Abundant quantitative trait loci exist for DNA methylation and gene expression in human brain

Glucocorticoid receptor gene (NR3C1) DNA methylation in association with trauma, psychopathology, transcript expression, or genotypic variation: A systematic review

The glucocorticoid receptor gene (NR3C1) is a critical component of the stress response system. Cytosine methylation of NR3C1 has been repeatedly associated with trauma and mental disorders, including major depression, post-traumatic stress disorder, anxiety, and personality disorders, suggesting that NR3C1 methylation may play a role in stress-related psychopathology. We systematically reviewed 55 studies examining NR3C1 DNA methylation in association with trauma exposure, psychopathology, gene expression, and/or common genetic variants. Overall, a number of NR3C1 CpG sites were significantly associated with trauma or psychopathology, but significant findings were often inconsistent across studies. This lack of consistency is likely influenced by significant methodological variability - experimentally and analytically - across studies. Selected common genetic variants show no significant effect on NR3C1 CpG methylation. In contrast, there was ample evidence linking increased methylation of NR3C1 to reduced expression of this gene. The inverse association between methylation and gene expression shown across eight out of ten studies supports the notion that methylation in the promoter region of NR3C1 is associated with transcriptional silencing.

FADS1-FADS2 genetic polymorphisms are associated with fatty acid metabolism through changes in DNA methylation and gene expression

Background

Genome-wide association studies (GWASs) have shown that genetic variants are important determinants of free fatty acid levels. The mechanisms underlying the associations between genetic variants and free fatty acid levels are incompletely understood. Here, we aimed to identify genetic markers that could influence diverse fatty acid levels in a Chinese population and uncover the molecular mechanisms in terms of DNA methylation and gene expression.

Results

We identified strong associations between single-nucleotide polymorphisms (SNPs) in the fatty acid desaturase (FADS) region and multiple polyunsaturated fatty acids. Expression quantitative trait locus (eQTL) analysis of rs174570 on FADS1 and FADS2 mRNA levels proved that minor allele of rs174570 was associated with decreased FADS1 and FADS2 expression levels (P < 0.05). Methylation quantitative trait locus (mQTL) analysis of rs174570 on DNA methylation levels in three selected regions of FADS region showed that the methylation levels at four CpG sites in FADS1, one CpG site in intragenic region, and three CpG sites in FADS2 were strongly associated with rs174570 (P < 0.05). Then, we demonstrated that methylation levels at three CpG sites in FADS1 were negatively associated with FADS1 and FADS2 expression, while two CpG sites in FADS2 were positively associated with FADS1 and FADS2 expression. Using mediation analysis, we further show that the observed effect of rs174570 on gene expression was tightly correlated with the effect predicted through association with methylation.

Conclusions

Our findings suggest that genetic variants in the FADS region are major genetic modifiers that can regulate fatty acid metabolism through epigenetic gene regulation.

Electronic supplementary material

The online version of this article (10.1186/s13148-018-0545-5) contains supplementary material, which is available to authorized users.

Identification of expression quantitative trait loci associated with schizophrenia and affective disorders in normal brain tissue

Schizophrenia and the affective disorders, here comprising bipolar disorder and major depressive disorder, are psychiatric illnesses that lead to significant morbidity and mortality worldwide. Whilst understanding of their pathobiology remains limited, large case-control studies have recently identified single nucleotide polymorphisms (SNPs) associated with these disorders. However, discerning the functional effects of these SNPs has been difficult as the associated causal genes are unknown. Here we evaluated whether schizophrenia and affective disorder associated-SNPs are correlated with gene expression within human brain tissue. Specifically, to identify expression quantitative trait loci (eQTLs), we leveraged disorder-associated SNPs identified from 11 genome-wide association studies with gene expression levels in post-mortem, neurologically-normal tissue from two independent human brain tissue expression datasets (UK Brain Expression Consortium (UKBEC) and Genotype-Tissue Expression (GTEx)). Utilizing stringent multi-region meta-analyses, we identified 2,224 cis-eQTLs associated with expression of 40 genes, including 11 non-coding RNAs. One cis-eQTL, rs16969968, results in a functionally disruptive missense mutation in CHRNA5, a schizophrenia-implicated gene. Importantly, comparing across tissues, we find that blood eQTLs capture < 10% of brain cis-eQTLs. Contrastingly, > 30% of brain-associated eQTLs are significant in tibial nerve. This study identifies putatively causal genes whose expression in region-specific tissue may contribute to the risk of schizophrenia and affective disorders.

A Perspective of the Cross-Tissue Interplay of Genetics, Epigenetics, and Transcriptomics, and Their Relation to Brain Based Phenotypes in Schizophrenia

Genetic association studies of psychiatric disorders have provided unprecedented insight into disease risk profiles with high confidence. Yet, the next research challenge is how to translate this rich information into mechanisms of disease, and further help interventions and treatments. Given other comprehensive reviews elsewhere, here we want to discuss the research approaches that integrate information across various tissue types. Taking schizophrenia as an example, the tissues, cells, or organisms being investigated include postmortem brain tissues or neurons, peripheral blood and saliva, in vivo brain imaging, and in vitro cell lines, particularly human induced pluripotent stem cells (iPSC) and iPSC derived neurons. There is a wealth of information on the molecular signatures including genetics, epigenetics, and transcriptomics of various tissues, along with neuronal phenotypic measurements including neuronal morphometry and function, together with brain imaging and other techniques that provide data from various spatial temporal points of disease development. Through consistent or complementary processes across tissues, such as cross-tissue methylation quantitative trait loci (QTL) and expression QTL effects, systemic integration of such information holds the promise to put the pieces of puzzle together for a more complete view of schizophrenia disease pathogenesis.

Characterizing genetic and environmental influences on variable DNA methylation using monozygotic and dizygotic twins

Variation in DNA methylation is being increasingly associated with health and disease outcomes. Although DNA methylation is hypothesized to be a mechanism by which both genetic and non-genetic factors can influence the regulation of gene expression, little is known about the extent to which DNA methylation at specific sites is influenced by heritable as well as environmental factors. We quantified DNA methylation in whole blood at age 18 in a birth cohort of 1,464 individuals comprising 426 monozygotic (MZ) and 306 same-sex dizygotic (DZ) twin pairs. Site-specific levels of DNA methylation were more strongly correlated across the genome between MZ than DZ twins. Structural equation models revealed that although the average contribution of additive genetic influences on DNA methylation across the genome was relatively low, it was notably elevated at the highly variable sites characterized by intermediate levels of DNAm that are most relevant for epigenetic epidemiology. Sites at which variable DNA methylation was most influenced by genetic factors were significantly enriched for DNA methylation quantitative trait loci (mQTL) effects, and overlapped with sites where inter-individual variation correlates across tissues. Finally, we show that DNA methylation at sites robustly associated with environmental exposures such as tobacco smoking and obesity is also influenced by additive genetic effects, highlighting the need to control for genetic background in analyses of exposure-associated DNA methylation differences. Estimates of the contribution of genetic and environmental influences to DNA methylation at all sites profiled in this study are available as a resource for the research community (http://www.epigenomicslab.com/online-data-resources).

The study of monozygotic (MZ) and dizygotic (DZ) twins provides an opportunity for exploring the extent to which heritable and environmental factors contribute to phenotypic variation in human populations. We exploit the twin study design to explore the factors influencing epigenetic variation between individuals, focussing on DNA methylation, the best-characterized and most stable epigenetic modification. We find that site-specific levels of DNA methylation are more strongly correlated across the genome between MZ than DZ twins. While the average contribution of additive genetic influences on DNA methylation is relatively low, it is notably elevated at sites that are highly variable and have intermediate levels of DNAm, which are most relevant for epigenetic epidemiology. Sites at which variable DNA methylation is strongly influenced by genetic factors are enriched for DNA methylation quantitative trait loci (mQTL) effects, and overlap with sites where inter-individual variation correlates across tissues. Importantly, we show that DNA methylation at sites robustly associated with environmental exposures such as smoking and obesity is also influenced by genetic effects, highlighting the need to control for genetic background in analyses of exposure-associated DNA methylation differences. Finally, we present a searchable database cataloguing the genetic and environmental contributions to variable DNA methylation across the genome (http://www.epigenomicslab.com/online-data-resources).

