Latest Science: Transcriptomics-based clustering and drug-interacting gene analysis help to predict drug–atherosclerotic tissue interactions
30 Aug 2021
Presented science not to be missed
In addition to their intended beneficial actions on blood vessel walls, anti-atherosclerosis therapies may also have other, potentially harmful, effects on vascular tissue and atherosclerotic plaques. Strategies to predict such detrimental effects of therapeutics would be invaluable in patient management.
Available in the on-demand programme, Professor Gerard Pasterkamp (University Medical Center Utrecht, the Netherlands) presents results of a study using a new transcriptomics-based classification to determine the association between gene expression of known drug target-encoding loci and atherosclerotic plaques.
Bulk RNA sequencing was performed in 654 carotid plaques obtained from symptomatic and asymptomatic patients. An unbiased transcriptomics-based clustering identified five different plaque types that were strongly associated with clinical presentation. Expression of genes known to interact with commonly prescribed statins or colchicine were examined in these five plaque types.
Among 116 statin-responsive genes, 87 were differentially expressed between the five plaque clusters. The most significant differences were found in a cluster (cluster 3) most strongly associated with severe clinical cerebral and coronary symptoms and including genes known to be causally related to plaque stabilisation and destabilisation, such as ABCA-1 and NOS1 (p<0.001). Thirty-four of 46 colchicine-interacting genes were differentially expressed in the five plaque clusters. There was differential expression of 10 different tubulin genes, and also inflammatory genes such as CXCL8 (p<0.001). Cluster 3 and another cluster, cluster 2, showed a high prevalence of severe symptoms, but the statin and colchicine interactive-gene expression differences between the two clusters were high in many cases, indicating differential drug responsive gene expression among symptomatic plaque types. No clear differences were seen between men and women.
The results indicate that there is diversity in plaque characteristics that can be described with transcriptomic clustering, an approach that can be used to investigate whether any interaction between a particular drug and the atherosclerotic vascular wall can be expected.
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