ArticleBMC cardiovascular disorders2020
Investigation of the underlying genes and mechanism of familial hypercholesterolemia through bioinformatics analysis.
Article in BMC cardiovascular disorders, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed, 15 citations in OpenAlex.
- The Role of Integrin Family in Atherosclerotic Cardiovascular Disease: A Prospective Cohort Study and Mendelian Randomization Analysis.Biomedicines · 2026Article
- Lipid-Laden M1-like Macrophages of Familial Hypercholesterolemia Patients Are Characterized by Increased Interleukin-1β Secretion and ReducedCurrent issues in molecular biology · 2026Article
- Genetically predicted triglyceride levels and endometriosis risk: Mendelian randomization with exploratory multi-omics analyses.PloS one · 2026Article
- USP18 Promotes Cholesterol Efflux and Mitigates Atherosclerosis by Deubiquitinating ABCG1.Journal of cellular and molecular medicine · 2025Article
- Integrin alpha L: structure, cellular functions, and emerging role in human diseases.Frontiers in immunology · 2025Review
- Integrated omics analysis of coronary artery calcifications and myocardial infarction: the Framingham Heart Study.Scientific reports · 2023Article
- Reducing Premature Coronary Artery Disease in Malaysia by Early Identification of Familial Hypercholesterolemia Using the Familial Hypercholesterolemia Case Ascertainment Tool (FAMCAT): Protocol for a Mixed Methods Evaluation Study.JMIR research protocols · 2023Article
- Dysfunctional network of hub genes in hypertrophic cardiomyopathy patients.American journal of translational research · 2022Article
- Article
- Coronary Artery Disease Genetics Enlightened by Genome-Wide Association Studies.JACC. Basic to translational science · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
backgroundFamilial hypercholesterolemia (FH) is one of the commonest inherited metabolic disorders. Abnormally high level of low-density lipoprotein cholesterol (LDL-C) in blood leads to premature atherosclerosis onset and a high risk of cardiovascular disease (CVD). However, the specific mechanisms of the progression process are still unclear. Our study aimed to investigate the potential differently expressed genes (DEGs) and mechanism of FH using various bioinformatic tools.
methodsGSE13985 and GSE6054 were downloaded from the Gene Expression Omnibus (GEO) database for bioinformatic analysis in this study. First, limma package of R was used to identify DEGs between blood samples of patients with FH and those from healthy individuals. Then, the functional annotation of DEGs was carried out by Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and Gene Ontology (GO) analysis. Based on Search Tool for the Retrieval of Interacting Genes (STRING) tool, we constructed the Protein-Protein Interactions (PPIs) network among DEGs and mined the core genes as well.
resultsA total of 102 communal DEGs (49 up-regulated and 53 down-regulated) are identified in FH samples compared with control samples. The functional changes of DEGs are mainly associated with the focal adhere and glucagon signaling pathway. Ten genes (ITGAL, TLN1, POLR2A, CD69, GZMA, VASP, HNRNPUL1, SF1, SRRM2, ITGAV) were identified as core genes. Bioinformatic analysis showed that the core genes are mainly enriched in numerous processes related to cell adhesion, integrin-mediated signaling pathway and cell-matrix adhesion. In the transcription factor (TF) target regulating network, 219 nodes were detected, including 214 DEGs and 5 TFs (SP1, EGR3, CREB, SEF1, HOX13). In conclusion, the DEGs and hub genes identified in this study may help us understand the potential etiology of the occurrence and development of AS.
conclusionUp-regulated ITGAL, TLN1, POLR2A, VASP, HNRNPUL1, SF1, SRRM2, and down-regulated CD69, GZMA and ITGAV performed important promotional effects for the formation of atherosclerotic plaques those suffering from FH. Moreover, SP1, EGR3, CREB, SEF1 and HOX13 were the potential transcription factors for DEGs and could serve as underlying targets for AS rupture prevention. These findings provide a theoretical basis for us to understand the potential etiology of the occurrence and development of AS in FH patients and we may be able to find potential diagnostic and therapeutic targets.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.