scholarly journals A transcriptome-wide Mendelian randomization study to uncover tissue-dependent regulatory mechanisms across the human phenome

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Tom G. Richardson ◽  
Gibran Hemani ◽  
Tom R. Gaunt ◽  
Caroline L. Relton ◽  
George Davey Smith
Keyword(s):  
Gene Expression ◽  
Complex Traits ◽  
Disease Susceptibility ◽  
Mendelian Randomization ◽  
Regulatory Mechanisms ◽  
Tissue Specific ◽  
Causal Pathways ◽  
Influence Gene Expression ◽  
Insight Into ◽  
Gene Expression Levels

AbstractDeveloping insight into tissue-specific transcriptional mechanisms can help improve our understanding of how genetic variants exert their effects on complex traits and disease. In this study, we apply the principles of Mendelian randomization to systematically evaluate transcriptome-wide associations between gene expression (across 48 different tissue types) and 395 complex traits. Our findings indicate that variants which influence gene expression levels in multiple tissues are more likely to influence multiple complex traits. Moreover, detailed investigations of our results highlight tissue-specific associations, drug validation opportunities, insight into the likely causal pathways for trait-associated variants and also implicate putative associations at loci yet to be implicated in disease susceptibility. Similar evaluations can be conducted at http://mrcieu.mrsoftware.org/Tissue_MR_atlas/.

scholarly journals Prioritizing putative influential genes in early life cardiovascular disease susceptibility by applying tissue-specific Mendelian randomization

2018 ◽  
Author(s):  
Kurt Taylor ◽  
George Davey Smith ◽  
Caroline L Relton ◽  
Tom R Gaunt ◽  
Tom G Richardson
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Disease Susceptibility ◽  
Mendelian Randomization ◽  
Analytical Framework ◽  
Specific Gene ◽  
Multiple Trait ◽  
Trait Variation ◽  
Tissue Specific ◽  
Insight Into

AbstractBackgroundThe extent to which changes in gene expression can influence cardiovascular disease risk across different tissue types has not yet been systematically explored. We have developed an analytical framework that integrates tissue-specific gene expression, Mendelian randomization and multiple-trait colocalization to develop functional mechanistic insight into the causal pathway from genetic variant to complex trait.MethodsWe undertook a transcriptome-wide association study in a population of young individuals to uncover genetic variants associated with both nearby gene expression and cardiovascular traits. Two-sample Mendelian randomization was then applied using large-scale datasets to investigate whether changes in gene expression within certain tissue types may influence cardiovascular trait variation. We subsequently performed Bayesian multiple-trait colocalization to further interrogate findings and also gain insight into whether DNA methylation, as well as gene expression, may play a role in disease susceptibility.ResultsEight genetic loci were associated with changes in gene expression and early life measures of cardiovascular function. Our Mendelian randomization analysis provided evidence of tissue-specific effects at multiple loci, of which the effects at theADCY3andFADS1loci for body mass index and cholesterol respectively were particularly insightful. Multiple trait colocalization uncovered evidence which suggested that changes in DNA methylation at the promoter region upstream ofFADS1/TMEM258may also play a role in cardiovascular trait variation along with gene expression. Furthermore, colocalization analyses were able to uncover evidence of tissue-specificity, most prominantly betweenSORT1expression in liver tissue and cholesterol levels.ConclusionsDisease susceptibility can be influenced by differential changes in tissue-specific gene expression and DNA methylation. Our analytical framework should prove valuable in elucidating mechanisms in disease, as well as helping prioritize putative causal genes at associated loci where multiple nearby genes may be co-regulated. Future studies which continue to uncover quantitative trait loci for molecular traits across various tissue and cell typse will further improve our capability to understand and prevent disease.

scholarly journals A transcriptome-wide Mendelian randomization study to uncover tissue-dependent regulatory mechanisms across the human phenome

2019 ◽  
Author(s):  
Tom G Richardson ◽  
Gibran Hemani ◽  
Tom R Gaunt ◽  
Caroline L Relton ◽  
George Davey Smith
Keyword(s):  
Gene Expression ◽  
Genetic Variants ◽  
Complex Traits ◽  
Mendelian Randomization ◽  
Drug Repositioning ◽  
Association Studies ◽  
Thyroid Tissue ◽  
Genome Wide Association Studies ◽  
Tissue Specific ◽  
Genome Wide

