Literature DB >> 23102864

Metabolomics platforms for genome wide association studies--linking the genome to the metabolome.

Jerzy Adamski1, Karsten Suhre.   

Abstract

Genome-wide association studies (GWAS) reveal links between genetic variance and predisposition to disease. With the advent of modern 'omics-technologies', GWAS can now identify the genetic factors that influence intermediate traits on pathways to disease, such as blood concentrations of carbohydrates, lipids, amino acids, and secondary metabolites, hormones and signal molecules. At the example of recent GWAS with metabolic traits (mGWAS) we review the high-throughput screening approaches that are available to further advance the field.
Copyright © 2012 Elsevier Ltd. All rights reserved.

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Year:  2012        PMID: 23102864     DOI: 10.1016/j.copbio.2012.10.003

Source DB:  PubMed          Journal:  Curr Opin Biotechnol        ISSN: 0958-1669            Impact factor:   9.740


  34 in total

1.  Plasma metabolomic profiles enhance precision medicine for volunteers of normal health.

Authors:  Lining Guo; Michael V Milburn; John A Ryals; Shaun C Lonergan; Matthew W Mitchell; Jacob E Wulff; Danny C Alexander; Anne M Evans; Brandi Bridgewater; Luke Miller; Manuel L Gonzalez-Garay; C Thomas Caskey
Journal:  Proc Natl Acad Sci U S A       Date:  2015-08-17       Impact factor: 11.205

2.  Metabolomic analysis to define and compare the effects of PAHs and oxygenated PAHs in developing zebrafish.

Authors:  Marc R Elie; Jaewoo Choi; Yasmeen M Nkrumah-Elie; Gregory D Gonnerman; Jan F Stevens; Robert L Tanguay
Journal:  Environ Res       Date:  2015-05-22       Impact factor: 6.498

Review 3.  Metabolomics in the studies of islet autoimmunity and type 1 diabetes.

Authors:  Matej Oresic
Journal:  Rev Diabet Stud       Date:  2012-12-28

Review 4.  Metabolomics and diabetes: analytical and computational approaches.

Authors:  Kelli M Sas; Alla Karnovsky; George Michailidis; Subramaniam Pennathur
Journal:  Diabetes       Date:  2015-03       Impact factor: 9.461

5.  Tear metabolite changes in keratoconus.

Authors:  D Karamichos; J D Zieske; H Sejersen; A Sarker-Nag; John M Asara; J Hjortdal
Journal:  Exp Eye Res       Date:  2015-01-09       Impact factor: 3.467

Review 6.  Metabolomics in rheumatic diseases: desperately seeking biomarkers.

Authors:  Monica Guma; Stefano Tiziani; Gary S Firestein
Journal:  Nat Rev Rheumatol       Date:  2016-03-03       Impact factor: 20.543

Review 7.  A Systems-Level View of Renal Metabolomics.

Authors:  Eugene P Rhee
Journal:  Semin Nephrol       Date:  2018-03       Impact factor: 5.299

Review 8.  Omics technologies and the study of human ageing.

Authors:  Ana M Valdes; Daniel Glass; Tim D Spector
Journal:  Nat Rev Genet       Date:  2013-08-13       Impact factor: 53.242

9.  Metabogenomics reveals four candidate regions involved in the pathophysiology of Equine Metabolic Syndrome.

Authors:  Laura Patterson Rosa; Martha F Mallicote; Maureen T Long; Samantha A Brooks
Journal:  Mol Cell Probes       Date:  2020-07-10       Impact factor: 2.365

10.  ProGeM: a framework for the prioritization of candidate causal genes at molecular quantitative trait loci.

Authors:  David Stacey; Eric B Fauman; Daniel Ziemek; Benjamin B Sun; Eric L Harshfield; Angela M Wood; Adam S Butterworth; Karsten Suhre; Dirk S Paul
Journal:  Nucleic Acids Res       Date:  2019-01-10       Impact factor: 16.971

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