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This meta-analysis was conducted to estimate associations between CDKN2B antisense () polymorphisms and susceptibility to atherosclerotic cardio-cerebral vascular diseases (ASCVD). A systematic literature research of PubMed, Medline, Web of Science, Embase, and CNKI was performed to identify eligible studies. Overall, 34 studies were included for meta-analyses. Pooled overall analyses showed that rs1333040, rs1333049, rs2383206, and rs2383207 polymorphisms were associated with susceptibility to ASCVD in the whole population. Further analyses by ethnicity revealed that all investigated polymorphisms were associated with susceptibility to ASCVD in East Asians. Moreover, rs2383206, rs2383207, rs10757274, and rs10757278 polymorphisms were associated with susceptibility to ASCVD in West Asians, while rs2383206, rs10757274, and rs10757278 were associated with susceptibility to ASCVD in Caucasians. When we stratified eligible studies by type of disease, positive results were found for all investigated polymorphisms in patients with coronary artery disease (CAD) or myocardial infarction, whereas positive results were only detected for rs2383206 and rs10757274 polymorphisms in patients with ischemic stroke (IS). Our findings suggest that rs1333040, rs1333049, rs2383206, rs2383207, rs10757274, and rs10757278 polymorphisms might serve as genetic biomarkers of CAD, and rs2383206 and rs10757274 polymorphisms might serve as genetic biomarkers of IS.
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http://dx.doi.org/10.1177/0003319720941387 | DOI Listing |
Atherosclerosis
September 2025
IRCCS MultiMedica, Sesto S. Giovanni, 20099, Italy; Department of Pharmacological and Biomolecular Sciences, Università Degli Studi di Milano, 20133 Milan, Italy.
Background And Aims: Atherosclerotic cardiovascular disease (ASCVD) is among the leading causes of death worldwide, and technological advances have made it possible to expand the repertoire of biomarkers used in diagnostics and treatment of ASCVD. These include different omics (genomics, epigenomics, transcriptomics, proteomics, and metabolomics). We introduce the various layers of omic data and how they can be used in diagnostics and treatment of ASCVD.
View Article and Find Full Text PDFJ Atheroscler Thromb
September 2025
Graduate School of Medicine, Tohoku University.
Polygenic risk scores (PRSs), constructed from numerous common single nucleotide polymorphisms (SNPs), have emerged as useful tools for predicting future atherosclerotic cardiovascular disease (ASCVD). PRSs have shown independent associations with ASCVD outcomes and are increasingly being considered to enhance risk stratification and guide primary prevention strategies. However, most evidence to date has been derived from populations of European ancestry, and their generalizability to other populations, including East Asians, remains uncertain.
View Article and Find Full Text PDFSci Rep
July 2025
Department of Internal Medicine, Seoul National University College of Medicine, Seoul, 03080, Republic of Korea.
Metabolic syndrome (MetS) is a major risk factor for cardiovascular and chronic diseases. This study evaluated how genetic predisposition and lifestyle factors contribute to MetS risk. We analysed data from 4,987 Koreans aged ≥ 40 years with at least one ASCVD risk factor (2014-2017).
View Article and Find Full Text PDFAtherosclerotic cardiovascular diseases (ASCVD) remain the leading cause of death globally. Animal and human studies link psychological stress-related disorders to ASCVD. Despite this accumulating evidence linking stress to increased cardiovascular disease (CVD) risk, it remains unclear whether stress impairs the benefits of standard risk-reduction therapies, of which lipid-lowering remains the most common, or whether this increased risk is driven by systemic inflammatory states.
View Article and Find Full Text PDFAm J Hum Genet
July 2025
Institute for Stroke and Dementia Research (ISD), Ludwig-Maximilians-University (LMU) Hospital, LMU Munich, 81377 Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), 81377 Munich, Germany; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA 0214
Genome-wide association studies (GWASs) have identified numerous genetic loci influencing human disease risk; however, linking these to causal genes remains challenging, limiting opportunities for drug target discovery. Transcriptome-wide association studies (TWASs) address this by linking variants to gene expression but typically rely on bulk RNA sequencing, limiting cell-specific resolution. Here, we present a single-cell TWAS pipeline combining cis-Mendelian randomization (MR) with colocalization analyses at the single-cell level.
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