A whole-blood transcriptome meta-analysis identifies gene expression signatures of cigarette smoking.

Cigarette smoking is a leading modifiable cause of death worldwide. We hypothesized that cigarette smoking induces extensive transcriptomic changes that lead to target-organ damage and smoking-related diseases. We performed a meta-analysis of transcriptome-wide gene expression using whole blood-derived RNA from 10,233 participants of European ancestry in six cohorts (including 1421 current and 3955 former smokers) to identify associations between smoking and altered gene expression levels. At a false discovery rate (FDR) <0.1, we identified 1270 differentially expressed genes in current vs. never smokers, and 39 genes in former vs. never smokers. Expression levels of 12 genes remained elevated up to 30 years after smoking cessation, suggesting that the molecular consequence of smoking may persist for decades. Gene ontology analysis revealed enrichment of smoking-related genes for activation of platelets and lymphocytes, immune response, and apoptosis. Many of the top smoking-related differentially expressed genes, including LRRN3 and GPR15, have DNA methylation loci in promoter regions that were recently reported to be hypomethylated among smokers. By linking differential gene expression with smoking-related disease phenotypes, we demonstrated that stroke and pulmonary function show enrichment for smoking-related gene expression signatures. Mediation analysis revealed the expression of several genes (e.g. ALAS2) to be putative mediators of the associations between smoking and inflammatory biomarkers (IL6 and C-reactive protein levels). Our transcriptomic study provides potential insights into the effects of cigarette smoking on gene expression in whole blood and their relations to smoking-related diseases. The results of such analyses may highlight attractive targets for treating or preventing smoking-related health effects.

The transcriptional landscape of age in human peripheral blood.

Disease incidences increase with age, but the molecular characteristics of ageing that lead to increased disease susceptibility remain inadequately understood. Here we perform a whole-blood gene expression meta-analysis in 14,983 individuals of European ancestry (including replication) and identify 1,497 genes that are differentially expressed with chronological age. The age-associated genes do not harbor more age-associated CpG-methylation sites than other genes, but are instead enriched for the presence of potentially functional CpG-methylation sites in enhancer and insulator regions that associate with both chronological age and gene expression levels. We further used the gene expression profiles to calculate the 'transcriptomic age' of an individual, and show that differences between transcriptomic age and chronological age are associated with biological features linked to ageing, such as blood pressure, cholesterol levels, fasting glucose, and body mass index. The transcriptomic prediction model adds biological relevance and complements existing epigenetic prediction models, and can be used by others to calculate transcriptomic age in external cohorts.

Molecular Characterization of the NLRC4 Expression in Relation to Interleukin-18 Levels.

BACKGROUND: Interleukin-18 (IL-18) is a pleiotropic cytokine centrally involved in the cytokine cascade with complex immunomodulatory functions in innate and acquired immunity. Circulating IL-18 concentrations are associated with type 2 diabetes mellitus, cardiovascular events, and diverse inflammatory and autoimmune disorders. METHODS AND RESULTS: To identify causal variants affecting circulating IL-18 concentrations, we applied various omics and molecular biology approaches. By genome-wide association study, we confirmed association of IL-18 levels with a single nucleotide polymorphism in the untranslated exon 2 of the inflammasome component NLRC4 (NLR family, caspase recruitment domain-containing 4) gene on chromosome 2 (rs385076; P=2.4 × 10(-45)). Subsequent molecular analyses by gene expression analysis and reporter gene assays indicated an effect of rs385076 on NLRC4 expression and differential isoform usage by modulating binding of the transcription factor PU.1. CONCLUSIONS: Our study provides evidence for the functional causality of single nucleotide polymorphism rs385076 within the NLRC4 gene in relation to IL-18 activation.

Mitochondrial GWA Analysis of Lipid Profile Identifies Genetic Variants to Be Associated with HDL Cholesterol and Triglyceride Levels.

