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pmid:35356421

Contribution of FBLN5 to Unstable Plaques in Carotid Atherosclerosis via mir128 and mir532-3p Based on Bioinformatics Prediction and Validation.

Lin Zheng · Xinyang Yue · Minhui Li · Jie Hu · Bojin Zhang · Ruijing Zhang · Guoping Zheng · Ruihan Chen · Honglin Dong

Frontiers in genetics · 2022 doi:10.3389/fgene.2022.821650

Paper

complete

Experiment

complete

Data

partial

Analysis

complete

Execution

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title
Contribution of FBLN5 to Unstable Plaques in Carotid Atherosclerosis via mir128 and mir532-3p Based on Bioinformatics Prediction and Validation.
doi
10.3389/fgene.2022.821650
pmid
35356421
authors array · 9 items
[0]
Lin Zheng
[1]
Xinyang Yue
[2]
Minhui Li
[3]
Jie Hu
[4]
Bojin Zhang
[5]
Ruijing Zhang
[6]
Guoping Zheng
[7]
Ruihan Chen
[8]
Honglin Dong
journal
Frontiers in genetics
year
2022
abstract
FBLN5, a member of the short fibulins in the fibulin family of extracellular matrix/matricellular proteins, is involved in interactions with components of the basement membrane and extracellular matrix proteins. It plays key roles in endothelial tissues in many vascular diseases. In this study, the relationship between FBLN5 and carotid atherosclerotic plaque stability as well as the regulatory roles of miRNAs were evaluated. Differential gene expression analyses and weighted gene co-expression network analysis (WGCNA) based on the GSE163154 dataset (including 16 samples without intraplaque hemorrhage and 27 samples with intraplaque hemorrhage) in GEO revealed that FBLN5 is related to plaque stability and is the most significantly differentially expressed gene. LASSO regression was used to evaluate genes obtained from the intersection of differentially expressed genes and clinically significant modules identified by WGCNA. A prediction model based on eight genes, including FBLN5, was constructed and showed an accuracy of 0.951 based on an ROC analysis. Low FBLN5 expression in plaque tissues was confirmed by immunohistochemistry and western blotting. GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analyses showed that FBLN5 acted mainly by the maintenance of the cellular matrix and reactive oxygen species production. miRNAs upstream of these eight predictive genes, including FBLN5, were identified and used to construct a network diagram. These results revealed that hsa-mir-128 and hsa-mir-532-3p were upstream regulatory factors of FBLN5, as verified by PCR assays of human plaque tissues demonstrating that both miRNAs were significantly up-regulated. Therefore, FBLN5 may play an important role in carotid atherosclerosis via hsa-mir-128 and hsa-mir-532-3p as well as become an essential target for treatment.
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The glmnet package in R was then used for a least absolute shrinkage and selection operator (LASSO) Cox regression analysis to find the genetic model with the best prognostic value.
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Publicly available datasets were analyzed in this study. This data can be found here: GSE163154 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE163154 GSE100927 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE100927 GSE28829 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE28829 GSE11794 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE11794 and also in the Supplementary materials.
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An eight-gene prediction model including FBLN5 achieved an ROC-analysis accuracy of 0.951 for identifying intraplaque hemorrhage.
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A prediction model based on eight genes, including FBLN5, was constructed and showed an accuracy of 0.951 based on an ROC analysis.
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An eight-gene prediction model including FBLN5 achieved an ROC-analysis accuracy of 0.951 for identifying intraplaque hemorrhage.
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The glmnet package in R was then used for a least absolute shrinkage and selection operator (LASSO) Cox regression analysis to find the genetic model with the best prognostic value.
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Publicly available datasets were analyzed in this study. This data can be found here: GSE163154 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE163154 GSE100927 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE100927 GSE28829 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE28829 GSE11794 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE11794 and also in the Supplementary materials.
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xpression in plaque tissues was confirmed by immunohistochemistry and western blotting. GO (Gene Ontology) and
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with non-plaque artery tissues (Figure 6C). Immunohistochemical staining results showed that the mean densit
