scholarly journals Integrative genomic analysis of blood pressure and related phenotypes in rats

Author(s):  
Fumihiko Takeuchi ◽  
Yi-Qiang Liang ◽  
Masato Isono ◽  
Michiko Tajima ◽  
Zong Hu Cui ◽  
...  

Despite remarkable progress made in human genome-wide association studies, there remains a substantial gap between statistical evidence for genetic associations and functional comprehension of the underlying mechanisms governing these associations. As a means of bridging this gap, we performed genomic analysis of blood pressure (BP) and related phenotypes in spontaneously hypertensive rats (SHR) and their sub-strain, stroke-prone SHR (SHRSP), both of which are unique genetic models of severe hypertension and cardiovascular complications. By integrating whole-genome sequencing, transcriptome profiling, genome-wide linkage scans (max n=1,415), fine congenic mapping (max n=8,704), pharmacological intervention and comparative analysis with transcriptome-wide association study (TWAS) datasets, we searched causal genes and causal pathways for the tested traits. The overall results validated the polygenic architecture of elevated BP compared with a non-hypertensive control strain, Wistar Kyoto rats (WKY); e.g., inter-strain BP differences between SHRSP and WKY could be largely explained by an aggregate of BP changes in seven SHRSP-derived consomic strains. We identified 26 potential target genes, including rat homologues of human TWAS loci, for the tested traits. In this study, we re-discovered 18 genes that had previously been determined to contribute to hypertension or cardiovascular phenotypes. Notably, five of these genes belong to the kallikrein-kinin/renin-angiotensin systems (KKS/RAS), where the most prominent differential expression between hypertensive and non-hypertensive alleles could be detected in rat Klk1 paralogues. In combination with a pharmacological intervention, we provide in vivo experimental evidence supporting the presence of key disease pathways, such as KKS/RAS, in a rat polygenic hypertension model.

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jamie W. Robinson ◽  
Richard M. Martin ◽  
Spiridon Tsavachidis ◽  
Amy E. Howell ◽  
Caroline L. Relton ◽  
...  

AbstractGenome-wide association studies (GWAS) have discovered 27 loci associated with glioma risk. Whether these loci are causally implicated in glioma risk, and how risk differs across tissues, has yet to be systematically explored. We integrated multi-tissue expression quantitative trait loci (eQTLs) and glioma GWAS data using a combined Mendelian randomisation (MR) and colocalisation approach. We investigated how genetically predicted gene expression affects risk across tissue type (brain, estimated effective n = 1194 and whole blood, n = 31,684) and glioma subtype (all glioma (7400 cases, 8257 controls) glioblastoma (GBM, 3112 cases) and non-GBM gliomas (2411 cases)). We also leveraged tissue-specific eQTLs collected from 13 brain tissues (n = 114 to 209). The MR and colocalisation results suggested that genetically predicted increased gene expression of 12 genes were associated with glioma, GBM and/or non-GBM risk, three of which are novel glioma susceptibility genes (RETREG2/FAM134A, FAM178B and MVB12B/FAM125B). The effect of gene expression appears to be relatively consistent across glioma subtype diagnoses. Examining how risk differed across 13 brain tissues highlighted five candidate tissues (cerebellum, cortex, and the putamen, nucleus accumbens and caudate basal ganglia) and four previously implicated genes (JAK1, STMN3, PICK1 and EGFR). These analyses identified robust causal evidence for 12 genes and glioma risk, three of which are novel. The correlation of MR estimates in brain and blood are consistently low which suggested that tissue specificity needs to be carefully considered for glioma. Our results have implicated genes yet to be associated with glioma susceptibility and provided insight into putatively causal pathways for glioma risk.


