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Metabolic syndrome: from the genetics to the pathophysiology

Published on Apr 1, 2011in Current Osteoporosis Reports
· DOI :10.1007/s11906-010-0164-9
Silvia Sookoian37
Estimated H-index: 37
(UBA: University of Buenos Aires),
Carlos J. Pirola41
Estimated H-index: 41
(UBA: University of Buenos Aires)
Abstract
The metabolic syndrome (MS) constitutes a combination of underlying risk factors for an adverse outcome, cardiovascular disease. Thus, the clinical behavior of the MS can be regarded as a whole. Nevertheless, from a pathogenic point of view, understanding of the underlying mechanisms of each MS intermediate phenotype is far beyond their understanding as an integrative process. Systems biology introduces a new concept for revealing the pathogenesis of human disorders and suggests the presence of common physiologic processes and molecular networks influencing the risk of a disease. This paper shows a model of this concept to explain the genetic determinants of MS-associated phenotypes. Based on the hypothesis that common physiologic processes and molecular networks may influence the risk of MS disease components, we propose two systems-biology approaches: a gene enrichment analysis and the use of a protein-protein interaction network. Our results show that a network driven by many members of the nuclear receptor superfamily of proteins, including retinoid X receptor and farnesoid X receptor (FXR), may be implicated in the pathogenesis of the MS by its interactions at multiple levels of complexity with genes associated with metabolism, cell differentiation, and oxidative stress. In addition, we review two alternative genetic mechanisms that are gaining acceptance in the physiopathology of the MS: the regulation of transcriptional and post-transcriptional gene expression by microRNAs and epigenetic modifications such as DNA methylation.
  • References (37)
  • Citations (54)
References37
Newest
#1Silvia Sookoian (UBA: University of Buenos Aires)H-Index: 37
#2Tomas Fernández Gianotti (UBA: University of Buenos Aires)H-Index: 23
Last.Carlos J. Pirola (UBA: University of Buenos Aires)H-Index: 41
view all 4 authors...
#1David Warde-Farley (U of T: University of Toronto)H-Index: 19
#2Sylva L. Donaldson (U of T: University of Toronto)H-Index: 9
Last.Quaid Morris (U of T: University of Toronto)H-Index: 47
view all 17 authors...
#1Katey J. Rayner (NYU: New York University)H-Index: 28
#2Yajaira Suárez (NYU: New York University)H-Index: 36
Last.Carlos Fernández-Hernando (NYU: New York University)H-Index: 46
view all 9 authors...
#1Carolina Gemma (UBA: University of Buenos Aires)H-Index: 19
#2Silvia Sookoian (UBA: University of Buenos Aires)H-Index: 37
Last.Carlos J. Pirola (UBA: University of Buenos Aires)H-Index: 41
view all 7 authors...
#1Silvia Sookoian (UBA: University of Buenos Aires)H-Index: 37
#2Carolina Gemma (UBA: University of Buenos Aires)H-Index: 19
Last.Carlos J. Pirola (UBA: University of Buenos Aires)H-Index: 41
view all 3 authors...
Cited By54
Newest
#1Yuxiang Huang (Southern Medical University)H-Index: 1
#2Yuxiang Yan (Capital Medical University)H-Index: 1
Last.Yongqiang Li (Southern Medical University)H-Index: 9
view all 7 authors...
#1Masoumeh Jabbari (Tabriz University of Medical Sciences)H-Index: 2
#2Sorayya Kheirouri (Tabriz University of Medical Sciences)H-Index: 7
Last.Mohammad Alizadeh (Tabriz University of Medical Sciences)H-Index: 11
view all 3 authors...
#1Philip J. Norris (University of Southern Queensland)H-Index: 38
#2Nicholas Ralph (University of Southern Queensland)H-Index: 7
Last.Clint Moloney (University of Southern Queensland)H-Index: 6
view all 3 authors...
#1K. Lippert (Austrian Institute of Technology)H-Index: 1
#2Lyudmyla KedenkoH-Index: 14
Last.E. Hackl (Austrian Institute of Technology)H-Index: 1
view all 9 authors...
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