GENOMIZER: an integrated analysis system for genome-wide association data

2006 ◽  
Vol 27 (6) ◽  
pp. 583-588 ◽  
Author(s):  
Andre Franke ◽  
Andreas Wollstein ◽  
Markus Teuber ◽  
Michael Wittig ◽  
Tim Lu ◽  
...  
Keyword(s):  
Genome Wide Association ◽  
Integrated Analysis ◽  
Genome Wide ◽  
Association Data ◽  
Analysis System

scholarly journals A Genome-Wide Association Study for Hypertensive Kidney Disease in Korean Men

Genes ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 751
Author(s):  
Hye-Rim Kim ◽  
Hyun-Seok Jin ◽  
Yong-Bin Eom
Keyword(s):  
Blood Pressure ◽  
Kidney Disease ◽  
Association Study ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Integrated Analysis ◽  
Eqtl Analysis ◽  
Strong Linkage Disequilibrium ◽  
Genome Wide ◽  
A Genome

Hypertension is one of the major risk factors for chronic kidney disease (CKD), and the coexistence of hypertension and CKD increases morbidity and mortality. Although many genetic factors have been identified separately for hypertension and kidney disease, studies specifically focused on hypertensive kidney disease (HKD) have been rare. Therefore, this study aimed to identify loci or genes associated with HKD. A genome-wide association study (GWAS) was conducted using two Korean cohorts, the Health Examinee (HEXA) and Korean Association REsource (KARE). Consequently, 19 single nucleotide polymorphisms (SNPs) were found to be significantly associated with HKD in the discovery and replication phases (p < 5 × 10−8, p < 0.05, respectively). We further analyzed HKD-related traits such as the estimated glomerular filtration rate (eGFR), creatinine, blood urea nitrogen (BUN), systolic blood pressure (SBP) and diastolic blood pressure (DBP) at the 14q21.2 locus, which showed a strong linkage disequilibrium (LD). Expression quantitative trait loci (eQTL) analysis was also performed to determine whether HKD-related SNPs affect gene expression changes in glomerular and arterial tissues. The results suggested that the FANCM gene may affect the development of HKD through an integrated analysis of eQTL and GWAS and was the most significantly associated candidate gene. Taken together, this study indicated that the FANCM gene is involved in the pathogenesis of HKD. Additionally, our results will be useful in prioritizing other genes for further experiments.

scholarly journals Meta-Analyses of Genome-Wide Association Data Hold New Promise for Addiction Genetics

2016 ◽  
Vol 77 (5) ◽  
pp. 676-680 ◽  
Author(s):  
Arpana Agrawal ◽  
Howard J. Edenberg ◽  
Joel Gelernter
Keyword(s):  
Genome Wide Association ◽  
Genome Wide ◽  
Association Data ◽  
Meta Analyses

scholarly journals Network-based Analysis of Genome Wide Association Data Provides Novel Candidate Genes for Lipid and Lipoprotein Traits

2013 ◽  
Vol 12 (11) ◽  
pp. 3398-3408 ◽  
Author(s):  
Amitabh Sharma ◽  
Natali Gulbahce ◽  
Samuel J. Pevzner ◽  
Jörg Menche ◽  
Claes Ladenvall ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Genome Wide Association ◽  
Genome Wide ◽  
Association Data

scholarly journals A gene-based recessive diplotype exome scan discovers FGF6, a novel hepcidin-regulating iron-metabolism gene

Blood ◽  
2019 ◽  
Vol 133 (17) ◽  
pp. 1888-1898 ◽  
Author(s):  
Shicheng Guo ◽  
Shuai Jiang ◽  
Narendranath Epperla ◽  
Yanyun Ma ◽  
Mehdi Maadooliat ◽  
...  
Keyword(s):  
Growth Factor ◽  
Fibroblast Growth Factor ◽  
Iron Metabolism ◽  
Iron Homeostasis ◽  
Genome Wide Association Study ◽  
Strong Association ◽  
Genome Wide Association ◽  
Fibroblast Growth ◽  
Genome Wide ◽  
Association Data

Abstract Standard analyses applied to genome-wide association data are well designed to detect additive effects of moderate strength. However, the power for standard genome-wide association study (GWAS) analyses to identify effects from recessive diplotypes is not typically high. We proposed and conducted a gene-based compound heterozygosity test to reveal additional genes underlying complex diseases. With this approach applied to iron overload, a strong association signal was identified between the fibroblast growth factor–encoding gene, FGF6, and hemochromatosis in the central Wisconsin population. Functional validation showed that fibroblast growth factor 6 protein (FGF-6) regulates iron homeostasis and induces transcriptional regulation of hepcidin. Moreover, specific identified FGF6 variants differentially impact iron metabolism. In addition, FGF6 downregulation correlated with iron-metabolism dysfunction in systemic sclerosis and cancer cells. Using the recessive diplotype approach revealed a novel susceptibility hemochromatosis gene and has extended our understanding of the mechanisms involved in iron metabolism.

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