Faculty Opinions recommendation of Common genetic variants account for differences in gene expression among ethnic groups.

Understanding the mechanisms that underlie genetic regulation of gene expression is crucial to explaining the diversity that governs complex traits. Large scale expression quantitative trait locus (eQTL) studies have been instrumental in identifying genetic variants that influence the expression of target genes. However, a large fraction of disease-associated genetic variants have not been clearly explained by current eQTL data, frustrating attempts to use these data to comprehensively characterize disease loci. One notable observation from recent studies is that cis-eQTL effects are often shared across different cell types and tissues. This would suggest that common genetic variants impacting steady-state, adult gene expression are largely tolerated, shared across tissues, and less relevant to disease. However, allelic heterogeneity and complex patterns of linkage disequilibrium (LD) within each locus may skew the quantification of sharing of genetic effects between tissues, impede our ability to identify causal variants, and hinder the identification of regulatory effects for disease-associated genetic variants. Indeed, recent research suggests that multiple causal variants are often present in many eQTL and complex trait associated loci. Here, we re-analyze tissue-specificity of genetic effects in the presence of LD and allelic heterogeneity, proposing a novel method, CAFEH, that improves the identification of causal regulatory variants across tissues and their relationship to disease loci.

Download Full-text

OR09-04 Common Genetic Variants Associated with SERPINA6 Expression in Liver Influence Cortisol-Responsive Transcriptional Networks in Human Adipose Tissue

Journal of the Endocrine Society ◽

10.1210/jendso/bvaa046.317 ◽

2020 ◽

Vol 4 (Supplement_1) ◽

Author(s):

Sean A Bankier ◽

Andrew A Crawford ◽

Lingfei Wang ◽

Katyayani Sukhavasi ◽

Raili Ermel ◽

...

Keyword(s):

Gene Expression ◽

Adipose Tissue ◽

Coronary Artery ◽

Genetic Variants ◽

Plasma Cortisol ◽

Transcriptional Networks ◽

Genome Wide ◽

Common Genetic Variants ◽

Regulated Gene Expression ◽

Genome Wide Significance

Abstract A genome wide meta-analysis by the CORtisol NETwork (CORNET) consortium(1) has identified genetic variants spanning the SERPINA6/SERPINA1 locus on chromosome 14, associated with morning plasma cortisol and predictive of cardiovascular disease (Crawford et al, Unpublished). SERPINA6 encodes Corticosteroid Binding Globulin (CBG), responsible for binding most cortisol in blood and putatively mediating delivery of cortisol to target tissues. We hypothesised that genetic variants in SERPINA6 influence CBG expression in liver and cortisol delivery to extra-hepatic tissues, influencing cortisol-regulated gene expression. The Stockholm Tartu Atherosclerosis Reverse Networks Engineering Task study (STARNET)(2) provides RNA sequencing data in 9 vascular and metabolic tissues from 600 genotyped individuals (mean age 65.8, 70.3% male) undergoing coronary artery bypass grafting. We used STARNET to identify SNPs associated with plasma cortisol at genome wide significance in CORNET as cis-eQTLs for SERPINA6 in liver and as trans-eQTLs for the expression of genes across STARNET tissues. Causal inference methodologies(3) were then employed for the network reconstruction of these trans-genes and their downstream targets. We identified 21 SNPs that both were associated with cortisol at genome wide significance in CORNET (p ≤ 5x10-8) and were cis-eQTLs for SERPINA6 expression in liver (q ≤ 0.05). Moreover, these SNPs were trans-eQTLs for sets of genes in liver, subcutaneous and visceral abdominal adipose tissue, with over-representation of known glucocorticoid-regulated genes in adipose. The highest confidence gene network identified was specific to subcutaneous adipose, with the interferon regulatory trans-gene, IRF2, controlling a putative glucocorticoid-regulated network. Targets in this network include LDB2 and LIPA, both associated with coronary artery disease. We conclude that variants in the SERPINA6/SERPINA1 locus mediate their effect on plasma cortisol through variation in SERPINA6 expression in liver, and in turn affect gene expression in extra-hepatic tissues through modulating cortisol delivery. This supports a dynamic role for CBG in modulating cortisol delivery to tissues. The cortisol-responsive gene networks identified here represent candidate pathways to mediate cardiovascular risk attributable to elevated cortisol. (1) Bolton, et al. (2014) PLOS Genet. 10:e1004474., (2) Franzén et al. (2016). Science 353:827., (3) Wang and Michoel. (2017). PLOS Comput. Biol. 13:e1005703.