Epigenetics: An emerging field in the pathogenesis of nonalcoholic fatty liver disease

Nonalcoholic fatty liver disease (NAFLD) is a major health concern associated with increased mortality due to cardiovascular disease, type II diabetes, insulin resistance, liver disease, and malignancy. The molecular mechanism underlying these processes is not fully understood but involves hepatic fat accumulation and alteration of energy metabolism and inflammatory signals derived from various cell types including immune cells. During the last two decades, epigenetic mechanisms have emerged as important regulators of chromatin alteration and the reprogramming of gene expression. Recently, epigenetic mechanisms have been implicated in the pathogenesis of NAFLD and nonalcoholic steatohepatitis (NASH) genesis. Epigenetic mechanisms could be used as potential therapeutic targets and as noninvasive diagnostic biomarkers for NAFLD. These mechanisms can determine disease progression and prognosis in NAFLD. In this review, we discuss the role of epigenetic mechanisms in the progression of NAFLD and potential therapeutic targets for the treatment of NAFLD.

Interferon-stimulated genes: new platforms and computational approaches

Interferon-stimulated genes (ISGs) are the effectors of interferon (IFN) actions and play major roles in innate immune defense against microbial infection. During virus infection, ISGs impart antiviral actions to control virus replication and spread but can also contribute to disease pathology if their expression is unchecked. Antiviral ISGs have been identified by a variety of biochemical, genetic, and virologic methods. New computational approaches are expanding and redefining ISGs as responders to a variety of stimuli beyond IFNs, including virus infection, stress, and other events that induce cytokines. These studies reveal that the expression of ISG subsets link to interferon regulatory factors (IRF)s, NF-kB, and other transcription factors that impart gene expression in specific cell types independently of IFNs, including stem cells and other cell types where ISGs are constitutively expressed. Here, we provide a broad overview of ISGs, define virus-induced genes (VSG)s, and discuss the application of computational approaches and bioinformatics platforms to evaluate the functional role of ISGs in epigenetics, immune programming, and vaccine responses.

Pattern of DNA Methylation in Daphnia: Evolutionary Perspective

DNA methylation is an evolutionary ancient epigenetic modification that is phylogenetically widespread. Comparative studies of the methylome across a diverse range of non-conventional and conventional model organisms is expected to help reveal how the landscape of DNA methylation and its functions have evolved. Here, we explore the DNA methylation profile of two species of the crustacean Daphnia using whole genome bisulfite sequencing. We then compare our data with the methylomes of two insects and two mammals to achieve a better understanding of the function of DNA methylation in Daphnia. Using RNA-sequencing data for all six species, we investigate the correlation between DNA methylation and gene expression. DNA methylation in Daphnia is mainly enriched within the coding regions of genes, with the highest methylation levels observed at exons 2–4. In contrast, vertebrate genomes are globally methylated, and increase towards the highest methylation levels observed at exon 2, and maintained across the rest of the gene body. Although DNA methylation patterns differ among all species, their methylation profiles share a bimodal distribution across the genomes. Genes with low levels of CpG methylation and gene expression are mainly enriched for species specific genes. In contrast, genes associated with high methylated CpG sites are highly transcribed and evolutionary conserved across all species. Finally, the positive correlation between internal exons and gene expression potentially points to an evolutionary conserved mechanism, whereas the negative regulation of gene expression via methylation of promoters and exon 1 is potentially a secondary mechanism that has been evolved in vertebrates.

Parkinson Disease from Mendelian Forms to Genetic Susceptibility: New Molecular Insights into the Neurodegeneration Process

Parkinson disease (PD) is known as a common progressive neurodegenerative disease which is clinically diagnosed by the manifestation of numerous motor and nonmotor symptoms. PD is a genetically heterogeneous disorder with both familial and sporadic forms. To date, researches in the field of Parkinsonism have identified 23 genes or loci linked to rare monogenic familial forms of PD with Mendelian inheritance. Biochemical studies revealed that the products of these genes usually play key roles in the proper protein and mitochondrial quality control processes, as well as synaptic transmission and vesicular recycling pathways within neurons. Despite this, large number of patients affected with PD typically tends to show sporadic forms of disease with lack of a clear family history. Recent genome-wide association studies (GWAS) meta-analyses on the large sporadic PD case-control samples from European populations have identified over 12 genetic risk factors. However, the genetic etiology that underlies pathogenesis of PD is also discussed, since it remains unidentified in 40% of all PD-affected cases. Nowadays, with the emergence of new genetic techniques, international PD genomics consortiums and public online resources such as PDGene, there are many hopes that future large-scale genetics projects provide further insights into the genetic etiology of PD and improve diagnostic accuracy and therapeutic clinical trial designs.

Reproductive period and epigenetic modifications of the oxidative phosphorylation pathway in the human prefrontal cortex

PURPOSE

Human females have a unique duration of post-reproductive longevity, during which sex-specific mechanisms ma influence later-life mechanisms of neuronal resilience and vulnerability. The maintenance of energy metabolism, through the oxidative phosphorylation (OXPHOS) apparatus, is essential for brain health. Given the known association between reproductive period (years from menarche to menopause) and cognitive aging, we examined the hypothesis that cumulative estrogen exposure across the lifetime may be associated with differential methylation of genes in the OXPHOS pathway.

METHODS

Using DNA methylation patterns in the post-mortem dorsolateral prefrontal cortex (DLPFC) of 426 women prospectively followed until death in the Religious Orders Study and Rush Memory and Aging Project, we examined the relationship between reproductive period (subtracting age at menarche from age at menopause) and DNA methylation of a published set of autosomal OXPHOS genes previously implicated in stroke susceptibility. We then performed an unsupervised analysis of methylation levels across the Hallmark pathways from the Molecular Signatures Database.

RESULTS

We observed a strong association between reproductive period and DNA methylation status across OXPHOS CpGs. We replicated this association between reproductive period and DNA methylation in a much larger set of OXPHOS genes in our unsupervised analysis. Here, reproductive period also showed associations with methylation in genes related to E2F, MYC and MTORC1 signaling, fatty acid metabolism and DNA repair.

CONCLUSION

This study provides evidence from both a supervised and unsupervised analyses, that lifetime cumulative endogenous steroid exposures may play a role in maintenance of post-menopausal cellular balance, including in brain tissue.

Genome-wide methylomic analysis in individuals with HNF1B intragenic mutation and 17q12 microdeletion

Heterozygous mutation of the transcription factor HNF1B is the most common cause of monogenetic developmental renal disease. Disease-associated mutations fall into two categories: HNF1B intragenic mutations and a 1.3 Mb deletion at chromosome 17q12. An increase in neurodevelopmental disorders has been observed in individuals harbouring the 17q12 deletion but not in patients with HNF1B coding mutations.Previous investigations have concentrated on identifying a genetic cause for the increase in behavioural problems seen in 17q12 deletion carriers. We have taken the alternative approach of investigating the DNA methylation profile of these two HNF1B genotype groups along with controls matched for age, gender and diabetes status using the Illumina 450K DNA methylation array (total sample n = 60).We identified a number of differentially methylated probes (DMPs) that were associated with HNF1B-associated disease and passed our stringent experiment-wide significance threshold. These associations were largely driven by the deletion patients and the majority of the significant probes mapped to the 17q12 deletion locus. The observed changes in DNA methylation at this locus were not randomly dispersed and occurred in clusters, suggesting a regulatory mechanism reacting to haploinsufficiency across the entire deleted region.Along with these deletion-specific changes in DNA methylation, we also identified a shared DNA methylation signature in both mutation and deletion patient groups indicating that haploinsufficiency of HNF1B impacts on the methylome of a number of genes, giving further insight to the role of HNF1B.

