Systems Approach to Study Associations between OxLDL and Abdominal Aortic Aneurysms

Gutowski, Łukasz; Gutowska, Kaja; Pioruńska-Stolzmann, Maria; Formanowicz, Piotr; Formanowicz, Dorota

doi:10.3390/ijms20163909

Cited by 10 publications

(4 citation statements)

References 54 publications

(92 reference statements)

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“…LDL-C may contribute to AAA via stromal degeneration caused by in ammation and atherosclerosis. [28,29]. Patients with AAA have HDL-C with reduced antioxidant activity and HDL-C can affect thrombotic components directly in order to have positive effects according to a study [30].…”

Section: Discussionmentioning

confidence: 99%

Association between low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and Lipoprotein(a) [Lp(a)] with aortic aneurysm: Univariable and Multivariable Mendelian Randomization Analysis

Wang

Chen

et al. 2022

Preprint

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To determine the relationship between blood lipids and the risk of aortic aneurysm (AA), including low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and Lipoprotein(a) [Lp(a)], we performed univariable and multivariable Mendelian randomization (MR) analysis.Methods: The UK Biobank study of European ancestry provided data for single nucleotide polymorphisms (SNPs) associated with LDL-C(n=440546), and HDL-C(n=403943). SNPs for Lp(a) (n=377590) was a Neale Lab genome-wide association study (GWAS) based on European populations. And the data on AA were obtained from the latest analysis of genome-wide association studies (GWASs) with 209,366 subjects of European ancestry. Univariate and multivariate MR analyses were performed.Results: The Inverse variance weighted(IVW1) estimate showed that the HDL-C(odds ratio [OR]:0.728, 95%confidence interval [CI]:0.629-0.842, P = 1.87E-05) was negatively correlated with AA. The causal association between LDL-C(OR:1.467, 95%CI:1.184-1.816, P=4.49E-4), Lp(a)(OR:1.005, 95%CI:1.001-1.010, P=0.009) and AA were observed in the IVW1 method. The multivariable MR(MVMR) analysis indicated that HDL(OR:0.685, 95%CI: 0.581-0.807, P=6.77E-06) remained negatively associated with AA after adjusting for the LDL-C and Lp(a).Conclusion: Genetic evidence supported the role of greater LDL-C, Lp(a), and lower HDL-C as risk factors for AA. our MVMR study revealed a negative correlation between HDL and AA. Furthermore, additional research is required to confirm the probable relationship between lipid traits and AA risk. Moreover, therapies to reduce LDL-C and Lp(a) may be advantageous for AA.

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Section: Discussionmentioning

confidence: 99%

Association between low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and Lipoprotein(a) [Lp(a)] with aortic aneurysm: Univariable and Multivariable Mendelian Randomization Analysis

Wang

Chen

et al. 2022

Preprint

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“…The significance analysis is based on the frequency occurrence of each transition (elementary subprocess) in all supports of t-invariants 42 . On the basis of such frequency, the significance of transition expressed in percentage can be calculated, i.e., , where frequency occurrence of transition, all supports of t-invariants, and significance of transition .…”

Section: Methodsmentioning

confidence: 99%

Petri nets and ODEs as complementary methods for comprehensive analysis on an example of the ATM–p53–NF-$$\kappa$$B signaling pathways