It has been suggested that mitochondrial dysfunction has an influence on lipid metabolism. The fact that mitochondrial defects can be accumulated over time as a normal part of aging may explain why cholesterol levels often are altered with age. To test the hypothesis whether mitochondrial variants are associated with lipid profile (total cholesterol, LDL, HDL, and triglycerides) we analyzed a total number of 978 mitochondrial single nucleotide polymorphisms (mtSNPs) in a sample of 2,815 individuals participating in the population-based KORA F4 study. To assess mtSNP association while taking the presence of heteroplasmy into account we used the raw signal intensity values measured on the microarray and applied linear regression. Ten mtSNPs (mt3285, mt3336, mt5285, mt6591, mt6671, mt9163, mt13855, mt13958, mt14000, and mt14580) were significantly associated with HDL cholesterol and one mtSNP (mt15074) with triglycerides levels. These results highlight the importance of the mitochondrial genome among the factors that contribute to the regulation of lipid levels. Focusing on mitochondrial variants may lead to further insights regarding the underlying physiological mechanisms, or even to the development of innovative treatments. Since this is the first mitochondrial genome-wide association analysis (mtGWAS) for lipid profile, further analyses are needed to follow up on the present findings.

Prenatal exposure to maternal cigarette smoking and DNA methylation: epigenome-wide association in a discovery sample of adolescents and replication in an independent cohort at birth through 17 years of age.

BACKGROUND: Prenatal exposure to maternal cigarette smoking (prenatal smoke exposure) had been associated with altered DNA methylation (DNAm) at birth. OBJECTIVE: We examined whether such alterations are present from birth through adolescence. METHODS: We used the Infinium HumanMethylation450K BeadChip to search across 473,395 CpGs for differential DNAm associated with prenatal smoke exposure during adolescence in a discovery cohort (n = 132) and at birth, during childhood, and during adolescence in a replication cohort (n = 447). RESULTS: In the discovery cohort, we found five CpGs in MYO1G (top-ranking CpG: cg12803068, p = 3.3 × 10-11) and CNTNAP2 (cg25949550, p = 4.0 × 10-9) to be differentially methylated between exposed and nonexposed individuals during adolescence. The CpGs in MYO1G and CNTNAP2 were associated, respectively, with higher and lower DNAm in exposed versus nonexposed adolescents. The same CpGs were differentially methylated at birth, during childhood, and during adolescence in the replication cohort. In both cohorts and at all developmental time points, the differential DNAm was in the same direction and of a similar magnitude, and was not altered appreciably by adjustment for current smoking by the participants or their parents. In addition, four of the five EWAS (epigenome-wide association study)-significant CpGs in the adolescent discovery cohort were also among the top sites of differential methylation in a previous birth cohort, and differential methylation of CpGs in CYP1A1, AHRR, and GFI1 observed in that study was also evident in our discovery cohort. CONCLUSIONS: Our findings suggest that modifications of DNAm associated with prenatal maternal smoking may persist in exposed offspring for many years-at least until adolescence.

On the potential of models for location and scale for genome-wide DNA methylation data.

BACKGROUND: With the help of epigenome-wide association studies (EWAS), increasing knowledge on the role of epigenetic mechanisms such as DNA methylation in disease processes is obtained. In addition, EWAS aid the understanding of behavioral and environmental effects on DNA methylation. In terms of statistical analysis, specific challenges arise from the characteristics of methylation data. First, methylation ß-values represent proportions with skewed and heteroscedastic distributions. Thus, traditional modeling strategies assuming a normally distributed response might not be appropriate. Second, recent evidence suggests that not only mean differences but also variability in site-specific DNA methylation associates with diseases, including cancer. The purpose of this study was to compare different modeling strategies for methylation data in terms of model performance and performance of downstream hypothesis tests. Specifically, we used the generalized additive models for location, scale and shape (GAMLSS) framework to compare beta regression with Gaussian regression on raw, binary logit and arcsine square root transformed methylation data, with and without modeling a covariate effect on the scale parameter. RESULTS: Using simulated and real data from a large population-based study and an independent sample of cancer patients and healthy controls, we show that beta regression does not outperform competing strategies in terms of model performance. In addition, Gaussian models for location and scale showed an improved performance as compared to models for location only. The best performance was observed for the Gaussian model on binary logit transformed ß-values, referred to as M-values. Our results further suggest that models for location and scale are specifically sensitive towards violations of the distribution assumption and towards outliers in the methylation data. Therefore, a resampling procedure is proposed as a mode of inference and shown to diminish type I error rate in practically relevant settings. We apply the proposed method in an EWAS of BMI and age and reveal strong associations of age with methylation variability that are validated in an independent sample. CONCLUSIONS: Models for location and scale are promising tools for EWAS that may help to understand the influence of environmental factors and disease-related phenotypes on methylation variability and its role during disease development.

