scholarly journals Identification of Atrial Fibrillation-Associated Genes ERBB2 and MYPN Using Genome-Wide Association and Transcriptome Expression Profile Data on Left–Right Atrial Appendages

2021 ◽  
Vol 12 ◽  
Author(s):  
Xiangguang Meng ◽  
Yali Nie ◽  
Keke Wang ◽  
Chen Fan ◽  
Juntao Zhao ◽  
...  

More reliable methods are needed to uncover novel biomarkers associated with atrial fibrillation (AF). Our objective is to identify significant network modules and newly AF-associated genes by integrative genetic analysis approaches. The single nucleotide polymorphisms with nominal relevance significance from the AF-associated genome-wide association study (GWAS) data were converted into the GWAS discovery set using ProxyGeneLD, followed by merging with significant network modules constructed by weighted gene coexpression network analysis (WGCNA) from one expression profile data set, composed of left and right atrial appendages (LAA and RAA). In LAA, two distinct network modules were identified (blue: p = 0.0076; yellow: p = 0.023). Five AF-associated biomarkers were identified (ERBB2, HERC4, MYH7, MYPN, and PBXIP1), combined with the GWAS test set. In RAA, three distinct network modules were identified and only one AF-associated gene LOXL1 was determined. Using human LAA tissues by real-time quantitative polymerase chain reaction, the differentially expressive results of ERBB2, MYH7, and MYPN were observed (p < 0.05). This study first demonstrated the feasibility of fusing GWAS with expression profile data by ProxyGeneLD and WGCNA to explore AF-associated genes. In particular, two newly identified genes ERBB2 and MYPN via this approach contribute to further understanding the occurrence and development of AF, thereby offering preliminary data for subsequent studies.

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Yousef Rahimi ◽  
Mohammad Reza Bihamta ◽  
Alireza Taleei ◽  
Hadi Alipour ◽  
Pär K. Ingvarsson

Abstract Background Identification of loci for agronomic traits and characterization of their genetic architecture are crucial in marker-assisted selection (MAS). Genome-wide association studies (GWAS) have increasingly been used as potent tools in identifying marker-trait associations (MTAs). The introduction of new adaptive alleles in the diverse genetic backgrounds may help to improve grain yield of old or newly developed varieties of wheat to balance supply and demand throughout the world. Landraces collected from different climate zones can be an invaluable resource for such adaptive alleles. Results GWAS was performed using a collection of 298 Iranian bread wheat varieties and landraces to explore the genetic basis of agronomic traits during 2016–2018 cropping seasons under normal (well-watered) and stressed (rain-fed) conditions. A high-quality genotyping by sequencing (GBS) dataset was obtained using either all original single nucleotide polymorphism (SNP, 10938 SNPs) or with additional imputation (46,862 SNPs) based on W7984 reference genome. The results confirm that the B genome carries the highest number of significant marker pairs in both varieties (49,880, 27.37%) and landraces (55,086, 28.99%). The strongest linkage disequilibrium (LD) between pairs of markers was observed on chromosome 2D (0.296). LD decay was lower in the D genome, compared to the A and B genomes. Association mapping under two tested environments yielded a total of 313 and 394 significant (−log10P >3) MTAs for the original and imputed SNP data sets, respectively. Gene ontology results showed that 27 and 27.5% of MTAs of SNPs in the original set were located in protein-coding regions for well-watered and rain-fed conditions, respectively. While, for the imputed data set 22.6 and 16.6% of MTAs represented in protein-coding genes for the well-watered and rain-fed conditions, respectively. Conclusions Our finding suggests that Iranian bread wheat landraces harbor valuable alleles that are adaptive under drought stress conditions. MTAs located within coding genes can be utilized in genome-based breeding of new wheat varieties. Although imputation of missing data increased the number of MTAs, the fraction of these MTAs located in coding genes were decreased across the different sub-genomes.


Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 1381-1381
Author(s):  
Melanie E. Garrett ◽  
Karen L. Soldano ◽  
Blair R. Anderson ◽  
Eugene P. Orringer ◽  
James R. Eckman ◽  
...  

