scholarly journals Identification of atrial fibrillation associated genes and functional non-coding variants

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Antoinette F. van Ouwerkerk ◽  
Fernanda M. Bosada ◽  
Karel van Duijvenboden ◽  
Matthew C. Hill ◽  
Lindsey E. Montefiori ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Genetic Variants ◽  
Target Gene ◽  
Target Genes ◽  
Association Studies ◽  
Regulatory Region ◽  
Regulatory Elements ◽  
Genome Wide Association Studies ◽  
Cx43 Expression

Abstract Disease-associated genetic variants that lie in non-coding regions found by genome-wide association studies are thought to alter the functionality of transcription regulatory elements and target gene expression. To uncover causal genetic variants, variant regulatory elements and their target genes, here we cross-reference human transcriptomic, epigenomic and chromatin conformation datasets. Of 104 genetic variant regions associated with atrial fibrillation candidate target genes are prioritized. We optimize EMERGE enhancer prediction and use accessible chromatin profiles of human atrial cardiomyocytes to more accurately predict cardiac regulatory elements and identify hundreds of sub-threshold variants that co-localize with regulatory elements. Removal of mouse homologues of atrial fibrillation-associated regions in vivo uncovers a distal regulatory region involved in Gja1 (Cx43) expression. Our analyses provide a shortlist of genes likely affected by atrial fibrillation-associated variants and provide variant regulatory elements in each region that link genetic variation and target gene regulation, helping to focus future investigations.

scholarly journals Chromatin Conformation Links Distal Target Genes to CKD Loci

2017 ◽  
Vol 29 (2) ◽  
pp. 462-476 ◽  
Author(s):  
Maarten M. Brandt ◽  
Claartje A. Meddens ◽  
Laura Louzao-Martinez ◽  
Noortje A.M. van den Dungen ◽  
Nico R. Lansu ◽  
...  
Keyword(s):  
Target Genes ◽  
Association Studies ◽  
Regulatory Region ◽  
Regulatory Elements ◽  
Genome Wide Association Studies ◽  
Mrna Levels ◽  
Nucleotide Polymorphisms ◽  
Common Variants ◽  
Circular Chromosome ◽  
Single Nucleotide

Genome-wide association studies (GWASs) have identified many genetic risk factors for CKD. However, linking common variants to genes that are causal for CKD etiology remains challenging. By adapting self-transcribing active regulatory region sequencing, we evaluated the effect of genetic variation on DNA regulatory elements (DREs). Variants in linkage with the CKD-associated single-nucleotide polymorphism rs11959928 were shown to affect DRE function, illustrating that genes regulated by DREs colocalizing with CKD-associated variation can be dysregulated and therefore, considered as CKD candidate genes. To identify target genes of these DREs, we used circular chromosome conformation capture (4C) sequencing on glomerular endothelial cells and renal tubular epithelial cells. Our 4C analyses revealed interactions of CKD-associated susceptibility regions with the transcriptional start sites of 304 target genes. Overlap with multiple databases confirmed that many of these target genes are involved in kidney homeostasis. Expression quantitative trait loci analysis revealed that mRNA levels of many target genes are genotype dependent. Pathway analyses showed that target genes were enriched in processes crucial for renal function, identifying dysregulated geranylgeranyl diphosphate biosynthesis as a potential disease mechanism. Overall, our data annotated multiple genes to previously reported CKD-associated single-nucleotide polymorphisms and provided evidence for interaction between these loci and target genes. This pipeline provides a novel technique for hypothesis generation and complements classic GWAS interpretation. Future studies are required to specify the implications of our dataset and further reveal the complex roles that common variants have in complex diseases, such as CKD.

scholarly journals Human genetic variants associated with COVID-19 severity are enriched in immune and epithelium regulatory networks

2021 ◽  
Author(s):  
Zhanying Feng ◽  
Xianwen Ren ◽  
Zhana Duren ◽  
Yong Wang
Keyword(s):  
Immune Cells ◽  
Genetic Variants ◽  
Chemokine Receptors ◽  
Regulatory Networks ◽  
Target Genes ◽  
Association Studies ◽  
Regulatory Elements ◽  
Genome Wide Association Studies ◽  
Context Specific ◽  
Epithelium Cells

Human genetic variants can influence the severity of infection with SARS-COV-2. Several genome-wide association studies (GWAS) have been conducted to identify human risk loci that may be involved with COVID-19 severity. However, candidate genes were investigated in the genomic proximity of each locus without considering their functional cellular contexts. Here, we compiled regulatory networks of 77 human contexts to interpret these risk loci by revealing their relevant contexts and associated transcript factors (TF), regulatory elements (REs), and target genes (TGs). 21 human contexts were identified to be associated with COVID-19 severity and grouped into two categories: immune cells and epithelium cells. We further investigated the risk loci in regulatory network of immune cells, epithelium cells and their crosstalk. Two genomic clusters, chemokine receptors cluster and OAS cluster showed the strongest association with COVID-19 severity in the context specific regulatory networks.