Neuroepigenetics of Schizophrenia

Schizophrenia is a complex disorder of the brain, where genetic variants explain only a portion of risk. Neuroepigenetic mechanisms may explain the remaining share of risk, as well as the transition from susceptibility to the actual disease. Here, we discuss the most recent findings in the field of brain epigenetics applied to the study of schizophrenia. Methylome studies have found several candidates exhibiting methylation modifications in association with the disorder, but genes affected do not always overlap. Notably, these studies converge in that genes within the schizophrenia risk loci or genes differentially methylated in patients affected with the disorder are dynamically regulated during early life. They also imply that schizophrenia-associated genetic variation may affect DNA methylation in fetal and adult brains. Histone modifications may help mediating the effect of genetic risk variants associated with schizophrenia, and regulating chromatin higher-order structure. The 3D-organization of chromatin in the brain creates physical interactions within chromosomes, so that schizophrenia-associated genetic variants can be linked with genes distant from their loci; this suggests that chromatin conformation matters in the mechanism of risk for the disorder. Non-coding RNAs provide a novel and complex mechanism of gene regulation potentially significant for schizophrenia, as proposed by research on specific microRNAs and long non-coding RNAs (lncRNAs). Finally, a recent study in epitranscriptomics identifies RNA methylation as a further epigenetic mechanism active in human brain and specifically in a portion of the transcriptome associated with schizophrenia susceptibility. These findings indicate that, as expected from the complexity of the brain and its development, several epigenetic mechanisms may intervene in the etiopathogenesis of schizophrenia. An understanding of their roles calls for research approaches integrating the investigation of different epigenetic mechanisms and of environmental and genetic risk, in the context of development.

Genotype-based gene signature of glioma risk

Background

Glioma accounts for 80% of malignant brain tumors, but its etiologic determinants remain elusive. Despite genetic susceptibility loci identified by genome-wide association study (GWAS), the agnostic approach leaves open the possibility that other susceptibility genes remain to be discovered. Here we conduct a gene-centric integrative GWAS (iGWAS) of glioma risk that combines transcriptomics and genetics.

Methods

We synthesized a brain transcriptomics dataset (n = 354), a GWAS dataset (n = 4203), and an advanced glioma tumor transcriptomic dataset (n = 483) to conduct an iGWAS. Using the expression quantitative trait loci (eQTL) dataset, we built models to predict gene expression for the GWAS data, based on eQTL genotypes. With the predicted gene expression, iGWAS analyses were performed using a novel statistical method. Gene signature risk score was constructed using a penalized logistic regression model.

Results

A total of 30527 transcripts were analyzed using the iGWAS approach. Four novel glioma susceptibility genes were identified with internal and external validation, including DRD5 (P = 3.0 × 10-79), WDR1 (P = 8.4 × 10-77), NOMO1 (P = 1.3 × 10-25), and PDXDC1 (P = 8.3 × 10-24). The genotype-predicted transcription pattern between cases and controls is consistent with that between tumor and its matched normal tissue. The genotype-based 4-gene signature improved the classification between glioma cases and controls based on age, gender, and population stratification, with area under the receiver operating characteristic curve increasing from 0.77 to 0.85 (P = 8.1 × 10-23).

Conclusion

A new genotype-based gene signature of glioma was identified using a novel iGWAS approach, which integrates multiplatform genomic data as well as different genetic association studies.

Genome-wide association study identifies a novel locus for cannabis dependence

Despite moderate heritability, only one study has identified genome-wide significant loci for cannabis-related phenotypes. We conducted meta-analyses of genome-wide association study data on 2080 cannabis-dependent cases and 6435 cannabis-exposed controls of European descent. A cluster of correlated single-nucleotide polymorphisms (SNPs) in a novel region on chromosome 10 was genome-wide significant (lowest P=1.3E-8). Among the SNPs, rs1409568 showed enrichment for H3K4me1 and H3K427ac marks, suggesting its role as an enhancer in addiction-relevant brain regions, such as the dorsolateral prefrontal cortex and the angular and cingulate gyri. This SNP is also predicted to modify binding scores for several transcription factors. We found modest evidence for replication for rs1409568 in an independent cohort of African American (896 cases and 1591 controls; P=0.03) but not European American (EA; 781 cases and 1905 controls) participants. The combined meta-analysis (3757 cases and 9931 controls) indicated trend-level significance for rs1409568 (P=2.85E-7). No genome-wide significant loci emerged for cannabis dependence criterion count (n=8050). There was also evidence that the minor allele of rs1409568 was associated with a 2.1% increase in right hippocampal volume in an independent sample of 430 EA college students (fwe-P=0.008). The identification and characterization of genome-wide significant loci for cannabis dependence is among the first steps toward understanding the biological contributions to the etiology of this psychiatric disorder, which appears to be rising in some developed nations.

Integrative Approaches to Understanding the Pathogenic Role of Genetic Variation in Rheumatic Diseases

The use of high-throughput omics may help to understand the contribution of genetic variants to the pathogenesis of rheumatic diseases. We discuss the concept of missing heritability: that genetic variants do not explain the heritability of rheumatoid arthritis and related rheumatologic conditions. In addition to an overview of how integrative data analysis can lead to novel insights into mechanisms of rheumatic diseases, we describe statistical approaches to prioritizing genetic variants for future functional analyses. We illustrate how analyses of large datasets provide hope for improved approaches to the diagnosis, treatment, and prevention of rheumatic diseases.

DNA methylation and transcriptome aberrations mediated by ERα in mouse seminal vesicles following developmental DES exposure

Early transient developmental exposure to an endocrine active compound, diethylstilbestrol (DES), a synthetic estrogen, causes late-stage effects in the reproductive tract of adult mice. Estrogen receptor alpha (ERα) plays a role in mediating these developmental effects. However, the developmental mechanism is not well known in male tissues. Here, we present genome-wide transcriptome and DNA methylation profiling of the seminal vesicles (SVs) during normal development and after DES exposure. ERα mediates aberrations of the mRNA transcriptome in SVs of adult mice following neonatal DES exposure. This developmental exposure impacts differential diseases between male (SVs) and female (uterus) tissues when mice reach adulthood due to most DES-altered genes that appear to be tissue specific during mouse development. Certain estrogen-responsive gene changes in SVs are cell-type specific. DNA methylation dynamically changes during development in the SVs of wild-type (WT) and ERα-knockout (αERKO) mice, which increases both the loss and gain of differentially methylated regions (DMRs). There are more gains of DMRs in αERKO compared with WT. Interestingly, the methylation changes between the two genotypes are in different genomic loci. Additionally, the expression levels of a subset of DES-altered genes are associated with their DNA methylation status following developmental DES exposure. Taken together, these findings provide an important basis for understanding the molecular and cellular mechanism of endocrine-disrupting chemicals (EDCs), such as DES, during development in the male mouse tissues. This unique evidence contributes to our understanding of developmental actions of EDCs in human health.

DNA Methylation and Psychiatric Disorders

DNA methylation has been an important area of research in the study of molecular mechanism to psychiatric disorders. Recent evidence has suggested that abnormalities in global methylation, methylation of genes, and pathways could play a role in the etiology of many forms of mental illness. In this article, we review the mechanisms of DNA methylation, including the genetic and environmental factors affecting methylation changes. We report and discuss major findings regarding DNA methylation in psychiatric patients, both within the context of global methylation studies and gene-specific methylation studies. Finally, we discuss issues surrounding data quality improvement, the limitations of current methylation analysis methods, and the possibility of using DNA methylation-based treatment for psychiatric disorders in the future.

Differences in DNA Methylation and Functional Expression in Lactase Persistent and Non-persistent Individuals

In humans the expression of lactase changes during post-natal development, leading to phenotypes known as lactase persistence and non-persistence. Polymorphisms within the lactase gene (LCT) enhancer, in particular the −13910C > T, but also others, are linked to these phenotypes. We were interested in identifying dynamic mediators of LCT regulation, beyond the genotype at −13910C > T. To this end, we investigated two levels of lactase regulation in human intestinal samples obtained from New England children and adolescents of mixed European ancestry: differential expression of transcriptional regulators of LCT, and variations in DNA methylation, and their relation to phenotype. Variations in expression of CDX2, POU2F1, GATA4, GATA6, and HNF1α did not correlate with phenotype. However, an epigenome-wide approach using the Illumina Infinium HM450 bead chip identified a differentially methylated position in the LCT promoter where methylation levels are associated with the genotype at −13910C > T, the persistence/non-persistence phenotype and lactase enzymatic activity. DNA methylation levels at this promoter site and CpGs in the LCT enhancer are associated with genotype. Indeed, taken together they have a higher power to predict lactase phenotypes than the genotype alone.

