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pmid:35663995

Altered Cellular Immunity and Differentially Expressed Immune-Related Genes in Patients With Systemic Sclerosis-Associated Pulmonary Arterial Hypertension.

Jianxin Tu · Jinji Jin · Xiaowei Chen · Li Sun · Zhen Cai

Frontiers in immunology · 2022 doi:10.3389/fimmu.2022.868983

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complete

Experiment

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Data

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Analysis

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:35663995
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title
Altered Cellular Immunity and Differentially Expressed Immune-Related Genes in Patients With Systemic Sclerosis-Associated Pulmonary Arterial Hypertension.
doi
10.3389/fimmu.2022.868983
pmid
35663995
authors array · 5 items
[0]
Jianxin Tu
[1]
Jinji Jin
[2]
Xiaowei Chen
[3]
Li Sun
[4]
Zhen Cai
journal
Frontiers in immunology
year
2022
abstract
Systemic sclerosis (SSc) is the most common connective tissue disease causing pulmonary hypertension (PAH). However, the cause and potential immune molecular events associated with PAH are still unclear. Therefore, it is particularly essential to analyze the changes in SSc-PAH-related immune cells and their immune-related genes. Three microarray datasets (GSE22356, GSE33463, and GSE19617) were obtained by the Gene Expression Omnibus (GEO). Compared with SSc, we found neutrophils have a statistically higher abundance, while T-cell CD4 naive and T-cell CD4 memory resting have a statistically lower abundance in peripheral blood mononuclear cells (PBMCs). Moreover, the results of Gene Set Enrichment Analysis (GSEA) showed there is a differential enrichment of multiple pathways between SSc and SSc-PAH. By combining differentiated expressed genes (DEGs) and immune-related genes (IRGs), fifteen IRGs were selected. In addition, we also analyzed the first five rich Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and the most abundant Gene Ontology (GO)-molecular functional terms. Furthermore, interleukin-7 receptor (IL-7R), tyrosine-protein kinase (LCK), histone deacetylase 1 (HDAC1), and epidermal growth factor receptor (EGFR) genes were identified as hub genes via protein-protein interaction (PPI) network analysis. The Comparative Toxic Genomics Database (CTD) analysis result showed that LCK, HDAC1, and EGFR have a higher score with SSc. Coexpression network analysis confirmed that IL-7R, LCK, and HDAC1 are key genes related to immune regulation in SSc without PAH and are involved in T-cell immune regulation. Subsequently, using GSE22356 and GSE33463 as the test sets and GSE19617 as the verification set, it was verified that the mRNA expression levels of the three central genes of SSc-PAH were significantly lower than those of the SSc without PAH samples. Consistent with previous predictions, the expressions of IL-7R, LCK, and HDAC1 are positively correlated with the numbers of T-cell CD4 naive and T-cell CD4 memory, while the expressions of IL-7R and LCK are negatively correlated with the numbers of neutrophils in the peripheral blood. Therefore, this evidence may suggest that these three immune-related genes: IL-7R, LCK, and HDAC1, may be highly related to the immunological changes in SSc-PAH. These three molecules can reduce T cells in SSc-PAH PBMCs through the regulation of T-cell activation, which suggests that these three molecules may be involved in the development of SSc-PAH. Meanwhile, the low expression of IL-7R, LCK, and HDAC1 detected in the peripheral blood of SSc may indicate the possibility of PAH and hopefully become a biomarker for the early detection of SSc-PAH. Finally, 49 target miRNAs of 3 specifically expressed hub genes were obtained, and 49 mRNA-miRNA pairs were identified, which provided directions for our further research.
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Differentially expressed genes (DEGs) between SSc and SSc-PAH samples were identified by the R package “Limma.”
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sections[6] "Differentially Expressed Genes, Enrichment Analysis, and Gene Set Enrichment Analysis" paragraph 2
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Differentially expressed genes (DEGs) between SSc and SSc-PAH samples were identified by the R package “Limma.”
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The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://www.ncbi.nlm.nih.gov/geo/, GSE22356; https://www.ncbi.nlm.nih.gov/geo/, GSE33463; and https://www.ncbi.nlm.nih.gov/geo/, GSE19617.
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sections[21] "Data Availability Statement" paragraph 2
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The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://www.ncbi.nlm.nih.gov/geo/, GSE22356; https://www.ncbi.nlm.nih.gov/geo/, GSE33463; and https://www.ncbi.nlm.nih.gov/geo/, GSE19617.
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As shown in Figures 6A, B , compared with the SSc samples, the mRNA expression levels of the 3 hub genes in the SSc-PAH were significantly decreased (p < 0.05).
