scholarly journals LeMeDISCO: A computational method for large-scale prediction & molecular interpretation of disease comorbidity

2021 ◽  
Author(s):  
Courtney Alexandra Astore ◽  
Hongyi Zhou ◽  
Jeffrey Skolnick
Keyword(s):  
Coronary Artery Disease ◽  
Molecular Basis ◽  
Large Scale ◽  
Scientific Investigation ◽  
Computational Method ◽  
Comorbid Disease ◽  
Essential Proteins ◽  
Molecular Interpretation ◽  
Comorbid Diseases ◽  
Artery Disease

Often different diseases tend to co-occur (i.e., they are comorbid), which yields the question: what is the molecular basis of their coincidence? Perhaps, common proteins are comorbid disease drivers. To understand the origin of disease comorbidity and to identify the essential proteins and pathways underlying comorbid diseases, we developed LeMeDISCO (Large-Scale Molecular Interpretation of Disease Comorbidity), an algorithm that predicts disease comorbidities from shared mode of action (MOA) proteins predicted by the AI-based MEDICASCY algorithm. LeMeDISCO was applied to predict the general occurrence of comorbid diseases for 3608 distinct diseases. To illustrate the power of LeMeDISCO, we elucidate the possible etiology of coronary artery disease and ovarian cancer by determining the comorbidity enriched MOA proteins and pathways and suggest hypotheses for subsequent scientific investigation. The LeMeDISCO web server is available for academic users at: http://sites.gatech.edu/cssb/LeMeDISCO.

Rare, Damaging DNA Variants in CORIN and Risk of Coronary Artery Disease: Insights From Functional Genomics and Large-Scale Sequencing Analyses

2021 ◽  
Author(s):  
Minxian Wang ◽  
Vivian S. Lee-Kim ◽  
Deepak S. Atri ◽  
Nadine H. Elowe ◽  
John Yu ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Association Analysis ◽  
Rare Variant ◽  
Odds Ratio ◽  
Large Scale ◽  
Missense Mutations ◽  
Rare Variant Association ◽  
Missense Variants ◽  
Artery Disease

Background: Corin is a protease expressed in cardiomyocytes that plays a key role in salt handling and intravascular volume homeostasis via activation of natriuretic peptides. It is unknown if Corin loss-of-function (LOF) is causally associated with risk of coronary artery disease (CAD). Methods: We analyzed all coding CORIN variants in an Italian case-control study of CAD. We functionally tested all 64 rare missense mutations in Western Blot and Mass Spectroscopy assays for proatrial natriuretic peptide cleavage. An expanded rare variant association analysis for Corin LOF mutations was conducted in whole exome sequencing data from 37 799 CAD cases and 212 184 controls. Results: We observed LOF variants in CORIN in 8 of 1803 (0.4%) CAD cases versus 0 of 1725 controls ( P , 0.007). Of 64 rare missense variants profiled, 21 (33%) demonstrated <30% of wild-type activity and were deemed damaging in the 2 functional assays for Corin activity. In a rare variant association study that aggregated rare LOF and functionally validated damaging missense variants from the Italian study, we observed no association with CAD—21 of 1803 CAD cases versus 12 of 1725 controls with adjusted odds ratio of 1.61 ([95% CI, 0.79–3.29]; P =0.17). In the expanded sequencing dataset, there was no relationship between rare LOF variants with CAD was also observed (odds ratio, 1.15 [95% CI, 0.89–1.49]; P =0.30). Consistent with the genetic analysis, we observed no relationship between circulating Corin concentrations with incident CAD events among 4744 participants of a prospective cohort study—sex-stratified hazard ratio per SD increment of 0.96 ([95% CI, 0.87–1.07], P =0.48). Conclusions: Functional testing of missense mutations improved the accuracy of rare variant association analysis. Despite compelling pathophysiology and a preliminary observation suggesting association, we observed no relationship between rare damaging variants in CORIN or circulating Corin concentrations with risk of CAD.

scholarly journals Prediction of comorbid diseases using weighted geometric embedding of human interactome

2019 ◽  
Vol 12 (S7) ◽  
Author(s):  
Pakeeza Akram ◽  
Li Liao
Keyword(s):  
Minimum Spanning Tree ◽  
Structural Characteristics ◽  
Computational Method ◽  
Supervised Machine Learning ◽  
High Dimensional ◽  
Comorbid Disease ◽  
Human Interactome ◽  
Geometric Space ◽  
Comorbid Diseases ◽  
Disease Modules

Abstract Background Comorbidity is the phenomenon of two or more diseases occurring simultaneously not by random chance and presents great challenges to accurate diagnosis and treatment. As an effort toward better understanding the genetic causes of comorbidity, in this work, we have developed a computational method to predict comorbid diseases. Two diseases sharing common genes tend to increase their comorbidity. Previous work shows that after mapping the associated genes onto the human interactome the distance between the two disease modules (subgraphs) is correlated with comorbidity. Methods To fully incorporate structural characteristics of interactome as features into prediction of comorbidity, our method embeds the human interactome into a high dimensional geometric space with weights assigned to the network edges and uses the projection onto different dimension to “fingerprint” disease modules. A supervised machine learning classifier is then trained to discriminate comorbid diseases versus non-comorbid diseases. Results In cross-validation using a benchmark dataset of more than 10,000 disease pairs, we report that our model achieves remarkable performance of ROC score = 0.90 for comorbidity threshold at relative risk RR = 0 and 0.76 for comorbidity threshold at RR = 1, and significantly outperforms the previous method and the interactome generated by annotated data. To further incorporate prior knowledge pathways association with diseases, we weight the protein-protein interaction network edges according to their frequency of occurring in those pathways in such a way that edges with higher frequency will more likely be selected in the minimum spanning tree for geometric embedding. Such weighted embedding is shown to lead to further improvement of comorbid disease prediction. Conclusion The work demonstrates that embedding the two-dimension planar graph of human interactome into a high dimensional geometric space allows for characterizing and capturing disease modules (subgraphs formed by the disease associated genes) from multiple perspectives, and hence provides enriched features for a supervised classifier to discriminate comorbid disease pairs from non-comorbid disease pairs more accurately than based on simply the module separation.

