MMP 1 circulating levels and promoter polymorphism in risk prediction of coronary artery disease in asymptomatic first degree relatives

Serum levels of matrix metalloproteinases 1, 2, and 7, and their tissue inhibitors 1, 2, 3, and 4 in polytraumatized patients: Time trajectories, correlations, and their ability to predict mortality

There has been limited research on assessing metalloproteinases (MMPs) 1, 2, and 7, as well as their tissue inhibitors (TIMPs) 1, 2, 3, and 4 in the context of polytrauma. These proteins play crucial roles in various physiological and pathological processes and could be a reliable tool in polytrauma care. We aimed to determine their clinical relevance. We assessed 24 blunt polytrauma survivors and 12 fatalities (mean age, 44.2 years, mean ISS, 45) who were directly admitted to our Level I trauma center and spent at least one night in the intensive care unit. We measured serum levels of the selected proteins on admission (day 0) and days 1, 3, 5, 7, and 10. The serum levels of the seven proteins varied considerably among individuals, resulting in similar median trend curves for TIMP1 and TIMP4 and for MMP1, MMP2, TIMP2, and TIMP3. We also found a significant interrelationship between the MMP2, TIMP2, and TIMP3 levels at the same measurement points. Furthermore, we calculated significant cross-correlations between MMP7 and MMP1, TIMP1 and MMP7, TIMP3 and MMP1, TIMP3 and MMP2, and TIMP4 and TIMP3 and an almost significant correlation between MMP7 and TIMP1 for a two-day-lag. The autocorrelation coefficient reached statistical significance for MMP1 and TIMP3. Finally, lower TIMP1 serum levels were associated with in-hospital mortality upon admission. The causal effects and interrelationships between selected proteins might provide new insights into the interactions of MMPs and TIMPs. Identifying the underlying causes might help develop personalized therapies for patients with multiple injuries. Administering recombinant TIMP1 or increasing endogenous production could improve outcomes for those with multiple injuries. However, before justifying further investigations into basic research and clinical relevance, our findings must be validated in a multicenter study using independent cohorts to account for clinical and biological variability.

PromGER: Promoter Prediction Based on Graph Embedding and Ensemble Learning for Eukaryotic Sequence

Promoters are DNA non-coding regions around the transcription start site and are responsible for regulating the gene transcription process. Due to their key role in gene function and transcriptional activity, the prediction of promoter sequences and their core elements accurately is a crucial research area in bioinformatics. At present, models based on machine learning and deep learning have been developed for promoter prediction. However, these models cannot mine the deeper biological information of promoter sequences and consider the complex relationship among promoter sequences. In this work, we propose a novel prediction model called PromGER to predict eukaryotic promoter sequences. For a promoter sequence, firstly, PromGER utilizes four types of feature-encoding methods to extract local information within promoter sequences. Secondly, according to the potential relationships among promoter sequences, the whole promoter sequences are constructed as a graph. Furthermore, three different scales of graph-embedding methods are applied for obtaining the global feature information more comprehensively in the graph. Finally, combining local features with global features of sequences, PromGER analyzes and predicts promoter sequences through a tree-based ensemble-learning framework. Compared with seven existing methods, PromGER improved the average specificity of 13%, accuracy of 10%, Matthew's correlation coefficient of 16%, precision of 4%, F1 score of 6%, and AUC of 9%. Specifically, this study interpreted the PromGER by the t-distributed stochastic neighbor embedding (t-SNE) method and SHAPley Additive exPlanations (SHAP) value analysis, which demonstrates the interpretability of the model.

Association of Matrix Metalloproteinases with Coronary Artery Calcification in Patients with CHD