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As shown in Figures 6A, B , compared with the SSc samples, the mRNA expression levels of the 3 hub genes in the SSc-PAH were significantly decreased (p < 0.05).
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sections[18] "Identification of Hub Genes" paragraph 2
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As shown in Figures 6A, B , compared with the SSc samples, the mRNA expression levels of the 3 hub genes in the SSc-PAH were significantly decreased (p < 0.05).
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As shown in Figures 6A, B , compared with the SSc samples, the mRNA expression levels of the 3 hub genes in the SSc-PAH were significantly decreased (p < 0.05).
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The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://www.ncbi.nlm.nih.gov/geo/, GSE22356; https://www.ncbi.nlm.nih.gov/geo/, GSE33463; and https://www.ncbi.nlm.nih.gov/geo/, GSE19617.
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The paper names GSE22356, GSE33463, GSE19617 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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cells and their immune-related genes. Three microarray datasets (GSE22356, GSE33463, and GSE19617)
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Differentially expressed genes (DEGs) between SSc and SSc-PAH samples were identified by the R package “Limma.”
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{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35663995", "kind": "science-record", "revision": 5, "content_hash": "sha256:90115146838846e3fa41f033d3adc9f939fd96095d6e48f05a732adfdee9c59f", "created_at": "2026-11-01T18:14:36Z", "updated_at": "2026-11-01T22:49:13Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Altered Cellular Immunity and Differentially Expressed Immune-Related Genes in Patients With Systemic Sclerosis-Associated Pulmonary Arterial Hypertension.", "doi": "10.3389/fimmu.2022.868983", "pmid": "35663995", "authors": ["Jianxin Tu", "Jinji Jin", "Xiaowei Chen", "Li Sun", "Zhen Cai"], "journal": "Frontiers in immunology", "year": 2022, "abstract": "Systemic sclerosis (SSc) is the most common connective tissue disease causing pulmonary hypertension (PAH). However, the cause and potential immune molecular events associated with PAH are still unclear. Therefore, it is particularly essential to analyze the changes in SSc-PAH-related immune cells and their immune-related genes. Three microarray datasets (GSE22356, GSE33463, and GSE19617) were obtained by the Gene Expression Omnibus (GEO). Compared with SSc, we found neutrophils have a statistically higher abundance, while T-cell CD4 naive and T-cell CD4 memory resting have a statistically lower abundance in peripheral blood mononuclear cells (PBMCs). Moreover, the results of Gene Set Enrichment Analysis (GSEA) showed there is a differential enrichment of multiple pathways between SSc and SSc-PAH. By combining differentiated expressed genes (DEGs) and immune-related genes (IRGs), fifteen IRGs were selected. In addition, we also analyzed the first five rich Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and the most abundant Gene Ontology (GO)-molecular functional terms. Furthermore, interleukin-7 receptor (IL-7R), tyrosine-protein kinase (LCK), histone deacetylase 1 (HDAC1), and epidermal growth factor receptor (EGFR) genes were identified as hub genes via protein-protein interaction (PPI) network analysis. The Comparative Toxic Genomics Database (CTD) analysis result showed that LCK, HDAC1, and EGFR have a higher score with SSc. Coexpression network analysis confirmed that IL-7R, LCK, and HDAC1 are key genes related to immune regulation in SSc without PAH and are involved in T-cell immune regulation. Subsequently, using GSE22356 and GSE33463 as the test sets and GSE19617 as the verification set, it was verified that the mRNA expression levels of the three central genes of SSc-PAH were significantly lower than those of the SSc without PAH samples. Consistent with previous predictions, the expressions of IL-7R, LCK, and HDAC1 are positively correlated with the numbers of T-cell CD4 naive and T-cell CD4 memory, while the expressions of IL-7R and LCK are negatively correlated with the numbers of neutrophils in the peripheral blood. Therefore, this evidence may suggest that these three immune-related genes: IL-7R, LCK, and HDAC1, may be highly related to the immunological changes in SSc-PAH. These three molecules can reduce T cells in SSc-PAH PBMCs through the regulation of T-cell activation, which suggests that these three molecules may be involved in the development of SSc-PAH. Meanwhile, the low expression of IL-7R, LCK, and HDAC1 detected in the peripheral blood of SSc may indicate the possibility of PAH and hopefully become a biomarker for the early detection of SSc-PAH. Finally, 49 target miRNAs of 3 specifically expressed hub genes were obtained, and 49 mRNA-miRNA pairs were identified, which provided directions for our further research.", "claims": [{"id": "claim-method", "statement": "Differentially expressed genes (DEGs) between SSc and SSc-PAH samples were identified by the R package “Limma.”", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35663995", "locator": "sections[6] \"Differentially Expressed Genes, Enrichment Analysis, and Gene Set Enrichment Analysis\" paragraph 2", "quote": "Differentially expressed genes (DEGs) between SSc and SSc-PAH samples were identified by the R package “Limma.”"