Drug Treatment in the Prevention of Coronary Artery Disease

1979 ◽  
Author(s):  
J.R.A. Mitchell
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Heart Disease ◽  
Clinical Trials ◽  
Heart Disease ◽  
Major Part ◽  
Large Scale ◽  
End Points ◽  
Pump Failure ◽  
Artery Disease

The disappointing performance of anticoagulants in the prophylaxis of coronary heart disease led to the realisation that components other than fibrin play a major part in the structure of arterial thrombi. Attention has therefore been focussed on the possible role of agents which modify platelet behaviour. Novel agents which alter thromboxane synthesis will not be available for large-scale clinical trials for some years, so the present trials are assessing the value of platelet-modifying agents which are already in use for other purposes. The implications of the Antura-Reinfarction study and the role of aspirin and persantin will be discussed.Attention will also be drawn to the importance of using valid end-points to assess potential anti-thrombotic regimes in coronary disease. The differential implications of using infarction, sudden death, pump failure, dysrhythmias and re-infarction as end-points in trials will be described.

scholarly journals Heterozygous ABCG5 Gene Deficiency and Risk of Coronary Artery Disease

2020 ◽  
Vol 13 (5) ◽  
pp. 417-423 ◽  
Author(s):  
Akihiro Nomura ◽  
Connor A. Emdin ◽  
Hong Hee Won ◽  
Gina M. Peloso ◽  
Pradeep Natarajan ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Large Scale ◽  
Carrier Status ◽  
Loss Of Function ◽  
Increased Risk ◽  
Genetic Deficiency ◽  
Heterozygous Carriers ◽  
Artery Disease ◽  
The Impact

Background: Familial sitosterolemia is a rare Mendelian disorder characterized by hyperabsorption and decreased biliary excretion of dietary sterols. Affected individuals typically have complete genetic deficiency—homozygous loss-of-function (LoF) variants—in the ABCG5 or ABCG8 genes and have substantially elevated plasma sitosterol and LDL (low-density lipoprotein) cholesterol (LDL-C) levels. The impact of partial genetic deficiency of ABCG5 or ABCG8 —as occurs in heterozygous carriers of LoF variants—on LDL-C and risk of coronary artery disease (CAD) has remained uncertain. Methods: We first recruited 9 sitosterolemia families, identified causative LoF variants in ABCG5 or ABCG8 , and evaluated the associations of these ABCG5 or ABCG8 LoF variants with plasma phytosterols and lipid levels. We next assessed for LoF variants in ABCG5 or ABCG8 in CAD cases (n=29 321) versus controls (n=357 326). We tested the association of rare LoF variants in ABCG5 or ABCG8 with blood lipids and risk for CAD. Rare LoF variants were defined as protein-truncating variants with minor allele frequency <0.1% in ABCG5 or ABCG8 . Results: In sitosterolemia families, 7 pedigrees harbored causative LoF variants in ABCG5 and 2 pedigrees in ABCG8 . Homozygous LoF variants in either ABCG5 or ABCG8 led to marked elevations in sitosterol and LDL-C. Of those sitosterolemia families, heterozygous carriers of ABCG5 LoF variants exhibited increased sitosterol and LDL-C levels compared with noncarriers. Within large-scale CAD case-control cohorts, prevalence of rare LoF variants in ABCG5 and in ABCG8 was ≈0.1% each. ABCG5 heterozygous LoF variant carriers had significantly elevated LDL-C levels (25 mg/dL [95% CI, 14–35]; P =1.1×10 −6 ) and were at 2-fold increased risk of CAD (odds ratio, 2.06 [95% CI, 1.27–3.35]; P =0.004). By contrast, ABCG8 heterozygous LoF carrier status was not associated with increased LDL-C or risk of CAD. Conclusions: Although familial sitosterolemia is traditionally considered as a recessive disorder, we observed that heterozygous carriers of an LoF variant in ABCG5 had significantly increased sitosterol and LDL-C levels and a 2-fold increase in risk of CAD.

scholarly journals Large Scale Association Analysis Identifies Three Susceptibility Loci for Coronary Artery Disease

PLoS ONE ◽  
2011 ◽  
Vol 6 (12) ◽  
pp. e29427 ◽  
Author(s):  
Stephanie Saade ◽  
Jean-Baptiste Cazier ◽  
Michella Ghassibe-Sabbagh ◽  
Sonia Youhanna ◽  
Danielle A. Badro ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Association Analysis ◽  
Large Scale ◽  
Susceptibility Loci ◽  
Artery Disease
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