scholarly journals Novel Genome-wide Interactions Mediated via BOLL and EDNRA Polymorphisms in Intracranial Aneurysm

Author(s):  
Eun Pyo Hong ◽  
Dong Hyuk Youn ◽  
Bong Jun Kim ◽  
Jae Jun Lee ◽  
Sehyeon Nam ◽  
...  

Abstract Association of boule (BOLL) and endothelin receptor type A (EDNRA) loci with intracranial aneurysm (IA) formation has been reported via genome-wide association studies. However, the underlying genome-wide interactions have yet to be reported. We sought to identify genome-wide interactions involving BOLL and EDNRA loci for IA. Genome-wide interaction analyses of BOLL and EDNRA involving 250 IA patients and 296 controls were performed under an additive effect model. Subsequent gene expression analyses were conducted using transcripts per million (TPM). A total of 23 and 11 SNPs suggested a genome-wide threshold (p < 1.25×10−8) interacting with rs700651 (BOLL) and rs6841581 (EDNRA), respectively. The rs1105980 (PTCH1) showed the most significant interaction with rs700651 (p = 6.41×10−11). The rs74585958 (RYK) interacted strongly with rs6841581 (p = 1.64×10−9). The BOLL-interacting CXCR4 was highly overexpressed in whole blood (TPM = 419.8) and CCDC3 was overexpressed in all artery-related tissues (TPM = 315.4 to 473.9). EDNRA-interacting EIF4H showed a comprehensively elevated expression across all tissues and cells (TPM = 85.8 to 372.0). Genome-wide interaction study shows that BOLL and EDNRA may contribute to IA formation by interacting with multiple genes in cardio-metabolic pathway. Our findings may provide insight into the functional relevant to IA susceptibility.

2019 ◽  
Vol 8 (2) ◽  
pp. 275 ◽  
Author(s):  
Eun Hong ◽  
Bong Kim ◽  
Steve Cho ◽  
Jin Yang ◽  
Hyuk Choi ◽  
...  

Genome-wide association studies found genetic variations with modulatory effects for intracranial aneurysm (IA) formations in European and Japanese populations. We aimed to identify the susceptibility of single nucleotide polymorphisms (SNPs) to IA in a Korean population consisting of 250 patients, and 294 controls using the Asian-specific Axiom Precision Medicine Research Array. Twenty-nine SNPs reached a genome-wide significance threshold (5 × 10−8). The rs371331393 SNP, with a stop-gain function of ARHGAP32 (11q24.3), showed the most significant association with the risk of IA (OR = 43.57, 95% CI: 21.84–86.95; p = 9.3 × 10−27). Eight out of 29 SNPs—GBA (rs75822236), TCF24 (rs112859779), OLFML2A (rs79134766), ARHGAP32 (rs371331393), CD163L1 (rs138525217), CUL4A (rs74115822), LOC102724084 (rs75861150), and LRRC3 (rs116969723)—demonstrated sufficient statistical power greater than or equal to 0.8. Two previously reported SNPs, rs700651 (BOLL, 2q33.1) and rs6841581 (EDNRA, 4q31.22), were validated in our GWAS (Genome-wide association study). In a subsequent analysis, three SNPs showed a significant difference in expressions: the rs6741819 (RNF144A, 2p25.1) was down-regulated in the adrenal gland tissue (p = 1.5 × 10−6), the rs1052270 (TMOD1. 9q22.33) was up-regulated in the testis tissue (p = 8.6 × 10−10), and rs6841581 (EDNRA, 4q31.22) was up-regulated in both the esophagus (p = 5.2 × 10−12) and skin tissues (1.2 × 10−6). Our GWAS showed novel candidate genes with Korean-specific variations in IA formations. Large population based studies are thus warranted.


2021 ◽  
Author(s):  
Eun Pyo Hong ◽  
Dong Hyuk Youn ◽  
Bong Jun Kim ◽  
Jun Hyong Ahn ◽  
Jeong Jin Park ◽  
...  

Abstract In addition to conventional genome-wide association studies (GWAS), a fine-mapping is increasingly used to identify the genetic function of variants associated with disease susceptibilities. Here, we used a fine-mapping approach to evaluate the casual variants based on a previous GWAS involving patients with intracranial aneurysm (IA). Fine-mapping analysis was conducted based on the chromosomal data provided by GWAS consisting 250 patients diagnosed with IA and 296 controls using posterior inclusion probability (PIP) and log10 transformed Bayes factor (log10BF). The narrow sense of heritability (h2) explained by each casual variant was estimated. Subsequent gene expression and functional network analyses were used to calculate the transcripts per million (TPM) values. Twenty causal candidate single nucleotide polymorphisms (SNPs) surpassed a genome-wide significance threshold for creditable evidence (log10BF > 6.1). Four SNPs including rs75822236 (R535H, GBA; log10BF = 15.06), rs112859779 (G141S, TCF24; log10BF = 12.12), rs79134766 (A208T, OLFML2A; log10BF = 14.92), and rs371331393 (Q1932X, ARHGAP32; log10BF = 20.88) showed a completed PIP value in each chromosomal region, suggesting a high probability of variant causality associated with IA. Expression in GBA was highly enriched in the whole blood (TPM = 33.13), while TCF24 were rarely expressed in all tissues and cells. No direct interaction was observed between the four casual genes; however, PSAP appeared to be particularly important via indirect correlation between other genes. Our results suggested that four mutations of GBA, TCF24, OLFML2A, and ARHGAP32 were linked to IA susceptibility and pathogenesis. Our approach may promise more informative mutations in the following GWAS.