scholarly journals INFERNO - INFERring the molecular mechanisms of NOncoding genetic variants

2017 ◽  
Author(s):  
Alexandre Amlie-Wolf ◽  
Mitchell Tang ◽  
Elisabeth E. Mlynarski ◽  
Pavel P. Kuksa ◽  
Otto Valladares ◽  
...  
Keyword(s):  
Genetic Variants ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Association Studies ◽  
Regulatory Elements ◽  
Genome Wide Association Studies ◽  
Cellular Processes ◽  
Genome Wide ◽  
Causal Variants ◽  
Novel Method

AbstractThe majority of variants identified by genome-wide association studies (GWAS) reside in the noncoding genome, where they affect regulatory elements including transcriptional enhancers. We propose INFERNO (INFERring the molecular mechanisms of NOncoding genetic variants), a novel method which integrates hundreds of diverse functional genomics data sources with GWAS summary statistics to identify putatively causal noncoding variants underlying association signals. INFERNO comprehensively infers the relevant tissue contexts, target genes, and downstream biological processes affected by causal variants. We apply INFERNO to schizophrenia GWAS data, recapitulating known schizophrenia-associated genes including CACNA1C and discovering novel signals related to transmembrane cellular processes.

scholarly journals Post-GWAS era in genetics of schizophrenia

2019 ◽  
pp. 6-7
Author(s):  
V. E. Golimbet ◽  
A. K. Golov ◽  
N. V. Kondratyev
Keyword(s):  
Genetic Variants ◽  
Target Genes ◽  
Disease Risk ◽  
Association Studies ◽  
Regulatory Elements ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Biological Mechanisms ◽  
Master Regulators ◽  
Genome Wide

Genome-wide association studies (GWASs) discovered multiple genetic variants associated with schizophrenia. Te next step (post-GWAS analysis) is aimed at identifying the causal genetic variants and biological mechanisms underlying the associations with disease risk. Te following strategies are considered: the study of transcriptional regulation in neuronal human cells and the use of epigenomic information for searching for regulatory elements involved in the pathogenesis of schizophrenia. Te frst strategy includes identifcation of neuronal enhancers, mapping of potential target genes and functional confrmation of enhancer-promoter interactions. Te second approach is focused on the identifcation of transcriptional factors, which appear to be master regulators of expression.

scholarly journals Epigenetic and Transcriptional Networks Underlying Atrial Fibrillation

2020 ◽  
Vol 127 (1) ◽  
pp. 34-50 ◽  
Author(s):  
Antoinette F. van Ouwerkerk ◽  
Amelia W. Hall ◽  
Zachary A. Kadow ◽  
Sonja Lazarevic ◽  
Jasmeet S. Reyat ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Transcription Factors ◽  
Target Genes ◽  
Transcriptional Regulatory Network ◽  
Association Studies ◽  
Regulatory Elements ◽  
Genome Wide Association ◽  
Transcriptional Networks ◽  
Genome Wide Association Studies ◽  
Genome Wide

Genome-wide association studies have uncovered over a 100 genetic loci associated with atrial fibrillation (AF), the most common arrhythmia. Many of the top AF-associated loci harbor key cardiac transcription factors, including PITX2, TBX5, PRRX1, and ZFHX3. Moreover, the vast majority of the AF-associated variants lie within noncoding regions of the genome where causal variants affect gene expression by altering the activity of transcription factors and the epigenetic state of chromatin. In this review, we discuss a transcriptional regulatory network model for AF defined by effector genes in Genome-wide association studies loci. We describe the current state of the field regarding the identification and function of AF-relevant gene regulatory networks, including variant regulatory elements, dose-sensitive transcription factor functionality, target genes, and epigenetic states. We illustrate how altered transcriptional networks may impact cardiomyocyte function and ionic currents that impact AF risk. Last, we identify the need for improved tools to identify and functionally test transcriptional components to define the links between genetic variation, epigenetic gene regulation, and atrial function.

scholarly journals A comprehensive integrated post-GWAS analysis of Type 1 diabetes reveals enhancer-based immune dysregulation

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0257265
Author(s):  
Seung-Soo Kim ◽  
Adam D. Hudgins ◽  
Jiping Yang ◽  
Yizhou Zhu ◽  
Zhidong Tu ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Target Genes ◽  
Association Studies ◽  
Regulatory Elements ◽  
Immune Dysregulation ◽  
Specific Gene ◽  
Genome Wide Association Studies ◽  
Gwas Analysis ◽  
Regulatory Variants