2018 ◽  
Vol 49 (13) ◽  
pp. 2197-2205 ◽  
Author(s):  
Hannah M. Sallis ◽  
George Davey Smith ◽  
Marcus R. Munafò

AbstractBackgroundDespite the well-documented association between smoking and personality traits such as neuroticism and extraversion, little is known about the potential causal nature of these findings. If it were possible to unpick the association between personality and smoking, it may be possible to develop tailored smoking interventions that could lead to both improved uptake and efficacy.MethodsRecent genome-wide association studies (GWAS) have identified variants robustly associated with both smoking phenotypes and personality traits. Here we use publicly available GWAS summary statistics in addition to individual-level data from UK Biobank to investigate the link between smoking and personality. We first estimate genetic overlap between traits using LD score regression and then use bidirectional Mendelian randomisation methods to unpick the nature of this relationship.ResultsWe found clear evidence of a modest genetic correlation between smoking behaviours and both neuroticism and extraversion. We found some evidence that personality traits are causally linked to certain smoking phenotypes: among current smokers each additional neuroticism risk allele was associated with smoking an additional 0.07 cigarettes per day (95% CI 0.02–0.12, p = 0.009), and each additional extraversion effect allele was associated with an elevated odds of smoking initiation (OR 1.015, 95% CI 1.01–1.02, p = 9.6 × 10−7).ConclusionWe found some evidence for specific causal pathways from personality to smoking phenotypes, and weaker evidence of an association from smoking initiation to personality. These findings could be used to inform future smoking interventions or to tailor existing schemes.


2021 ◽  
Vol 12 ◽  
Author(s):  
Martina Rauner ◽  
Ines Foessl ◽  
Melissa M. Formosa ◽  
Erika Kague ◽  
Vid Prijatelj ◽  
...  

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.


2019 ◽  
Vol 15 ◽  
pp. 117693431986086
Author(s):  
Shan-Shan Dong ◽  
Yan Guo ◽  
Tie-Lin Yang

Genome-wide association studies (GWASs) have successfully identified thousands of susceptibility loci for human complex diseases. However, missing heritability is still a challenging problem. Considering most GWAS loci are located in regulatory elements, we recently developed a pipeline named functional disease-associated single-nucleotide polymorphisms (SNPs) prediction (FDSP), to predict novel susceptibility loci for complex diseases based on the interpretation of regulatory features and published GWAS results with machine learning. When applied to type 2 diabetes and hypertension, the predicted susceptibility loci by FDSP were proved to be capable of explaining additional heritability. In addition, potential target genes of the predicted positive SNPs were significantly enriched in disease-related pathways. Our results suggested that taking regulatory features into consideration might be a useful way to address the missing heritability problem. We hope FDSP could offer help for the identification of novel susceptibility loci for complex diseases.


2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Antoinette F. van Ouwerkerk ◽  
Fernanda M. Bosada ◽  
Karel van Duijvenboden ◽  
Matthew C. Hill ◽  
Lindsey E. Montefiori ◽  
...  

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.


2020 ◽  
Vol 117 (34) ◽  
pp. 20753-20763 ◽  
Author(s):  
Lynn M. Williams ◽  
Fiona E. McCann ◽  
Marisa A. Cabrita ◽  
Thomas Layton ◽  
Adam Cribbs ◽  
...  

Fibrotic diseases remain a major cause of morbidity and mortality, yet there are few effective therapies. The underlying pathology of all fibrotic conditions is the activity of myofibroblasts. Using cells from freshly excised disease tissue from patients with Dupuytren’s disease (DD), a localized fibrotic disorder of the palm, we sought to identify new therapeutic targets for fibrotic disease. We hypothesized that the persistent activity of myofibroblasts in fibrotic diseases might involve epigenetic modifications. Using a validated genetics-led target prioritization algorithm (Pi) of genome wide association studies (GWAS) data and a broad screen of epigenetic inhibitors, we found that the acetyltransferase CREBBP/EP300 is a major regulator of contractility and extracellular matrix production via control of H3K27 acetylation at the profibrotic genes,ACTA2andCOL1A1. Genomic analysis revealed that EP300 is highly enriched at enhancers associated with genes involved in multiple profibrotic pathways, and broad transcriptomic and proteomic profiling of CREBBP/EP300 inhibition by the chemical probe SGC-CBP30 identified collagen VI (Col VI) as a prominent downstream regulator of myofibroblast activity. Targeted Col VI knockdown results in significant decrease in profibrotic functions, including myofibroblast contractile force, extracellular matrix (ECM) production, chemotaxis, and wound healing. Further evidence for Col VI as a major determinant of fibrosis is its abundant expression within Dupuytren’s nodules and also in the fibrotic foci of idiopathic pulmonary fibrosis (IPF). Thus, Col VI may represent a tractable therapeutic target across a range of fibrotic disorders.