}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://www.ncbi.nlm.nih.gov/geo/, GSE22356; https://www.ncbi.nlm.nih.gov/geo/, GSE33463; and https://www.ncbi.nlm.nih.gov/geo/, GSE19617.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35663995", "locator": "sections[21] \"Data Availability Statement\" paragraph 2", "quote": "The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://www.ncbi.nlm.nih.gov/geo/, GSE22356; https://www.ncbi.nlm.nih.gov/geo/, GSE33463; and https://www.ncbi.nlm.nih.gov/geo/, GSE19617."}], "state": "complete"}, {"id": "claim-target-result", "statement": "As shown in Figures 6A, B , compared with the SSc samples, the mRNA expression levels of the 3 hub genes in the SSc-PAH were significantly decreased (p < 0.05).", "kind": "quantitative", "target": {"value": 0.05, "unit": "p-value", "tolerance": null, "source": "As shown in Figures 6A, B , compared with the SSc samples, the mRNA expression levels of the 3 hub genes in the SSc-PAH were significantly decreased (p < 0.05)."}, "evidence": [{"asset": "source:pmid:35663995", "locator": "sections[18] \"Identification of Hub Genes\" paragraph 2", "quote": "As shown in Figures 6A, B , compared with the SSc samples, the mRNA expression levels of the 3 hub genes in the SSc-PAH were significantly decreased (p < 0.05)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "As shown in Figures 6A, B , compared with the SSc samples, the mRNA expression levels of the 3 hub genes in the SSc-PAH were significantly decreased (p < 0.05).", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:35663995"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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A run that reproduces the effect is judged against this threshold."}], "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": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: limma_voom."}, "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": ["GSE22356", "GSE33463", "GSE19617"], "resolved_accessions": ["GSE22356", "GSE33463", "GSE19617"], "statements": ["The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://www.ncbi.nlm.nih.gov/geo/, GSE22356; https://www.ncbi.nlm.nih.gov/geo/, GSE33463; and https://www.ncbi.nlm.nih.gov/geo/, GSE19617."], "basis": "The paper names GSE22356, GSE33463, GSE19617 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "assets": ["source:pmid:35663995", "data:geo:GSE19617"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE19617"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T17:49:08Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 16810, "completion_tokens": 1561, "cached_tokens": 128}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:35663995", "type": "paper", "label": "pmid:35663995"}, {"id": "source:pmid:35663995", "type": "manuscript", "label": "PMID 35663995 full text"}, {"id": "data:geo:GSE19617", "type": "dataset", "label": "GEO GSE19617"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:35663995", "type": "paper", "label": "pmid:35663995"}, {"id": "source:pmid:35663995", "type": "manuscript", "label": "PMID 35663995 full text"}, {"id": "data:geo:GSE19617", "type": "dataset", "label": "GEO GSE19617"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-35663995", "type": "extraction", "used": ["source:pmid:35663995"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE19617", "type": "accession_resolution", "used": ["data:geo:GSE19617"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:35663995", "parent_hash": "sha256:ab13f92213e8316e1583bb4eaf2feb5e767aba37ba03e1401ea67bad44bb391b", "fork_of": null, "generation": 4}, "gaps": ["asset:data:geo:GSE19617 licence not read", "asset:data:geo:GSE19617 not downloaded", "asset:data:geo:GSE22356 licence not read", "asset:data:geo:GSE22356 not downloaded", "asset:data:geo:GSE33463 licence not read", "asset:data:geo:GSE33463 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "microarray", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["cells and their immune-related genes. Three microarray datasets (GSE22356, GSE33463, and GSE19617)"], "order_basis": "paper_text_order:449", "id": "assay:1"}, {"role": "analysis", "definition_id": "differential_expression", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["normalise_counts", "differential_expression_fit", "fdr_bh"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["Differentially expressed genes (DEGs) between SSc and SSc-PAH samples were identified by the R package “Limma.”"], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}