Transgenerational epigenetic inheritance in birds

While it has been shown that epigenetics accounts for a portion of the variability of complex traits linked to interactions with the environment, the real contribution of epigenetics to phenotypic variation remains to be assessed. In recent years, a growing number of studies have revealed that epigenetic modifications can be transmitted across generations in several animal species. Numerous studies have demonstrated inter- or multi-generational effects of changing environment in birds, but very few studies have been published showing epigenetic transgenerational inheritance in these species. In this review, we mention work conducted in parent-to-offspring transmission analyses in bird species, with a focus on the impact of early stressors on behaviour. We then present recent advances in transgenerational epigenetics in birds, which involve germline linked non-Mendelian inheritance, underline the advantages and drawbacks of working on birds in this field and comment on future directions of transgenerational studies in bird species.

Single nucleotide polymorphism rs3124599 in Notch1 is associated with the risk of lung cancer in northeast Chinese non-smoking females

Lung cancer is one of the most common cancers and the main cause of cancer-related deaths. Notch1 might play a part in tumorigenesis of lung cancer. Here we explored the relationship of three SNPs (rs3124599, rs3124607 and rs3124594) in Notch1 with the risk and the survival of lung cancer in non-smoking females, including 556 cases and 395 controls. Chi-square tests, logistic regression analysis and crossover analysis were conducted to estimate the association between SNPs and the risk of lung cancer and the interaction between SNPs and environmental exposure. Survival analysis was conducted to explore the association between SNPs and survival of lung cancer. The results demonstrated that the polymorphism of rs3124599 was associated with the susceptibility of lung cancer in recessive model (AA+AG vs. GG). Compared to the those with AA or AG genotype, individuals with GG genotype had a 1.562-fold increased risk of lung cancer (P = 0.023, OR = 1.562, 95% CI = 1.062-2.297). In stratified analysis, the GG genotype of rs3124599 would increase the risk of small cell lung cancer (SCLC) (P = 0.011, OR = 2.167, 95% CI = 1.193-3.396). However, no significant interaction between rs3124599 and cooking oil fume exposure was observed either in addictive model or multiplicative model. The results of survival analysis showed there was no significant association between SNPs and prognosis of lung cancer (P = 0.949 for rs3124599, P = 0.508 for rs3124607, P = 0.884 for rs3124594). Our study might indicate that rs312599 in Notch1 may be a novel biomarker for SCLC risk in Chinese non-smoking females.

Insights into Epigenome Evolution from Animal and Plant Methylomes

Evolutionary studies of DNA methylation offer insights into the mechanisms governing the variation of genomic DNA methylation across different species. Comparisons of gross levels of DNA methylation between distantly related species indicate that the size of the genome and the level of genomic DNA methylation are positively correlated. In plant genomes, this can be reliably explained by the genomic contents of repetitive sequences. In animal genomes, the role of repetitive sequences on genomic DNA methylation is less clear. On a shorter timescale, population-level comparisons demonstrate that genetic variation can explain the observed variability of DNA methylation to some degree. The amount of DNA methylation variation that has been attributed to genetic variation in the human population studies so far is substantially lower than that from Arabidopsis population studies, but this disparity might reflect the differences in the computational and experimental techniques used. The effect of genetic variation on DNA methylation has been directly examined in mammalian systems, revealing several causative factors that govern DNA methylation. On the other hand, studies from Arabidopsis have furthered our understanding of spontaneous mutations of DNA methylation, termed “epimutations.” Arabidopsis has an extremely high rate of spontaneous epimutations, which may play a major role in shaping the global DNA methylation landscape in this genome. Key missing information includes the frequencies of spontaneous epimutations in other lineages, in particular animal genomes, and how population-level variation of DNA methylation leads to species-level differences.

Post-genomic behavioral genetics: From revolution to routine

What was once expensive and revolutionary-full-genome sequence-is now affordable and routine. Costs will continue to drop, opening up new frontiers in behavioral genetics. This shift in costs from the genome to the phenome is most notable in large clinical studies of behavior and associated diseases in cohorts that exceed hundreds of thousands of subjects. Examples include the Women's Health Initiative (www.whi.org), the Million Veterans Program (www.

RESEARCH

va.gov/MVP), the 100 000 Genomes Project (genomicsengland.co.uk) and commercial efforts such as those by deCode (www.decode.com) and 23andme (www.23andme.com). The same transition is happening in experimental neuro- and behavioral genetics, and sample sizes of many hundreds of cases are becoming routine (www.genenetwork.org, www.mousephenotyping.org). There are two major consequences of this new affordability of massive omics datasets: (1) it is now far more practical to explore genetic modulation of behavioral differences and the key role of gene-by-environment interactions. Researchers are already doing the hard part-the quantitative analysis of behavior. Adding the omics component can provide powerful links to molecules, cells, circuits and even better treatment. (2) There is an acute need to highlight and train behavioral scientists in how best to exploit new omics approaches. This review addresses this second issue and highlights several new trends and opportunities that will be of interest to experts in animal and human behaviors.

QuASAR-MPRA: accurate allele-specific analysis for massively parallel reporter assays

Motivation

The majority of the human genome is composed of non-coding regions containing regulatory elements such as enhancers, which are crucial for controlling gene expression. Many variants associated with complex traits are in these regions, and may disrupt gene regulatory sequences. Consequently, it is important to not only identify true enhancers but also to test if a variant within an enhancer affects gene regulation. Recently, allele-specific analysis in high-throughput reporter assays, such as massively parallel reporter assays (MPRAs), have been used to functionally validate non-coding variants. However, we are still missing high-quality and robust data analysis tools for these datasets.

Results

We have further developed our method for allele-specific analysis QuASAR (quantitative allele-specific analysis of reads) to analyze allele-specific signals in barcoded read counts data from MPRA. Using this approach, we can take into account the uncertainty on the original plasmid proportions, over-dispersion, and sequencing errors. The provided allelic skew estimate and its standard error also simplifies meta-analysis of replicate experiments. Additionally, we show that a beta-binomial distribution better models the variability present in the allelic imbalance of these synthetic reporters and results in a test that is statistically well calibrated under the null. Applying this approach to the MPRA data, we found 602 SNPs with significant (false discovery rate 10%) allele-specific regulatory function in LCLs. We also show that we can combine MPRA with QuASAR estimates to validate existing experimental and computational annotations of regulatory variants. Our study shows that with appropriate data analysis tools, we can improve the power to detect allelic effects in high-throughput reporter assays.

Availability and implementation

http://github.com/piquelab/QuASAR/tree/master/mpra.

Contact

fluca@wayne.edu or rpique@wayne.edu.

Supplementary information

Supplementary data are available online at Bioinformatics.

Characterization of cross-tissue genetic-epigenetic effects and their patterns in schizophrenia

Background

One of the major challenges in current psychiatric epigenetic studies is the tissue specificity of epigenetic changes since access to brain samples is limited. Peripheral tissues have been studied as surrogates but the knowledge of cross-tissue genetic-epigenetic characteristics remains largely unknown. In this work, we conducted a comprehensive investigation of genetic influence on DNA methylation across brain and peripheral tissues with the aim to characterize cross-tissue genetic-epigenetic effects and their roles in the pathophysiology of psychiatric disorders.

Methods

Genome-wide methylation quantitative trait loci (meQTLs) from brain prefrontal cortex, whole blood, and saliva were identified separately and compared. Focusing on cis-acting effects, we tested the enrichment of cross-tissue meQTLs among cross-tissue expression QTLs and genetic risk loci of various diseases, including major psychiatric disorders. CpGs targeted by cross-tissue meQTLs were also tested for genomic distribution and functional enrichment as well as their contribution to methylation correlation across tissues. Finally, a consensus co-methylation network analysis on the cross-tissue meQTL targeted CpGs was performed on data of the three tissues collected from schizophrenia patients and controls.