Gutowska

Kogut

Kardyńska

et al. 2022

Sci Rep

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Intracellular processes are cascades of biochemical reactions, triggered in response to various types of stimuli. Mathematical models describing their dynamics have become increasingly popular in recent years, as tools supporting experimental work in analysis of pathways and regulatory networks. Not only do they provide insights into general properties of these systems, but also help in specific tasks, such as search for drug molecular targets or treatment protocols. Different tools and methods are used to model complex biological systems. In this work, we focus on ordinary differential equations (ODEs) and Petri nets. We consider specific methods of analysis of such models, i.e., sensitivity analysis (SA) and significance analysis. So far, they have been applied separately, with different goals. In this paper, we show that they can complement each other, combining the sensitivity of ODE models and the significance analysis of Petri nets. The former is used to find parameters, whose change results in the greatest quantitative and qualitative changes in the model response, while the latter is a structural analysis and allows indicating the most important subprocesses in terms of information flow in Petri net. Ultimately, both methods facilitate finding the essential processes in a given signaling pathway or regulatory network and may be used to support medical therapy development. In the paper, the use of dual modeling is illustrated with an example of ATM/p53/NF-$$\kappa$$ κ B pathway. Each method was applied to analyze this system, resulting in finding different subsets of important processes that might be prospective targets for changing this system behavior. While some of the processes were indicated in each of the approaches, others were found by one method only and would be missed if only that method was applied. This leads to the conclusion about the complementarity of the methods under investigation. The dual modeling approach of comprehensive structural and parametric analysis yields results that would not be possible if these two modeling approaches were applied separately. The combined approach, proposed in this paper, facilitates finding not only key processes, with which significant parameters are associated, but also significant modules, corresponding to subsystems of regulatory networks. The results provide broader insight into therapy targets in diseases in which the natural control of intracellular processes is disturbed, leading to the development of more effective therapies in medicine.

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“…Apart from the analysis of MCT sets, there are other methods of analysis of Petri net-based models, for example, the significance analysis, the knockout analysis and the knockout simulation [ 61 , 62 ]. It should be noted that the knockout analysis and the knockout simulation are two different methods of knockouts.…”

Section: Methodsmentioning

confidence: 99%

The Crosstalk between SARS-CoV-2 Infection and the RAA System in Essential Hypertension—Analyses Using Systems Approach

Formanowicz

Gutowska

Szawulak

et al. 2021

IJMS

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The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), responsible for the coronavirus disease of 2019 (COVID-19) pandemic, has affected and continues to affect millions of people across the world. Patients with essential arterial hypertension and renal complications are at particular risk of the fatal course of this infection. In our study, we have modeled the selected processes in a patient with essential hypertension and chronic kidney disease (CKD) suffering from COVID-19, emphasizing the function of the renin-angiotensin-aldosterone (RAA) system. The model has been built in the language of Petri nets theory. Using the systems approach, we have analyzed how COVID-19 may affect the studied organism, and we have checked whether the administration of selected anti-hypertensive drugs (angiotensin-converting enzyme inhibitors (ACEIs) and/or angiotensin receptor blockers (ARBs)) may impact the severity of the infection. Besides, we have assessed whether these drugs effectively lower blood pressure in the case of SARS-CoV-2 infection affecting essential hypertensive patients. Our research has shown that neither the ACEIs nor the ARBs worsens the course infection. However, when assessing the treatment of hypertension in the active SARS-CoV-2 infection, we have observed that ARBs might not effectively reduce blood pressure; they may even have the slightly opposite effect. On the other hand, we have confirmed the effectiveness of arterial hypertension treatment in patients receiving ACEIs. Moreover, we have found that the simultaneous use of ARBs and ACEIs averages the effects of taking both drugs, thus leading to only a slight decrease in blood pressure. We are a way from suggesting that ARBs in all hypertensive patients with COVID-19 are ineffective, but we have shown that research in this area should still be continued.

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Systems Approach to Study Associations between OxLDL and Abdominal Aortic Aneurysms

Cited by 10 publications

References 54 publications

Association between low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and Lipoprotein(a) [Lp(a)] with aortic aneurysm: Univariable and Multivariable Mendelian Randomization Analysis

Association between low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and Lipoprotein(a) [Lp(a)] with aortic aneurysm: Univariable and Multivariable Mendelian Randomization Analysis

Petri nets and ODEs as complementary methods for comprehensive analysis on an example of the ATM–p53–NF-$$\kappa$$B signaling pathways

The Crosstalk between SARS-CoV-2 Infection and the RAA System in Essential Hypertension—Analyses Using Systems Approach

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