Network graph analysis of gene-gene interactions in genome-wide association study data

The association of TGFB1 genetic polymorphisms with high myopia: a systematic review and meta-analysis

OBJECTIVE

The TGFB1 gene is among the most studied genes in high myopia due to its role in scleral remodeling. But reported findings of association on TGFB1 and high myopia are inconsistent. This present study is to evaluate the association of TGFB1 polymorphisms and high myopia.

METHODS

A comprehensive literature search was conducted on studies published up to April 5, 2015. Summary odds ratios (ORs) and 95% confidence intervals were analyzed. Heterogeneity across studies was evaluated by Cochran Q statistic test and the I(2) index. Sensitivity analyses were conducted by the approach of one-study remove to assess the influence of single study on the combined effect.

RESULTS

Eight studies were included in this study for meta-analysis. Rs1982073 was associated with high myopia in dominant model (OR=1.64; 95% CI=1.04~2.58; P<0.05), heterozygous model (OR=1.54; 95% CI=1.02~2.33; P<0.05), homozygous model (OR=1.90; 95% CI=1.01~3.55; P=0.05) and allelic model (OR=1.36; 95% CI=1.01~1.84; P=0.05). However, there was no statistical significance when Bonferroni correction was considered. Rs4803455 was associated with high myopia in recessive model (OR=0.40; 95% CI=0.25~0.64; P<0.01) and homozygous model (OR=0.42; 95% CI=0.26~0.68; P<0.01). Rs1800469 was associated with high myopia in allelic model (OR=0.78; 95% CI=0.64~0.96; P<0.05). And the associations can withstand Bonferroni correction in models mentioned above when referring to rs4803455 (P<0.01) and rs1800469 (P<0.05).

CONCLUSIONS

Meta-analysis of existing data revealed a suggestive association of TGFB1 rs1982073 and rs4803455 with high myopia.

Differential Associations between CDH13 Genotypes, Adiponectin Levels, and Circulating Levels of Cellular Adhesive Molecules

CDH13 gene variants with lower adiponectin levels are paradoxically associated with a more favorable metabolic profile. We investigated the statistical association between CDH13 locus variants and adiponectin levels by examining 12 circulating inflammation marker levels and adiposity status in 530 Han Chinese people in Taiwan. After adjustments for clinical covariates, adiponectin levels were positively associated with soluble vascular cell adhesion molecule-1 (sVCAM1) levels and negatively associated with adiposity status and levels of C-reactive protein (CRP), soluble E-selectin (sE-selectin), and soluble intercellular adhesion molecule-1 (sICAM1). In addition, minor alleles of the CDH13 rs12051272 polymorphism were found to have lower adiponectin levels and higher CRP, sE-selectin, sICAM1, and sVCAM1 levels as well as higher body mass indices and waist circumferences in participants (all P < 0.05). In a subgroup analysis stratified by sex, significant associations between CDH13 genotypes and sE-selectin levels occurred only in men (P = 3.9 × 10⁻⁴ and interaction P = 0.005). CDH13 locus variants and adiponectin levels are associated with circulating levels of cellular adhesion molecules and adiposity status in a differential manner that interacts with sex. These results provide further evidence for the crucial role of adiponectin levels and CDH13 gene variants in immune-mediated and inflammatory diseases.

Epistatic effects of multiple receptor genes on pathophysiology of asthma - its limits and potential for clinical application

To date, genome-wide association studies (GWAS) permit a comprehensive scan of the genome in an unbiased manner, with high sensitivity, and thereby have the potential to identify candidate genes for the prevalence or development of multifactorial diseases such as bronchial asthma. However, most studies have only managed to explain a small additional percentage of hereditability estimates, and often fail to show consistent results among studies despite large sample sizes. Epistasis is defined as the interaction between multiple different genes affecting phenotypes. By applying epistatic analysis to clinical genetic research, we can analyze interactions among more than 2 molecules (genes) considering the whole system of the human body, illuminating dynamic molecular mechanisms. An increasing number of genetic studies have investigated epistatic effects on the risk for development of asthma. The present review highlights a concept of epistasis to overcome traditional genetic studies in humans and provides an update of evidence on epistatic effects on asthma. Furthermore, we review concerns regarding recent trends in epistatic analyses from the perspective of clinical physicians. These concerns include biological plausibility of genes identified by computational statistics, and definition of the diagnostic label of 'physician-diagnosed asthma'. In terms of these issues, further application of epistatic analysis will prompt identification of susceptibility of diseases and lead to the development of a new generation of pharmacological strategies to treat asthma.

What is next after the genes for autoimmunity?

Clinical pathologies draw us to envisage disease as either an independent entity or a diverse set of traits governed by common physiopathological mechanisms, prompted by environmental assaults throughout life. Autoimmune diseases are not an exception, given they represent a diverse collection of diseases in terms of their demographic profile and primary clinical manifestations. Although they are pleiotropic outcomes of non-specific disease genes underlying similar immunogenetic mechanisms, research generally focuses on a single disease. Drastic technologic advances are leading research to organize clinical genomic multidisciplinary approaches to decipher the nature of human biological systems. Once the currently costly omic-based technologies become universally accessible, the way will be paved for a cleaner picture to risk quantification, prevention, prognosis and diagnosis, allowing us to clearly define better phenotypes always ensuring the integrity of the individuals studied. However, making accurate predictions for most autoimmune diseases is an ambitious challenge, since the understanding of these pathologies is far from complete. Herein, some pitfalls and challenges of the genetics of autoimmune diseases are reviewed, and an approximation to the future of research in this field is presented.