Genetic estimators of DNA methylation provide insights into the molecular basis of polygenic traits

Freytag, Virginie; Vukojević, Vanja; Wagner-Thelen, Holger; Milnik, Annette; Vogler, Christian; Leber, Markus; Weinhold, Leonie; Böhmer, Anne C.; Riedel‐Heller, Steffi G.; Maier, Wolfgang; Quervain, Dominique J.‐F. de; Ramı́rez, Alfredo; Papassotiropoulos, Andreas

doi:10.1038/s41398-017-0070-x

Cited by 12 publications

(8 citation statements)

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“…To this end, we trained functional expression and splicing reference panels based on the AMP-AD bulk brain and EADB LCL cohorts, and we leveraged precalculated reference panel weights 86 for the GTEx dataset 75 in tissues and cells of interest. Lastly, for the mQTL-GWAS integration domain, we also tested for associations between ADD and genetically driven DNA methylation (MetaMeth analysis) in blood (with blood–brain methylation correlation estimates obtained from BECon 87 ) using the procedures described by Freytag et al 88 and Barbeira et al 89 . A detailed description of the datasets and methods used for each of these analyses is given in the Supplementary Note .…”

Section: Methodsmentioning

confidence: 99%

New insights into the genetic etiology of Alzheimer’s disease and related dementias

et al. 2022

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Characterization of the genetic landscape of Alzheimer’s disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/‘proxy’ AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele.

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Section: Methodsmentioning

confidence: 99%

New insights into the genetic etiology of Alzheimer’s disease and related dementias

et al. 2022

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“…Methylation is essential in facilitating embryonic development, chromosomal infrastructure, cell viability, imprinting, X chromosome-inactivation and transcription [ 3 – 6 ]. Methylation patterns in DNA samples from blood are associated with disease pathogenesis and are influenced by underlying genetic variation [ 7 – 10 ]. Difficulty accessing disease-relevant tissues has meant many studies make use of large gene expression and methylation datasets from peripheral blood as a proxy.…”

Section: Introductionmentioning

confidence: 99%

Genetic regulation of methylation in human endometrium and blood and gene targets for reproductive diseases

et al. 2019

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BackgroundMajor challenges in understanding the functional consequences of genetic risk factors for human disease are which tissues and cell types are affected and the limited availability of suitable tissue. The aim of this study was to evaluate tissue-specific genotype-epigenetic characteristics in DNA samples from both endometrium and blood collected from women at different stages of the menstrual cycle and relate results to genetic risk factors for reproductive traits and diseases.ResultsWe analysed DNA methylation (DNAm) data from endometrium and blood samples from 66 European women. Methylation profiles were compared between stages of the menstrual cycle, and changes in methylation overlaid with changes in transcription and genotypes. We observed large changes in methylation (27,262 DNAm probes) across the menstrual cycle in endometrium that were not observed in blood. Individual genotype data was tested for association with methylation at 443,016 and 443,101 DNAm probes in endometrium and blood respectively to identify methylation quantitative trait loci (mQTLs). A total of 4546 sentinel cis-mQTLs (P < 1.13 × 10−10) and 434 sentinel trans-mQTLs (P < 2.29 × 10−12) were detected in endometrium and 6615 sentinel cis-mQTLs (P < 1.13 × 10−10) and 590 sentinel trans-mQTLs (P < 2.29 × 10−12) were detected in blood. Following secondary analyses, conducted to test for overlap between mQTLs in the two tissues, we found that 62% of endometrial cis-mQTLs were also observed in blood and the genetic effects between tissues were highly correlated. A number of mQTL SNPs were associated with reproductive traits and diseases, including one mQTL located in a known risk region for endometriosis (near GREB1).ConclusionsWe report novel findings characterising genetic regulation of methylation in endometrium and the association of endometrial mQTLs with endometriosis risk and other reproductive traits and diseases. The high correlation of genetic effects between tissues highlights the potential to exploit the power of large mQTL datasets in endometrial research and identify target genes for functional studies. However, tissue-specific methylation profiles and genetic effects also highlight the importance of also using disease-relevant tissues when investigating molecular mechanisms of disease risk.Electronic supplementary materialThe online version of this article (10.1186/s13148-019-0648-7) contains supplementary material, which is available to authorized users.