An integrated epigenetic and transcriptomic analysis reveals distinct tissue-specific patterns of DNA methylation associated with atopic dermatitis.

Epigenetic alterations are increasingly recognized as mechanisms for disease-associated changes in genome function and important risk factors for complex diseases. The epigenome differs between cell types and so far has been characterized in few human tissues only. In order to identify disease-associated DNA methylation differences for atopic dermatitis (AD), we investigated DNA from whole blood, T cells, B cells, as well as lesional and non-lesional epidermis from AD patients and healthy controls. To elicit functional links, we examined epidermal mRNA expression profiles. No genome-wide significant DNA methylation differences between AD cases and controls were observed in whole blood, T cells, and B cells, and, in general, intra-individual differences in DNA methylation were larger than interindividual differences. However, striking methylation differences were observed between lesional epidermis from patients and healthy control epidermis for various CpG sites, which partly correlated with altered transcript levels of genes predominantly relevant for epidermal differentiation and innate immune response. Significant DNA methylation differences were discordant in skin and blood samples, suggesting that blood is not an ideal surrogate for skin tissue. Our pilot study provides preliminary evidence for functionally relevant DNA methylation differences associated with AD, particularly in the epidermis, and represents a starting point for future investigations of epigenetic mechanisms in AD.

Metabolite profiling reveals new insights into the regulation of serum urate in humans.

Serum urate, the final breakdown product of purine metabolism, is causally involved in the pathogenesis of gout, and implicated in cardiovascular disease and type 2 diabetes. Serum urate levels highly differ between men and women; however the underlying biological processes in its regulation are still not completely understood and are assumed to result from a complex interplay between genetic, environmental and lifestyle factors. In order to describe the metabolic vicinity of serum urate, we analyzed 355 metabolites in 1,764 individuals of the population-based KORA F4 study and constructed a metabolite network around serum urate using Gaussian Graphical Modeling in a hypothesis-free approach. We subsequently investigated the effect of sex and urate lowering medication on all 38 metabolites assigned to the network. Within the resulting network three main clusters could be detected around urate, including the well-known pathway of purine metabolism, as well as several dipeptides, a group of essential amino acids, and a group of steroids. Of the 38 assigned metabolites, 25 showed strong differences between sexes. Association with uricostatic medication intake was not only confined to purine metabolism but seen for seven metabolites within the network. Our findings highlight pathways that are important in the regulation of serum urate and suggest that dipeptides, amino acids, and steroid hormones are playing a role in its regulation. The findings might have an impact on the development of specific targets in the treatment and prevention of hyperuricemia.

Epigenetics meets metabolomics: an epigenome-wide association study with blood serum metabolic traits.

Previously, we reported strong influences of genetic variants on metabolic phenotypes, some of them with clinical relevance. Here, we hypothesize that DNA methylation may have an important and potentially independent effect on human metabolism. To test this hypothesis, we conducted what is to the best of our knowledge the first epigenome-wide association study (EWAS) between DNA methylation and metabolic traits (metabotypes) in human blood. We assess 649 blood metabolic traits from 1814 participants of the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) population study for association with methylation of 457 004 CpG sites, determined on the Infinium HumanMethylation450 BeadChip platform. Using the EWAS approach, we identified two types of methylome-metabotype associations. One type is driven by an underlying genetic effect; the other type is independent of genetic variation and potentially driven by common environmental and life-style-dependent factors. We report eight CpG loci at genome-wide significance that have a genetic variant as confounder (P = 3.9 × 10(-20) to 2.0 × 10(-108), r(2) = 0.036 to 0.221). Seven loci display CpG site-specific associations to metabotypes, but do not exhibit any underlying genetic signals (P = 9.2 × 10(-14) to 2.7 × 10(-27), r(2) = 0.008 to 0.107). We further identify several groups of CpG loci that associate with a same metabotype, such as 4-vinylphenol sulfate and 4-androsten-3-beta,17-beta-diol disulfate. In these cases, the association between CpG-methylation and metabotype is likely the result of a common external environmental factor, including smoking. Our study shows that analysis of EWAS with large numbers of metabolic traits in large population cohorts are, in principle, feasible. Taken together, our data suggest that DNA methylation plays an important role in regulating human metabolism.