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blotting. (D) Representative images of FBLN5 immunohistochemistry in carotid tissue. Supplementary Material Th
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es was confirmed by immunohistochemistry and western blotting. GO (Gene Ontology) and KEGG (Kyoto Encyclop
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Expression at the Protein Level in Human and Rat Samples Using GSE28829 and GSE100927 dataset
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advanced plaque formation, we constructed a rat model by feeding rats subjected to carotid a
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ation, we constructed a rat model by feeding rats subjected to carotid artery ligation a high-
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The glmnet package in R was then used for a least absolute shrinkage and selection operator (LASSO) Cox regression analysis to find the genetic model with the best prognostic value.
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It plays key roles in endothelial tissues in many vascular diseases. In this study, the relationship between FBLN5 and carotid atherosclerotic plaque stability as well as the regulatory roles of miRNAs were evaluated. Differential gene expression analyses and weighted gene co-expression network analysis (WGCNA) based on the GSE163154 dataset (including 16 samples without intraplaque hemorrhage and 27 samples with intraplaque hemorrhage) in GEO revealed that FBLN5 is related to plaque stability and is the most significantly differentially expressed gene. LASSO regression was used to evaluate genes obtained from the intersection of differentially expressed genes and clinically significant modules identified by WGCNA. A prediction model based on eight genes, including FBLN5, was constructed and showed an accuracy of 0.951 based on an ROC analysis. Low FBLN5 expression in plaque tissues was confirmed by immunohistochemistry and western blotting. GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analyses showed that FBLN5 acted mainly by the maintenance of the cellular matrix and reactive oxygen species production. miRNAs upstream of these eight predictive genes, including FBLN5, were identified and used to construct a network diagram. These results revealed that hsa-mir-128 and hsa-mir-532-3p were upstream regulatory factors of FBLN5, as verified by PCR assays of human plaque tissues demonstrating that both miRNAs were significantly up-regulated. 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This data can be found here: GSE163154 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE163154 GSE100927 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE100927 GSE28829 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE28829 GSE11794 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE11794 and also in the Supplementary materials.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM4973394", "GSM4973395", "GSM4973397", "GSM4973398", "GSM4973400", "GSM4973401", "GSM4973403", "GSM4973404", "GSM4973406", "GSM4973408", "GSM4973409", "GSM4973411", "GSM4973412", "GSM4973414", "GSM4973415", "GSM4973417", "GSM4973418", "GSM4973419", "GSM4973421", "GSM4973422", "GSM4973424", "GSM4973425", "GSM4973427", "GSM4973429", "GSM4973430", "GSM4973432", "GSM4973433", "GSM4973435", "GSM4973436", "GSM4973438", "GSM4973439", "GSM4973440", "GSM4973441", "GSM4973443", "GSM4973444", "GSM4973445", "GSM4973446", "GSM4973448", "GSM4973449", "GSM4973451", "GSM4973452", "GSM4973454", "GSM4973456"], "sample_count": 43, "group_sizes": null, "group_sizes_basis": null, "platform": "6104", "taxon": "Homo sapiens", "title": "Maastricht Human Plaque Study (MaasHPS)", "resolution_checked_at": "2026-11-01T18:06:43Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "data:geo:GSE28829", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE28829", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE28829", "version": null, "note": "Publicly available datasets were analyzed in this study. This data can be found here: GSE163154 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE163154 GSE100927 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE100927 GSE28829 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE28829 GSE11794 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE11794 and also in the Supplementary materials.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "Publicly available datasets were analyzed in this study. This data can be found here: GSE163154 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE163154 GSE100927 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE100927 GSE28829 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE28829 GSE11794 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE11794 and also in the Supplementary materials.