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Published on: January 16, 2019
Decoding aortic dissection from potential drug targets to genetic risk factors: A Mendelian randomization study
Jiaqi Hou1, Lihua Lin1, Jing Huang1
1Department of Forensic Medicine, Tongji Medical College of Huazhong University of Science and Technology, Wuhan, China.
Insights
This study identified five novel drug targets for aortic dissection (AD), a fatal condition lacking effective treatments. Findings may aid in predicting AD and developing new therapies.
Area of Science:
- Cardiovascular Genetics
- Pharmacogenomics
- Medical Research
Background:
- Aortic dissection (AD) is a life-threatening condition involving aortic wall damage.
- Current treatments for AD lack preventative medications.
- Identifying risk factors and therapeutic targets is crucial for AD management.
Purpose of the Study:
- To identify potential pharmacological targets for aortic dissection (AD).
- To evaluate the medicinal value and therapeutic potential of identified targets.
- To explore mediating factors in AD development.
Main Methods:
- Utilized Mendelian randomization (MR) with cis-expression quantitative trait loci (cis-eQTL) and genome-wide association analysis (GWAS) data.
- Performed colocalization analysis to identify shared genetic signals between drug targets and AD.
- Employed drug prediction and molecular docking to assess therapeutic potential.
Main Results:
- Identified 76 significantly associated genes through MR.
- Revealed five potential drug targets for AD via colocalization analysis.
- Confirmed drug-target associations using prediction and molecular docking; identified diastolic blood pressure, hip circumference, and ascending aorta diameter as potential mediators.
Conclusions:
- This research successfully identified five promising pharmacological targets for AD.
- Drug prediction and molecular docking validated the therapeutic potential of these targets.
- The findings are expected to enhance AD prediction and accelerate drug development efforts.
Aims:
The aortic dissection (AD) is defined as the destruction of the tunica media and separation of the aortic wall, which can be fatal. To date, there is no clinical medication that has been developed to effectively prevent the progression of AD. Therefore, it is imperative to identify risk factors associated with AD and to discover potential therapeutic targets.
Methods:
To identify therapeutic targets for AD, we used cis-expression quantitative trait loci (cis-eQTL) data from the eQTLgen Consortium and genome-wide association analysis (GWAS) data from the Finngen Consortium for Mendelian randomization (MR). Colocalization analysis screened drug targets with shared SNPs in the disease. Drug prediction and molecular docking verified the targets' medicinal value. Finally, mediation analysis was performed to explore how drug targets might influence AD development.
Results:
Using MR, we identified 76 genes exhibiting significant associations. Subsequent colocalization analysis revealed five drug targets sharing genetic signals with AD. Drug prediction analyses were conducted, and molecular docking demonstrated a robust association between the predicted drugs and the implicated genes. Furthermore, our findings suggest that diastolic blood pressure, hip circumference and ascending aorta diameter may serve as potential mediating factors in the development of AD.
Conclusion:
This study identified five potential pharmacological targets for AD. Additionally, drug prediction and molecular docking were employed to assess the therapeutic potential of these targets. The findings of this research are anticipated to offer valuable screening indicators for AD prediction and facilitate advancements in AD drug development.
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