Ana Viñuela

Cigarette smoking reduces DNA methylation levels at multiple genomic loci but the effect is partially reversible upon cessation.

Smoking is a major risk factor in many diseases. Genome wide association studies have linked genes for nicotine dependence and smoking behavior to increased risk of cardiovascular, pulmonary, and malignant diseases. We conducted an epigenome wide association study in peripheral-blood DNA in 464 individuals (22 current smokers and 263 ex-smokers), using the Human Methylation 450 K array. Upon replication in an independent sample of 356 twins (41 current and 104 ex-smokers), we identified 30 probes in 15 distinct loci, all of which reached genome-wide significance in the combined analysis P < 5 × 10−8. All but one probe (cg17024919) remained significant after adjusting for blood cell counts. We replicated all 9 known loci and found an independent signal at CPOX near GPR15. In addition, we found 6 new loci at PRSS23, AVPR1B, PSEN2, LINC00299, RPS6KA2, and KIAA0087. Most of the lead probes (13 out of 15) associated with cigarette smoking, overlapped regions of open chromatin (FAIRE and DNaseI hypersensitive sites) or / and H3K27Ac peaks (ENCODE data set), which mark regulatory elements. The effect of smoking on DNA methylation was partially reversible upon smoking cessation for longer than 3 months. We report the first statistically significant interaction between a SNP (rs2697768) and cigarette smoking on DNA methylation (cg03329539). We provide evidence that the metSNP for cg03329539 regulates expression of the CHRND gene located circa 95 Kb downstream of the methylation site. Our findings suggest the existence of dynamic, reversible site-specific methylation changes in response to cigarette smoking , which may contribute to the extended health risks associated with cigarette smoking.

Gene expression changes with age in skin, adipose tissue, blood and brain

BackgroundPrevious studies have demonstrated that gene expression levels change with age. These changes are hypothesized to influence the aging rate of an individual. We analyzed gene expression changes with age in abdominal skin, subcutaneous adipose tissue and lymphoblastoid cell lines in 856 female twins in the age range of 39-85 years. Additionally, we investigated genotypic variants involved in genotype-by-age interactions to understand how the genomic regulation of gene expression alters with age.ResultsUsing a linear mixed model, differential expression with age was identified in 1,672 genes in skin and 188 genes in adipose tissue. Only two genes expressed in lymphoblastoid cell lines showed significant changes with age. Genes significantly regulated by age were compared with expression profiles in 10 brain regions from 100 postmortem brains aged 16 to 83 years. We identified only one age-related gene common to the three tissues. There were 12 genes that showed differential expression with age in both skin and brain tissue and three common to adipose and brain tissues.ConclusionsSkin showed the most age-related gene expression changes of all the tissues investigated, with many of the genes being previously implicated in fatty acid metabolism, mitochondrial activity, cancer and splicing. A significant proportion of age-related changes in gene expression appear to be tissue-specific with only a few genes sharing an age effect in expression across tissues. More research is needed to improve our understanding of the genetic influences on aging and the relationship with age-related diseases.

Genome-wide meta-analysis points to CTC1 and ZNF676 as genes regulating telomere homeostasis in humans

Leukocyte telomere length (LTL) is associated with a number of common age-related diseases and is a heritable trait. Previous genome-wide association studies (GWASs) identified two loci on chromosomes 3q26.2 (TERC) and 10q24.33 (OBFC1) that are associated with the inter-individual LTL variation. We performed a meta-analysis of 9190 individuals from six independent GWAS and validated our findings in 2226 individuals from four additional studies. We confirmed previously reported associations with OBFC1 (rs9419958 P = 9.1 × 10−11) and with the telomerase RNA component TERC (rs1317082, P = 1.1 × 10−8). We also identified two novel genomic regions associated with LTL variation that map near a conserved telomere maintenance complex component 1 (CTC1; rs3027234, P = 3.6 × 10−8) on chromosome17p13.1 and zinc finger protein 676 (ZNF676; rs412658, P = 3.3 × 10−8) on 19p12. The minor allele of rs3027234 was associated with both shorter LTL and lower expression of CTC1. Our findings are consistent with the recent observations that point mutations in CTC1 cause short telomeres in both Arabidopsis and humans affected by a rare Mendelian syndrome. Overall, our results provide novel insights into the genetic architecture of inter-individual LTL variation in the general population.

Gene-gene and gene-environment interactions detected by transcriptome sequence analysis in twins

Understanding the genetic architecture of gene expression is an intermediate step in understanding the genetic architecture of complex diseases. RNA sequencing technologies have improved the quantification of gene expression and allow measurement of allele-specific expression (ASE). ASE is hypothesized to result from the direct effect of cis regulatory variants, but a proper estimation of the causes of ASE has not been performed thus far. In this study, we take advantage of a sample of twins to measure the relative contributions of genetic and environmental effects to ASE, and we find substantial effects from gene × gene (G×G) and gene × environment (G×E) interactions. We propose a model where ASE requires genetic variability in cis, a difference in the sequence of both alleles, but where the magnitude of the ASE effect depends on trans genetic and environmental factors that interact with the cis genetic variants.

