PXD053422

PXD053422 is an original dataset announced via ProteomeXchange.

Title	Data-driven Clustering of the Cerebrospinal Fluid Proteome Reflects Disease Phenotypes of Systemic Lupus Erythematosus
Description	In this study, we employed a hypothesis-free and data-driven analytical approach to investigate the CSF proteome in 29 patients with SLE. Herein, our aim was to explore the CSF proteome with data-independent acquisition mass spectrometry (DIA-MS) and cluster SLE patients based on their CSF proteomic patterns. In addition, we aimed to investigate the relationship between protein patterns and a comprehensive clinical dataset including demographic variables, medical history, clinical rheumatologic and neurologic disease manifestations, neurocognitive functionality, cerebral MRI and laboratory measurements.The proteomic data was used for sample clustering and clusters were analyzed for clinical dataset variance. Proteins were clustered in modules using Weighted Gene Co-expression Correlation Network Analysis (WGCNA) and modules were biologically characterized and analyzed for correlation to the clinical dataset. 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 SSA-antibodies, and a low frequency of cognitive impairment. Cluster 3 had a higher frequency of autonomic neuropathy and lupus headache. Six protein modules were identified (M1-M6). The modules were characterized by nervous tissue proteins (M1), CNS lipoproteins (M2), macrophage proteins (M3), plasma proteins (M4), immunoglobulins (M5), and intracellular metabolic proteins (M6). Module 1 and M2 proteins were most abundant in patient cluster 1 and correlated with nephritis, depression and cognitive impairment. Increased abundance of M4 and M5 proteins were most distinct in patient cluster 2 and inversely correlated to cognitive impairment and brain atrophy. We conclude that 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.
HostingRepository	PRIDE
AnnounceDate	2026-02-09
AnnouncementXML	Submission_2026-02-08_16:17:48.650.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	ELSA GRENMYR
SpeciesList	scientific name: Homo sapiens (Human); NCBI TaxID: NEWT:9606;
ModificationList	acetylated residue; monohydroxylated residue; iodoacetamide derivatized residue
Instrument	timsTOF

Revision	Datetime	Status	ChangeLog Entry
0	2024-06-26 05:09:39	ID requested
⏵ 1	2026-02-08 16:17:52	announced

10.1002/acr2.70089;

Grenmyr E, Zervides K, Najibi SM, Gullstrand B, Welinder C, Nystedt J, Nilsson PC, Sundgren PC, Kahn R, J, ö, nsen A, Bengtsson AA, Data-Driven Cluster Analysis of Cerebrospinal Fluid Proteome and Associations with Clinical Phenotypes in Systemic Lupus Erythematosus. ACR Open Rheumatol, 7(9):e70089(2025) [pubmed]

submitter keyword: Human, Cerebrospinal fluid, Systemic Lupus Erythematosus

Elsa Grenmyr
contact affiliation	Rheumatology, Department of Clinical Science in Lund Medical Faculty, Lund University, Sweden
contact email	elsa.grenmyr@med.lu.se
lab head
ELSA GRENMYR
contact affiliation	Rheumatology Department of Clinical Science in Lund Lund University
contact email	elsa.grenmyr@med.lu.se
dataset submitter

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PRIDE project URI

• PRIDE
  1. PXD053422
     1. Label: PRIDE project
     2. Name: Data-driven Clustering of the Cerebrospinal Fluid Proteome Reflects Disease Phenotypes of Systemic Lupus Erythematosus