Genetic markers: Potential candidates for cardiovascular disease

Rather, Riyaz Ahmad; Dhawan, Veena

doi:10.1016/j.ijcard.2016.06.251

Cited by 7 publications

(6 citation statements)

References 171 publications

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“…For genotype II, in the comparison between the patients and controls, no statistical relevance was identified with a high power in any coronary risk factor. This demonstrates that the participation of these genotypes in the genesis of CAD is determined by more complex associations than other studies have indicated when analysing the genotypes as part of a single sample [34][35][36][37][38].…”

Section: Discussionmentioning

confidence: 63%

A New Investigative Approach: How the Angiotensin-Converting Enzyme Gene Interacts with Coronary Risk Factors

Araújo¹,

Neto²,

Souza³

et al. 2017

J Cardiovasc Dis Diagn

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Section: Discussionmentioning

confidence: 63%

A New Investigative Approach: How the Angiotensin-Converting Enzyme Gene Interacts with Coronary Risk Factors

Araújo¹,

Neto²,

Souza³

et al. 2017

J Cardiovasc Dis Diagn

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“…A gene can signify a disease state if its expression is suppressive or augmentative under certain clinical conditions 37 . However, some diseases result from multifaceted gene webs that interact with each other in complex ways 38 .…”

Section: Resultsmentioning

confidence: 99%

A Computational Method of Defining Potential Biomarkers based on Differential Sub-Networks

Huang

Lin

Zeng

et al. 2017

Sci Rep

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Analyzing omics data from a network-based perspective can facilitate biomarker discovery. To improve disease diagnosis and identify prospective information indicating the onset of complex disease, a computational method for identifying potential biomarkers based on differential sub-networks (PB-DSN) is developed. In PB-DSN, Pearson correlation coefficient (PCC) is used to measure the relationship between feature ratios and to infer potential networks. A differential sub-network is extracted to identify crucial information for discriminating different groups and indicating the emergence of complex diseases. Subsequently, PB-DSN defines potential biomarkers based on the topological analysis of these differential sub-networks. In this study, PB-DSN is applied to handle a static genomics dataset of small, round blue cell tumors and a time-series metabolomics dataset of hepatocellular carcinoma. PB-DSN is compared with support vector machine-recursive feature elimination, multivariate empirical Bayes statistics, analyzing time-series data based on dynamic networks, molecular networks based on PCC, PinnacleZ, graph-based iterative group analysis, KeyPathwayMiner and BioNet. The better performance of PB-DSN not only demonstrates its effectiveness for the identification of discriminative features that facilitate disease classification, but also shows its potential for the identification of warning signals.

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“…In contrast to the field of venous thrombosis, genetic mutations related to arterial thrombosis have been much more difficult to establish. In this case, most of the variants found in coagulation and/or protease cascade genes are only associated to minor differences in the risk of arterial thrombosis (33), suggesting that there is a genuine specificity in pathological mechanisms among the two branches of the cardiovascular tree.…”

Section: The Genetic Basis Of the Anticoagulant Defence Mechanisms Anmentioning

confidence: 90%

Coagulation factor and protease pathways in thrombosis and cardiovascular disease

Cate

Hackeng²,

Frutos

2017

Thromb Haemost

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SummaryThe biochemical characterisation of the proteolytic pathways that constitute blood coagulation was one of the most relevant achievements in biomedical research during the second half of the 20th century. Understanding these pathways was of crucial importance for improving global health through application in haemostasis and thrombosis pathologies. Immediately after the cloning of the genes corresponding to these proteins, mutations were discovered in them that were associated with imbalances in haemostasis. Later, the importance of coagulation pathways in other pathological processes was demonstrated, such as in atherosclerosis and inflammation, both essential processes involved in vascular disease. In the present review we evaluate the concepts that have allowed us to reach the integrated vision on coagulation that we have today. The thrombo-inflammation model encompassing these aspects includes a pivotal role for the proteases of the coagulation pathway as well as the regulatory proteins thereof. These concepts illustrate the importance of the coagulation cascade in cardiovascular pathology, not only in thrombotic processes, but also in atherosclerotic processes and in the response to ischaemia-reperfusion injury, making it a central mechanism in cardiovascular disease.

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Genetic markers: Potential candidates for cardiovascular disease

Cited by 7 publications

References 171 publications

A New Investigative Approach: How the Angiotensin-Converting Enzyme Gene Interacts with Coronary Risk Factors

A New Investigative Approach: How the Angiotensin-Converting Enzyme Gene Interacts with Coronary Risk Factors

A Computational Method of Defining Potential Biomarkers based on Differential Sub-Networks

Coagulation factor and protease pathways in thrombosis and cardiovascular disease

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