Different FCER1A polymorphisms influence IgE levels in asthmatics and non-asthmatics.

BACKGROUND: Recently, three genome-wide association studies (GWAS) demonstrated FCER1A, the gene encoding a ligand-binding subunit of the high-affinity IgE receptor, to be a major susceptibility locus for serum IgE levels. The top association signal differed between the two studies from the general population and the one based on an asthma case-control design. In this study, we investigated whether different FCER1A polymorphisms are associated with total serum IgE in the general population and asthmatics specifically. METHODS: Nineteen polymorphisms were studied in FCER1A based on a detailed literature search and a tagging approach. Polymorphisms were genotyped by the Illumina HumanHap300Chip (6 polymorphisms) or MALDI-TOF MS (13 polymorphisms) in at least 1303 children (651 asthmatics) derived from the German International Study of Asthma and Allergies in Childhood II and Multicentre Asthma Genetics in Childhood Study. RESULTS: Similar to two population-based GWAS, the peak association with total serum IgE was observed for SNPs rs2511211, rs2427837, and rs2251746 (mean r(2) > 0.8), with the lowest p-value of 4.37 × 10(-6). The same 3 polymorphisms showed the strongest association in non-asthmatics (lowest p = 0.0003). While these polymorphisms were also associated with total serum IgE in asthmatics (lowest p = 0.003), additional polymorphisms (rs3845625, rs7522607, and rs2427829) demonstrated associations with total serum IgE in asthmatics only (lowest p = 0.01). CONCLUSIONS: These data suggest that FCER1A polymorphisms not only drive IgE levels in the general population but that specific polymorphisms may also influence IgE in association with asthma, suggesting that disease-specific mechanisms in IgE regulation exist.

Tobacco smoking leads to extensive genome-wide changes in DNA methylation.

Environmental factors such as tobacco smoking may have long-lasting effects on DNA methylation patterns, which might lead to changes in gene expression and in a broader context to the development or progression of various diseases. We conducted an epigenome-wide association study (EWAs) comparing current, former and never smokers from 1793 participants of the population-based KORA F4 panel, with replication in 479 participants from the KORA F3 panel, carried out by the 450K BeadChip with genomic DNA obtained from whole blood. We observed wide-spread differences in the degree of site-specific methylation (with p-values ranging from 9.31E-08 to 2.54E-182) as a function of tobacco smoking in each of the 22 autosomes, with the percent of variance explained by smoking ranging from 1.31 to 41.02. Depending on cessation time and pack-years, methylation levels in former smokers were found to be close to the ones seen in never smokers. In addition, methylation-specific protein binding patterns were observed for cg05575921 within AHRR, which had the highest level of detectable changes in DNA methylation associated with tobacco smoking (-24.40% methylation; p = 2.54E-182), suggesting a regulatory role for gene expression. The results of our study confirm the broad effect of tobacco smoking on the human organism, but also show that quitting tobacco smoking presumably allows regaining the DNA methylation state of never smokers.

Umbilical cord PUFA are determined by maternal and child fatty acid desaturase (FADS) genetic variants in the Avon Longitudinal Study of Parents and Children (ALSPAC).

Fetal supply with long-chain PUFA (LC-PUFA) during pregnancy is important for brain growth and visual and cognitive development and is provided by materno-fetal placental transfer. We recently showed that maternal fatty acid desaturase (FADS) genotypes modulate the amounts of LC-PUFA in maternal blood. Whether FADS genotypes influence the amounts of umbilical cord fatty acids has not been investigated until now. The aim of the present study was to investigate the influence of maternal and child FADS genotypes on the amounts of LC-PUFA in umbilical cord venous plasma as an indicator of fetal fatty acid supply during pregnancy. A total of eleven cord plasma n-6 and n-3 fatty acids were analysed for association with seventeen FADS gene cluster SNP in over 2000 mothers and children from the Avon Longitudinal Study of Parents and Children. In a multivariable analysis, the maternal genotype effect was adjusted for the child genotype and vice versa to estimate which of the two has the stronger influence on cord plasma fatty acids. Both maternal and child FADS genotypes and haplotypes influenced amounts of cord plasma LC-PUFA and fatty acid ratios. Specifically, most analysed maternal SNP were associated with cord plasma levels of the precursor n-6 PUFA, whereas the child genotypes were mainly associated with more highly desaturated n-6 LC-PUFA. This first study on FADS genotypes and cord fatty acids suggests that fetal LC-PUFA status is determined to some extent by fetal fatty acid conversion. Associations of particular haplotypes suggest specific effects of SNP rs498793 and rs968567 on fatty acid metabolism.

