Gene expression pathways across multiple tissues in antineutrophil cytoplasmic antibody-associated vasculitis reveal core pathways of disease pathology

Marcia A. Friedman, Dongseok Choi, Stephen Planck, James (Jim) Rosenbaum, Cailin Sibley

Research output: Contribution to journalArticle

Abstract

Objective. To identify commonalities in gene expression data across all antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) tissues thus far characterized. Methods. Gene expression data were collected from the 3 AAV tissues thus far characterized (orbit, peripheral leukocytes, and sinus brushings). These data were analyzed to identify commonly expressed genes and disease pathways. The pathways data were adjusted for multiple comparisons using a combined local false discovery rate, which estimates the probability of a false discovery of a given pathway in all 3 tissues analyzed. Results. Only 4 genes were upregulated in all 3 tissues - IL1RN, TLR2, SLC11A1, and MMP9. After multiple comparison adjustments, the network pathway analysis revealed 28 pathways associated with all 3 tissues. The most strongly associated pathway for all 3 tissues was the neutrophil degranulation pathway [multidimensional local false discovery (md-locfdr) = 1.05 × 10-12], followed by the osteoclast differentiation (md-locfdr = 3.8 × 10-05), cell surface interactions at the vascular wall (md-locfdr = 4.2 × 10-04), signaling by interleukins (md-locfdr = 6.1 × 10-04), and phagosome (md-locfdr = 0.003) pathways. There were no downregulated genes or pathways common to all 3 tissues. Conclusion. This analysis identified individual genes and pathways of disease common to all AAV tissues thus far characterized. The use of a network pathway analysis allowed us to identify pathologic mechanisms that were not readily apparent in the commonly expressed genes alone. Many of these pathways are consistent with current theories about infectious drivers and the crossroads of innate and adaptive immune mechanisms. In addition, this analysis highlights novel pathways, such as vessel wall interactions and platelet activation, which require further investigation.

Original languageEnglish (US)
Pages (from-to)609-615
Number of pages7
JournalJournal of Rheumatology
Volume46
Issue number6
DOIs
StatePublished - Jan 1 2019

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Antineutrophil Cytoplasmic Antibodies
Vasculitis
Pathology
Gene Expression
Anti-Neutrophil Cytoplasmic Antibody-Associated Vasculitis
Genes
Phagosomes
Interleukins
Platelet Activation
Orbit
Osteoclasts
Cell Communication
Blood Vessels
Neutrophils
Leukocytes
Down-Regulation

Keywords

  • Antineutrophil Cytoplasmic Antibody-associated Vasculitis
  • Gene Expression
  • Granulomatosis With Polyangiitis
  • Metaanalysis
  • Microscopic Polyangiitis
  • Vasculitis

ASJC Scopus subject areas

  • Rheumatology
  • Immunology and Allergy
  • Immunology

Cite this

@article{bc8b6d0f45cd47018e598444d9430e2e,
title = "Gene expression pathways across multiple tissues in antineutrophil cytoplasmic antibody-associated vasculitis reveal core pathways of disease pathology",
abstract = "Objective. To identify commonalities in gene expression data across all antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) tissues thus far characterized. Methods. Gene expression data were collected from the 3 AAV tissues thus far characterized (orbit, peripheral leukocytes, and sinus brushings). These data were analyzed to identify commonly expressed genes and disease pathways. The pathways data were adjusted for multiple comparisons using a combined local false discovery rate, which estimates the probability of a false discovery of a given pathway in all 3 tissues analyzed. Results. Only 4 genes were upregulated in all 3 tissues - IL1RN, TLR2, SLC11A1, and MMP9. After multiple comparison adjustments, the network pathway analysis revealed 28 pathways associated with all 3 tissues. The most strongly associated pathway for all 3 tissues was the neutrophil degranulation pathway [multidimensional local false discovery (md-locfdr) = 1.05 × 10-12], followed by the osteoclast differentiation (md-locfdr = 3.8 × 10-05), cell surface interactions at the vascular wall (md-locfdr = 4.2 × 10-04), signaling by interleukins (md-locfdr = 6.1 × 10-04), and phagosome (md-locfdr = 0.003) pathways. There were no downregulated genes or pathways common to all 3 tissues. Conclusion. This analysis identified individual genes and pathways of disease common to all AAV tissues thus far characterized. The use of a network pathway analysis allowed us to identify pathologic mechanisms that were not readily apparent in the commonly expressed genes alone. Many of these pathways are consistent with current theories about infectious drivers and the crossroads of innate and adaptive immune mechanisms. In addition, this analysis highlights novel pathways, such as vessel wall interactions and platelet activation, which require further investigation.",
keywords = "Antineutrophil Cytoplasmic Antibody-associated Vasculitis, Gene Expression, Granulomatosis With Polyangiitis, Metaanalysis, Microscopic Polyangiitis, Vasculitis",
author = "Friedman, {Marcia A.} and Dongseok Choi and Stephen Planck and Rosenbaum, {James (Jim)} and Cailin Sibley",
year = "2019",
month = "1",
day = "1",
doi = "10.3899/jrheum.180455",
language = "English (US)",
volume = "46",
pages = "609--615",
journal = "Journal of Rheumatology",
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TY - JOUR