Abstract BACKGROUND: Nephropathy is a common and devastating complication of sickle cell disease (SCD) associated with mortality (Elmariah et al, 2014). However, early detection of SCD nephropathy (SCDN) has proven difficult. Discovery of genetic markers associated with SCDN could greatly improve our ability to identify patients at risk for renal decline. To that end, we have performed a genome-wide association study (GWAS) of glomerular filtration rate (GFR) in our adult SCD cohort. METHODS: Medical history, laboratory values and DNA for genotyping were collected as part of a multicenter study of outcome-modifying genes in SCD. Participating institutions included sickle cell centers at Duke University, University of North Carolina at Chapel Hill, Emory University, and East Carolina University. GFR was estimated using the ‘Modification of Diet in Renal Disease’ (MDRD) study definition (Levey et al, 1999) and dichotomized at the clinically relevant threshold of 90 ml/min/1.73m2. 463 patients with complete data were included in the analysis (54.6% female, mean age 34.2 ± 12 years, 17.5% GFR < 90 ml/min/1.73m2). Genotyping was performed using the Illumina Human610-Quad BeadChip (Illumina, San Diego, CA), and a global reference panel from the 1000 Genomes project was used to impute genotypes not covered on the GWAS chip. Samples were pre-phased with SHAPEIT (Delaneau et al, 2012) and genotypes inferred using IMPUTE2 (Howie et al, 2009). After data cleaning and removal of single nucleotide polymorphisms (SNPs) with minor allele frequency (MAF) < 5%, 3,021,990 SNPs were available for analysis. Principal component (PC) analysis was performed to obtain measures of population stratification in our data set using EIGENSOFT (Patterson et al, 2006). Logistic regression was utilized to test for association between each SNP and dichotomized GFR, controlling for genome-wide PCs using PLINK (Purcell et al, 2008). False discovery rate (FDR) p-values were generated using PROC MULTTEST in SAS (SAS Systems, Cary, NC). RESULTS: Because GWAS chips capture common variation, several of the most highly associated SNPs were intergenic. The SNP with the most evidence for association that also lies within a gene was rs72777730 in XYLT1 (p=6.8E-6). For each additional C allele, the odds of having GFR < 90 ml/min/1.73m2 increased by 2.7. Other top hits included rs1990628 in ZNF423 (p=2.7E-5) and rs6449202 in SLC2A9 (p=3.8E-5). None of the findings met FDR significance. To further investigate our findings, we assessed the role of rare variants on renal function in our data set. We observed SNPs in XYLT1 from the Illumina HumanExome BeadChips associated with proteinuria (p=0.008) using the gene-based SKAT test (Wu et al, 2011). Further, we performed whole-exome sequencing of 15 patients with disparate GFR levels using VCRome 2.1 capture and 100bp paired-end reads generated from an Illumina HiSeq. One novel non-synonymous SNP (chr16:17353261, C>T) was identified in XYLT1 in 6 of 7 patients with low GFR (≤ 70 ml/min/1.73m2) but was absent in patients with normal GFR (> 90 ml/min/1.73m2). Additionally, four known non-synonymous SNPs were observed in low GFR patients but were absent in those with normal GFR levels. DISCUSSION: Xylosyltransferase 1 (XYLT1, also known as XT-1) encodes the enzyme responsible for biosynthesis of heparin sulfate proteoglycans, which affect permeability of the glomerular basement membrane. The c.343G>T polymorphism in XYLT1 has been implicated in diabetic nephropathy (Schön et al, 2006), and XT-1 is up-regulated in rats with adriamycin nephropathy (Sichuan et al, 2007). Zinc finger protein 423 (ZNF423) is involved in DNA damage response signaling, and mutations in ZNF423 have been identified in patients with nephronophthisis and Joubert syndrome (Chaki et al, 2012). Finally, solute carrier family 2 member 9 (SLC2A9, also known as GLUT9) is a transporter involved in urate reabsorption in the renal tubules. Mutations in this gene have been identified in patients with renal hypouricemia-2 (Matsuo et al, 2008). Thus, while none of the SNPs reached genome-wide significance, likely due to the modest size of our data set, we have identified several promising candidate genes nominally associated with renal function in our cohort of SCD patients and demonstrate that both common and rare variation in these genes likely contributes to risk for renal decline. Disclosures No relevant conflicts of interest to declare.


2018 ◽  
Author(s):  
Jessica van Setten ◽  
Jennifer A. Brody ◽  
Yalda Jamshidi ◽  
Brenton R. Swenson ◽  
Anne M. Butler ◽  
...  

ABSTRACTElectrocardiographic PR interval measures atrial and atrioventricular depolarization and conduction, and abnormal PR interval is a risk factor for atrial fibrillation and heart block. We performed a genome-wide association study in over 92,000 individuals of European descent and identified 44 loci associated with PR interval (34 novel). Examination of the 44 loci revealed known and novel biological processes involved in cardiac atrial electrical activity, and genes in these loci were highly over-represented in several cardiac disease processes. Nearly half of the 61 independent index variants in the 44 loci were associated with atrial or blood transcript expression levels, or were in high linkage disequilibrium with one or more missense variants. Cardiac regulatory regions of the genome as measured by cardiac DNA hypersensitivity sites were enriched for variants associated with PR interval, compared to non-cardiac regulatory regions. Joint analyses combining PR interval with heart rate, QRS interval, and atrial fibrillation identified additional new pleiotropic loci. The majority of associations discovered in European-descent populations were also present in African-American populations. Meta-analysis examining over 105,000 individuals of African and European descent identified additional novel PR loci. These additional analyses identified another 13 novel loci. Together, these findings underscore the power of GWAS to extend knowledge of the molecular underpinnings of clinical processes.