Type 1 diabetes (T1D) is an organ-specific autoimmune disease, whereby immune cell-mediated killing leads to loss of the insulin-producing β cells in the pancreas. Genome-wide association studies (GWAS) have identified over 200 genetic variants associated with risk for T1D. The majority of the GWAS risk variants reside in the non-coding regions of the genome, suggesting that gene regulatory changes substantially contribute to T1D. However, identification of causal regulatory variants associated with T1D risk and their affected genes is challenging due to incomplete knowledge of non-coding regulatory elements and the cellular states and processes in which they function. Here, we performed a comprehensive integrated post-GWAS analysis of T1D to identify functional regulatory variants in enhancers and their cognate target genes. Starting with 1,817 candidate T1D SNPs defined from the GWAS catalog and LDlink databases, we conducted functional annotation analysis using genomic data from various public databases. These include 1) Roadmap Epigenomics, ENCODE, and RegulomeDB for epigenome data; 2) GTEx for tissue-specific gene expression and expression quantitative trait loci data; and 3) lncRNASNP2 for long non-coding RNA data. Our results indicated a prevalent enhancer-based immune dysregulation in T1D pathogenesis. We identified 26 high-probability causal enhancer SNPs associated with T1D, and 64 predicted target genes. The majority of the target genes play major roles in antigen presentation and immune response and are regulated through complex transcriptional regulatory circuits, including those in HLA (6p21) and non-HLA (16p11.2) loci. These candidate causal enhancer SNPs are supported by strong evidence and warrant functional follow-up studies.

scholarly journals Perspective of the GEMSTONE Consortium on Current and Future Approaches to Functional Validation for Skeletal Genetic Disease Using Cellular, Molecular and Animal-Modeling Techniques

2021 ◽  
Vol 12 ◽  
Author(s):  
Martina Rauner ◽  
Ines Foessl ◽  
Melissa M. Formosa ◽  
Erika Kague ◽  
Vid Prijatelj ◽  
...  
Keyword(s):  
Resource Sharing ◽  
Complex Traits ◽  
Cellular Localization ◽  
Target Genes ◽  
Mission Statement ◽  
Association Studies ◽  
Repetitive Sequences ◽  
Genome Wide Association Studies ◽  
Causal Genes

The availability of large human datasets for genome-wide association studies (GWAS) and the advancement of sequencing technologies have boosted the identification of genetic variants in complex and rare diseases in the skeletal field. Yet, interpreting results from human association studies remains a challenge. To bridge the gap between genetic association and causality, a systematic functional investigation is necessary. Multiple unknowns exist for putative causal genes, including cellular localization of the molecular function. Intermediate traits (“endophenotypes”), e.g. molecular quantitative trait loci (molQTLs), are needed to identify mechanisms of underlying associations. Furthermore, index variants often reside in non-coding regions of the genome, therefore challenging for interpretation. Knowledge of non-coding variance (e.g. ncRNAs), repetitive sequences, and regulatory interactions between enhancers and their target genes is central for understanding causal genes in skeletal conditions. Animal models with deep skeletal phenotyping and cell culture models have already facilitated fine mapping of some association signals, elucidated gene mechanisms, and revealed disease-relevant biology. However, to accelerate research towards bridging the current gap between association and causality in skeletal diseases, alternative in vivo platforms need to be used and developed in parallel with the current -omics and traditional in vivo resources. Therefore, we argue that as a field we need to establish resource-sharing standards to collectively address complex research questions. These standards will promote data integration from various -omics technologies and functional dissection of human complex traits. In this mission statement, we review the current available resources and as a group propose a consensus to facilitate resource sharing using existing and future resources. Such coordination efforts will maximize the acquisition of knowledge from different approaches and thus reduce redundancy and duplication of resources. These measures will help to understand the pathogenesis of osteoporosis and other skeletal diseases towards defining new and more efficient therapeutic targets.

scholarly journals Asthma-associated genetic variants induce IL33 differential expression through an enhancer-blocking regulatory region

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ivy Aneas ◽  
Donna C. Decker ◽  
Chanie L. Howard ◽  
Débora R. Sobreira ◽  
Noboru J. Sakabe ◽  
...  
Keyword(s):  
Association Studies ◽  
Regulatory Region ◽  
Airway Epithelial Cells ◽  
Genome Wide Association Studies ◽  
Airway Epithelial ◽  
Allele Specific ◽  
Enhancer Blocking ◽  
Underlying Mechanisms