AbstractBackgroundDeveloping insight into tissue-specific transcriptional mechanisms can help improve our understanding of how genetic variants exert their effects on complex traits and disease. By applying the principles of Mendelian randomization, we have undertaken a systematic analysis to evaluate transcriptome-wide associations between gene expression across 48 different tissue types and 395 complex traits.ResultsOverall, we identified 100,025 gene-trait associations based on conventional genome-wide corrections (P < 5 × 10−08) that also provided evidence of genetic colocalization. These results indicated that genetic variants which influence gene expression levels in multiple tissues are more likely to influence multiple complex traits. We identified many examples of tissue-specific effects, such as genetically-predicted TPO, NR3C2 and SPATA13 expression only associating with thyroid disease in thyroid tissue. Additionally, FBN2 expression was associated with both cardiovascular and lung function traits, but only when analysed in heart and lung tissue respectively.We also demonstrate that conducting phenome-wide evaluations of our results can help flag adverse on-target side effects for therapeutic intervention, as well as propose drug repositioning opportunities. Moreover, we find that exploring the tissue-dependency of associations identified by genome-wide association studies (GWAS) can help elucidate the causal genes and tissues responsible for effects, as well as uncover putative novel associations.ConclusionsThe atlas of tissue-dependent associations we have constructed should prove extremely valuable to future studies investigating the genetic determinants of complex disease. The follow-up analyses we have performed in this study are merely a guide for future research. Conducting similar evaluations can be undertaken systematically at http://mrcieu.mrsoftware.org/Tissue_MR_atlas/.

scholarly journals Hard wiring of normal tissue-specific chromosome-wide gene expression levels is an additional factor driving cancer type-specific aneuploidies

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Sushant Patkar ◽  
Kerstin Heselmeyer-Haddad ◽  
Noam Auslander ◽  
Daniela Hirsch ◽  
Jordi Camps ◽  
...  
Keyword(s):  
Gene Expression ◽  
Normal Tissue ◽  
Cancer Type ◽  
Tissue Specific ◽  
Expression Levels ◽  
Specific Distribution ◽  
Tumor Origin ◽  
Chromosome Arm ◽  
Gains And Losses ◽  
Gene Expression Levels

Abstract Background Many carcinomas have recurrent chromosomal aneuploidies specific to the tissue of tumor origin. The reason for this specificity is not completely understood. Methods In this study, we looked at the frequency of chromosomal arm gains and losses in different cancer types from the The Cancer Genome Atlas (TCGA) and compared them to the mean gene expression of each chromosome arm in corresponding normal tissues of origin from the Genotype-Tissue Expression (GTEx) database, in addition to the distribution of tissue-specific oncogenes and tumor suppressors on different chromosome arms. Results This analysis revealed a complex picture of factors driving tumor karyotype evolution in which some recurrent chromosomal copy number reflect the chromosome arm-wide gene expression levels of the their normal tissue of tumor origin. Conclusions We conclude that the cancer type-specific distribution of chromosomal arm gains and losses is potentially “hardwiring” gene expression levels characteristic of the normal tissue of tumor origin, in addition to broadly modulating the expression of tissue-specific tumor driver genes.

scholarly journals Tissue-specific sex differences in human gene expression

2019 ◽  
Vol 28 (17) ◽  
pp. 2976-2986 ◽  
Author(s):  
Irfahan Kassam ◽  
Yang Wu ◽  
Jian Yang ◽  
Peter M Visscher ◽  
Allan F McRae
Keyword(s):  
Gene Expression ◽  
Sex Differences ◽  
Complex Traits ◽  
Tissue Expression ◽  
Regulatory Elements ◽  
Tissue Specific ◽  
Significance Threshold ◽  
Expression Of Genes ◽  
Causal Variants ◽  
Similar Distance

Abstract Despite extensive sex differences in human complex traits and disease, the male and female genomes differ only in the sex chromosomes. This implies that most sex-differentiated traits are the result of differences in the expression of genes that are common to both sexes. While sex differences in gene expression have been observed in a range of different tissues, the biological mechanisms for tissue-specific sex differences (TSSDs) in gene expression are not well understood. A total of 30 640 autosomal and 1021 X-linked transcripts were tested for heterogeneity in sex difference effect sizes in n = 617 individuals across 40 tissue types in Genotype–Tissue Expression (GTEx). This identified 65 autosomal and 66 X-linked TSSD transcripts (corresponding to unique genes) at a stringent significance threshold. Results for X-linked TSSD transcripts showed mainly concordant direction of sex differences across tissues and replicate previous findings. Autosomal TSSD transcripts had mainly discordant direction of sex differences across tissues. The top cis-expression quantitative trait loci (eQTLs) across tissues for autosomal TSSD transcripts are located a similar distance away from the nearest androgen and estrogen binding motifs and the nearest enhancer, as compared to cis-eQTLs for transcripts with stable sex differences in gene expression across tissue types. Enhancer regions that overlap top cis-eQTLs for TSSD transcripts, however, were found to be more dispersed across tissues. These observations suggest that androgen and estrogen regulatory elements in a cis region may play a common role in sex differences in gene expression, but TSSD in gene expression may additionally be due to causal variants located in tissue-specific enhancer regions.