This work is aimed at studying the relationship of matrix metalloproteinases with calcification of the coronary arteries. The study included 78 people with coronary heart disease (CHD) and 36 without CHD. Blood and samples of coronary arteries obtained as a result of endarterectomy were examined. Serum levels of metalloproteinases (MMP) MMP-1, MMP-2, MMP-3, MMP-7, MMP-9, MMP-10, MMP-12, and MMP-13 were determined by multiplex analysis. In blood vessel samples, MMP-1, MMP-3, MMP-7, and MMP-9 were determined by enzyme immunoassay; MMP-9 expression was evaluated by immunohistochemistry. Patients with CHD had higher serum levels of MMP-1, MMP-7, and MMP-12. Blood levels of MMP-1 and MMP-3 were associated with calcium levels, MMP-9 with osteoprotegerin and osteonectin, MMP-7 and MMP-10 with osteoprotegerin, MMP-12 with osteocalcin, and MMP-13 with osteopontin. Calcified plaques had higher levels of MMP-1 and MMP-9 compared to plaques without calcification. The relative risk of coronary arteries calcification was associated with MMP-9, which is confirmed by the results of immunohistochemistry. The results obtained indicate the participation of some MMPs, and especially MMP-9, in the calcification processes. The study can serve as a basis for the further study of the possibility of using MMP-1, MMP-7 and MMP-12 as potential biomarkers of CHD.

Matrix metalloproteinase 1 1 G/2 G gene polymorphism is associated with acquired atrioventricular block via linking a higher serum protein level

Limited studies are available regarding the pathophysiological mechanism of acquired atrioventricular block (AVB). Matrix metalloproteinases (MMPs) and angiotensin-converting enzyme (ACE) have been implicated in the pathogenesis of arrhythmia. However, the relationship between these molecules and acquired AVB is still unclear. One hundred and two patients with documented acquired AVB and 100 controls were studied. Gene polymorphisms of the MMP1 and ACE encoding genes were screened by the gene sequencing method or polymerase chain reaction-fragment length polymorphism assay, followed by an association study. The frequencies of the MMP1 −1607 2G2G genotype and MMP1 −1607 2 G allele were significantly higher in the AVB group than that in the controls (OR = 1.933, P = 0.027 and OR = 1.684, P = 0.012, respectively). Consistently, the level of serum MMP1 was significantly greater in acquired AVB patients than that in controls (6568.9 ± 5748.6 pg/ml vs. 4730.5 ± 3377.1 pg/ml, P = 0.019). In addition, the MMP1 2G2G genotype showed a higher MMP-1 serum level than the other genotypes (1G1G/1G2G) (7048.1 ± 5683.0 pg/ml vs. 5072.4 ± 4267.6 pg/ml, P = 0.042). MMP1 1 G/2 G gene polymorphism may contribute to determining the disease susceptibility of acquired AVB by linking the MMP serum protein level.

Association of serum ADAMTS7 levels and genetic variant rs1994016 with acute coronary syndrome in a Chinese population: A case control study

BACKGROUND AND AIMS

Acute coronary syndrome (ACS) is commonly caused by rupture or erosion of coronary atherosclerotic plaques and secondary thrombus formation. Metalloproteinase ADAMTS7 was found to play an important role in atherogenesis. This study aimed to explore the association of serum ADAMTS7 levels and rs1994016 polymorphism at ADAMTS7 locus with ACS in a Chinese population.

METHODS

1881 patients who underwent coronary angiography were consecutively recruited. Among them, 426 patients were matched for case-controlled analysis. Serum ADAMTS7 levels were determined through enzyme-linked immunosorbent assay (ELISA) and rs1994016 polymorphism was detected by polymerase chain reaction (PCR).

RESULTS

Serum ADAMTS7 levels in patients with unstable angina pectoris were much higher than in non-atherosclerotic patients, however, no difference was found among non-atherosclerotic patients, the coronary atherosclerosis subgroup and stable angina pectoris subgroup. A higher serum ADAMTS7 level was found in the ACS group than in the non-ACS group (0.61 ± 0.04 vs. 0.47 ± 0.02 ng/mL, p = 0.002) and serum ADAMTS7 level was found to be an independent risk factor for ACS after adjusting for major confounding factors (OR:2.81, 95% CI:1.33-5.93, p = 0.007). ADAMTS7 rs1994016 CT/TT polymorphism was negatively associated with the risk of ACS (OR:0.40, 95% CI:0.22-0.71, p = 0.002). Meanwhile, crossover analysis revealed that in CT/TT homozygotes, ACS risk was reduced nearly 80% in patients with serum ADAMTS7 levels <0.594 ng/mL (Interaction p = 0.002).

CONCLUSIONS

Serum level of ADAMTS7 was positively associated and rs1994016 CT/TT genotype was negatively associated with the risk of ACS. Patients with lower serum ADAMTS7 level and rs1994016 CT/TT genotype are less likely to suffer from ACS in a Chinese population.