Large-Scale Proteome Profiling Identifies Biomarkers Associated with Suspected Neurosyphilis Diagnosis

Area of Science:

• Neuroscience
• Infectious Diseases
• Biomarker Discovery

Background:

• Neurosyphilis (NS), a central nervous system (CNS) infection by Treponema pallidum, presents diverse symptoms and is often misdiagnosed due to a lack of definitive diagnostic tests.
• Delayed diagnosis of NS can result in severe, irreversible organ damage, highlighting the urgent need for reliable diagnostic markers.

Purpose of the Study:

• To identify novel diagnostic biomarkers for Neurosyphilis (NS) using proteomic and machine learning approaches.
• To gain insights into the inflammatory mechanisms underlying NS pathogenesis in the CNS.

Main Methods:

• Proteomic analysis and machine learning models were applied to 223 cerebrospinal fluid (CSF) samples to identify potential NS diagnostic markers.
• Multicenter validation was performed on an additional 115 CSF samples to confirm the diagnostic utility of identified biomarkers.

Main Results:

• Three biomarkers—SEMA7A, SERPINA3, and ITIH4—were identified and validated as significant contributors to NS diagnosis in CSF.
• The study provides insights into the pathogenesis of NS and associated inflammatory responses within brain tissue.

Conclusions:

• The validated biomarkers (SEMA7A, SERPINA3, ITIH4) show promise as effective tools for assisting in the diagnosis of Neurosyphilis (NS).
• Findings may inform future therapeutic strategies and drug discovery for NS patients, improving treatment outcomes.