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“…We examined whether significant genes discovered by MWAS could be similarly uncovered by three alternative strategies. The first strategy utilized the MWAS framework, but used SNP weights derived from a blood-based methylome reference from http://mcn.unibas.ch/files/EstiMethDistribution.zip (39). The second strategy was TWAS with the weights derived from gene expression data using dorsolateral prefrontal cortex, downloaded from the TWAS website (http://gusevlab.org/projects/fusion/#reference-functional-data).…”

Section: Methodsmentioning

confidence: 99%

Integrating brain methylome with GWAS for psychiatric risk gene discovery

Han¹,

Lin

Wang

et al. 2018

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DNA methylation (DNAm) is heritable and plays a role in brain development and function through transcriptional regulation. Aberrant DNAm in human brain has been linked to psychiatric disorders, potentially as mediators of common genetic risk variants. In this study, we hypothesize that common risk variants for psychiatric disorders may act through affecting DNAm level in human brain. We first aimed to investigate the heritability pattern of DNAm levels in the human prefrontal cortex. Secondly, through imputation-driven methylome-wide association study (MWAS), we aimed to identify CpG sites whose methylation levels are genetically associated and that show methylation-trait associations in the prefrontal cortex of patients with schizophrenia or bipolar disorder. Our heritability analysis showed that, of ~370,000 CpG sites measured with the Illumina HumanMethylation450 microarray, 17% were heritable (p < 0.05), with a mean heritability of 0.22. Heritable CpG sites were enriched in intergenic regions, CpG shore, and regulatory regions in prefrontal cortex. Our MWAS approach identified known and potentially novel risk genes harboring CpG sites of methylation-trait associations for schizophrenia or bipolar disorder, which were not detectable using three alternative strategies (blood-based methylome reference, transcriptome-wide association study, and two gene-based association tests). Gene set enrichment analysis for genes with methylation-trait association evidence revealed pathways clearly related to neuronal functions, but also highlighted additional biological mechanisms that may underlie psychiatric disorders, such as microRNA-related regulation. In conclusion, our results showed the power of integrating brain methylation data with GWAS for psychiatric risk gene discovery, with potential applications in brain-related disorders or traits. peripheral tissue (blood), which may not correlate with methylation signals in the brain (18, 19).Additionally, due to the challenges of accessing brain tissues, studies that examined brain samples were often limited by small sample size. Finally, it is hard to establish a causal role between DNAm change and disease as it is unclear whether aberrant DNAm causes disease or vice versa.Genome-wide association studies (GWAS) indicate that most common genetic risk variants underlying complex diseases are noncoding and enriched in regulatory genomic regions in cells or tissues related to disease (20), suggesting that risk variants may act through regulation of cell/tissue-specific molecular mechanisms, such as methylation or gene expression. For example, SCZ risk variants from GWAS were enriched at enhancers active in brain, but not in tissues unlikely to be relevant to SCZ (21). Furthermore, statistical genetic approaches like linkage disequilibrium (LD) score regression have shown enrichment of trait heritability in regions with functional annotations that are trait-related and cell-type-specific, including enrichment of heritability for SCZ and BP in functional regions specific to th...

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Genetic estimators of DNA methylation provide insights into the molecular basis of polygenic traits

Cited by 12 publications

References 50 publications

New insights into the genetic etiology of Alzheimer’s disease and related dementias

New insights into the genetic etiology of Alzheimer’s disease and related dementias

Genetic regulation of methylation in human endometrium and blood and gene targets for reproductive diseases

Integrating brain methylome with GWAS for psychiatric risk gene discovery

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