Genetic Risk Factors Related to Coronary Artery Disease and Role of Transforming Growth Factor Beta 1 Polymorphisms.

Coronary artery disease (CAD) is one of the leading causes of mortality globally and has long been known to be heritable; however, the specific genetic factors involved have yet to be identified. Recent advances have started to unravel the genetic architecture of this disease and set high expectations about the future use of novel susceptibility variants for its prevention, diagnosis, and treatment. In the past decade, there has been major progress in this area. New tools, like common variant association studies, genome-wide association studies, meta-analyses, and genetic risk scores, allow a better understanding of the genetic risk factors driving CAD. In recent years, researchers have conducted further studies that confirmed the role of numerous genetic factors in the development of CAD. These include genes that affect lipid and carbohydrate metabolism, regulate the function of the endothelium and vascular smooth muscles, influence the coagulation system, or affect the immune system. Many CAD-associated single-nucleotide polymorphisms have been identified, although many of their functions are largely unknown. The inflammatory process that occurs in the coronary vessels is very important in the development of CAD. One important mediator of inflammation is TGFß1. TGFß1 plays an important role in the processes leading to CAD, such as by stimulating macrophage and fibroblast chemotaxis, as well as increasing extracellular matrix synthesis. This review discusses the genetic risk factors related to the development of CAD, with a particular focus on polymorphisms of the transforming growth factor ß (TGFß) gene and its receptor.

CD28, CTLA-4 and CCL5 gene polymorphisms in patients with rheumatoid arthritis.

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by joint destruction caused by infiltrating leukocytes including T cells. An important role in T cell co-stimulation is played by the CD28, as a stimulatory signal transducer and the inhibitory CTLA-4. CCL5 is produced by circulating T cells and plays an active role in the chemotactic activity of T cells in RA. The aim of this study was to examine the associations between polymorphisms within CD28, CTLA-4, and CCL5 genes and RA. We examined 422 patients (340 female, 82 male, mean age 57.5 ± 12.5 years) with rheumatoid arthritis and 338 healthy subjects (261 female, 77 male). Disease activity was determined on the basis of DAS28 score. The patients with DAS28 of ≤2.5 were classified as subjects in remission of disease symptoms; the patients who had DAS28 of >2.5 were classified as subjects with active form of RA. There were no statistically significant differences in the distribution of studied genotypes and alleles between RA patients and the control group. A statistically significant difference was observed in the distribution of CTLA4 exon 1 +49A>G rs231775 genotypes between patients with DAS28 ≤ 2.5 and DAS28 > 2.5 where the increased frequency of AA genotype among patients with DAS28 > 2.5 was revealed (OR 1.55; 95% CI 1.01-2.38). The results of our study suggest no significant association between CD28 rs1980422, CCL5 rs2107538, CTLA-4 exon 1 +49A>G rs231775 and rs3087243 gene polymorphisms and RA in the Polish population. Our results indicate a possible association between CTLA-4 exon 1 +49A>G rs231775 gene polymorphism and RA activity.

Diagnostic usefulness of the Risk of Ovarian Malignancy Algorithm using the electrochemiluminescence immunoassay for HE4 and the chemiluminescence microparticle immunoassay for CA125.

The present study aimed to investigate the usefulness of the Risk of Ovarian Malignancy Algorithm (ROMA) in the preoperative stratification of patients with ovarian tumors using a novel combination of laboratory tests. The study group (n=619) consisted of 354 premenopausal and 265 postmenopausal patients. The levels of carbohydrate antigen 125 (CA125) and human epididymis protein 4 (HE4) were determined, and ROMA calculations were performed for each pre- and postmenopausal patient. HE4 levels were determined using an electrochemiluminescence immunoassay, while CA125 levels were determined by a chemiluminescence microparticle immunoassay. A contingency table was applied to calculate the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). Receiver operating characteristic curves were also constructed, and areas under the curves (AUCs) were compared between the marker determinations and ROMA algorithms. In terms of distinguishing between ovarian cancer and benign disease, the sensitivity of ROMA was 88.3%, specificity was 88.2%, PPV was 75.3% and NPV was 94.9% among all patients. The respective parameters were 71.1, 90.1, 48.2 and 91.1% in premenopausal patients and 93.6, 82.9, 86.6 and 91.6% in postmenopausal patients. The AUC value for the ROMA algorithm was 0.926 for the ovarian cancer vs. benign groups in all patients, 0.813 in premenopausal patients and 0.939 in postmenopausal patients. The respective AUC values were 0.911, 0.879 and 0.934 for CA125; and 0.879, 0.783 and 0.889 for HE4. In this combination, the ROMA algorithm is characterized by an extremely high sensitivity of prediction of ovarian cancer in women with pelvic masses, and may constitute a precise tool with which to support the qualification of patients to appropriate surgical procedures. The ROMA may be useful in diagnosing ovarian endometrial changes in young patients.