2019 ◽  
Vol 8 (5) ◽  
pp. 692
Author(s):  
Eun Pyo Hong ◽  
Bong Jun Kim ◽  
Jin Pyeong Jeon

Previous genome-wide association studies did not show a consistent association between the BOLL gene (rs700651, 2q33.1) and intracranial aneurysm (IA) susceptibility. We aimed to perform an updated meta-analysis for the potential IA-susceptibility locus in large-scale multi-ethnic populations. We conducted a systematic review of studies identified by an electronic search from January 1990 to March 2019. The overall estimates of the “G” allele of rs700651, indicating IA susceptibility, were calculated under the fixed- and random-effect models using the inverse-variance method. Subsequent in silico function and cis-expression quantitative trait loci (cis-eQTL) analyses were performed to evaluate biological functions and genotype-specific expressions in human tissues. We included 4513 IA patients and 13,506 controls from five studies with seven independent populations: three European-ancestry, three Japanese, and one Korean population. The overall result showed a genome-wide significance threshold between rs700651 and IA susceptibility after controlling for study heterogeneity (OR = 1.213, 95% CI: 1.135–1.296). Subsequent cis-eQTL analysis showed significant genome-wide expressions in three human tissues, i.e., testis (p = 8.04 × 10−15 for ANKRD44), tibial nerves (p = 3.18 × 10−10 for SF3B1), and thyroid glands (p = 4.61 × 10−9 for SF3B1). The rs700651 common variant of the 2q33.1 region may be involved in genetic mechanisms that increase the risk of IA and may play crucial roles in regulatory functions.


Diabetes ◽  
2021 ◽  
Vol 70 (Supplement 1) ◽  
pp. 26-OR
Author(s):  
K. ALAINE BROADAWAY ◽  
XIANYONOG YIN ◽  
ALICE WILLIAMSON ◽  
EMMA WILSON ◽  
MAGIC INVESTIGATORS

2019 ◽  
Vol 22 (8) ◽  
pp. 1063-1069 ◽  
Author(s):  
N. S. Yudin ◽  
N. L. Podkolodnyy ◽  
T. A. Agarkova ◽  
E. V. Ignatieva

Selection by means of genetic markers is a promising approach to the eradication of infectious diseases in farm animals, especially in the absence of effective methods of treatment and prevention. Bovine leukemia virus (BLV) is spread throughout the world and represents one of the biggest problems for the livestock production and food security in Russia. However, recent genome-wide association studies have shown that sensitivity/resistance to BLV is polygenic. The aim of this study was to create a catalog of cattle genes and genes of other mammalian species involved in the pathogenesis of BLV-induced infection and to perform gene prioritization using bioinformatics methods. Based on manually collected information from a range of open sources, a total of 446 genes were included in the catalog of cattle genes and genes of other mammals involved in the pathogenesis of BLV-induced infection. The following criteria were used to prioritize 446 genes from the catalog: (1) the gene is associated with leukemia according to a genome-wide association study; (2) the gene is associated with leukemia according to a case-control study; (3) the role of the gene in leukemia development has been studied using knockout mice; (4) protein-protein interactions exist between the gene-encoded protein and either viral particles or individual viral proteins; (5) the gene is annotated with Gene Ontology terms that are overrepresented for a given list of genes; (6) the gene participates in biological pathways from the KEGG or REACTOME databases, which are over-represented for a given list of genes; (7) the protein encoded by the gene has a high number of protein-protein interactions with proteins encoded by other genes from the catalog. Based on each criterion, a rank was assigned to each gene. Then the ranks were summarized and an overall rank was determined. Prioritization of 446 candidate genes allowed us to identify 5 genes of interest (TNF,LTB,BOLA-DQA1,BOLA-DRB3,ATF2), which can affect the sensitivity/resistance of cattle to leukemia.


2021 ◽  
Author(s):  
Ronald J Yurko ◽  
Kathryn Roeder ◽  
Bernie Devlin ◽  
Max G'Sell

In genome-wide association studies (GWAS), it has become commonplace to test millions of SNPs for phenotypic association. Gene-based testing can improve power to detect weak signal by reducing multiple testing and pooling signal strength. While such tests account for linkage disequilibrium (LD) structure of SNP alleles within each gene, current approaches do not capture LD of SNPs falling in different nearby genes, which can induce correlation of gene-based test statistics. We introduce an algorithm to account for this correlation. When a gene's test statistic is independent of others, it is assessed separately; when test statistics for nearby genes are strongly correlated, their SNPs are agglomerated and tested as a locus. To provide insight into SNPs and genes driving association within loci, we develop an interactive visualization tool to explore localized signal. We demonstrate our approach in the context of weakly powered GWAS for autism spectrum disorder, which is contrasted to more highly powered GWAS for schizophrenia and educational attainment. To increase power for these analyses, especially those for autism, we use adaptive p-value thresholding (AdaPT), guided by high-dimensional metadata modeled with gradient boosted trees, highlighting when and how it can be most useful. Notably our workflow is based on summary statistics.