2017 ◽  
Vol 242 (13) ◽  
pp. 1325-1334 ◽  
Author(s):  
Yizhou Zhu ◽  
Cagdas Tazearslan ◽  
Yousin Suh

Genome-wide association studies have shown that the far majority of disease-associated variants reside in the non-coding regions of the genome, suggesting that gene regulatory changes contribute to disease risk. To identify truly causal non-coding variants and their affected target genes remains challenging but is a critical step to translate the genetic associations to molecular mechanisms and ultimately clinical applications. Here we review genomic/epigenomic resources and in silico tools that can be used to identify causal non-coding variants and experimental strategies to validate their functionalities. Impact statement Most signals from genome-wide association studies (GWASs) map to the non-coding genome, and functional interpretation of these associations remained challenging. We reviewed recent progress in methodologies of studying the non-coding genome and argued that no single approach allows one to effectively identify the causal regulatory variants from GWAS results. By illustrating the advantages and limitations of each method, our review potentially provided a guideline for taking a combinatorial approach to accurately predict, prioritize, and eventually experimentally validate the causal variants.


2020 ◽  
Author(s):  
Dylan M. Glubb ◽  
Deborah J. Thompson ◽  
Katja K.H. Aben ◽  
Ahmad Alsulimani ◽  
Frederic Amant ◽  
...  

AbstractAccumulating evidence suggests a relationship between endometrial cancer and epithelial ovarian cancer. For example, endometrial cancer and epithelial ovarian cancer share epidemiological risk factors and molecular features observed across histotypes are held in common (e.g. serous, endometrioid and clear cell). Independent genome-wide association studies (GWAS) for endometrial cancer and epithelial ovarian cancer have identified 16 and 27 risk regions, respectively, four of which overlap between the two cancers. Using GWAS summary statistics, we explored the shared genetic etiology between endometrial cancer and epithelial ovarian cancer. Genetic correlation analysis using LD Score regression revealed significant genetic correlation between the two cancers (rG = 0.43, P = 2.66 × 10−5). To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e. inverse-variance meta-analysis, co-localization, and M-values), and performed analyses by stratified by subtype. We found seven loci associated with risk for both cancers (PBonferroni < 2.4 × 10−9). In addition, four novel regions at 7p22.2, 7q22.1, 9p12 and 11q13.3 were identified at a sub-genome wide threshold (P < 5 × 10−7). Integration with promoter-associated HiChIP chromatin loops from immortalized endometrium and epithelial ovarian cell lines, and expression quantitative trait loci (eQTL) data highlighted candidate target genes for further investigation.


2018 ◽  
Author(s):  
Satish K Nandakumar ◽  
Sean K McFarland ◽  
Laura Marlene Mateyka ◽  
Caleb A Lareau ◽  
Jacob C Ulirsch ◽  
...  

Genome-wide association studies (GWAS) have identified thousands of variants associated with human diseases and traits. However, the majority of GWAS-implicated variants are in non-coding genomic regions and require in depth follow-up to identify target genes and decipher biological mechanisms. Here, rather than focusing on causal variants, we have undertaken a pooled loss-of-function screen in primary hematopoietic cells to interrogate 389 candidate genes contained in 75 loci associated with red blood cell traits. Using this approach, we identify 77 genes at 38 GWAS loci, with most loci harboring 1-2 candidate genes. Importantly, the hit set was strongly enriched for genes validated through orthogonal genetic approaches. Genes identified by this approach are enriched in relevant biological pathways, allowing regulators of human erythropoiesis and blood disease modifiers to be defined. More generally, this functional screen provides a paradigm for gene-centric follow up of GWAS for a variety of human diseases and traits.


Sign in / Sign up

Export Citation Format

Share Document