2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
J Fill ◽  
A Fokina ◽  
G Klappacher

Abstract Background Based on observational evidence, atrial fibrillation is a well-established risk factor of stroke to be considered for antithrombotic treatment in presence of additional clinical conditions derived from multivariate risk models. Although biologically plausible, it however still is unknown whether this association is causal and confined to the embolic stroke subtype. Purpose Our objective was to explore whether genetically determined manifestation of atrial fibrillation was associated with stroke and its etiologic subtypes by conducting a 2-sample Mendelian randomization (MR) study on publicly available summary statistics from GWAS consortia. Methods Genetic instruments for atrial fibrillation were obtained from the AFGen Consortium comprising 17,931 cases and 115,142 controls. Their associations with stroke and stroke subtypes were evaluated in the MEGASTROKE genome-wide association study data set (67 162 cases; 454 450 controls) applying inverse variance–weighted meta-analysis, weighted-median analysis, Mendelian randomization–Egger regression, and multivariable Mendelian randomization. The dataset of Nielsen et al. comprising a total of 60,620 cases with atrial fibrillation and 970,216 controls of European ancestry from six contributing studies was used as an independent validation sample. Genetic instruments for atrial fibrillation were further tested for association with etiologically related traits by using publicly available genome-wide association study data. Results Genetic predisposition to atrial fibrillation was associated with higher risk of any stroke (beta coefficient [b] ± standard error [se] = 0.22±0.04; P=0.0001), any ischemic stroke (b ± se = 0.24±0.05; P=0.0003), and cardioembolic stroke (b ± se = 0.76±0.10; P&lt;0.0001), but not with small-vessel stroke or large artery stroke, see figure. Analyses in the validation sample showed similar associations (any stroke: b ± se = 0.19±0.04; P&lt;0.0001; any ischemic stroke: b ± se = 0.21±0.04; P&lt;0.0001; cardioembolic stroke: b ± se = 0.82±0.13; P&lt;0.0001). Genetically determined atrial fibrillation was further weakly associated with chronic kidney disease (b ± se = 0.10±0.04; P=0.0261), but not with coronary artery disease and myocardial infarction or any other available phenotype. Conclusions Genetic predisposition to atrial fibrillation is associated with higher risk of any stroke, mainly driven by the ischemic and cardioembolic subtypes. In contrast, large artery and small-vessel strokes did not exhibit a causal relationship with atrial fibrillation. Funding Acknowledgement Type of funding source: Public hospital(s). Main funding source(s): Medical University of Vienna, Austria


2014 ◽  
Vol 114 (4) ◽  
pp. 593-600 ◽  
Author(s):  
Matthew J. Kolek ◽  
Todd L. Edwards ◽  
Raafia Muhammad ◽  
Adnan Balouch ◽  
M. Benjamin Shoemaker ◽  
...  

2018 ◽  
Vol 17 ◽  
pp. 117693511877510 ◽  
Author(s):  
Yi Yang ◽  
Saonli Basu ◽  
Lisa Mirabello ◽  
Logan Spector ◽  
Lin Zhang

Osteosarcoma is considered to be the most common primary malignant bone cancer among children and young adults. Previous studies suggest growth spurts and height to be risk factors for osteosarcoma. However, studies on the genetic cause are still limited given the rare occurrence of the disease. In this study, we investigated in a family trio data set that is composed of 209 patients and their unaffected parents and conducted a genome-wide association study (GWAS) to identify genetic risk factors for osteosarcoma. We performed a Bayesian gene-based GWAS based on the single-nucleotide polymorphism (SNP)-level summary statistics obtained from a likelihood ratio test of the trio data, which uses a hierarchically structured prior that incorporates the SNP-gene hierarchical structure. The Bayesian approach has higher power than SNP-level GWAS analysis due to the reduced number of tests and is robust by accounting for the correlations between SNPs so that it borrows information across SNPs within a gene. We identified 217 genes that achieved genome-wide significance. Ingenuity pathway analysis of the gene set indicated that osteosarcoma is potentially related to TP53, estrogen receptor signaling, xenobiotic metabolism signaling, and RANK signaling in osteoclasts.


2019 ◽  
Author(s):  
Sonia Shah ◽  
Albert Henry ◽  
Carolina Roselli ◽  
Honghuang Lin ◽  
Garðar Sveinbjörnsson ◽  
...  

AbstractHeart failure (HF) is a leading cause of morbidity and mortality worldwide1. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained2–4. We report the largest GWAS meta-analysis of HF to-date, comprising 47,309 cases and 930,014 controls. We identify 12 independent variant associations with HF at 11 genomic loci, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function suggesting shared genetic aetiology. Expression quantitative trait analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homeostasis (BAG3), and cellular senescence (CDKN1A). Using Mendelian randomisation analysis we provide new evidence supporting previously equivocal causal roles for several HF risk factors identified in observational studies, and demonstrate CAD-independent effects for atrial fibrillation, body mass index, hypertension and triglycerides. These findings extend our knowledge of the genes and pathways underlying HF and may inform the development of new therapeutic approaches.


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