Whole genome expression as a quantitative trait

2009 ◽  
Vol 37 (6) ◽  
pp. 1276-1277 ◽  
Author(s):  
John Hardy ◽  
Danyah Trabzuni ◽  
Mina Ryten
Keyword(s):  
Gene Expression ◽  
Genetic Variability ◽  
Disease Risk ◽  
Neurological Diseases ◽  
Whole Genome ◽  
Genome Expression ◽  
Genome Analyses ◽  
Whole Genome Expression ◽  
Influence Gene Expression ◽  
Gene Expression Levels

Surprisingly, whole genome analyses of complex human neurological and psychiatric disorders have revealed that many genetic risk factors are likely to influence gene expression rather than alter protein sequences. Previous analyses of neurological diseases have shown that genetic variability in gene expression levels of deposited proteins influence disease risk. With this background, we have embarked on a comprehensive project to determine the effects of common genetic variability on whole genome gene expression.

scholarly journals Imprinted gene expression at the Dlk1-Dio3 cluster is controlled by both maternal and paternal IG-DMRs in a tissue-specific fashion

2019 ◽  
Author(s):  
Katherine A. Alexander ◽  
María J. García-García
Keyword(s):  
Gene Expression ◽  
Regulatory Elements ◽  
Enhancer Activity ◽  
Enhancer Element ◽  
Tissue Specific ◽  
Imprinted Gene ◽  
Imprinting Control Region ◽  
Regulatory Landscape ◽  
Insight Into ◽  
Different Tissues

ABSTRACTImprinting at the Dlk1-Dio3 cluster is controlled by the IG-DMR, an imprinting control region differentially methylated between maternal and paternal chromosomes. The maternal IG-DMR is essential for imprinting control, functioning as a cis enhancer element. Meanwhile, DNA methylation at the paternal IG-DMR is thought to prevent enhancer activity. To explore whether suppression of enhancer activity at the methylated IG-DMR requires the transcriptional repressor TRIM28, we analyzed Trim28chatwo embryos and performed epistatic experiments with IG-DMR deletion mutants. We found that while TRIM28 regulates the enhancer properties of the paternal IG-DMR, it also controls imprinting through other mechanisms. Additionally, we found that the paternal IG-DMR, previously deemed dispensable for imprinting, is required in certain tissues, demonstrating that imprinting is regulated in a tissue-specific manner. Using PRO-seq to analyze nascent transcription, we identified 30 novel transcribed regulatory elements, including 23 that are tissue-specific. These results demonstrate that different tissues have a distinctive regulatory landscape at the Dlk1-Dio3 cluster and provide insight into potential mechanisms of tissue-specific imprinting control. Together, our findings challenge the premise that Dlk1-Dio3 imprinting is regulated through a single mechanism and demonstrate that different tissues use distinct strategies to accomplish imprinted gene expression.

scholarly journals A novel Mendelian randomization method identifies causal relationships between gene expression and low-density lipoprotein cholesterol levels

2019 ◽  
Author(s):  
Adriaan van der Graaf ◽  
Annique Claringbould ◽  
Antoine Rimbert ◽  
Harm-Jan Westra ◽  
Yang Li ◽  
...  
Keyword(s):  
Gene Expression ◽  
Complex Traits ◽  
Mendelian Randomization ◽  
Low Density Lipoprotein ◽  
Density Lipoprotein ◽  
Lipoprotein Cholesterol ◽  
Low Density ◽  
Causal Relationships ◽  
Low Density Lipoprotein Cholesterol ◽  
Individual Level