CXCR1 and CXCR2 haplotypes synergistically modulate cystic fibrosis lung disease.

Cystic fibrosis (CF) lung disease severity is largely independent on the CF transmembrane conductance regulator (CFTR) genotype, indicating the contribution of genetic modifiers. The chemokine receptors CXCR1 and CXCR2 have been found to play essential roles in the pathogenesis of CF lung disease. Here, we determine whether genetic variation of CXCR1 and CXCR2 influences CF lung disease severity. Genomic DNA of CF patients in Germany (n = 442) was analysed for common variations in CXCR1 and CXCR2 using a single-nucleotide polymorphism (SNP) tagging approach. Associations of CXCR1 and CXCR2 SNPs and haplotypes with CF lung disease severity, CXCR1 and CXCR2 expression, and neutrophil effector functions were assessed. Four SNPs in CXCR1 and three in CXCR2 strongly correlated with age-adjusted lung function in CF patients. SNPs comprising haplotypes CXCR1_Ha and CXCR2_Ha were in high linkage disequilibrium and patients heterozygous for the CXCR1-2 haplotype cluster (CXCR1-2_Ha) had lower lung function compared with patients with homozygous wild-type alleles (forced expiratory volume in 1 s ≤ 70% predicted, OR 7.24; p = 2.30 × 10(-5)). CF patients carrying CXCR1-2_Ha showed decreased CXCR1 combined with increased CXCR2 mRNA and protein expression, and displayed disturbed antibacterial effector functions. CXCR1 and CXCR2 genotypes modulate lung function and antibacterial host defence in CF lung disease.

Genetic variants of the fatty acid desaturase gene cluster predict amounts of red blood cell docosahexaenoic and other polyunsaturated fatty acids in pregnant women: findings from the Avon Longitudinal Study of Parents and Children.

BACKGROUND: Blood and tissue long-chain polyunsaturated fatty acid (LC-PUFA) amounts, which have been associated with early development and lifelong health, depend on dietary intake and endogenous conversion of precursor fatty acids (FAs) by the enzymes Δ5-desaturase and Δ6-desaturase. Polymorphisms in the desaturase encoding genes FADS1 and FADS2 have been associated with several n-6 (omega-6) and n-3 (omega-3) FAs and especially with arachidonic acid (AA) amounts. Associations with docosahexaenoic acid (DHA), which is considered particularly important for brain and retina development, are hardly existent. OBJECTIVE: We explored the relation between FADS gene cluster polymorphisms and red blood cell (RBC) FA amounts in > 4000 pregnant women participating in the Avon Longitudinal Study of Parents and Children. DESIGN: Linear regression analysis of 17 single nucleotide polymorphisms (SNPs) in the FADS gene cluster was conducted with RBC phospholipid FAs from 6711 samples from 4457 women obtained throughout pregnancy (mean ± SD gestational age: 26.8 ± 8.2 wk). RESULTS: Independent of dietary effects, the minor alleles were consistently positively associated with precursor FAs and negatively associated with LC-PUFAs and product:substrate ratios of the n-6 (AA:linoleic acid ratio) and n-3 (eicosapentaenoic acid:α-linolenic acid ratio) pathways. In contrast to previous studies, we also showed significant inverse associations with DHA. Similar but weaker associations were shown for the FADS3 SNP rs174455. CONCLUSIONS: FADS genotypes influence DHA amounts in maternal RBC phospholipids and might affect the child's DHA supply during pregnancy. It is highly likely that a gene product of FADS3 has a desaturating activity.