Download Full-text

Core gene identification using gene expression

10.33612/diss.145227875 ◽

2020 ◽

Author(s):

◽

Annique Claringbould

Keyword(s):

Gene Expression ◽

Genetic Variation ◽

Genetic Code ◽

Genetic Variants ◽

Complex Traits ◽

Drug Targets ◽

Molecular Mechanisms ◽

Expression Patterns ◽

Altered Level ◽

Common Genetic Variants

While humans share most of their genetic code with one another, small differences in the DNA can have an impact on an individual’s risk of disease. Common genetic variants exert individually small effects on the development of a disease, but their combined impact is substantial. Although recent research has identified thousands of variants that are associated to complex traits, our understanding of the molecular mechanisms that eventually lead to disease is limited. One way to dive into the molecular changes that result from genetic variation, is to look at changes in gene activity (‘gene expression’). Each cell contains the same genetic code, but genes are only expressed when and where they are required. Research has shown that many disease-associated genetic variants also affect gene expression. Such a change in the expression of a gene can lead to an altered level of the protein it encodes, which in turn can be the start of a dysregulation in the system that can eventually develop into a disease. This thesis describes how gene expression patterns can be used to prioritise and describe the function of trait-relevant genes. The first chapters evaluate methodological considerations for doing gene expression research. Another study covers the systematic linking of genetic variation to gene expression in blood and the last research chapter describes a method for gene prioritisation that leverages the idea that multiple genetic variants converge onto disease-causing genes. These insights can be used to better understand disease and to identify potential drug targets.

Download Full-text

Common genetic variants in the PSCA gene influence gene expression and bladder cancer risk

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1202189109 ◽

2012 ◽

Vol 109 (13) ◽

pp. 4974-4979 ◽

Cited By ~ 50

Author(s):

Y.-P. Fu ◽

I. Kohaar ◽

N. Rothman ◽

J. Earl ◽

J. D. Figueroa ◽

...

Keyword(s):

Gene Expression ◽

Bladder Cancer ◽

Cancer Risk ◽

Genetic Variants ◽

Bladder Cancer Risk ◽

Common Genetic Variants ◽

Influence Gene Expression

Download Full-text

Common genetic variants regulating ADD3 gene expression alter biliary atresia risk

Journal of Hepatology ◽

10.1016/j.jhep.2013.07.021 ◽

2013 ◽

Vol 59 (6) ◽

pp. 1285-1291 ◽

Cited By ~ 41

Author(s):

Guo Cheng ◽

Clara Sze-Man Tang ◽

Emily Hoi-Man Wong ◽

William Wai-Chun Cheng ◽

Man-Ting So ◽

...

Keyword(s):

Gene Expression ◽

Biliary Atresia ◽

Genetic Variants ◽

Common Genetic Variants

Download Full-text

377 Multiple Common Genetic Variants for Celiac Disease Influencing Immune Gene Expression

Gastroenterology ◽

10.1016/s0016-5085(10)60245-4 ◽

2010 ◽

Vol 138 (5) ◽

pp. S-54 ◽

Cited By ~ 2

Author(s):

Patrick C. Dubois

Keyword(s):

Gene Expression ◽

Celiac Disease ◽

Genetic Variants ◽

Immune Gene ◽

Immune Gene Expression ◽

Common Genetic Variants

Download Full-text

Mendelian pathway analysis of laboratory traits reveals distinct roles for ciliary subcompartments in common disease pathogenesis

10.1101/2020.08.31.275685 ◽

2020 ◽

Author(s):

Theodore George Drivas ◽

Anastasia Lucas ◽

Xinyuan Zhang ◽

Marylyn DeRiggi Ritchie

Keyword(s):

