Multi-omics examination of Q fever fatigue syndrome identifies similarities with chronic fatigue syndrome
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Journal of Translational Medicine Open Access
RESEARCH
Multi‑omics examination of Q fever fatigue syndrome identifies similarities with chronic fatigue syndrome Ruud P. H. Raijmakers1,2* , Megan E. Roerink2, Anne F. M. Jansen1,2, Stephan P. Keijmel1,2, Ranko Gacesa3, Yang Li2,4,5, Leo A. B. Joosten1,2,6, Jos W. M. van der Meer1,2, Mihai G. Netea1,2,6, Chantal P. Bleeker‑Rovers1,2,6 and Cheng‑Jian Xu2,4,5
Abstract Background: Q fever fatigue syndrome (QFS) is characterised by a state of prolonged fatigue that is seen in 20% of acute Q fever infections and has major health-related consequences. The molecular mechanisms underlying QFS are largely unclear. In order to better understand its pathogenesis, we applied a multi-omics approach to study the pat‑ terns of the gut microbiome, blood metabolome, and inflammatory proteome of QFS patients, and compared these with those of chronic fatigue syndrome (CFS) patients and healthy controls (HC). Methods: The study population consisted of 31 QFS patients, 50 CFS patients, and 72 HC. All subjects were matched for age, gender, and general geographical region (South-East part of the Netherlands). The gut microbiome composi‑ tion was assessed by Metagenomic sequencing using the Illumina HiSeq platform. A total of 92 circulating inflam‑ matory markers were measured using Proximity Extension Essay and 1607 metabolic features were assessed with a high-throughput non-targeted metabolomics approach. Results: Inflammatory markers, including 4E-BP1 (P = 9.60–16 and 1.41–7) and MMP-1 (P = 7.09–9 and 3.51–9), are sig‑ nificantly more expressed in both QFS and CFS patients compared to HC. Blood metabolite profiles show significant differences when comparing QFS (319 metabolites) and CFS (441 metabolites) patients to HC, and are significantly enriched in pathways like sphingolipid (P = 0.0256 and 0.0033) metabolism. When comparing QFS to CFS patients, almost no significant differences in metabolome were found. Comparison of microbiome taxonomy of QFS and CFS patients with that of HC, shows both in- and decreases in abundancies in Bacteroidetes (with emphasis on Bacteroides and Alistiples spp.), and Firmicutes and Actinobacteria (with emphasis on Ruminococcus and Bifidobacterium spp.). When we compare QFS patients to CFS patients, there is a striking resemblance and hardly any significant differences in microbiome taxonomy are found. Conclusions: We show that QFS and CFS patients are similar across three different omics layers and 4E-BP1 and MMP-1 have the potential to distinguish QFS and CFS patients from HC. Keywords: QFS, CFS, Fatigue, Q fever, Omics, Inflammation, Metabolome, Microbiome
*Correspondence: [email protected] 1 Division of Infectious Diseases 463, Department of Internal Medicine, Radboud Expertise Center for Q Fever, Radboud University Medical Center, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands Full list of author information is available at the end of the article
Background Q fever fatigue syndrome (QFS) is characterised as a state of prolonged fa
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