Herpes Simplex Encephalopathy
and the Development of ME / CFS
STUDY AIM
The purpose of this study is to better understand what may cause the onset of ME/CFS after an initial infection.
LEAD INVESTIGATORS
- Jonas Bergquist, MD, PhD
- Wenzhong Xiao, PhD
- Chris Armstrong, PhD
UPDATES AND POTENTIAL
- Based on data analysis, the team has identified a central mechanism for neuronal dysregulation that shows up early in the disease process, and we could predict those individuals with the most severe outcomes. This work has been published: Nääs, A., et al. (2023). Temporal pathway analysis of cerebrospinal fluid proteome in herpes simplex encephalitis. Infectious Diseases, 55(10), 694-705. doi:10.1080/23744235.2023.2230281
- Plasma metabolomics data have been analysed and resulted in close to 1,500 metabolites or metabolic ratios. Clinical data sent to Melbourne for additional analysis.
- The OMF computation team will assist with the multi-omics correlation.
STUDY HYPOTHESIS AND DESCRIPTION
The further understanding of the post-viral fatigue phenomenon that many HSE patients present with could give new insights in the initial episode of Myalgic Encephalomyelitis/ Chronic Fatigue Syndrome (ME / CFS) since very many of the patients (70-80%) reports on an initial infection (eg mononucleosis) in the onset of the disease.
Our findings could give predictive evidence of long-term neurocognitive outcome in HSE, and suggest a causative chain of events where brain tissue damage increases the risk of subsequent prolongation of CSF inflammation and post-viral fatigue. The data could provide guidance for a future intervention study of immunosuppressive therapy administered in the recovery phase of HSE and other viral infections with neurological sequelae.
OBJECTIVES
- Analyse cerebrospinal fluid for biomarkers of brain injury, inflammation and synaptic damage using proteomics.
- Conduct metabolic profiling of plasma concentration.
- Correlate CSF biomarkers and MDRS followed by evaluation of post-viral fatigue and ME/CFS
- Conduct a merged multi-omics evaluation of the data including both proteomic and metabolomic data and the correlation between the two.
