Association of genetic variants with myocardial infarction in Japanese individuals with or without metabolic syndrome

Analysis of Effect of Schisandra in the Treatment of Myocardial Infarction Based on Three-Mode Gene Ontology Network

Schisandra chinensis is a commonly used traditional Chinese medicine, which has been widely used in the treatment of acute myocardial infarction in China. However, it has been difficult to systematically clarify the major pharmacological effect of Schisandra, due to its multi-component complex mechanism. In order to solve this problem, a comprehensive network analysis method was established based-on “component–gene ontology–effect” interactions. Through the network analysis, reduction of cardiac preload and myocardial contractility was shown to be the major effect of Schisandra components, which was further experimentally validated. In addition, the expression of NCOR2 and NFAT in myocyte were experimentally confirmed to be associated with Schisandra in the treatment of AMI, which may be responsible for the preservation effect of myocardial contractility. In conclusion, the three-mode gene ontology network can be an effective network analysis workflow to evaluate the pharmacological effects of a multi-drug complex system.

Gender-specific associations of genetic variants with metabolic syndrome components in the Tunisian population

AIM OF THE STUDY

Recent genome-wide association studies (GWASs) have identified many genetic variants associated with metabolic syndrome (MetS). However, their contribution to MetS in ethnic groups in Tunisia is largely unexplored. In this study, we aim to examine the associations of related loci with a risk of metabolic syndrome in a sample of Tunisians.

MATERIALS AND METHODS

Overall seven polymorphisms rs7265718, rs10401969, rs762861, rs12310367, rs1562398, rs2059807, rs4420638 located at C20orf152, CILP2, LRPAP1, ZNF664, KLF14, INSR, APOE, respectively, were analyzed in 356 samples from the Tunisian population. Anthropometric and biochemical parameters were assessed. Metabolic syndrome was defined according to the International Diabetes Federation (IDF).

RESULTS

We find that LRPAP1-rs762861 C allele increases susceptibility to MetS (OR = 1.39, 95% CI = 0.99-1.95, p = 0.041). Separate analysis in men and women revealed the association of rs762861 among females (OR = 1.6, 95% CI = 1.057-2.41, p = 0.021), but not among males (OR = 0.953, 95% CI = 0.51-1.78, p = 0.882). ZNF664-rs12310367 was also found to be associated with body mass index (BMI) in women (p = 0.01) and not in men (p = 0.18). KLF14-rs1562398 was significantly correlated with impaired fasting glucose (p = 0.004) only in men.

CONCLUSIONS

Our results reveal new candidate genes for MetS in the Tunisian population and suggest that the genetic basis of this syndrome is gender dependent. Further studies are necessary to understand why these associations differ between males and females.

Integrative computational and experimental approaches to establish a post-myocardial infarction knowledge map

Vast research efforts have been devoted to providing clinical diagnostic markers of myocardial infarction (MI), leading to over one million abstracts associated with “MI” and “Cardiovascular Diseases” in PubMed. Accumulation of the research results imposed a challenge to integrate and interpret these results. To address this problem and better understand how the left ventricle (LV) remodels post-MI at both the molecular and cellular levels, we propose here an integrative framework that couples computational methods and experimental data. We selected an initial set of MI-related proteins from published human studies and constructed an MI-specific protein-protein-interaction network (MIPIN). Structural and functional analysis of the MIPIN showed that the post-MI LV exhibited increased representation of proteins involved in transcriptional activity, inflammatory response, and extracellular matrix (ECM) remodeling. Known plasma or serum expression changes of the MIPIN proteins in patients with MI were acquired by data mining of the PubMed and UniProt knowledgebase, and served as a training set to predict unlabeled MIPIN protein changes post-MI. The predictions were validated with published results in PubMed, suggesting prognosticative capability of the MIPIN. Further, we established the first knowledge map related to the post-MI response, providing a major step towards enhancing our understanding of molecular interactions specific to MI and linking the molecular interaction, cellular responses, and biological processes to quantify LV remodeling.

Heart attack, known medically as myocardial infarction, often occurs as a result of partial shortage of blood supply to a portion of the heart, leading to the death of heart muscle cells. Following myocardial infarction, complications might arise, including arrhythmia, myocardial rupture, left ventricular dysfunction, and heart failure. Although myocardial infarction can be quickly diagnosed using a various number of tests, including blood tests and electrocardiography, there have been no available prognostic tests to predict the long-term outcome in response to myocardial infarction. Here, we present a framework to analyze how the left ventricle responds to myocardial infarction by combining protein interactome and experimental results retrieved from published human studies. The framework organized current understanding of molecular interactions specific to myocardial infarction, cellular responses, and biological processes to quantify left ventricular remodeling process. Specifically, our knowledge map showed that transcriptional activity, inflammatory response, and extracellular matrix remodeling are the main functional themes post myocardial infarction. In addition, text analytics of relevant abstracts revealed differentiated protein expressions in plasma or serum expressions from patients with myocardial infarction. Using this data, we predicted expression levels of other proteins following myocardial infarction.