scholarly journals A Generalized Genetic Random Field Method for the Genetic Association Analysis of Sequencing Data

2014 ◽  
Vol 38 (3) ◽  
pp. 242-253 ◽  
Author(s):  
Ming Li ◽  
Zihuai He ◽  
Min Zhang ◽  
Xiaowei Zhan ◽  
Changshuai Wei ◽  
...  
Keyword(s):  
Random Field ◽  
Genetic Association ◽  
Association Analysis ◽  
Field Method ◽  
Sequencing Data ◽  
Genetic Association Analysis

Genetic association analysis between IL9 and coronary artery disease in a Chinese Han population

Cytokine ◽  
2022 ◽  
Vol 150 ◽  
pp. 155761
Author(s):  
Lingfeng Zha ◽  
Jiangtao Dong ◽  
Qianwen Chen ◽  
Yuhua Liao ◽  
Hongsong Zhang ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Genetic Association ◽  
Association Analysis ◽  
Chinese Han Population ◽  
Chinese Han ◽  
Genetic Association Analysis ◽  
Han Population ◽  
Artery Disease

scholarly journals Prevalence, Patterns, and Genetic Association Analysis of Modic Vertebral Endplate Changes

2017 ◽  
Vol 11 (4) ◽  
pp. 594-600 ◽  
Author(s):  
Rishi Mugesh Kanna ◽  
Rajasekaran Shanmuganathan ◽  
Veera Ranjani Rajagopalan ◽  
Senthil Natesan ◽  
Raveendran Muthuraja ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Genetic Association ◽  
Association Analysis ◽  
Disc Degeneration ◽  
Lumbar Disc ◽  
Nucleotide Polymorphisms ◽  
Lumbar Disc Degeneration ◽  
Vertebral Endplate ◽  
Genetic Association Analysis ◽  
Study Population

<sec><title>Study Design</title><p>A prospective genetic association study.</p></sec><sec><title>Purpose</title><p>The etiology of Modic changes (MCs) is unclear. Recently, the role of genetic factors in the etiology of MCs has been evaluated. However, studies with a larger patient subset are lacking, and candidate genes involved in other disc degeneration phenotypes have not been evaluated. We studied the prevalence of MCs and genetic association of 41 candidate genes in a large Indian cohort.</p></sec><sec><title>Overview of Literature</title><p>MCs are vertebral endplate signal changes predominantly observed in the lumbar spine. A significant association between MCs and lumbar disc degeneration and nonspecific low back pain has been described, with the etiopathogenesis implicating various mechanical, infective, and biochemical factors.</p></sec><sec><title>Methods</title><p>We studied 809 patients using 1.5-T magnetic resonance imaging to determine the prevalence, patterns, distribution, and type of lumbar MCs. Genetic association analysis of 71 single nucleotide polymorphisms (SNPs) of 41 candidate genes was performed based on the presence or absence of MCs. SNPs were genotyped using the Sequenome platform, and an association test was performed using PLINK software.</p></sec><sec><title>Results</title><p>The mean age of the study population (n=809) was 36.7±10.8 years. Based on the presence of MCs, the cohort was divided into 702 controls and 107 cases (prevalence, 13%). MCs were more commonly present in the lower (149/251, 59.4%) than in the upper (102/251, 40.6%) endplates. L4–5 endplates were the most commonly affected levels (30.7%). Type 2 MCs were the most commonly observed pattern (n=206, 82%). The rs2228570 SNP of VDR (<italic>p</italic>=0.02) and rs17099008 SNP of MMP20 (<italic>p</italic>=0.03) were significantly associated with MCs.</p></sec><sec><title>Conclusions</title><p>Genetic polymorphisms of SNPs of VDR and MMP20 were significantly associated with MCs. Understanding the etiopathogenetic mechanisms of MCs is important for planning preventive and therapeutic strategies.</p></sec>

scholarly journals Bioinformatic and Genetic Association Analysis of MicroRNA Target Sites in One-Carbon Metabolism Genes

PLoS ONE ◽  
2011 ◽  
Vol 6 (7) ◽  
pp. e21851 ◽  
Author(s):  
Nicole Stone ◽  
Faith Pangilinan ◽  
Anne M. Molloy ◽  
Barry Shane ◽  
John M. Scott ◽  
...  
Keyword(s):  
Genetic Association ◽  
Association Analysis ◽  
Carbon Metabolism ◽  
Microrna Target ◽  
Genetic Association Analysis ◽  
Target Sites ◽  
One Carbon Metabolism

scholarly journals Genetic Association Analysis of Cell Cycle Regulators Reveals YWHAZ Has Prognostic Significance in Prostate Cancer

