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Even when significant and replicated associations are combined across studies, only a small percentage (< 2%) of the variance in heritable disorders for many MetS-related traits are explained by genetic markers (Zhang, Ma, Brismar, Efendic, & Gu, 2009). Equally important, the incremental predictive performance of genetic markers over traditional cardiovascular and other risk factors remains uncertain (Ioannidis, 2009). While there may be a number of reasons to explain this ��missing heritability�� (Maher, 2008; Zhang et al., 2009), an inherent limitation of Pramipexole GWA studies is that the effect size (attributable risk for disease phenotype) for each genetic variant that is positively associated with the disease is often very small (Mechanic et al., 2011). Another problem with most GWA studies available today is that available genotyping platforms typically represent only relatively common SNPs derived from a Caucasian reference sequence. But it has been shown that some genetic markers may only have relevance in certain racial or ethnic populations (Yancy, 2008). To address the issue of ethnic ancestry in diverse populations, admixture mapping should be utilized to determine percent ancestry. This method enables researchers to associate the degree of ancestry with disease phenotype, such as hypertension in African Americans. If admixture mapping is not used, genetic associations can be confounded by variances in markers that are only appropriate www.selleckchem.com for certain ethnic and racial groups. The future for genomics of MetS may lie in systems-based approaches (i.e., expression arrays, mass spectrometry, bioinformatics) to address EX 527 solubility dmso input from hundreds of genes and environmental factors. The interactions of the components are possibly more important than the individual components themselves (Lusis, Attie, & Reue, 2008). As direct sequencing becomes more affordable, analysis of rare variants may play an increasing role in the understanding the genomics of MetS (Fung, Zhang, Zhang, Rao, & O��Connor, 2011). Other sequence changes (e.g., gene copy number variations) and nonsequence changes (e.g., epigenetics, or heritable changes to the genome that alter gene expression without alterations in sequence) will be increasingly studied for their association with MetS disease traits. For clinical practice the goal of genomic health care is to integrate clinical and biological data for improving patient outcomes. Clinicians should be aware of the genetic tools that are available to improve their understanding and development of patient treatment plans based on screening for complex disorders such as MetS. However, clinicians need to have realistic expectations in this area of emerging research. There are still many potential benefits and limitations of genetic-based assessment, treatment, and management for many common disorders (Calzone et al., 2010).
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