2018 ◽  
Vol 28 (1) ◽  
pp. 166-174 ◽  
Author(s):  
Sara L Pulit ◽  
Charli Stoneman ◽  
Andrew P Morris ◽  
Andrew R Wood ◽  
Craig A Glastonbury ◽  
...  

Abstract More than one in three adults worldwide is either overweight or obese. Epidemiological studies indicate that the location and distribution of excess fat, rather than general adiposity, are more informative for predicting risk of obesity sequelae, including cardiometabolic disease and cancer. We performed a genome-wide association study meta-analysis of body fat distribution, measured by waist-to-hip ratio (WHR) adjusted for body mass index (WHRadjBMI), and identified 463 signals in 346 loci. Heritability and variant effects were generally stronger in women than men, and we found approximately one-third of all signals to be sexually dimorphic. The 5% of individuals carrying the most WHRadjBMI-increasing alleles were 1.62 times more likely than the bottom 5% to have a WHR above the thresholds used for metabolic syndrome. These data, made publicly available, will inform the biology of body fat distribution and its relationship with disease.


2021 ◽  
pp. ASN.2020111599
Author(s):  
Zhi Yu ◽  
Jin Jin ◽  
Adrienne Tin ◽  
Anna Köttgen ◽  
Bing Yu ◽  
...  

Background: Genome-wide association studies (GWAS) have revealed numerous loci for kidney function (estimated glomerular filtration rate, eGFR). The relationship of polygenic predictors of eGFR, risk of incident adverse kidney outcomes, and the plasma proteome is not known. Methods: We developed a genome-wide polygenic risk score (PRS) for eGFR by applying the LDpred algorithm to summary statistics generated from a multiethnic meta-analysis of CKDGen Consortium GWAS (N=765,348) and UK Biobank GWAS (90% of the cohort; N=451,508), followed by best parameter selection using the remaining 10% of UK Biobank (N=45,158). We then tested the association of the PRS in the Atherosclerosis Risk in Communities (ARIC) study (N=8,866) with incident chronic kidney disease, kidney failure, and acute kidney injury. We also examined associations between the PRS and 4,877 plasma proteins measured at at middle age and older adulthood and evaluated mediation of PRS associations by eGFR. Results: The developed PRS showed significant associations with all outcomes with hazard ratios (95% CI) per 1 SD lower PRS ranged from 1.06 (1.01, 1.11) to 1.33 (1.28, 1.37). The PRS was significantly associated with 132 proteins at both time points. The strongest associations were with cystatin-C, collagen alpha-1(XV) chain, and desmocollin-2. Most proteins were higher at lower kidney function, except for 5 proteins including testican-2. Most correlations of the genetic PRS with proteins were mediated by eGFR. Conclusions: A PRS for eGFR is now sufficiently strong to capture risk for a spectrum of incident kidney diseases and broadly influences the plasma proteome, primarily mediated by eGFR.


Genetics ◽  
2019 ◽  
Vol 213 (4) ◽  
pp. 1225-1236 ◽  
Author(s):  
Weimiao Wu ◽  
Zhong Wang ◽  
Ke Xu ◽  
Xinyu Zhang ◽  
Amei Amei ◽  
...  

Longitudinal phenotypes have been increasingly available in genome-wide association studies (GWAS) and electronic health record-based studies for identification of genetic variants that influence complex traits over time. For longitudinal binary data, there remain significant challenges in gene mapping, including misspecification of the model for phenotype distribution due to ascertainment. Here, we propose L-BRAT (Longitudinal Binary-trait Retrospective Association Test), a retrospective, generalized estimating equation-based method for genetic association analysis of longitudinal binary outcomes. We also develop RGMMAT, a retrospective, generalized linear mixed model-based association test. Both tests are retrospective score approaches in which genotypes are treated as random conditional on phenotype and covariates. They allow both static and time-varying covariates to be included in the analysis. Through simulations, we illustrated that retrospective association tests are robust to ascertainment and other types of phenotype model misspecification, and gain power over previous association methods. We applied L-BRAT and RGMMAT to a genome-wide association analysis of repeated measures of cocaine use in a longitudinal cohort. Pathway analysis implicated association with opioid signaling and axonal guidance signaling pathways. Lastly, we replicated important pathways in an independent cocaine dependence case-control GWAS. Our results illustrate that L-BRAT is able to detect important loci and pathways in a genome scan and to provide insights into genetic architecture of cocaine use.


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