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. 2017 May 11;15(1):102.
doi: 10.1186/s12967-017-1201-0.

Whole blood gene expression in adolescent chronic fatigue syndrome: an exploratory cross-sectional study suggesting altered B cell differentiation and survival

Chinh Bkrong Nguyen  1   2 , Lene Alsøe  3 , Jessica M Lindvall  4 , Dag Sulheim  5 , Even Fagermoen  6 , Anette Winger  7 , Mari Kaarbø  8 , Hilde Nilsen  3 , Vegard Bruun Wyller  9   10
Affiliations

Whole blood gene expression in adolescent chronic fatigue syndrome: an exploratory cross-sectional study suggesting altered B cell differentiation and survival

Chinh Bkrong Nguyen et al. J Transl Med. .

Abstract

Background: Chronic fatigue syndrome (CFS) is a prevalent and disabling condition affecting adolescents. The pathophysiology is poorly understood, but immune alterations might be an important component. This study compared whole blood gene expression in adolescent CFS patients and healthy controls, and explored associations between gene expression and neuroendocrine markers, immune markers and clinical markers within the CFS group.

Methods: CFS patients (12-18 years old) were recruited nation-wide to a single referral center as part of the NorCAPITAL project. A broad case definition of CFS was applied, requiring 3 months of unexplained, disabling chronic/relapsing fatigue of new onset, whereas no accompanying symptoms were necessary. Healthy controls having comparable distribution of gender and age were recruited from local schools. Whole blood samples were subjected to RNA sequencing. Immune markers were blood leukocyte counts, plasma cytokines, serum C-reactive protein and immunoglobulins. Neuroendocrine markers encompassed plasma and urine levels of catecholamines and cortisol, as well as heart rate variability indices. Clinical markers consisted of questionnaire scores for symptoms of post-exertional malaise, inflammation, fatigue, depression and trait anxiety, as well as activity recordings.

Results: A total of 29 CFS patients and 18 healthy controls were included. We identified 176 genes as differentially expressed in patients compared to controls, adjusting for age and gender factors. Gene set enrichment analyses suggested impairment of B cell differentiation and survival, as well as enhancement of innate antiviral responses and inflammation in the CFS group. A pattern of co-expression could be identified, and this pattern, as well as single gene transcripts, was significantly associated with indices of autonomic nervous activity, plasma cortisol, and blood monocyte and eosinophil counts. Also, an association with symptoms of post-exertional malaise was demonstrated.

Conclusion: Adolescent CFS is characterized by differential gene expression pattern in whole blood suggestive of impaired B cell differentiation and survival, and enhanced innate antiviral responses and inflammation. This expression pattern is associated with neuroendocrine markers of altered HPA axis and autonomic nervous activity, and with symptoms of post-exertional malaise. Trial registration Clinical Trials NCT01040429.

Keywords: Adolescent; B cell differentiation; B cell survival; Chronic fatigue syndrome; Gene expression; Inflammation.

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Figures

Fig. 1
Fig. 1
a Hierarchal clustering of all 47 samples based on the rlog value [48]. The color density at the top right panel reflects the Euclidean distance. P CFS patients, C healthy controls. b Output of variation removal of our RNA-Seq data using RUVSeq. principle component analysis (PCA) is performed without using any differently expressed genes, and demonstrates relatively good separation between CFS patients (orange) and healthy controls (green). c Relative log expression (RLE) plot shows the distribution of read counts across all samples centered around zero. The y axis corresponds to the deviation of each RLE per gene per sample compared to median RLE over all samples (x axis). (CFS patients orange. Healthy controls green)
Fig. 2
Fig. 2
a Volcano plot showing the alignment between DESeq p values versus log2 fold changes of CFS patients against healthy controls. Red points indicate DEGs with a log2 fold change >0.2 and p < 0.0016 (Table 2). b Hierarchical clustering of all 176 differently expressed genes. The heatmap was constructed based on the deviation of gene expression levels of individual sample from averaged gene expression across all samples (Table 2). The color code for variance value is shown in the upper right corner of the panel
Fig. 3
Fig. 3
RT-qPCR results of 12 selected transcripts. CFS patients and controls are plotted on the x axis and relative fold change difference normalized against GAPDH is plotted on the y axis. For three transcript, the differential expression between patients and controls were below or close to the level of significance (APOBEC3A, p = 0.0005; PLSCR1, p = 0.0498; IL1RN, p = 0.0507)
Fig. 4
Fig. 4
The RNA-Seq identified five down-regulated genes encoding proteins associated with B cell differentiation and survival. FLT3 encodes FLT3 (fms-related tyrosine kinase 3), which is important during the very early stages of differentiation in the bone marrow of the hematopoietic stem cell into the Pro-B cell. EBF1 encodes EBF (early B-cell factor 1), which is important during all stages of B cell differentiation except for the plasma cell. CD79A encodes Igα (immunoglobulin-associated alpha), which is a co-molecule in the membrane bound Pre-BCR and the BCR, and ensures a functional receptor. TNFRSF13C encodes BAFFR (B-cell activating factor receptor), which is important for the peripheral B cells to receive survival signal. CXCR5 encodes CXCR5 [chemokine (C-X-C motif) receptor 5], which ensures that matured B cells migrate to B cell follicles of the spleen and Peyer patches. Assuming that the down-regulation of these genes is reflected at the protein and pathway level, our data suggest that the efficiency of B cell differentiation is impaired and that their survival is reduced in the CFS. HSC hematopoietic stem cell, BCR B cell receptor, B B cell, Ig immunoglobulin
Fig. 5
Fig. 5
Multiple regression model on the associations between neuroendocrine markers (upper row), immune markers (middle row) and co-expression of genes as captured in Factor 3 from a principal component analysis (lower row). LF/HF, B-Mono, B-Eos and P-Cort are all independently and significantly associated with Factor 3, explaining 67% of the total variance. For LF/HF, B-Mono and P-Cort, the association is positive; for B-Eos the association is negative. In addition, LF/HF is significantly associated with B-Mono. P plasma, U urine, B blood, LF/HF low-frequency/high-frequency power of heart rate (an index of sympathetic vs parasympathetic balance), RMSSD square root of the mean squared differences of subsequent RR-intervals (an index of parasympathetic activity), Cort cortisol, Epi epinephrine, Mono monocytes, Eos eosinophils, Neu neutrophils, PCA principal component analysis, B regression coefficient (unstandardized), R 2 explained variance of the dependent variable in the multiple regression model
Fig. 6
Fig. 6
Multiple regression models on the associations between neuroendocrine markers, immune markers and single gene transcripts within the CFS group. a Three genes related to B cell differentiation and survival, with negative loadings of Factor 3 and down-regulated expression in the CFS-group as compared to healthy controls. b Three genes related to innate immunity, with positive loadings of Factor 3 and up-regulated expression in the CFS group as compared to healthy controls. P plasma, U urine, B blood, LF/HF low-frequency/high-frequency power of heart rate (an index of sympathetic vs parasympathetic balance), RMSSD square root of the mean squared differences of subsequent RR-intervals (an index of parasympathetic activity), Cort cortisol, Epi epinephrine, Mono monocytes, Eos eosinophils, Neu neutrophils, PCA principal component analysis, B regression coefficient (unstandardized), R 2 explained variance of the dependent variable in the multiple regression model
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