ReviewFrontiers in cardiovascular medicine2018
Exploring Coronary Artery Disease GWAs Targets With Functional Links to Immunometabolism.
Review in Frontiers in cardiovascular medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed, 2 syntheses or guidelines pooled it, 15 citations in OpenAlex.
- Shared genetic risk factors and causal association between psoriasis and coronary artery disease.Nature communications · 2022Pooled it
- Potential Interplay between Dietary Saturated Fats and Genetic Variants of the NLRP3 Inflammasome to Modulate Insulin Resistance and Diabetes Risk: Insights from a Meta-Analysis of 19 005 Individuals.Molecular nutrition & food research · 2019Pooled it
- Emerging Role and Potential Therapeutic Application of TRIM Proteins in Cardiovascular Diseases.Biomolecules · 2026Review
- Targeted proteomics reveals immune protein patterns in serum from patients with calcific aortic stenosis.iScience · 2025Article
- Genetic Insights Into Coronary Microvascular Disease.Microcirculation (New York, N.Y. : 1994) · 2025Review
- Article
- System Genetics Analysis Reveals Sex Differences in Human Aortic Smooth Muscle Gene Expression.Bioinformatics and biology insights · 2024Article
- Genetic Variants ofGenes · 2022Article
- KRIT1 Deficiency Promotes Aortic Endothelial Dysfunction.International journal of molecular sciences · 2019Article
- Cardiovascular Disease and Hair Cortisol: a Novel Biomarker of Chronic Stress.Current cardiology reports · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Finding genetic variants that cause functional disruption or regulatory change among the many implicated GWAs variants remains a key challenge to translating the findings from GWAs to therapeutic treatments. Defining the causal mechanisms behind the variants require functional screening experiments that can be complex and costly. Prioritizing variants for functional characterization using techniques that capture important functional and regulatory elements can assist this. The genetic architecture of complex traits such as cardiovascular disease and type II diabetes comprise an enormously large number of variants of small effect contributing to heritability and spread throughout the genome. This makes it difficult to distinguish which variants or core genes are most relevant for prioritization and how they contribute to the regulatory networks that become dysregulated leading to disease. Despite these challenges, recent GWAs for CAD prioritized genes associated with lipid metabolism, coagulation and adhesion along with novel signals related to innate immunity, adipose tissue and, vascular function as important core drivers of risk. We focus on three examples of novel signals associated with CAD which affect risk through missense or UTR mutations indicating their potential for therapeutic modification. These variants play roles in adipose tissue function vascular function and innate immunity which form the cornerstones of immuno-metabolism. In addition we have explored the putative, but potentially important interactions between the environment, specifically food and nutrition, with respect to key processes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.