Send to

Choose Destination
Clin Proteomics. 2013 Mar 22;10(1):3. doi: 10.1186/1559-0275-10-3.

Quantitative proteomics for identifying biomarkers for Rabies.

Author information

McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, 733 N, Broadway, BRB 527, Baltimore, MD, 21205, USA.



Rabies is a fatal acute viral disease of the central nervous system, which is a serious public health problem in Asian and African countries. Based on the clinical presentation, rabies can be classified into encephalitic (furious) or paralytic (numb) rabies. Early diagnosis of this disease is particularly important as rabies is invariably fatal if adequate post exposure prophylaxis is not administered immediately following the bite.


In this study, we carried out a quantitative proteomic analysis of the human brain tissue from cases of encephalitic and paralytic rabies along with normal human brain tissues using an 8-plex isobaric tags for relative and absolute quantification (iTRAQ) strategy.


We identified 402 proteins, of which a number of proteins were differentially expressed between encephalitic and paralytic rabies, including several novel proteins. The differentially expressed molecules included karyopherin alpha 4 (KPNA4), which was overexpressed only in paralytic rabies, calcium calmodulin dependent kinase 2 alpha (CAMK2A), which was upregulated in paralytic rabies group and glutamate ammonia ligase (GLUL), which was overexpressed in paralytic as well as encephalitic rabies. We validated two of the upregulated molecules, GLUL and CAMK2A, by dot blot assays and further validated CAMK2A by immunohistochemistry. These molecules need to be further investigated in body fluids such as cerebrospinal fluid in a larger cohort of rabies cases to determine their potential use as antemortem diagnostic biomarkers in rabies. This is the first study to systematically profile clinical subtypes of human rabies using an iTRAQ quantitative proteomics approach.

Supplemental Content

Full text links

Icon for PubMed Central
Loading ...
Support Center