Gene Expression ◽

Rare Disease ◽

Genetic Variants ◽

Association Studies ◽

European Ancestry ◽

Specific Gene ◽

Common Disease ◽

Mendelian Disease ◽

Disease Pathogenesis ◽

Common Genetic Variants

SummaryRare monogenic disorders of the primary cilium, termed ciliopathies, are characterized by extreme presentations of otherwise-common diseases, such as diabetes, hepatic fibrosis, and kidney failure. However, despite a revolution in our understanding of the cilium’s role in rare disease pathogenesis, the organelle’s contribution to common disease remains largely unknown. We hypothesized that common genetic variants affecting Mendelian ciliopathy genes might also contribute to common complex diseases pathogenesis more generally. To address this question, we performed association studies of 16,875 common genetic variants across 122 well-characterized ciliary genes with 12 quantitative laboratory traits characteristic of ciliopathy syndromes in 378,213 European-ancestry individuals in the UK BioBank. We incorporated tissue-specific gene expression analysis, expression quantitative trait loci (eQTL) and Mendelian disease information into our analysis, and replicated findings in meta-analysis to increase our confidence in observed associations between ciliary genes and human phenotypes. 73 statistically-significant gene-trait associations were identified across 34 of the 122 ciliary genes that we examined (including 8 novel, replicating associations). With few exceptions, these ciliary genes were found to be widely expressed in human tissues relevant to the phenotypes being studied, and our eQTL analysis revealed strong evidence for correlation between ciliary gene expression levels and patient phenotypes. Perhaps most interestingly our analysis identified different ciliary subcompartments as being specifically associated with distinct sets of patient phenotypes, offering a number of testable hypotheses regarding the cilium’s role in common complex disease. Taken together, our data demonstrate the utility of a Mendelian pathway-based approach to genomic association studies, and challenge the widely-held belief that the cilium is an organelle important mainly in development and in rare syndromic disease pathogenesis. The continued application of techniques similar to those described here to other phenotypes/Mendelian diseases is likely to yield many additional fascinating associations that will begin to integrate the fields of common and rare disease genetics, and provide insight into the pathophysiology of human diseases of immense public health [email protected]

Download Full-text

The impact of rare variation on gene expression across tissues

Nature ◽

10.1038/nature24267 ◽

2017 ◽

Vol 550 (7675) ◽

pp. 239-243 ◽

Cited By ~ 112

Author(s):

Xin Li ◽

◽

Yungil Kim ◽

Emily K. Tsang ◽

Joe R. Davis ◽

...

Keyword(s):

Gene Expression ◽

Genetic Variants ◽

Rare Variants ◽

Disease Risk ◽

Association Studies ◽

Genetic Association Studies ◽

Sequencing Data ◽

Common Genetic Variants ◽

Coding Variants ◽

The Impact

Abstract Rare genetic variants are abundant in humans and are expected to contribute to individual disease risk1,2,3,4. While genetic association studies have successfully identified common genetic variants associated with susceptibility, these studies are not practical for identifying rare variants1,5. Efforts to distinguish pathogenic variants from benign rare variants have leveraged the genetic code to identify deleterious protein-coding alleles1,6,7, but no analogous code exists for non-coding variants. Therefore, ascertaining which rare variants have phenotypic effects remains a major challenge. Rare non-coding variants have been associated with extreme gene expression in studies using single tissues8,9,10,11, but their effects across tissues are unknown. Here we identify gene expression outliers, or individuals showing extreme expression levels for a particular gene, across 44 human tissues by using combined analyses of whole genomes and multi-tissue RNA-sequencing data from the Genotype-Tissue Expression (GTEx) project v6p release12. We find that 58% of underexpression and 28% of overexpression outliers have nearby conserved rare variants compared to 8% of non-outliers. Additionally, we developed RIVER (RNA-informed variant effect on regulation), a Bayesian statistical model that incorporates expression data to predict a regulatory effect for rare variants with higher accuracy than models using genomic annotations alone. Overall, we demonstrate that rare variants contribute to large gene expression changes across tissues and provide an integrative method for interpretation of rare variants in individual genomes.

Download Full-text