Title

Serum Nogo - A as a predictor of neurological recovery in spinal cord injury

Authors

Shah Waliullah^1,*, Akash Singh¹, Devarshi Rastogi¹, Deepak Kumar¹, Ashish Kumar¹, Amar Chandra Sharma², Zeenat Ara¹ & Uday Raj¹

Affiliation

¹Department of Orthopaedic Surgery, King George’s Medical University, Lucknow, Uttar Pradesh-226003, India; ²Department of Trauma Surgery, King George’s Medical University, Lucknow, Uttar Pradesh-226003, India; *Corresponding author

Email

Shah Waliullah - E-mail: shahwali2008@gmail.com
Akash Singh - E-mail: akash.84493@gmail.com
Devarshi Rastogi - E-mail: drdevrastogi@gmail.com

Deepak Kumar - E-mail: drdeepakkumarkgmc@gmail.com
Ashish Kumar - E-mail: drashish_kumar20202@yahoo.com
Amar Chandra Sharma - E-mail: amar.kgmu1@gmail.com
Zeenat Farghan - E-mail: zeenatfarghan123@gmail.com
Uday Raj - E-mail: rajuday910@gmail.com

Article Type

Research Article

Date

Received September 1, 2025; Revised September 30, 2025; Accepted September 30, 2025, Published September 30, 2025

Abstract

Spinal Cord Injury (SCI) leads to severe neurological impairment due to irreversible damage to spinal axons and limited Spinal Cord Injury (SCI) causes severe neurological impairment due to irreversible axonal damage and limited regenerative capacity. Current treatments, including surgical decompression and neuroprotective agents, have limited effectiveness, with no consensus on the optimal therapeutic combination. Anti-Nogo-A therapies show promise in preclinical studies, but their clinical efficacy remains uncertain. Emerging evidence suggests that serum Nogo-A levels may serve as prognostic biomarkers for neurological recovery in SCI patients. This study explores the potential of targeting the Nogo A/Nogo receptor pathway to enhance axonal regeneration and support the development of personalized treatment strategies.

Keywords

Spinal cord injury, neurological recovery, serum nogo-a, prognostic biomarker and therapeutic target, receptor antagonists and gene therapy.

Citation

Waliullah et al. Bioinformation 21(9): 3387-3390 (2025)

Edited by

P Kangueane

ISSN

0973-2063

Publisher

Biomedical Informatics

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.