Chinh Bkrong Nguyen1, Surendra Kumar2, Manuela Zucknick3, Vessela N Kristensen4, Johannes Gjerstad5, Hilde Nilsen6, Vegard Bruun Wyller7. 1. Institute of Clinical Medicine, University of Oslo, 0372 Oslo, Norway; Department of Pediatrics and Adolescent Health, Akershus University Hospital, 1478 Lørenskog, Norway. Electronic address: c.b.nguyen@medisin.uio.no. 2. Department of Genetics, Institute of Cancer Research, Oslo University Hospital Radiumhospitalet, 0310 Oslo, Norway. 3. Oslo Centre for Biostatistics and Epidemiology, Department of Biostatistics, Institute of Basic Medical Sciences, University of Oslo, 0317 Oslo, Norway. 4. Institute of Clinical Medicine, University of Oslo, 0372 Oslo, Norway; Department of Genetics, Institute of Cancer Research, Oslo University Hospital Radiumhospitalet, 0310 Oslo, Norway; Department of Clinical Molecular Biology, Akershus University Hospital, 1478 Lørenskog, Norway. 5. National Institute of Occupational Health, P.O. Box 8149 Dep., N-0033 Oslo, Norway. 6. Institute of Clinical Medicine, University of Oslo, 0372 Oslo, Norway; Department of Clinical Molecular Biology, Akershus University Hospital, 1478 Lørenskog, Norway. 7. Institute of Clinical Medicine, University of Oslo, 0372 Oslo, Norway; Department of Pediatrics and Adolescent Health, Akershus University Hospital, 1478 Lørenskog, Norway.
Abstract
BACKGROUND: Chronic Fatigue Syndrome (CFS) is one of the most important causes of disability among adolescents while limited knowledge exists on genetic determinants underlying disease pathophysiology. METHODS: We analyzed deregulated immune-gene modules using Pathifier software on whole blood gene expression data (29 CFS patients, 18 controls). Deconvolution of immune cell subtypes based on gene expression profile was performed using CIBERSORT. Supervised consensus clustering on pathway deregulation score (PDS) was used to define CFS subgroups. Associations between PDS and immune, neuroendocrine/autonomic and clinical markers were examined. The impact of plasma norepinephrine level on clinical markers over time was assessed in a larger cohort (91 patients). RESULTS: A group of 29 immune-gene sets was shown to differ patients from controls and detect subgroups within CFS. Group 1P (high PDS, low norepinephrine, low naïve CD4+ composition) had strong association with levels of serum C-reactive protein and Transforming Growth Factor-beta. Group 2P (low PDS, high norepinephrine, high naïve CD4+ composition) had strong associations with neuroendocrine/autonomic markers. The corresponding plasma norepinephrine level delineated 91 patients into two subgroups with significant differences in fatigue score. CONCLUSION: We identified 29 immune-gene sets linked to plasma norepinephrine level that could delineate CFS subgroups. Plasma norepinephrine stratification revealed that lower levels of norepinephrine were associated with higher fatigue. Our data suggests potential involvement of neuro-immune dysregulation and genetic stratification in CFS.
BACKGROUND:Chronic Fatigue Syndrome (CFS) is one of the most important causes of disability among adolescents while limited knowledge exists on genetic determinants underlying disease pathophysiology. METHODS: We analyzed deregulated immune-gene modules using Pathifier software on whole blood gene expression data (29 CFS patients, 18 controls). Deconvolution of immune cell subtypes based on gene expression profile was performed using CIBERSORT. Supervised consensus clustering on pathway deregulation score (PDS) was used to define CFS subgroups. Associations between PDS and immune, neuroendocrine/autonomic and clinical markers were examined. The impact of plasma norepinephrine level on clinical markers over time was assessed in a larger cohort (91 patients). RESULTS: A group of 29 immune-gene sets was shown to differ patients from controls and detect subgroups within CFS. Group 1P (high PDS, low norepinephrine, low naïve CD4+ composition) had strong association with levels of serum C-reactive protein and Transforming Growth Factor-beta. Group 2P (low PDS, high norepinephrine, high naïve CD4+ composition) had strong associations with neuroendocrine/autonomic markers. The corresponding plasma norepinephrine level delineated 91 patients into two subgroups with significant differences in fatigue score. CONCLUSION: We identified 29 immune-gene sets linked to plasma norepinephrine level that could delineate CFS subgroups. Plasma norepinephrine stratification revealed that lower levels of norepinephrine were associated with higher fatigue. Our data suggests potential involvement of neuro-immune dysregulation and genetic stratification in CFS.