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Data-Driven Cluster Analysis of Cerebrospinal Fluid Proteome and Associations with Clinical Phenotypes in Systemic Lupus Erythematosus

Grenmyr, Elsa LU orcid ; Zervides, Kristoffer LU orcid ; Najibi, Seyed Morteza LU orcid ; Gullstrand, Birgitta LU ; Welinder, Charlotte LU ; Nystedt, Jessika LU ; Nilsson, Petra C LU ; Sundgren, Pia C LU orcid ; Kahn, Robin LU and Jönsen, Andreas LU , et al. (2025) In ACR Open Rheumatology 7(9). p.1-13
Abstract

OBJECTIVE: To explore the cerebrospinal fluid (CSF) proteome in systemic lupus erythematosus (SLE) and the associations between the CSF proteomic patterns and clinical manifestations.

METHODS: CSF samples from 29 female outpatients with SLE were analyzed with label-free liquid chromatography tandem mass spectrometry. Inclusion and CSF collection were conducted irrespective of clinical manifestations and disease duration. Proteomic data were used for sample clustering and analyzed for clinical variance. Proteins were clustered using Weighted Gene Co-expression Correlation Network Analysis. Modules were biologically characterized and analyzed for correlation to the clinical dataset.

RESULTS: Three patient clusters were... (More)

OBJECTIVE: To explore the cerebrospinal fluid (CSF) proteome in systemic lupus erythematosus (SLE) and the associations between the CSF proteomic patterns and clinical manifestations.

METHODS: CSF samples from 29 female outpatients with SLE were analyzed with label-free liquid chromatography tandem mass spectrometry. Inclusion and CSF collection were conducted irrespective of clinical manifestations and disease duration. Proteomic data were used for sample clustering and analyzed for clinical variance. Proteins were clustered using Weighted Gene Co-expression Correlation Network Analysis. Modules were biologically characterized and analyzed for correlation to the clinical dataset.

RESULTS: Three patient clusters were identified. Cluster 1 was characterized by the highest frequency of nephritis, depression, and cognitive dysfunction. Cluster 2 showed the highest frequency of alopecia and Sjogren disease antigen A-antibodies (anti-SSA) and a low frequency of cognitive impairment. Cluster 3 had a higher frequency of autonomic neuropathy and headache. Six protein modules were identified (module 1 [M1]-M6). Modules were characterized by nervous tissue proteins (M1), central nervous system (CNS) lipoproteins (M2), macrophage proteins (M3), plasma proteins (M4), Ig (M5), and intracellular metabolic proteins (M6). M1 and M2 proteins were most abundant in cluster 1 and correlated with nephritis, depression, and cognitive impairment. Increased abundance of M4 and M5 proteins were most distinct in cluster 2 and inversely correlated to cognitive impairment and brain atrophy.

CONCLUSION: Patients clustered by their CSF proteomic pattern had different disease phenotypes. Nephritis and neuronal damage defined the group with higher levels of neuronal proteins in CSF, which may suggest shared pathogenetic pathways in SLE affecting the kidney and CNS.

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organization
publishing date
type
Contribution to journal
publication status
published
subject
in
ACR Open Rheumatology
volume
7
issue
9
article number
e70089
pages
1 - 13
publisher
Wiley
external identifiers
  • pmid:40874685
  • scopus:105014618559
ISSN
2578-5745
DOI
10.1002/acr2.70089
language
English
LU publication?
yes
additional info
© 2025 The Author(s). ACR Open Rheumatology published by Wiley Periodicals LLC on behalf of American College of Rheumatology.
id
2192140c-a482-481b-87d1-8bf30e76a7bc
date added to LUP
2025-09-05 16:39:17
date last changed
2025-09-09 03:32:32
@article{2192140c-a482-481b-87d1-8bf30e76a7bc,
  abstract     = {{<p>OBJECTIVE: To explore the cerebrospinal fluid (CSF) proteome in systemic lupus erythematosus (SLE) and the associations between the CSF proteomic patterns and clinical manifestations.</p><p>METHODS: CSF samples from 29 female outpatients with SLE were analyzed with label-free liquid chromatography tandem mass spectrometry. Inclusion and CSF collection were conducted irrespective of clinical manifestations and disease duration. Proteomic data were used for sample clustering and analyzed for clinical variance. Proteins were clustered using Weighted Gene Co-expression Correlation Network Analysis. Modules were biologically characterized and analyzed for correlation to the clinical dataset.</p><p>RESULTS: Three patient clusters were identified. Cluster 1 was characterized by the highest frequency of nephritis, depression, and cognitive dysfunction. Cluster 2 showed the highest frequency of alopecia and Sjogren disease antigen A-antibodies (anti-SSA) and a low frequency of cognitive impairment. Cluster 3 had a higher frequency of autonomic neuropathy and headache. Six protein modules were identified (module 1 [M1]-M6). Modules were characterized by nervous tissue proteins (M1), central nervous system (CNS) lipoproteins (M2), macrophage proteins (M3), plasma proteins (M4), Ig (M5), and intracellular metabolic proteins (M6). M1 and M2 proteins were most abundant in cluster 1 and correlated with nephritis, depression, and cognitive impairment. Increased abundance of M4 and M5 proteins were most distinct in cluster 2 and inversely correlated to cognitive impairment and brain atrophy.</p><p>CONCLUSION: Patients clustered by their CSF proteomic pattern had different disease phenotypes. Nephritis and neuronal damage defined the group with higher levels of neuronal proteins in CSF, which may suggest shared pathogenetic pathways in SLE affecting the kidney and CNS.</p>}},
  author       = {{Grenmyr, Elsa and Zervides, Kristoffer and Najibi, Seyed Morteza and Gullstrand, Birgitta and Welinder, Charlotte and Nystedt, Jessika and Nilsson, Petra C and Sundgren, Pia C and Kahn, Robin and Jönsen, Andreas and Bengtsson, Anders A}},
  issn         = {{2578-5745}},
  language     = {{eng}},
  number       = {{9}},
  pages        = {{1--13}},
  publisher    = {{Wiley}},
  series       = {{ACR Open Rheumatology}},
  title        = {{Data-Driven Cluster Analysis of Cerebrospinal Fluid Proteome and Associations with Clinical Phenotypes in Systemic Lupus Erythematosus}},
  url          = {{http://dx.doi.org/10.1002/acr2.70089}},
  doi          = {{10.1002/acr2.70089}},
  volume       = {{7}},
  year         = {{2025}},
}