Genetic interactions affecting human gene expression identified by variance association mapping

Non-additive interaction between genetic variants, or epistasis, is a possible explanation for the gap between heritability of complex traits and the variation explained by identified genetic loci. Interactions give rise to genotype dependent variance, and therefore the identification of variance quantitative trait loci can be an intermediate step to discover both epistasis and gene by environment effects (GxE). Using RNA-sequence data from lymphoblastoid cell lines (LCLs) from the TwinsUK cohort, we identify a candidate set of 508 variance associated SNPs. Exploiting the twin design we show that GxE plays a role in ∼70% of these associations. Further investigation of these loci reveals 57 epistatic interactions that replicated in a smaller dataset, explaining on average 4.3% of phenotypic variance. In 24 cases, more variance is explained by the interaction than their additive contributions. Using molecular phenotypes in this way may provide a route to uncovering genetic interactions underlying more complex traits. DOI: http://dx.doi.org/10.7554/eLife.01381.001

An integrated epigenomic analysis for type 2 diabetes susceptibility loci in monozygotic twins

DNA methylation has a great potential for understanding the aetiology of common complex traits such as Type 2 diabetes (T2D). Here we perform genome-wide methylated DNA immunoprecipitation sequencing (MeDIP-seq) in whole-blood-derived DNA from 27 monozygotic twin pairs and follow up results with replication and integrated omics analyses. We identify predominately hypermethylated T2D-related differentially methylated regions (DMRs) and replicate the top signals in 42 unrelated T2D cases and 221 controls. The strongest signal is in the promoter of the MALT1 gene, involved in insulin and glycaemic pathways, and related to taurocholate levels in blood. Integrating the DNA methylome findings with T2D GWAS meta-analysis results reveals a strong enrichment for DMRs in T2D-susceptibility loci. We also detect signals specific to T2D-discordant twins in the GPR61 and PRKCB genes. These replicated T2D associations reflect both likely causal and consequential pathways of the disease. The analysis indicates how an integrated genomics and epigenomics approach, utilizing an MZ twin design, can provide pathogenic insights as well as potential drug targets and biomarkers for T2D and other complex traits.

Sixteen new lung function signals identified through 1000 Genomes Project reference panel imputation.

Lung function measures are used in the diagnosis of chronic obstructive pulmonary disease. In 38,199 European ancestry individuals, we studied genome-wide association of forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC) and FEV1/FVC with 1000 Genomes Project (phase 1)-imputed genotypes and followed up top associations in 54,550 Europeans. We identify 14 novel loci (P<5 × 10−8) in or near ENSA, RNU5F-1, KCNS3, AK097794, ASTN2, LHX3, CCDC91, TBX3, TRIP11, RIN3, TEKT5, LTBP4, MN1 and AP1S2, and two novel signals at known loci NPNT and GPR126, providing a basis for new understanding of the genetic determinants of these traits and pulmonary diseases in which they are altered.

Genome-Wide Gene Expression Analysis in Response to Organophosphorus Pesticide Chlorpyrifos and Diazinon in C. elegans

Organophosphorus pesticides (OPs) were originally designed to affect the nervous system by inhibiting the enzyme acetylcholinesterase, an important regulator of the neurotransmitter acetylcholine. Over the past years evidence is mounting that these compounds affect many other processes. Little is known, however, about gene expression responses against OPs in the nematode Caenorhabditis elegans. This is surprising because C. elegans is extensively used as a model species in toxicity studies. To address this question we performed a microarray study in C. elegans which was exposed for 72 hrs to two widely used Ops, chlorpyrifos and diazinon, and a low dose mixture of these two compounds. Our analysis revealed transcriptional responses related to detoxification, stress, innate immunity, and transport and metabolism of lipids in all treatments. We found that for both compounds as well as in the mixture, these processes were regulated by different gene transcripts. Our results illustrate intense, and unexpected crosstalk between gene pathways in response to chlorpyrifos and diazinon in C. elegans.

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same region.

Aging Uncouples Heritability and Expression-QTL in Caenorhabditis elegans

The number and distribution of gene expression QTL (eQTL) represent the genetic architecture of many complex traits, including common human diseases. We previously reported that the heritable eQTL patterns are highly dynamic with age in an N2 × CB4856 recombinant inbred population of the nematode Caenorhabditis elegans. In particular, we showed that the number of eQTL decreased with age. Here, we investigated the reason for this decrease by combining gene expression profiles at three ages in the wild types N2 and CB4856 with the reported expression profiles of the RIL population. We determined heritability and transgression (when gene expression levels in the RILs are more extreme than the parents) and investigated their relation with eQTL changes with age. Transgressive segregation was widespread but depended on physiological age. The percentage of genes with an eQTL increased with a higher heritability in young worms. However, for old worms this percentage hardly increased. Using a single marker approach, we found that almost 20% of genes with heritability >0.9 had an eQTL in developing worms. Surprisingly, only 10% was found in old worms. Using a multimarker approach, this percentage increased to almost 30% for both age groups. Comparison of the single marker to a multiple marker eQTL mapping indicated that heritable regulation of gene expression becomes more polygenic in aging worms due to multiple loci and possible epistatic interactions. We conclude that linkage studies should account for the relation between increased polygenic regulation and diminished effects at older ages.