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM714070", "GSM714071", "GSM714072", "GSM714073", "GSM714074", "GSM714075", "GSM714076", "GSM714077", "GSM714078", "GSM714079", "GSM714080", "GSM714081", "GSM714082", "GSM714083", "GSM714084", "GSM714085", "GSM714086", "GSM714087", "GSM714088", "GSM714089", "GSM714090", "GSM714091", "GSM714092", "GSM714093", "GSM714094", "GSM714095", "GSM714096", "GSM714097", "GSM714098"], "sample_count": 29, "group_sizes": null, "group_sizes_basis": null, "platform": "570", "taxon": "Homo sapiens", "title": "Gene Expression in early and advanced atherosclerotic plaque from human carotid", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE100927 not downloaded", "asset:data:geo:GSE100927 licence not read", "asset:data:geo:GSE11794 not downloaded", "asset:data:geo:GSE11794 licence not read", "asset:data:geo:GSE163154 not downloaded", "asset:data:geo:GSE163154 licence not read", "asset:data:geo:GSE28829 not downloaded", "asset:data:geo:GSE28829 licence not read"]}, "analysis": {"state": "complete", "methods": [{"id": "method-1", "family": "survival_analysis", "specific": "cox_proportional_hazards", "label": "Survival analysis", "dsl_operations": ["cox_ph"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "The glmnet package in R was then used for a least absolute shrinkage and selection operator (LASSO) Cox regression analysis to find the genetic model with the best prognostic value."}}, {"id": "method-2", "family": "clustering", "specific": "hierarchical", "label": "Clustering", "dsl_operations": ["hierarchical_cluster"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["feature_matrix"], "evidence": {"score": 0.8, "band": "high", "quote": "dendrogram"}}, {"id": "method-3", "family": "network_analysis", "specific": "pathway_enrichment", "label": "Network / pathway analysis", "dsl_operations": ["pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.8, "band": "high", "quote": "GO enrichment"}}, {"id": "method-4", "family": "diagnostic_evaluation", "specific": "roc", "label": "Diagnostic test evaluation", "dsl_operations": ["confusion_counts", "roc_curve", "sensitivity_specificity", "solve_confusion_matrix", "classification_metrics", "published_precision_envelope"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["reference_standard_and_test"], "evidence": {"score": 0.7, "band": "medium", "quote": "ROC analysis"}}], "targets": [], "gaps": []}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["cox_ph"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: cox_proportional_hazards."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE163154", "GSE100927", "GSE28829", "GSE11794"], "resolved_accessions": ["GSE163154", "GSE100927", "GSE28829", "GSE11794"], "statements": ["Publicly available datasets were analyzed in this study. This data can be found here: GSE163154 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE163154 GSE100927 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE100927 GSE28829 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE28829 GSE11794 https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE11794 and also in the Supplementary materials."], "basis": "The paper names GSE163154, GSE100927, GSE28829, GSE11794 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. 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GO (Gene Ontology) and", "with non-plaque artery tissues (Figure 6C). Immunohistochemical staining results showed that the mean densit", "blotting. (D) Representative images of FBLN5 immunohistochemistry in carotid tissue. Supplementary Material Th"], "order_basis": "paper_text_order:1225", "id": "assay:1"}, {"role": "data_generation", "definition_id": "western_blot", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["es was confirmed by immunohistochemistry and western blotting. GO (Gene Ontology) and KEGG (Kyoto Encyclop", "of FBLN5 in human carotid plaque tissues by western blotting, indicating that FBLN5 was significantly dow", "otid atherosclerosis tissues was detected by western blotting. (D) Representative images of FBLN5 immunohi"], "order_basis": "paper_text_order:1250", "id": "assay:2"}, {"role": "data_generation", "definition_id": "animal_model", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["Expression at the Protein Level in Human and Rat Samples Using GSE28829 and GSE100927 dataset", "advanced plaque formation, we constructed a rat model by feeding rats subjected to carotid a", "ation, we constructed a rat model by feeding rats subjected to carotid artery ligation a high-"], "order_basis": "paper_text_order:8059", "id": "assay:3"}, {"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["cox_ph"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["The glmnet package in R was then used for a least absolute shrinkage and selection operator (LASSO) Cox regression analysis to find the genetic model with the best prognostic value."], "order_basis": "consumes_earlier_output", "id": "assay:4"}]}