Over the last few years, new high-throughput biotechnologies are revolutionizing our ways to utilize human biospecimens for understanding atherosclerotic disease. These recent advances allow deep profiling of individual cells at the genomics, epigenomics, transcriptomics and proteomics levels, or even simultaneous detection of various combinations of ‘Omics’ in the same cell. Additionally, novel methods to integrate data at different levels from tissue sections and dissociated tissues are the emerging trends in large and institutional biobank studies. Growing literature has shown the value of such sequencing and bioinformatic strategies in shedding light on (1) how risk genes, as identified by the Genome-Wide Association Study, contribute to atherogenesis (genotype to phenotype), and (2) how features of atherosclerotic lesions affect patient response in clinical trials (phenotype to the clinical outcome). The hybrid of cutting-edge biotechnologies and bioinformatic approaches helps us maximize biobank resources to accelerate bench-to-bedside research.
Moving forward, we need to prioritize applications of these state-of-the-art technologies to address clinically relevant questions. To our knowledge, numerous biobank-based studies are moving in this direction, aiming to explore the pathology, therapeutics, and biomarkers for atherosclerotic disease. This relies on dissecting the relationship of lesion characteristics, including cell composition, phenotypes, and spatial distribution, with cellular functions, biological processes, interactions with microenvironment, and disease trajectories. The heterogeneity and plasticity of lesion cells complicate the studies of human atherosclerotic lesions. In this research topic, we aim to showcase examples of endeavors, understand specific challenges, and brainstorm ideas of how advances in next-generation sequencing, computational biology and/or spatial biology could benefit biobank-based studies of atherosclerosis.
We welcome manuscripts show-casing the following:
1) Use of next-generation sequencing, computational biology and/or spatial biology in studies of human atherosclerotic disease. These include but are not limited to single cell analysis, network analysis, machine learning, and artificial intelligence-based imaging analysis.
2) Integration of multiomics data (eg. scRNA-seq, ATAC-seq, proteomics, multiplex imaging) to find therapeutic targets, repurpose therapeutics, and develop biomarkers in the field of atherosclerosis and vascular medicine.
3) New concepts and tools that utilize cardiovascular biobank resources to address clinically relevant questions, with a focus on, but not limited to sequencing, imaging, and/or data analysis platforms.
Over the last few years, new high-throughput biotechnologies are revolutionizing our ways to utilize human biospecimens for understanding atherosclerotic disease. These recent advances allow deep profiling of individual cells at the genomics, epigenomics, transcriptomics and proteomics levels, or even simultaneous detection of various combinations of ‘Omics’ in the same cell. Additionally, novel methods to integrate data at different levels from tissue sections and dissociated tissues are the emerging trends in large and institutional biobank studies. Growing literature has shown the value of such sequencing and bioinformatic strategies in shedding light on (1) how risk genes, as identified by the Genome-Wide Association Study, contribute to atherogenesis (genotype to phenotype), and (2) how features of atherosclerotic lesions affect patient response in clinical trials (phenotype to the clinical outcome). The hybrid of cutting-edge biotechnologies and bioinformatic approaches helps us maximize biobank resources to accelerate bench-to-bedside research.
Moving forward, we need to prioritize applications of these state-of-the-art technologies to address clinically relevant questions. To our knowledge, numerous biobank-based studies are moving in this direction, aiming to explore the pathology, therapeutics, and biomarkers for atherosclerotic disease. This relies on dissecting the relationship of lesion characteristics, including cell composition, phenotypes, and spatial distribution, with cellular functions, biological processes, interactions with microenvironment, and disease trajectories. The heterogeneity and plasticity of lesion cells complicate the studies of human atherosclerotic lesions. In this research topic, we aim to showcase examples of endeavors, understand specific challenges, and brainstorm ideas of how advances in next-generation sequencing, computational biology and/or spatial biology could benefit biobank-based studies of atherosclerosis.
We welcome manuscripts show-casing the following:
1) Use of next-generation sequencing, computational biology and/or spatial biology in studies of human atherosclerotic disease. These include but are not limited to single cell analysis, network analysis, machine learning, and artificial intelligence-based imaging analysis.
2) Integration of multiomics data (eg. scRNA-seq, ATAC-seq, proteomics, multiplex imaging) to find therapeutic targets, repurpose therapeutics, and develop biomarkers in the field of atherosclerosis and vascular medicine.
3) New concepts and tools that utilize cardiovascular biobank resources to address clinically relevant questions, with a focus on, but not limited to sequencing, imaging, and/or data analysis platforms.
