Multi-omics examination of Q fever fatigue syndrome identifies similarities with chronic fatigue syndrome
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,...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2020-11-01
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| Series: | Journal of Translational Medicine |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12967-020-02585-5 |
| _version_ | 1828976589930496000 |
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| author | Ruud P. H. Raijmakers Megan E. Roerink Anne F. M. Jansen Stephan P. Keijmel Ranko Gacesa Yang Li Leo A. B. Joosten Jos W. M. van der Meer Mihai G. Netea Chantal P. Bleeker-Rovers Cheng-Jian Xu |
| author_facet | Ruud P. H. Raijmakers Megan E. Roerink Anne F. M. Jansen Stephan P. Keijmel Ranko Gacesa Yang Li Leo A. B. Joosten Jos W. M. van der Meer Mihai G. Netea Chantal P. Bleeker-Rovers Cheng-Jian Xu |
| author_sort | Ruud P. H. Raijmakers |
| collection | DOAJ |
| description | 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 patterns 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 composition was assessed by Metagenomic sequencing using the Illumina HiSeq platform. A total of 92 circulating inflammatory 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 significantly 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. |
| first_indexed | 2024-12-14T14:41:30Z |
| format | Article |
| id | doaj.art-272ed69de73146399ef0ba3f4f57919e |
| institution | Directory Open Access Journal |
| issn | 1479-5876 |
| language | English |
| last_indexed | 2024-12-14T14:41:30Z |
| publishDate | 2020-11-01 |
| publisher | BMC |
| record_format | Article |
| series | Journal of Translational Medicine |
| spelling | doaj.art-272ed69de73146399ef0ba3f4f57919e2022-12-21T22:57:25ZengBMCJournal of Translational Medicine1479-58762020-11-0118111310.1186/s12967-020-02585-5Multi-omics examination of Q fever fatigue syndrome identifies similarities with chronic fatigue syndromeRuud P. H. Raijmakers0Megan E. Roerink1Anne F. M. Jansen2Stephan P. Keijmel3Ranko Gacesa4Yang Li5Leo A. B. Joosten6Jos W. M. van der Meer7Mihai G. Netea8Chantal P. Bleeker-Rovers9Cheng-Jian Xu10Division of Infectious Diseases 463, Department of Internal Medicine, Radboud Expertise Center for Q Fever, Radboud University Medical CenterDepartment of Internal Medicine, Radboud University Medical CenterDivision of Infectious Diseases 463, Department of Internal Medicine, Radboud Expertise Center for Q Fever, Radboud University Medical CenterDivision of Infectious Diseases 463, Department of Internal Medicine, Radboud Expertise Center for Q Fever, Radboud University Medical CenterDepartment of Genetics, University Medical Center GroningenDepartment of Internal Medicine, Radboud University Medical CenterDivision of Infectious Diseases 463, Department of Internal Medicine, Radboud Expertise Center for Q Fever, Radboud University Medical CenterDivision of Infectious Diseases 463, Department of Internal Medicine, Radboud Expertise Center for Q Fever, Radboud University Medical CenterDivision of Infectious Diseases 463, Department of Internal Medicine, Radboud Expertise Center for Q Fever, Radboud University Medical CenterDivision of Infectious Diseases 463, Department of Internal Medicine, Radboud Expertise Center for Q Fever, Radboud University Medical CenterDepartment of Internal Medicine, Radboud University Medical CenterAbstract 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 patterns 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 composition was assessed by Metagenomic sequencing using the Illumina HiSeq platform. A total of 92 circulating inflammatory 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 significantly 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.http://link.springer.com/article/10.1186/s12967-020-02585-5QFSCFSFatigueQ feverOmicsInflammation |
| spellingShingle | Ruud P. H. Raijmakers Megan E. Roerink Anne F. M. Jansen Stephan P. Keijmel Ranko Gacesa Yang Li Leo A. B. Joosten Jos W. M. van der Meer Mihai G. Netea Chantal P. Bleeker-Rovers Cheng-Jian Xu Multi-omics examination of Q fever fatigue syndrome identifies similarities with chronic fatigue syndrome Journal of Translational Medicine QFS CFS Fatigue Q fever Omics Inflammation |
| title | Multi-omics examination of Q fever fatigue syndrome identifies similarities with chronic fatigue syndrome |
| title_full | Multi-omics examination of Q fever fatigue syndrome identifies similarities with chronic fatigue syndrome |
| title_fullStr | Multi-omics examination of Q fever fatigue syndrome identifies similarities with chronic fatigue syndrome |
| title_full_unstemmed | Multi-omics examination of Q fever fatigue syndrome identifies similarities with chronic fatigue syndrome |
| title_short | Multi-omics examination of Q fever fatigue syndrome identifies similarities with chronic fatigue syndrome |
| title_sort | multi omics examination of q fever fatigue syndrome identifies similarities with chronic fatigue syndrome |
| topic | QFS CFS Fatigue Q fever Omics Inflammation |
| url | http://link.springer.com/article/10.1186/s12967-020-02585-5 |
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