Results

We found a significant overlap of cis meQTLs (45–73 %) and targeted CpG sites (31–68 %) among tissues. The majority of cross-tissue meQTLs showed consistent signs of cis-acting effects across tissues. They were significantly enriched in genetic risk loci of various diseases, especially schizophrenia, and also enriched in cross-tissue expression QTLs. Compared to CpG sites not targeted by any meQTLs, cross-tissue targeted CpGs were more distributed in CpG island shores and enhancer regions, and more likely had strong correlation with methylation levels across tissues. The targeted CpGs were also annotated to genes enriched in multiple psychiatric disorders and neurodevelopment-related pathways. Finally, we identified one co-methylation network shared between brain and blood showing significant schizophrenia association (p = 5.5 × 10⁻⁶).

Conclusions

Our results demonstrate prevalent cross-tissue meQTL effects and their contribution to the correlation of CpG methylation across tissues, while at the same time a large portion of meQTLs show tissue-specific characteristics, especially in brain. Significant enrichment of cross-tissue meQTLs in expression QTLs and genetic risk loci of schizophrenia suggests the potential of these cross-tissue meQTLs for studying the genetic effect on schizophrenia. The study provides compelling motivation for a well-designed experiment to further validate the use of surrogate tissues in the study of psychiatric disorders.

Electronic supplementary material

The online version of this article (10.1186/s13073-018-0519-4) contains supplementary material, which is available to authorized users.

Dyslexia risk variant rs600753 is linked with dyslexia-specific differential allelic expression of DYX1C1

An increasing number of genetic variants involved in dyslexia development were discovered during the last years, yet little is known about the molecular functional mechanisms of these SNPs. In this study we investigated whether dyslexia candidate SNPs have a direct, disease-specific effect on local expression levels of the assumed target gene by using a differential allelic expression assay. In total, 12 SNPs previously associated with dyslexia and related phenotypes were suitable for analysis. Transcripts corresponding to four SNPs were sufficiently expressed in 28 cell lines originating from controls and a family affected by dyslexia. We observed a significant effect of rs600753 on expression levels of DYX1C1 in forward and reverse sequencing approaches. The expression level of the rs600753 risk allele was increased in the respective seven cell lines from members of the dyslexia family which might be due to a disturbed transcription factor binding sites. When considering our results in the context of neuroanatomical dyslexia-specific findings, we speculate that this mechanism may be part of the pathomechanisms underlying the dyslexia-specific brain phenotype. Our results suggest that allele-specific DYX1C1 expression levels depend on genetic variants of rs600753 and contribute to dyslexia. However, these results are preliminary and need replication.

Network analysis of coronary artery disease risk genes elucidates disease mechanisms and druggable targets

Genome-wide association studies (GWAS) have identified over two hundred chromosomal loci that modulate risk of coronary artery disease (CAD). The genes affected by variants at these loci are largely unknown and an untapped resource to improve our understanding of CAD pathophysiology and identify potential therapeutic targets. Here, we prioritized 68 genes as the most likely causal genes at genome-wide significant loci identified by GWAS of CAD and examined their regulatory roles in 286 metabolic and vascular tissue gene-protein sub-networks (“modules”). The modules and genes within were scored for CAD druggability potential. The scoring enriched for targets of cardiometabolic drugs currently in clinical use and in-depth analysis of the top-scoring modules validated established and revealed novel target tissues, biological processes, and druggable targets. This study provides an unprecedented resource of tissue-defined gene–protein interactions directly affected by genetic variance in CAD risk loci.

Identification of expression quantitative trait loci of MTOR associated with the progression of glioma

Mechanistic target of rapamycin (MTOR) encodes a key modulator of cell growth, proliferation, and apoptosis. Previous studies have demonstrated that the dysregulation of MTOR is involved in the development and progression of several types of cancer, including glioma. In the present study, a comprehensive analysis was conducted to examine whether the expression quantitative trait loci (eQTLs) of MTOR are associated with the progression of glioma. Candidate eQTLs of MTOR were obtained from the Genotype-Tissue Expression eQTL Browser. The Kaplan-Meier method and multivariate Cox model were used to analyze the progression-free survival time of glioma patients. Based on the analysis of 138 glioma patients, one eQTL of MTOR, rs4845964, was demonstrated to be significantly associated with the progression of glioma in a dominant manner. The adjusted hazard ratios (HRs) for patients with the AG or AA genotype at rs4845964 were 2.82 [95% confidence interval (CI), 1.27-6.27; P=0.0111] and 2.79 (95% CI, 1.10-7.07; P=0.0312), respectively, compared with those with the GG genotype. When the rs4845964 AG and AA genotypes were combined for analysis, the HR was 2.70 (95% CI, 1.25-5.82; P=0.0114) vs. the GG genotype. Stratified analyses revealed similar associations between the rs4845964 genotypes and the progression of glioma in all subgroups (following stratification by age, sex and tumor grade). These results demonstrate for the first time that the MTOR eQTL rs4845964 is associated with the progression of glioma.

Cross-Tissue Exploration of Genetic and Epigenetic Effects on Brain Gray Matter in Schizophrenia

Closely linking genetics and environment factors, epigenetics has been of increasing interest in psychiatric disease studies. In this work, we integrated single nucleotide polymorphisms (SNPs), DNA methylation of blood and saliva, and brain gray matter (GM) measures to explore the role of genetic and epigenetic variation to the brain structure changes in schizophrenia (SZ). By focusing on the reported SZ genetic risk regions, we applied a multi-stage multivariate analysis to a discovery dataset (92 SZ patients and 110 controls, blood) and an independent replication dataset (93 SZ patients and 99 controls, saliva). Two pairs of SNP-methylation components were significantly correlated (r = .48 and .35) in blood DNA, and replicated (r = .46 and .29) in saliva DNA, reflecting cross-tissue SNP cis-effects. In the discovery data, both SNP-related methylation components were also associated with one GM component primarily located in cerebellum, caudate, and thalamus. Additionally, another methylation component in NOSIP gene with significant SZ patient differences (P = .009), was associated with 8 GM components (7 with patient differences) including superior, middle, and inferior frontal gyri, superior, middle, and inferior temporal gyri, cerebellum, insula, cuneus, and lingual gyrus. Of these, 5 methylation-GM associations were replicated (P < .05). In contrast, no pairwise significant associations were observed between SNP and GM components. This study strongly supports that compared to genetic variation, epigenetics show broader and more significant associations with brain structure as well as diagnosis, which can be cross-tissue, and the potential in explaining the mechanism of genetic risks in SZ.

Epigenome-wide association study of rheumatoid arthritis identifies differentially methylated loci in B cells

Epigenetic regulation of immune cell types could be critical for the development and maintenance of autoimmune diseases like rheumatoid arthritis (RA). B cells are highly relevant in RA, since patients express autoantibodies and depleting this cell type is a successful therapeutic approach. Epigenetic variation, such as DNA methylation, may mediate the pathogenic activity of B cells. In this study, we performed an epigenome-wide association study (EWAS) for RA with three different replication cohorts, to identify disease-specific alterations in DNA methylation in B cells. CpG methylation in isolated B lymphocytes was assayed on the Illumina HumanMethylation450 BeadChip in a discovery cohort of RA patients (N = 50) and controls (N = 75). Differential methylation was observed in 64 CpG sites (q < 0.05). Six biological pathways were also differentially methylated in RA B cells. Analysis in an independent cohort of patients (N = 15) and controls (N = 15) validated the association of 10 CpG sites located on 8 genes CD1C, TNFSF10, PARVG, NID1, DHRS12, ITPK1, ACSF3 and TNFRSF13C, and 2 intergenic regions. Differential methylation at the CBL signaling pathway was replicated. Using an additional case-control cohort (N = 24), the association between RA risk and CpGs cg18972751 at CD1C (P = 2.26 × 10-9) and cg03055671 at TNFSF10 (P = 1.67 × 10-8) genes was further validated. Differential methylation at genes CD1C, TNFSF10, PARVG, NID1, DHRS12, ITPK1, ACSF3, TNFRSF13C and intergenic region chr10p12.31 was replicated in a cohort of systemic lupus erythematosus (SLE) patients (N = 47) and controls (N = 56). Our results highlight genes that may drive the pathogenic activity of B cells in RA and suggest shared methylation patterns with SLE.