AbstractRobust inference of causal relationships between gene expression and complex traits using Mendelian Randomization (MR) approaches is confounded by pleiotropy and linkage disequilibrium (LD) between gene expression quantitative loci (eQTLs). Here we propose a new MR method, MR-link, that accounts for unobserved pleiotropy and LD by leveraging information from individual-level data. In simulations, MR-link shows false positive rates close to expectation (median 0.05) and high power (up to 0.89), outperforming all other MR methods we tested, even when only one eQTL variant is present. Application of MR-link to low-density lipoprotein cholesterol (LDL-C) measurements in 12,449 individuals and eQTLs summary statistics from whole blood and liver identified 19 genes causally linked to LDL-C. These include the previously functionally validatedSORT1gene, and thePVRL2gene, located in theAPOElocus, for which a causal role in liver was yet unknown. Our results showcase the strength of MR-link for transcriptome-wide causal inferences.

scholarly journals Integrative transcriptome imputation reveals tissue-specific and shared biological mechanisms mediating susceptibility to complex traits

2019 ◽  
Author(s):  
Wen Zhang ◽  
Georgios Voloudakis ◽  
Veera M. Rajagopal ◽  
Ben Reahead ◽  
Joel T. Dudley ◽  
...  
Keyword(s):  
Gene Expression ◽  
Complex Traits ◽  
Large Scale ◽  
Association Studies ◽  
Drug Repurposing ◽  
Joint Analysis ◽  
Expression Trait ◽  
Significant Expression ◽  
Insight Into ◽  
Trait Associations

AbstractTranscriptome-wide association studies integrate gene expression data with common risk variation to identify gene-trait associations. By incorporating epigenome data to estimate the functional importance of genetic variation on gene expression, we improve the accuracy of transcriptome prediction and the power to detect significant expression-trait associations. Joint analysis of 14 large-scale transcriptome datasets and 58 traits identify 13,724 significant expression-trait associations that converge to biological processes and relevant phenotypes in human and mouse phenotype databases. We perform drug repurposing analysis and identify known and novel compounds that mimic or reverse trait-specific changes. We identify genes that exhibit agonistic pleiotropy for genetically correlated traits that converge on shared biological pathways and elucidate distinct processes in disease etiopathogenesis. Overall, this comprehensive analysis provides insight into the specificity and convergence of gene expression on susceptibility to complex traits.

scholarly journals Estimating the proportion of disease heritability mediated by gene expression levels

2017 ◽  
Author(s):  
Luke J. O’Connor ◽  
Alexander Gusev ◽  
Xuanyao Liu ◽  
Po-Ru Loh ◽  
Hilary K. Finucane ◽  
...  
Keyword(s):  
Gene Expression ◽  
Complex Traits ◽  
Disease Risk ◽  
Genetic Component ◽  
Effect Sizes ◽  
Expression Levels ◽  
Risk Variants ◽  
Regulatory Effects ◽  
Disease Effect ◽  
Gene Expression Levels

AbstractDisease risk variants identified by GWAS are predominantly noncoding, suggesting that gene regulation plays an important role. eQTL studies in unaffected individuals are often used to link disease-associated variants with the genes they regulate, relying on the hypothesis that noncoding regulatory effects are mediated by steady-state expression levels. To test this hypothesis, we developed a method to estimate the proportion of disease heritability mediated by the cis-genetic component of assayed gene expression levels. The method, gene expression co-score regression (GECS regression), relies on the idea that, for a gene whose expression level affects a phenotype, SNPs with similar effects on the expression of that gene will have similar phenotypic effects. In order to distinguish directional effects mediated by gene expression from non-directional pleiotropic or tagging effects, GECS regression operates on pairs of cis SNPs in linkage equilibrium, regressing pairwise products of disease effect sizes on products of cis-eQTL effect sizes. We verified that GECS regression produces robust estimates of mediated effects in simulations. We applied the method to eQTL data in 44 tissues from the GTEx consortium (average NeQTL = 158 samples) in conjunction with GWAS summary statistics for 30 diseases and complex traits (average NGWAS = 88K) with low pairwise genetic correlation, estimating the proportion of SNP-heritability mediated by the cis-genetic component of assayed gene expression in the union of the 44 tissues. The mean estimate was 0.21 (s.e. = 0.01) across 30 traits, with a significantly positive estimate (p < 0.001) for every trait. Thus, assayed gene expression in bulk tissues mediates a statistically significant but modest proportion of disease heritability, motivating the development of additional assays to capture regulatory effects and the use of our method to estimate how much disease heritability they mediate.

Sign in / Sign up

Export Citation Format

Share Document