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1929f9f7-3eb2-4aff-8f20-38db402cfff5 - samples

ABSTRACT: WES for Patient 9 to 14 of NIBIT-M4 clinical trial

PROVIDER: EGAD00001009700 | EGA |

REPOSITORIES: EGA

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Project 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.

Dataset Information

1929f9f7-3eb2-4aff-8f20-38db402cfff5 - samples

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