Obligatory and facilitative allelic variation in the DNA methylome within common disease-associated loci

Integrating epigenetic data with genome-wide association study (GWAS) results can reveal disease mechanisms. The genome sequence itself also shapes the epigenome, with CpG density and transcription factor binding sites (TFBSs) strongly encoding the DNA methylome. Therefore, genetic polymorphism impacts on the observed epigenome. Furthermore, large genetic variants alter epigenetic signal dosage. Here, we identify DNA methylation variability between GWAS-SNP risk and non-risk haplotypes. In three subsets comprising 3128 MeDIP-seq peripheral-blood DNA methylomes, we find 7173 consistent and functionally enriched Differentially Methylated Regions. 36.8% can be attributed to common non-SNP genetic variants. CpG-SNPs, as well as facilitative TFBS-motifs, are also enriched. Highlighting their functional potential, CpG-SNPs strongly associate with allele-specific DNase-I hypersensitivity sites. Our results demonstrate strong DNA methylation allelic differences driven by obligatory or facilitative genetic effects, with potential direct or regional disease-related repercussions. These allelic variations require disentangling from pure tissue-specific modifications, may influence array studies, and imply underestimated population variability in current reference epigenomes.

Genomic polymorphisms affect the epigenome, which in turn influences how epigenome- and genome-wide analysis are interpreted. Here, the authors characterise allelic differences in DNA methylation driven by obligatory or facilitative genetic effects, which may affect disease-related loci.

Brain donation at autopsy: clinical characterization and toxicologic analyses

The study of postmortem human brain tissue is central to the advancement of neurobiologic studies of psychiatric and neurologic illnesses, particularly the study of brain-specific isoforms and molecules. Due to tissue demands, especially pertaining to brain regions strongly implicated in the pathophysiology of neuropsychiatric disorders, the success and future of this research depend on the availability of high-quality brain specimens from large numbers of subjects, including nonpsychiatric controls, both of which may be obtained from brain banks. In this chapter, we elaborate on the need for and acquisition of well-curated and properly diagnosed postmortem human brains, relying upon our experience with the Human Brain and Tissue Repository located at the Lieber Institute for Brain Development in Baltimore, MD. We explain the advantages of sourcing postmortem human tissue from medical examiner offices, which provide access to cases of all ages, both with and without central nervous system disorders. Neuropathology analyses and toxicologic screenings, along with autopsy reports and extensive interviews with family members and treating physicians, are invaluable to the diagnoses of postmortem cases. Ultimately, the study of psychiatric and neurologic disorders is the study of brain disease, and accordingly, there is no substitution for human brain tissue.

The effects of DNA methylation on human psychology

DNA methylation is a fundamental epigenetic modification in the human genome; pivotal in development, genomic imprinting, X inactivation, chromosome stability, gene expression and methylation aberrations are involved in an array of human diseases. Methylation at promoters is associated with transcriptional repression, whereas gene body methylation is generally associated with gene expression. Extrinsic factors such as age, diets and lifestyle affect DNA methylation which consequently alters gene expression. Stress, anxiety, depression, life satisfaction, emotion among numerous other psychological factors also modify DNA methylation patterns. This correlation is frequently investigated in four candidate genes; NR3C1, SLC6A4, BDNF and OXTR, since regulation of these genes directly impact responses to social situations, stress, threats, behaviour and neural functions. Such studies underpin the hypothesis that DNA methylation is involved in deviant human behaviour, psychological and psychiatric conditions. These candidate genes may be targeted in future to assess the correlation between methylation, social experiences and long-term behavioural phenotypes in humans; and may potentially serve as biomarkers for therapeutic intervention.

Impact of regulatory variation across human iPSCs and differentiated cells

Induced pluripotent stem cells (iPSCs) are an essential tool for studying cellular differentiation and cell types that are otherwise difficult to access. We investigated the use of iPSCs and iPSC-derived cells to study the impact of genetic variation on gene regulation across different cell types and as models for studies of complex disease. To do so, we established a panel of iPSCs from 58 well-studied Yoruba lymphoblastoid cell lines (LCLs); 14 of these lines were further differentiated into cardiomyocytes. We characterized regulatory variation across individuals and cell types by measuring gene expression levels, chromatin accessibility, and DNA methylation. Our analysis focused on a comparison of inter-individual regulatory variation across cell types. While most cell-type-specific regulatory quantitative trait loci (QTLs) lie in chromatin that is open only in the affected cell types, we found that 20% of cell-type-specific regulatory QTLs are in shared open chromatin. This observation motivated us to develop a deep neural network to predict open chromatin regions from DNA sequence alone. Using this approach, we were able to use the sequences of segregating haplotypes to predict the effects of common SNPs on cell-type-specific chromatin accessibility.

Risk alleles of genes with monoallelic expression are enriched in gain-of-function variants and depleted in loss-of-function variants for neurodevelopmental disorders

Over 3000 human genes can be expressed from a single allele in one cell, and from the other allele-or both-in neighboring cells. Little is known about the consequences of this epigenetic phenomenon, monoallelic expression (MAE). We hypothesized that MAE increases expression variability, with a potential impact on human disease. Here, we use a chromatin signature to infer MAE for genes in lymphoblastoid cell lines and human fetal brain tissue. We confirm that across clones MAE status correlates with expression level, and that in human tissue data sets, MAE genes show increased expression variability. We then compare mono- and biallelic genes at three distinct scales. In the human population, we observe that genes with polymorphisms influencing expression variance are more likely to be MAE (P<1.1 × 10-6). At the trans-species level, we find gene expression differences and directional selection between humans and chimpanzees more common among MAE genes (P<0.05). Extending to human disease, we show that MAE genes are under-represented in neurodevelopmental copy number variants (CNVs) (P<2.2 × 10-10), suggesting that pathogenic variants acting via expression level are less likely to involve MAE genes. Using neuropsychiatric single-nucleotide polymorphism (SNP) and single-nucleotide variant (SNV) data, we see that genes with pathogenic expression-altering or loss-of-function variants are less likely MAE (P<7.5 × 10-11) and genes with only missense or gain-of-function variants are more likely MAE (P<1.4 × 10-6). Together, our results suggest that MAE genes tolerate a greater range of expression level than biallelic expression (BAE) genes, and this information may be useful in prediction of pathogenicity.

Enhancing GTEx by bridging the gaps between genotype, gene expression, and disease

Genetic variants have been associated with myriad molecular phenotypes that provide new insight into the range of mechanisms underlying genetic traits and diseases. Identifying any particular genetic variant's cascade of effects, from molecule to individual, requires assaying multiple layers of molecular complexity. We introduce the Enhancing GTEx (eGTEx) project that extends the GTEx project to combine gene expression with additional intermediate molecular measurements on the same tissues to provide a resource for studying how genetic differences cascade through molecular phenotypes to impact human health.

Common DNA methylation alterations of Alzheimer's disease and aging in peripheral whole blood

Alzheimer's disease (AD) is a common aging-related neurodegenerative illness. Recently, many studies have tried to identify AD- or aging-related DNA methylation (DNAm) biomarkers from peripheral whole blood (PWB). However, the origin of PWB biomarkers is still controversial. In this study, by analyzing 2565 DNAm profiles for PWB and brain tissue, we showed that aging-related DNAm CpGs (Age-CpGs) and AD-related DNAm CpGs (AD-CpGs) observable in PWB both mainly reflected DNAm alterations intrinsic in leukocyte subtypes rather than methylation differences introduced by the increased ratio of myeloid to lymphoid cells during aging or AD progression. The PWB Age-CpGs and AD-CpGs significantly overlapped 107 sites (P-value = 2.61×10⁻¹²) and 97 had significantly concordant methylation alterations in AD and aging (P-value < 2.2×10⁻¹⁶), which were significantly enriched in nervous system development, neuron differentiation and neurogenesis. More than 60.8% of these 97 concordant sites were found to be significantly correlated with age in normal peripheral CD4⁺ T cells and CD14⁺ monocytes as well as in four brain regions, and 44 sites were also significantly differentially methylated in different regions of AD brain tissue. Taken together, the PWB DNAm alterations related to both aging and AD could be exploited for identification of AD biomarkers.

