Identifying the most influential gene expression profile in distinguishing ANCA-associated vasculitis from healthy controls

Yanaoka, Haruyuki; Nagafuchi, Yasuo; Hanata, Norio; Takeshima, Yusuke; M, Ota; Suwa, Yuichi; Shirai, Hiroko; Sugimori, Yusuke; Okubo, Masaaki; Kobayashi, Satomi; Hatano, Hiroaki; Yamada, Shûzô; Tsuchida, Yoshiaki; Iwasaki, Yukiko; Sumitomo, Shuji; Shoda, Hirofumi; Okada, Masato; Okamura, Tomohisa; Yamamoto, Kazuhiko; Fujio, Keishi

doi:10.1016/j.jaut.2021.102617

Cited by 7 publications

(6 citation statements)

References 65 publications

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“…An iterative weighted gene correlation network and random forest analysis by Yanaoka et al identified a neutrophil module, comprising pro-inflammatory genes such as S100A12 and S100A9 and neutrophil extracellular traps (NET)osis-related genes, as the most important gene module in the differentiation of patients with AAV with healthy controls. 17 The neutrophil module correlated significantly with disease state as it was more abundant in patients with active AAV compared with patients in remission (p<0.05).…”

Section: Resultsmentioning

confidence: 95%

Non-invasive biomarkers of disease activity and organ damage in ANCA-associated vasculitis: a systematic review

Renson,

Kelly,

Benediktsson

et al. 2024

RMD Open

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BackgroundIn anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV), histopathological assessment of affected tissue is often necessary for diagnosis and assessment of disease extent. There is a requirement for validated non-invasive biomarkers to avoid the need for serial tissue biopsies.MethodsA systematic review of scientific databases from 2012 until present was performed to identify studies fulfilling the inclusion criteria. Studies were assessed for quality using the Strengthening the Reporting of Observational Studies in Epidemiology checklist for cohort, case–control and cross-sectional studies and the Risk of Bias Assessment tool for Non-randomised Studies, or the Cochrane Risk of Bias tool 2.0 for randomised controlled trials. A descriptive synthesis of the data for non-invasive (blood-based or urinary) biomarkers of AAV-related disease activity and organ damage was performed.ResultsTwenty-two high quality studies were included. These articles reported the value of blood-based and urinary biomarkers including anti-neutrophil cytoplasmic antibodies, immune cells, complement factors, gene expression profiles, cytokines, chemokines and other proteins in the assessment of disease activity and/or organ damage in patients with AAV. Many of these biomarkers involve the alternative complement pathway, neutrophil activation and macrophage activation.ConclusionThis is the first contemporary systematic review synthesising the value of non-invasive biomarkers of AAV-related disease activity and organ damage. The incorporation of individual markers in combined biomarker profiles might enhance clinical decision-making. Many unmet needs were identified; few studies involve oeosinophilic granulomatosis with polyangiitis and patients with childhood-onset AAV. Further validation of the candidate biomarkers is warranted in large prospective studies to bridge the existing knowledge gaps and apply precision health to systemic vasculitis.

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Section: Resultsmentioning

confidence: 95%

Non-invasive biomarkers of disease activity and organ damage in ANCA-associated vasculitis: a systematic review

Renson,

Kelly,

Benediktsson

et al. 2024

RMD Open

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“…Microarrays have been extensively implemented in medical research, such as biomarkers for disease diagnosis, and prognosis ( 28 , 29 ). Consequently, we investigated the differential genes in the kidney tissue of diabetic nephropathy and healthy people by microarray transcriptome analysis ( Figure 2 ).…”

Section: Discussionmentioning

confidence: 99%

APOC1 as a novel diagnostic biomarker for DN based on machine learning algorithms and experiment

Wang

et al. 2023

Front. Endocrinol.

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IntroductionDiabetic nephropathy is the leading cause of end-stage renal disease, which imposes a huge economic burden on individuals and society, but effective and reliable diagnostic markers are still not available.MethodsDifferentially expressed genes (DEGs) were characterized and functional enrichment analysis was performed in DN patients. Meanwhile, a weighted gene co-expression network (WGCNA) was also constructed. For further, algorithms Lasso and SVM-RFE were applied to screening the DN core secreted genes. Lastly, WB, IHC, IF, and Elias experiments were applied to demonstrate the hub gene expression in DN, and the research results were confirmed in mouse models and clinical specimens.Results17 hub secretion genes were identified in this research by analyzing the DEGs, the important module genes in WGCNA, and the secretion genes. 6 hub secretory genes (APOC1, CCL21, INHBA, RNASE6, TGFBI, VEGFC) were obtained by Lasso and SVM-RFE algorithms. APOC1 was discovered to exhibit elevated expression in renal tissue of a DN mouse model, and APOC1 is probably a core secretory gene in DN. Clinical data demonstrate that APOC1 expression is associated significantly with proteinuria and GFR in DN patients. APOC1 expression in the serum of DN patients was 1.358±0.1292μg/ml, compared to 0.3683±0.08119μg/ml in the healthy population. APOC1 was significantly elevated in the sera of DN patients and the difference was statistical significant (P > 0.001). The ROC curve of APOC1 in DN gave an AUC = 92.5%, sensitivity = 95%, and specificity = 97% (P < 0.001).ConclusionsOur research indicates that APOC1 might be a novel diagnostic biomarker for diabetic nephropathy for the first time and suggest that APOC1 may be available as a candidate intervention target for DN.

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“…Over the last decade, high-throughput microarray technology has been applied to investigate new core genes associated with ANCA-GN. 23 According to these transcriptome data, we obtained six hub genes ( PTPRC , CD86 , TLR2 , IL1B , CSF-1R , and CCL2 ) using logical methods. These hub genes expression levels are all significantly upregulated in ANCA-GN tissues.…”

Section: Discussionmentioning

confidence: 99%

Identification of potential biomarkers and therapeutic targets for antineutrophil cytoplasmic antibody-associated glomerulonephritis

Wang,

Cao,

Liu

et al. 2023

iScience

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Identifying the most influential gene expression profile in distinguishing ANCA-associated vasculitis from healthy controls

Cited by 7 publications

References 65 publications

Non-invasive biomarkers of disease activity and organ damage in ANCA-associated vasculitis: a systematic review

Non-invasive biomarkers of disease activity and organ damage in ANCA-associated vasculitis: a systematic review

APOC1 as a novel diagnostic biomarker for DN based on machine learning algorithms and experiment

Identification of potential biomarkers and therapeutic targets for antineutrophil cytoplasmic antibody-associated glomerulonephritis

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