Abstract
An increased risk of cardiovascular events was identified in patients with peripheral artery disease (PAD). Clopidogrel is one of the most widely used antiplatelet medications. However, there are heterogeneous outcomes when clopidogrel is used to prevent cardiovascular events in PAD patients. Here, we use an artificial intelligence (AI)-assisted methodology to identify genetic factors potentially involved in the clopidogrel-resistant mechanism, which is currently unclear. Several discoveries can be pinpointed. Firstly, a high proportion (>50%) of clopidogrel resistance was found among diabetic PAD patients in Taiwan. Interestingly, our result suggests that platelet function test-guided antiplatelet therapy appears to reduce the post-interventional occurrence of major adverse cerebrovascular and cardiac events in diabetic PAD patients. Secondly, AI-assisted genome-wide association study of a single-nucleotide polymorphism (SNP) database identified a SNP signature composed of 20 SNPs, which are mapped into 9 protein-coding genes (SLC37A2, IQSEC1, WASHC3, PSD3, BTBD7, GLIS3, PRDM11, LRBA1, and CNR1). Finally, analysis of the protein connectivity map revealed that LRBA, GLIS3, BTBD7, IQSEC1, and PSD3 appear to form a protein interaction network. Intriguingly, the genetic factors seem to pinpoint a pathway related to endocytosis and recycling of P2Y12 receptor, which is the drug target of clopidogrel. Our findings reveal that a combination of AI-assisted discovery of SNP signatures and clinical parameters has the potential to develop an ethnic-specific precision medicine for antiplatelet therapy in diabetic PAD patients.
Highlights
Peripheral artery disease (PAD) affected 202 million people worldwide in 2010 [1].The prevalence of peripheral artery disease (PAD) among adults has been estimated to be 5.8 to 10.7%, 6.5%, and3.1% to 24% in the United States, Chinese populations [2], and the sub-Saharan African region [3], respectively
artificial intelligence (AI)-assisted genome-wide association study of a single nucleotide polymorphism (SNP) database identified an single-nucleotide polymorphism (SNP) signature composed of 20 SNPs, which are mapped into 9 protein-coding genes (SLC37A2, IQSEC1, WASHC3, PSD3, BTBD7, GLIS3, PRDM11, LRBA1 and CNR1)
Our findings reveal that a combination of AI-assisted discovery of SNP signatures and clinical parameters has a potential to develop an ethnic-specific precision medicine for antiplatelet therapy in diabetic PAD patients
Summary
Peripheral artery disease (PAD) affected 202 million people worldwide in 2010 [1].The prevalence of PAD among adults has been estimated to be 5.8 to 10.7%, 6.5%, and3.1% to 24% in the United States, Chinese populations [2], and the sub-Saharan African region [3], respectively. Diabetes markedly increases the risk of PAD; diabetes increases the incidence of major adverse cerebrovascular and cardiac events (MACCEs) in PAD patients. For diabetic patients with PAD complications, especially those who have received a PAD revascularization procedure, a standard anti-platelet regimen for the prevention of limb loss and MACCE has not yet been established. Evidence proves that dual anti-platelet therapy (DAPT) can be more effective in reducing the rate of ischemic vascular events, target lesion revascularization [5], and post-revascularization MACCE [6] among PAD patients compared to patients receiving monotherapy with aspirin [7]. There have been heterogeneous outcomes when clopidogrel [10] is used to prevent cardiovascular events among diabetic PAD patients. The available major studies of anti-platelet regimens involving
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