Literature DB >> 17967522

Genome-wide association studies in aging-related processes such as diabetes mellitus, atherosclerosis and cancer.

Florian Kronenberg1.   

Abstract

Recent technological developments allow to genotype several hundreds of thousands of genetic variants in a single person in one step. This enables genome-wide association studies (GWAS) by genotyping a large number of patients with diseases of interest and controls at reasonable costs. Compared to a hypothesis-driven candidate gene approach the hypothesis-free GWAS can identify new susceptibility genes without making any a priori biological assumptions. They permit to identify genes involved in pathways which until now were unknown to be involved in a certain phenotype. GWAS are therefore a new and very powerful tool to identify genetic contributors to aging-related phenotypes. This paper provides a short overview about design and methods of GWAS and reviews recent advances in the identification of susceptibility genes for type 2 diabetes mellitus, atherosclerosis and cancer using GWAS.

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Year:  2007        PMID: 17967522     DOI: 10.1016/j.exger.2007.09.005

Source DB:  PubMed          Journal:  Exp Gerontol        ISSN: 0531-5565            Impact factor:   4.032


  15 in total

1.  Assessment of Subtle Changes in Diabetes-Associated Arteriosclerosis using Photoplethysmographic Pulse Wave from Index Finger.

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Journal:  J Med Syst       Date:  2018-01-24       Impact factor: 4.460

2.  Genome-wide gene-set analysis for identification of pathways associated with alcohol dependence.

Authors:  Joanna M Biernacka; Jennifer Geske; Gregory D Jenkins; Colin Colby; David N Rider; Victor M Karpyak; Doo-Sup Choi; Brooke L Fridley
Journal:  Int J Neuropsychopharmacol       Date:  2012-05-02       Impact factor: 5.176

3.  Adiponectin gene polymorphisms in Egyptian type 2 diabetes mellitus patients with and without diabetic nephropathy.

Authors:  Amal S El-Shal; Haidy E Zidan; Nearmeen M Rashad
Journal:  Mol Biol Rep       Date:  2014-01-28       Impact factor: 2.316

4.  Domain altering SNPs in the human proteome and their impact on signaling pathways.

Authors:  Yichuan Liu; Aydin Tozeren
Journal:  PLoS One       Date:  2010-09-23       Impact factor: 3.240

Review 5.  Emerging risk factors and markers of chronic kidney disease progression.

Authors:  Florian Kronenberg
Journal:  Nat Rev Nephrol       Date:  2009-12       Impact factor: 28.314

Review 6.  Genetic-epidemiological evidence on genes associated with HDL cholesterol levels: a systematic in-depth review.

Authors:  Eva Boes; Stefan Coassin; Barbara Kollerits; Iris M Heid; Florian Kronenberg
Journal:  Exp Gerontol       Date:  2008-11-17       Impact factor: 4.032

Review 7.  Gene-environment interaction and children's health and development.

Authors:  Robert O Wright; David Christiani
Journal:  Curr Opin Pediatr       Date:  2010-04       Impact factor: 2.856

Review 8.  The role of vascular endothelial growth factor SNPs as predictive and prognostic markers for major solid tumors.

Authors:  Lokesh Jain; Craig A Vargo; Romano Danesi; Tristan M Sissung; Douglas K Price; David Venzon; Jürgen Venitz; William D Figg
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Review 9.  [Genomwide association studies on obesity: what can we learn from these studies].

Authors:  Florian Kronenberg; Bernhard Paulweber; Claudia Lamina
Journal:  Wien Med Wochenschr       Date:  2016-01-21

10.  Polymorphisms in the p63 and p73 genes are associated with ovarian cancer risk and clinicopathological variables.

Authors:  Xiao Guan; Ning Zhang; Yongshuo Yin; Beihua Kong; Qifeng Yang; Zhiyan Han; Xingsheng Yang
Journal:  J Exp Clin Cancer Res       Date:  2012-10-24
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