2020 ◽  
Vol 17 (2) ◽  
pp. 209-216 ◽  
Author(s):  
CHIA-CHENG YU ◽  
LIH-CHYANG CHEN ◽  
WEN-HSIN LIN ◽  
VICTOR C. LIN ◽  
CHAO-YUAN HUANG ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cell Cycle ◽  
Genetic Association ◽  
Association Analysis ◽  
Prognostic Significance ◽  
Cell Cycle Regulators ◽  
Genetic Association Analysis

scholarly journals Diverse tumour susceptibility in Collaborative Cross mice: identification of a new mouse model for human gastric tumourigenesis

Gut ◽  
2019 ◽  
Vol 68 (11) ◽  
pp. 1942-1952 ◽  
Author(s):  
Pin Wang ◽  
Yunshan Wang ◽  
Sasha A Langley ◽  
Yan-Xia Zhou ◽  
Kuang-Yu Jen ◽  
...  
Keyword(s):  
Inflammatory Response ◽  
Mouse Model ◽  
Rna Sequencing ◽  
Genetic Association ◽  
Association Analysis ◽  
Collaborative Cross ◽  
Sequencing Analysis ◽  
Genetic Association Analysis ◽  
Mouse Population ◽  
Wide Range

ObjectiveThe Collaborative Cross (CC) is a mouse population model with diverse and reproducible genetic backgrounds used to identify novel disease models and genes that contribute to human disease. Since spontaneous tumour susceptibility in CC mice remains unexplored, we assessed tumour incidence and spectrum.DesignWe monitored 293 mice from 18 CC strains for tumour development. Genetic association analysis and RNA sequencing were used to identify susceptibility loci and candidate genes. We analysed genomes of patients with gastric cancer to evaluate the relevance of genes identified in the CC mouse model and measured the expression levels of ISG15 by immunohistochemical staining using a gastric adenocarcinoma tissue microarray. Association of gene expression with overall survival (OS) was assessed by Kaplan-Meier analysis.ResultsCC mice displayed a wide range in the incidence and types of spontaneous tumours. More than 40% of CC036 mice developed gastric tumours within 1 year. Genetic association analysis identified Nfκb1 as a candidate susceptibility gene, while RNA sequencing analysis of non-tumour gastric tissues from CC036 mice showed significantly higher expression of inflammatory response genes. In human gastric cancers, the majority of human orthologues of the 166 mouse genes were preferentially altered by amplification or deletion and were significantly associated with OS. Higher expression of the CC036 inflammatory response gene signature is associated with poor OS. Finally, ISG15 protein is elevated in gastric adenocarcinomas and correlated with shortened patient OS.ConclusionsCC strains exhibit tremendous variation in tumour susceptibility, and we present CC036 as a spontaneous laboratory mouse model for studying human gastric tumourigenesis.

scholarly journals VikNGS: A C ++ Variant Integration Kit for Next Generation Sequencing Association Analysis

2019 ◽  
Author(s):  
Zeynep Baskurt ◽  
Scott Mastromatteo ◽  
Jiafen Gong ◽  
Richard F Wintle ◽  
Stephen W Scherer ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Genetic Association ◽  
Association Analysis ◽  
Supplementary Information ◽  
Next Generation Sequencing Data ◽  
Data Sets ◽  
Next Generation ◽  
Sequencing Data ◽  
Combining Data ◽  
Generation Sequencing

Abstract Integration of next generation sequencing data (NGS) across different research studies can improve the power of genetic association testing by increasing sample size and can obviate the need for sequencing controls. If differential genotype uncertainty across studies is not accounted for, combining data sets can produce spurious association results. We developed the Variant Integration Kit for NGS (VikNGS), a fast cross-platform software package, to enable aggregation of several data sets for rare and common variant genetic association analysis of quantitative and binary traits with covariate adjustment. VikNGS also includes a graphical user interface, power simulation functionality and data visualization tools. Availability The VikNGS package can be downloaded at http://www.tcag.ca/tools/index.html. Supplementary information Supplementary data are available at Bioinformatics online.

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