T1 - Gene expression pathways across multiple tissues in antineutrophil cytoplasmic antibody-associated vasculitis reveal core pathways of disease pathology

AU - Friedman, Marcia A.

AU - Choi, Dongseok

AU - Planck, Stephen

AU - Rosenbaum, James (Jim)

AU - Sibley, Cailin

PY - 2019/1/1

Y1 - 2019/1/1

N2 - Objective. To identify commonalities in gene expression data across all antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) tissues thus far characterized. Methods. Gene expression data were collected from the 3 AAV tissues thus far characterized (orbit, peripheral leukocytes, and sinus brushings). These data were analyzed to identify commonly expressed genes and disease pathways. The pathways data were adjusted for multiple comparisons using a combined local false discovery rate, which estimates the probability of a false discovery of a given pathway in all 3 tissues analyzed. Results. Only 4 genes were upregulated in all 3 tissues - IL1RN, TLR2, SLC11A1, and MMP9. After multiple comparison adjustments, the network pathway analysis revealed 28 pathways associated with all 3 tissues. The most strongly associated pathway for all 3 tissues was the neutrophil degranulation pathway [multidimensional local false discovery (md-locfdr) = 1.05 × 10-12], followed by the osteoclast differentiation (md-locfdr = 3.8 × 10-05), cell surface interactions at the vascular wall (md-locfdr = 4.2 × 10-04), signaling by interleukins (md-locfdr = 6.1 × 10-04), and phagosome (md-locfdr = 0.003) pathways. There were no downregulated genes or pathways common to all 3 tissues. Conclusion. This analysis identified individual genes and pathways of disease common to all AAV tissues thus far characterized. The use of a network pathway analysis allowed us to identify pathologic mechanisms that were not readily apparent in the commonly expressed genes alone. Many of these pathways are consistent with current theories about infectious drivers and the crossroads of innate and adaptive immune mechanisms. In addition, this analysis highlights novel pathways, such as vessel wall interactions and platelet activation, which require further investigation.

AB - Objective. To identify commonalities in gene expression data across all antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) tissues thus far characterized. Methods. Gene expression data were collected from the 3 AAV tissues thus far characterized (orbit, peripheral leukocytes, and sinus brushings). These data were analyzed to identify commonly expressed genes and disease pathways. The pathways data were adjusted for multiple comparisons using a combined local false discovery rate, which estimates the probability of a false discovery of a given pathway in all 3 tissues analyzed. Results. Only 4 genes were upregulated in all 3 tissues - IL1RN, TLR2, SLC11A1, and MMP9. After multiple comparison adjustments, the network pathway analysis revealed 28 pathways associated with all 3 tissues. The most strongly associated pathway for all 3 tissues was the neutrophil degranulation pathway [multidimensional local false discovery (md-locfdr) = 1.05 × 10-12], followed by the osteoclast differentiation (md-locfdr = 3.8 × 10-05), cell surface interactions at the vascular wall (md-locfdr = 4.2 × 10-04), signaling by interleukins (md-locfdr = 6.1 × 10-04), and phagosome (md-locfdr = 0.003) pathways. There were no downregulated genes or pathways common to all 3 tissues. Conclusion. This analysis identified individual genes and pathways of disease common to all AAV tissues thus far characterized. The use of a network pathway analysis allowed us to identify pathologic mechanisms that were not readily apparent in the commonly expressed genes alone. Many of these pathways are consistent with current theories about infectious drivers and the crossroads of innate and adaptive immune mechanisms. In addition, this analysis highlights novel pathways, such as vessel wall interactions and platelet activation, which require further investigation.

KW - Antineutrophil Cytoplasmic Antibody-associated Vasculitis

KW - Gene Expression

KW - Granulomatosis With Polyangiitis

KW - Metaanalysis

KW - Microscopic Polyangiitis

KW - Vasculitis

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