Abstract
The pathogenesis of metabolic syndrome, i.e. of each of its components, is complex and has not been entirely elucidated. As a result, it is very difficult to establish a definition of which clinical factors are the most important determinants of its development. The objective of this review is to describe Brazilian scientific research investigating associations between the metabolic syndrome and genetic factors. We selected fifteen studies that met the inclusion and exclusion criteria. Our analysis revealed that there is a modest volume of Brazilian studies investigating relationships between genes, their polymorphic variants and the metabolic syndrome and its risk factors. Therefore, more studies are needed to better understand the biological roles played by genetic polymorphisms and their relationships with metabolic syndrome or its risk factors.
Highlights
Metabolic syndrome (MS) is used as a clinical tool for identifying patients with metabolic risk of cardiovascular diseases.[1]
All of them were conducted with the general objective of investigating relationships between genes and their polymorphic variations and MS and its risk factors
The genes investigated to test for associations were NOS, MMP-2, IL6R, VDR, UCP1, ADRB3, ApoE, IRS-1, PPARG, APOA5, leptin gene (LEP), leptin receptor gene (LEPR), NR3C1, glucocorticoid receptor (GR), IL1B, IL2, IL4, IL8, IL10, IFNγ, TNFa and ACE
Summary
Metabolic syndrome (MS) is used as a clinical tool for identifying patients with metabolic risk of cardiovascular diseases.[1]. There is consensus on the principal components of MS that are associated with increased cardiovascular morbidity and mortality: excess weight, elevated arterial blood pressure, and disorders of sugar and lipid metabolism.[2,4,5,6,7]. Since it is a multifactorial disorder, both the genetic factor and the environmental factor are important to understanding the interactions between all of the components of risk of development of MS. Many different gene loci are involved in expression of the components of energy metabolism, which makes it a very complex task to determine the influence of gene-environment and gene-gene interactions on each of the different cardiovascular risk factors.[8]
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