AbstractGenome-wide association studies (GWAS) have implicated the IL33 locus in asthma, but the underlying mechanisms remain unclear. Here, we identify a 5 kb region within the GWAS-defined segment that acts as an enhancer-blocking element in vivo and in vitro. Chromatin conformation capture showed that this 5 kb region loops to the IL33 promoter, potentially regulating its expression. We show that the asthma-associated single nucleotide polymorphism (SNP) rs1888909, located within the 5 kb region, is associated with IL33 gene expression in human airway epithelial cells and IL-33 protein expression in human plasma, potentially through differential binding of OCT-1 (POU2F1) to the asthma-risk allele. Our data demonstrate that asthma-associated variants at the IL33 locus mediate allele-specific regulatory activity and IL33 expression, providing a mechanism through which a regulatory SNP contributes to genetic risk of asthma.

GWAS contribution to atrial fibrillation and atrial fibrillation-related stroke: pathophysiological implications

2019 ◽  
Vol 20 (10) ◽  
pp. 765-780 ◽  
Author(s):  
Diana Cruz ◽  
Ricardo Pinto ◽  
Margarida Freitas-Silva ◽  
José Pedro Nunes ◽  
Rui Medeiros
Keyword(s):  
Atrial Fibrillation ◽  
Genetic Variants ◽  
Complex Traits ◽  
Association Studies ◽  
Cardioembolic Stroke ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Genetic Determinants ◽  
Genome Wide ◽  
Genome Wide Significance

Atrial fibrillation (AF) and stroke are included in a group of complex traits that have been approached regarding of their study by susceptibility genetic determinants. Since 2007, several genome-wide association studies (GWAS) aiming to identify genetic variants modulating AF risk have been conducted. Thus, 11 GWAS have identified 26 SNPs (p < 5 × 10-2), of which 19 reached genome-wide significance (p < 5 × 10-8). From those variants, seven were also associated with cardioembolic stroke and three reached genome-wide significance in stroke GWAS. These associations may shed a light on putative shared etiologic mechanisms between AF and cardioembolic stroke. Additionally, some of these identified variants have been incorporated in genetic risk scores in order to elucidate new approaches of stroke prediction, prevention and treatment.

scholarly journals Quantitative Proteomics of Human Heart Samples Collected In Vivo Reveal the Remodeled Protein Landscape of Dilated Left Atrium Without Atrial Fibrillation

2020 ◽  
Vol 19 (7) ◽  
pp. 1132-1144
Author(s):  
Nora Linscheid ◽  
Pi Camilla Poulsen ◽  
Ida Dalgaard Pedersen ◽  
Emilie Gregers ◽  
Jesper Hastrup Svendsen ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
Mitral Valve ◽  
Protein Expression ◽  
High Resolution Mass Spectrometry ◽  
Association Studies ◽  
Genomic Research ◽  
Genome Wide Association Studies ◽  
History Of ◽  
The Impact

Genetic and genomic research has greatly advanced our understanding of heart disease. Yet, comprehensive, in-depth, quantitative maps of protein expression in hearts of living humans are still lacking. Using samples obtained during valve replacement surgery in patients with mitral valve prolapse (MVP), we set out to define inter-chamber differences, the intersect of proteomic data with genetic or genomic datasets, and the impact of left atrial dilation on the proteome of patients with no history of atrial fibrillation (AF).We collected biopsies from right atria (RA), left atria (LA) and left ventricle (LV) of seven male patients with mitral valve regurgitation with dilated LA but no history of AF. Biopsy samples were analyzed by high-resolution mass spectrometry (MS), where peptides were pre-fractionated by reverse phase high-pressure liquid chromatography prior to MS measurement on a Q-Exactive-HF Orbitrap instrument. We identified 7,314 proteins based on 130,728 peptides. Results were confirmed in an independent set of biopsies collected from three additional individuals. Comparative analysis against data from post-mortem samples showed enhanced quantitative power and confidence level in samples collected from living hearts. Our analysis, combined with data from genome wide association studies suggested candidate gene associations to MVP, identified higher abundance in ventricle for proteins associated with cardiomyopathies and revealed the dilated LA proteome, demonstrating differential representation of molecules previously associated with AF, in non-AF hearts.This is the largest dataset of cardiac protein expression from human samples collected in vivo. It provides a comprehensive resource that allows insight into molecular fingerprints of MVP and facilitates novel inferences between genomic data and disease mechanisms. We propose that over-representation of proteins in ventricle is consequent not to redundancy but to functional need, and conclude that changes in abundance of proteins known to associate with AF are not sufficient for arrhythmogenesis.

Sign in / Sign up

Export Citation Format

Share Document