Role of genetic and environmental factors in DNA methylation of lipid metabolism

A number of recent studies revealed that DNA methylation plays a central role in the regulation of lipid metabolism. DNA methylation modifications are important regulators of transcriptional networks that do not affect the DNA sequence and can translate genetic variants and environmental factors into phenotypic traits. Therefore, elucidating the factors that underlie inter-individual DNA methylation variations gives us an opportunity to predict diseases and interfere with the establishment of aberrant DNA methylation early. In this review, we summarize the findings of DNA methylation-related studies focused on unravelling the potential role of genetic and environmental factors in DNA methylation and the regulatory effect of DNA methylation on gene expression in lipid metabolism.

Major Shifts in Glial Regional Identity Are a Transcriptional Hallmark of Human Brain Aging

Gene expression studies suggest that aging of the human brain is determined by a complex interplay of molecular events, although both its region- and cell-type-specific consequences remain poorly understood. Here, we extensively characterized aging-altered gene expression changes across ten human brain regions from 480 individuals ranging in age from 16 to 106 years. We show that astrocyte- and oligodendrocyte-specific genes, but not neuron-specific genes, shift their regional expression patterns upon aging, particularly in the hippocampus and substantia nigra, while the expression of microglia- and endothelial-specific genes increase in all brain regions. In line with these changes, high-resolution immunohistochemistry demonstrated decreased numbers of oligodendrocytes and of neuronal subpopulations in the aging brain cortex. Finally, glial-specific genes predict age with greater precision than neuron-specific genes, thus highlighting the need for greater mechanistic understanding of neuron-glia interactions in aging and late-life diseases.

Parkinson disease polygenic risk score is associated with Parkinson disease status and age at onset but not with alpha-synuclein cerebrospinal fluid levels

BACKGROUND

The genetic architecture of Parkinson's Disease (PD) is complex and not completely understood. Multiple genetic studies to date have identified multiple causal genes and risk loci. Nevertheless, most of the expected genetic heritability remains unexplained. Polygenic risk scores (PRS) may provide greater statistical power and inform about the genetic architecture of multiple phenotypes. The aim of this study was to test the association between PRS and PD risk, age at onset and cerebrospinal fluid (CSF) biomarkers (α-synuclein, Aβ_1-42, t-tau and p-tau).

METHODS

The weighted PRS was created using the genome-wide loci from Nalls et al., 2014 PD GWAs meta-analysis. The PRS was tested for association with PD status, age at onset and CSF biomarker levels in 829 cases and 432 controls of European ancestry.

RESULTS

The PRS was associated with PD status (p = 5.83×10^-08) and age at onset (p = 5.70×10^-07). The CSF t-tau levels showed a nominal association with the PRS (p = 0.02). However, CSF α-synuclein, amyloid beta and phosphorylated tau were not found to be associated with the PRS.

CONCLUSION

Our study suggests that there is an overlap in the genetic architecture of PD risk and onset, although the different loci present different weights for those phenotypes. In our dataset we found a marginal association of the PRS with CSF t-tau but not with α-synuclein CSF levels, suggesting that the genetic architecture for the CSF biomarker levels is different from that of PD risk.

Genome-wide mapping of genetic determinants influencing DNA methylation and gene expression in human hippocampus

Emerging evidence emphasizes the strong impact of regulatory genomic elements in neurodevelopmental processes and the complex pathways of brain disorders. The present genome-wide quantitative trait loci analyses explore the cis-regulatory effects of single-nucleotide polymorphisms (SNPs) on DNA methylation (meQTL) and gene expression (eQTL) in 110 human hippocampal biopsies. We identify cis-meQTLs at 14,118 CpG methylation sites and cis-eQTLs for 302 3'-mRNA transcripts of 288 genes. Hippocampal cis-meQTL-CpGs are enriched in flanking regions of active promoters, CpG island shores, binding sites of the transcription factor CTCF and brain eQTLs. Cis-acting SNPs of hippocampal meQTLs and eQTLs significantly overlap schizophrenia-associated SNPs. Correlations of CpG methylation and RNA expression are found for 34 genes. Our comprehensive maps of cis-acting hippocampal meQTLs and eQTLs provide a link between disease-associated SNPs and the regulatory genome that will improve the functional interpretation of non-coding genetic variants in the molecular genetic dissection of brain disorders.

Epigenetic regulation of AXL and risk of childhood asthma symptoms

Background

AXL is one of the TAM (TYRO3, AXL and MERTK) receptor tyrosine kinases and may affect numerous immune-related health conditions. However, the role for AXL in asthma, including its epigenetic regulation, has not been extensively studied.

Methods

We investigated the association between AXL DNA methylation at birth and risk of childhood asthma symptoms at age 6 years. DNA methylation of multiple CpG loci across the regulatory regions of AXL was measured in newborn bloodspots using the Illumina HumanMethylation450 array on a subset of 246 children from the Children's Health Study (CHS). Logistic regression models were fitted to assess the association between asthma symptoms and DNA methylation. Findings were evaluated for replication in a separate population of 1038 CHS subjects using Pyrosequencing on newborn bloodspot samples. AXL genotypes were extracted from genome-wide data.

Results

Higher average methylation of CpGs in the AXL gene at birth was associated with higher risk of parent-reported wheezing, and the association was stronger in girls than in boys. This relationship reflected the methylation status of the gene-body region near the 5' end, for which a 1% higher methylation level was significantly associated with a 72% increased risk of ever having wheezed by 6 years. The association of one CpG locus, cg00360107 was replicated using Pyrosequencing. Increased AXL methylation was also associated with lower mRNA expression level of this gene in lung tissue from the Cancer Genome Atlas (TCGA) dataset. Furthermore, AXL DNA methylation was strongly linked to underlying genetic polymorphisms.

Conclusions

AXL DNA methylation at birth was associated with higher risk for asthma-related symptoms in early childhood.

Epigenomics and human adaptation to high altitude

Over the past decade, major technological and analytical advancements have propelled efforts toward identifying the molecular mechanisms that govern human adaptation to high altitude. Despite remarkable progress with respect to the identification of adaptive genomic signals that are strongly associated with the "hypoxia-tolerant" physiological characteristics of high-altitude populations, many questions regarding the fundamental biological processes underlying human adaptation remain unanswered. Vital to address these enduring questions will be determining the role of epigenetic processes, or non-sequence-based features of the genome, that are not only critical for the regulation of transcriptional responses to hypoxia but heritable across generations. This review proposes that epigenomic processes are involved in shaping patterns of adaptation to high altitude by influencing adaptive potential and phenotypic variability under conditions of limited oxygen supply. Improved understanding of the interaction between genetic, epigenetic, and environmental factors holds great promise to provide deeper insight into the mechanisms underlying human adaptive potential, and clarify its implications for biomedical research.

Protocol for the EMPHASIS study; epigenetic mechanisms linking maternal pre-conceptional nutrition and children's health in India and Sub-Saharan Africa

Background

Animal studies have shown that nutritional exposures during pregnancy can modify epigenetic marks regulating fetal development and susceptibility to later disease, providing a plausible mechanism to explain the developmental origins of health and disease. Human observational studies have shown that maternal peri-conceptional diet predicts DNA methylation in offspring. However, a causal pathway from maternal diet, through changes in DNA methylation, to later health outcomes has yet to be established. The EMPHASIS study (Epigenetic Mechanisms linking Pre-conceptional nutrition and Health Assessed in India and Sub-Saharan Africa, ISRCTN14266771) will investigate epigenetically mediated links between peri-conceptional nutrition and health-related outcomes in children whose mothers participated in two randomized controlled trials of micronutrient supplementation before and during pregnancy.

