by unmeasured confounders associated with low gestational age. We conducted external validation of predictive models, though the sample size (N = 49) and the scope of the available out-sample placental dataset are limited. Further validation of the models is merited.

CONCLUSIONS

Aggregating information from biomarkers within and among molecular data types improves prediction of complex traits like social and intellectual ability in children born extremely preterm, suggesting that traits within the placenta-brain axis may be omnigenic.

Association analyses of repeated measures on triglyceride and high-density lipoprotein levels: insights from GAW20

BACKGROUND

The GAW20 group formed on the theme of methods for association analyses of repeated measures comprised 4sets of investigators. The provided "real" data set included genotypes obtained from a human whole-genome association study based on longitudinal measurements of triglycerides (TGs) and high-density lipoprotein in addition to methylation levels before and after administration of fenofibrate. The simulated data set contained 200 replications of methylation levels and posttreatment TGs, mimicking the real data set.

RESULTS

The different investigators in the group focused on the statistical challenges unique to family-based association analyses of phenotypes measured longitudinally and applied a wide spectrum of statistical methods such as linear mixed models, generalized estimating equations, and quasi-likelihood-based regression models. This article discusses the varying strategies explored by the group's investigators with the common goal of improving the power to detect association with repeated measures of a phenotype.

CONCLUSIONS

Although it is difficult to identify a common message emanating from the different contributions because of the diversity in the issues addressed, the unifying theme of the contributions lie in the search for novel analytic strategies to circumvent the limitations of existing methodologies to detect genetic association.

Epigenome-wide association analysis revealed that SOCS3 methylation influences the effect of cumulative stress on obesity

Chronic stress has a significant impact on obesity. However, how stress influences obesity remains unclear. We conducted an epigenome-wide DNA methylation association analysis of obesity (N=510) and examined whether cumulative stress influenced the DNA methylation on body weight. We identified 20 CpG sites associated with body mass index at the false discovery rate q<0.05, including a novel site, cg18181703, in suppressor of cytokine signaling 3 (SOCS3) gene (coefficient β=-0.0022, FDR q=4.94×10-5). The interaction between cg18181703 and cumulative adverse life stress contributed to variations in body weight (p=0.002). Individuals with at least five major life events and lower methylation of cg1818703 showed a 1.38-fold higher risk of being obese (95%CI: 1.17-1.76). Our findings suggest that aberrant in DNA methylation is associated with body weight and that methylation of SOCS3 moderates the effect of cumulative stress on obesity.

Fast and robust adjustment of cell mixtures in epigenome-wide association studies with SmartSVA

Background

One problem that plagues epigenome-wide association studies is the potential confounding due to cell mixtures when purified target cells are not available. Reference-free adjustment of cell mixtures has become increasingly popular due to its flexibility and simplicity. However, existing methods are still not optimal: increased false positive rates and reduced statistical power have been observed in many scenarios.

Methods

We develop SmartSVA, an optimized surrogate variable analysis (SVA) method, for fast and robust reference-free adjustment of cell mixtures. SmartSVA corrects the limitation of traditional SVA under highly confounded scenarios by imposing an explicit convergence criterion and improves the computational efficiency for large datasets.

Results

Compared to traditional SVA, SmartSVA achieves an order-of-magnitude speedup and better false positive control. It protects the signals when capturing the cell mixtures, resulting in significant power increase while controlling for false positives. Through extensive simulations and real data applications, we demonstrate a better performance of SmartSVA than the existing methods.

Conclusions

SmartSVA is a fast and robust method for reference-free adjustment of cell mixtures for epigenome-wide association studies. As a general method, SmartSVA can be applied to other genomic studies to capture unknown sources of variability.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-017-3808-1) contains supplementary material, which is available to authorized users.

Epigenome-wide differential DNA methylation between HIV-infected and uninfected individuals

Epigenetic control of human immunodeficiency virus-1 (HIV-1) genes is critical for viral integration and latency. However, epigenetic changes in the HIV-1-infected host genome have not been well characterized. Here, we report the first large-scale epigenome-wide association study of DNA methylation for HIV-1 infection. We recruited HIV-infected (n = 261) and uninfected (n = 117) patients from the Veteran Aging Cohort Study (VACS) and all samples were profiled for 485,521 CpG sites in DNA extracted from the blood. After adjusting for cell type and clinical confounders, we identified 20 epigenome-wide significant CpGs for HIV-1 infection. Importantly, 2 CpGs in the promoter of the NLR family, CARD domain containing gene 5 (NLRC5), a key regulator of major histocompatibility complex class I gene expression, showed significantly lower methylation in HIV-infected subjects than in uninfected subjects (cg07839457: t = −6.03, P_nominal = 4.96 × 10⁻⁹; cg16411857: t = −7.63, P_nominal = 3.07 × 10⁻¹³). Hypomethylation of these 2 CpGs was replicated in an independent sample (GSE67705: cg07839457: t = −4.44, P_nominal = 1.61 × 10⁻⁵; cg16411857: t = −5.90; P = 1.99 × 10⁻⁸). Methylation of these 2 CpGs in NLRC5 was negatively correlated with viral load in the 2 HIV-infected samples (cg07839457: P = 1.8 × 10⁻⁴; cg16411857: P = 0.03 in the VACS; and cg07839457: P = 0.04; cg164111857: P = 0.01 in GSE53840). Our findings demonstrate that differential DNA methylation is associated with HIV infection and suggest the involvement of a novel host gene, NLRC5, in HIV pathogenesis.