The term metabolic syndrome (occasionally called insulin resistance syndrome) refers to a constellation of clinical findings including obesity, hypertension, hyperlipidemia, and insulin resistance, with increased risk for type 2 diabetes and cardiovascular disease. It has also been linked with chronic kidney disease, liver disease with steatosis, fibrosis, and cirrhosis, and cognitive decline and dementia. Despite recent controversy regarding the concept of a metabolic syndrome, the International Diabetes Federation (IDF) developed a new unifying worldwide definition building upon the World Health Organization (WHO) and ATP III definitions, as will be discussed in later chapters (82).
On the basis of the IDF definition, almost 40% of US adults are classified as having the metabolic syndrome (83) . Although environmental factors such as smoking, low economic status, high intake of carbohydrates, no alcohol consumption, and physical inactivity can play a role in the development of the metabolic syndrome, a series of evidence indicates that there is also a genetic component involved. Specifically the metabolic syndrome has different prevalence between men and women, and among ethnic groups, as well as different concordance rates between monozygotic twins. Furthermore, there is increased incidence in individuals with a parental history of metabolic syndrome, and a general familial clustering of the metabolic syndrome and its components (83-91).
Ongoing work on spontaneous and engineered animal models has revealed that several genetic loci are associated with metabolic syndrome components in different rodent models (92). Examples of metabolic syndrome rodent models include the spontaneous hypertensive rat (SHR), the transgenic SHR overexpressing a dominant-positive form of the human sterol regulatory element binding transcription factor 1 (SREBP-1), the SHR/
NDmcr-cp rat, the polydactylous rat strain (PD/cub), the obese Zucker rats (OZR), the New Zealand obese (NZO), the Wistar Ottawa Karlsburg W rats, as well as congenic, consomic, and double-introgressed strains (93-100).
Linkage analyses in patients with the metabolic syndrome have aimed at identifying loci with pleiotropic effects on multiple aspects of the syndrome. Several different linkage analysis approaches have been applied in the study of the metabolic syndrome, such as principal components or principal factor analysis, multivariate analysis, metabolic syndrome score from combined residuals and the structural equation model (101). One of the most consistent findings was the linkage to chromosome 1q, while multiple phenotypes linked to this region indicate that it likely harbors a gene with pleiotropic effects on measure of glucose, lipids, hypertension, and adipocity, or multiple genes that contribute to each one of these features (102-106). Other consistent loci implicated in the development of the metabolic syndrome include chromosomes 2p, 2q, 3p, 6q, 7q, 9q, and 15q (103,106-111).
Many of these loci have also been linked to individual components of the metabolic syndrome. For example, chromosome 2p has been linked to serum triglycerides, systolic blood pressure, obesity, body fat percentage, and HDL (111-113), while chromosome 7q has been linked to systolic blood pressure, triglyceride-HDL-C ratio, fasting glucose, insulin, and insulin resistance (114-116).
Despite the wide use and important findings that have emerged from linkage analysis, this method presents with a number of limitations that need to be carefully considered and addressed in the interpretation of current findings and the design of future studies. Some of the common obstacles in this type of studies are the inadequate statistical power, the multiple hypothesis testing, the population stratification, the publication bias and phenotypic variation (117). The identification of true genetic associations in common multifactorial conditions, such as the metabolic syndrome, requires large studies consisting of thousands of subjects. This need is further accentuated by the large number of implicated genetic loci and their potentially small contribution to the phenotype when individually considered.
In parallel to linkage and association studies, several studies have evaluated the contribution of specific candidate genes to the metabolic syndrome pathogenesis. These candidate genes have been selected based on their biological function and/or previous associations to any of the phenotypic aspects of the syndrome. However, the large number of metabolic pathways implicated in the pathogenesis of the metabolic syndrome (including insulin signaling, glucose homeostasis, lipoprotein metabolism, adipogenesis, inflammation, coagulation, etc.) renders this search a highly challenging task that has yielded a relatively limited success. There are many examples of genes directly or indirectly implicated in the development of the metabolic syndrome or specific clinical features related to it, but an equal number of negative studies have also been published (118).
The peroxisome proliferator-activated receptor y (PPARg) is one of the strong candidates for conferring susceptibility to the metabolic syndrome because of its involvement in adipocyte differentiation, fatty acid metabolism, insulin sensitivity, and glucose homeostasis (119-121). Despite some inconsistencies in the PPARy association studies, the overall evidence seems to suggest that PPARg polymorphisms can increase the risk for developing the metabolic syndrome (122-124). Direct correlations to the metabolic syndrome have also been described for genetic variants of the ^-adrenergic receptor (ADRfi-3)), nitric oxide synthase 3 (NOS3), angiotensin I converting enzyme (ACE), beacon (BEACON), lamin A/C (LMNA), interleukin-6 (IL-6), interleukin-p (IL1-b), and protein tyrosine phosphatase nonreceptor type 1 (PTPN1) genes (122,125-131). Interestingly, PPARgand IL1-ft polymorphisms have been implicated in gene-environment interactions (see Sect. 4).
Fatty acid binding protein 2 (FABP2) and apolipoprotein C-III (APOC3) polymorphisms have been directly associated with increased risk for dyslipidemia and the metabolic syndrome in Asian-Indians (132). Other examples include a number of lipid-sensitive transcription factors (nuclear receptor subfamily 1, member 4 (FXR), nuclear receptor subfamily 1, member 3 (LXR-a), retinoid X receptor a (RXR-a), PPAR-a, PPAR-ô, peroxisome proliferator-activated receptor (PGC1-a), PCG1-fi, sterol regulatory element binding transcription factor 1 (SREBP-1c)) that have been implicated in the development of dyslipidemia, one of the very early features of the metabolic syndrome (124), Since lipoprotein metabolism plays a central role in the metabolic syndrome, several genes related to the former are also good candidates for the latter. These include variants of scavenger receptor class B, member 1 (SCARB1), ATP-binding cassette subfamily A, member 1 (ABCA1), cholesteryl ester transfer protein (CETP), lipoprotein lipase (LPL), lipase (LIPG), pancreatic lipase (PNLIP), apolipoprotein A-V (APOA5), and the apolipoprotein gene clusters ApoA1/C3/A4/A5and ApoE/C1/C2that affect HDL-cholesterol and triaglyceride metabolism (133-138).
Was this article helpful?