Methods

The original trials were the Mumbai Maternal Nutrition Project (MMNP, ISRCTN62811278) in which Indian women were offered a daily snack made from micronutrient-rich foods or low-micronutrient foods (controls), and the Peri-conceptional Multiple Micronutrient Supplementation Trial (PMMST, ISRCTN13687662) in rural Gambia, in which women were offered a daily multiple micronutrient (UNIMMAP) tablet or placebo. In the EMPHASIS study, DNA methylation will be analysed in the children of these women (~1100 children aged 5–7 y in MMNP and 298 children aged 7–9 y in PMMST). Cohort-specific and cross-cohort effects will be explored. Differences in DNA methylation between allocation groups will be identified using the Illumina Infinium MethylationEPIC array, and by pyrosequencing top hits and selected candidate loci. Associations will be analysed between DNA methylation and health-related phenotypic outcomes, including size at birth, and children’s post-natal growth, body composition, skeletal development, cardio-metabolic risk markers (blood pressure, serum lipids, plasma glucose and insulin) and cognitive function. Pathways analysis will be used to test for enrichment of nutrition-sensitive loci in biological pathways. Causal mechanisms for nutrition-methylation-phenotype associations will be explored using Mendelian Randomization. Associations between methylation unrelated to supplementation and phenotypes will also be analysed.

Conclusion

The study will increase understanding of the epigenetic mechanisms underpinning the long-term impact of maternal nutrition on offspring health. It will potentially lead to better nutritional interventions for mothers preparing for pregnancy, and to identification of early life biomarkers of later disease risk.

Mapping eQTL by leveraging multiple tissues and DNA methylation

Background

DNA methylation is an important tissue-specific epigenetic event that influences transcriptional regulation of gene expression. Differentially methylated CpG sites may act as mediators between genetic variation and gene expression, and this relationship can be exploited while mapping multi-tissue expression quantitative trait loci (eQTL). Current multi-tissue eQTL mapping techniques are limited to only exploiting gene expression patterns across multiple tissues either in a joint tissue or tissue-by-tissue frameworks. We present a new statistical approach that enables us to model the effect of germ-line variation on tissue-specific gene expression in the presence of effects due to DNA methylation.

Results

Our method efficiently models genetic and epigenetic variation to identify genomic regions of interest containing combinations of mRNA transcripts, CpG sites, and SNPs by jointly testing for genotypic effect and higher order interaction effects between genotype, methylation and tissues. We demonstrate using Monte Carlo simulations that our approach, in the presence of both genetic and DNA methylation effects, gives an improved performance (in terms of statistical power) to detect eQTLs over the current eQTL mapping approaches. When applied to an array-based dataset from 150 neuropathologically normal adult human brains, our method identifies eQTLs that were undetected using standard tissue-by-tissue or joint tissue eQTL mapping techniques. As an example, our method identifies eQTLs by leveraging methylated CpG sites in a LIM homeobox member gene (LHX9), which may have a role in the neural development.

Conclusions

Our score test-based approach does not need parameter estimation under the alternative hypothesis. As a result, our model parameters are estimated only once for each mRNA - CpG pair. Our model specifically studies the effects of non-coding regions of DNA (in this case, CpG sites) on mapping eQTLs. However, we can easily model micro-RNAs instead of CpG sites to study the effects of post-transcriptional events in mapping eQTL. Our model’s flexible framework also allows us to investigate other genomic events such as alternative gene splicing by extending our model to include gene isoform-specific data.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1856-9) contains supplementary material, which is available to authorized users.

Consensus Genome-Wide Expression Quantitative Trait Loci and Their Relationship with Human Complex Trait Disease

Most of the risk loci identified from genome-wide association (GWA) studies do not provide direct information on the biological basis of a disease or on the underlying mechanisms. Recent expression quantitative trait locus (eQTL) association studies have provided information on genetic factors associated with gene expression variation. These eQTLs might contribute to phenotype diversity and disease susceptibility, but interpretation is handicapped by low reproducibility of the expression results. To address this issue, we have generated a set of consensus eQTLs by integrating publicly available data for specific human populations and cell types. Overall, we find over 4000 genes that are involved in high-confidence eQTL relationships. To elucidate the role that eQTLs play in human common diseases, we matched the high-confidence eQTLs to a set of 335 disease risk loci identified from the Wellcome Trust Case Control Consortium GWA study and follow-up studies for 7 human complex trait diseases-bipolar disorder (BD), coronary artery disease (CAD), Crohn's disease (CD), hypertension (HT), rheumatoid arthritis (RA), type 1 diabetes (T1D), and type 2 diabetes (T2D). The results show that the data are consistent with ∼50% of these disease loci arising from an underlying expression change mechanism.

RL-SKAT: An Exact and Efficient Score Test for Heritability and Set Tests

Testing for the existence of variance components in linear mixed models is a fundamental task in many applicative fields. In statistical genetics, the score test has recently become instrumental in the task of testing an association between a set of genetic markers and a phenotype. With few markers, this amounts to set-based variance component tests, which attempt to increase power in association studies by aggregating weak individual effects. When the entire genome is considered, it allows testing for the heritability of a phenotype, defined as the proportion of phenotypic variance explained by genetics. In the popular score-based Sequence Kernel Association Test (SKAT) method, the assumed distribution of the score test statistic is uncalibrated in small samples, with a correction being computationally expensive. This may cause severe inflation or deflation of P-values, even when the null hypothesis is true. Here, we characterize the conditions under which this discrepancy holds, and show it may occur also in large real datasets, such as a dataset from the Wellcome Trust Case Control Consortium 2 (n = 13,950) study, and, in particular, when the individuals in the sample are unrelated. In these cases, the SKAT approximation tends to be highly overconservative and therefore underpowered. To address this limitation, we suggest an efficient method to calculate exact P-values for the score test in the case of a single variance component and a continuous response vector, which can speed up the analysis by orders of magnitude. Our results enable fast and accurate application of the score test in heritability and in set-based association tests. Our method is available in http://github.com/cozygene/RL-SKAT.

Genome-wide association analysis identifies 30 new susceptibility loci for schizophrenia

We conducted a genome-wide association study (GWAS) with replication in 36,180 Chinese individuals and performed further transancestry meta-analyses with data from the Psychiatry Genomics Consortium (PGC2). Approximately 95% of the genome-wide significant (GWS) index alleles (or their proxies) from the PGC2 study were overrepresented in Chinese schizophrenia cases, including ∼50% that achieved nominal significance and ∼75% that continued to be GWS in the transancestry analysis. The Chinese-only analysis identified seven GWS loci; three of these also were GWS in the transancestry analyses, which identified 109 GWS loci, thus yielding a total of 113 GWS loci (30 novel) in at least one of these analyses. We observed improvements in the fine-mapping resolution at many susceptibility loci. Our results provide several lines of evidence supporting candidate genes at many loci and highlight some pathways for further research. Together, our findings provide novel insight into the genetic architecture and biological etiology of schizophrenia.

Inferring Past Environments from Ancient Epigenomes

Analyzing the conditions in which past individuals lived is key to understanding the environments and cultural transitions to which humans had to adapt. Here, we suggest a methodology to probe into past environments, using reconstructed premortem DNA methylation maps of ancient individuals. We review a large body of research showing that differential DNA methylation is associated with changes in various external and internal factors, and propose that loci whose DNA methylation level is environmentally responsive could serve as markers to infer about ancient daily life, diseases, nutrition, exposure to toxins, and more. We demonstrate this approach by showing that hunger-related DNA methylation changes are found in ancient hunter-gatherers. The strategy we present here opens a window to reconstruct previously inaccessible aspects of the lives of past individuals.

An xQTL map integrates the genetic architecture of the human brain's transcriptome and epigenome

We report a multi-omic resource generated by applying quantitative trait locus (xQTL) analyses to RNA sequence, DNA methylation and histone acetylation data from the dorsolateral prefrontal cortex of 411 older adults who have all three data types. We identify SNPs significantly associated with gene expression, DNA methylation and histone modification levels. Many of these SNPs influence multiple molecular features, and we demonstrate that SNP effects on RNA expression are fully mediated by epigenetic features in 9% of these loci. Further, we illustrate the utility of our new resource, xQTL Serve, by using it to prioritize the cell type(s) most affected by an xQTL. We also reanalyze published genome wide association studies using an xQTL-weighted analysis approach and identify 18 new schizophrenia and 2 new bipolar susceptibility variants, which is more than double the number of loci that can be discovered with a larger blood-based expression eQTL resource.