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, 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.

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Multi-omics examination of Q fever fatigue syndrome identifies similarities with chronic fatigue syndrome

Journal of Translational Medicine ◽

10.1186/s12967-020-02585-5 ◽

2020 ◽

Vol 18 (1) ◽

Author(s):

Ruud P. H. Raijmakers ◽

Megan E. Roerink ◽

Anne F. M. Jansen ◽

Stephan P. Keijmel ◽

Ranko Gacesa ◽

...

Keyword(s):

Chronic Fatigue Syndrome ◽

Gut Microbiome ◽

Inflammatory Markers ◽

Molecular Mechanisms ◽

Q Fever ◽

Chronic Fatigue ◽

Metagenomic Sequencing ◽

Illumina Hiseq ◽

Fatigue Syndrome ◽

Q Fever 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, 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.

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Multi-omics Examination of Q Fever Fatigue Syndrome Identifies Similarities with Chronic Fatigue Syndrome

10.21203/rs.3.rs-54097/v1 ◽

2020 ◽

Author(s):

Ruud Raijmakers ◽

Megan E. Roerink ◽

Anne F.M. Jansen ◽

Stephan P. Keijmel ◽

Ranko Gacesa ◽

...

Keyword(s):

Chronic Fatigue Syndrome ◽

Gut Microbiome ◽

Inflammatory Markers ◽

Molecular Mechanisms ◽

Q Fever ◽

Chronic Fatigue ◽

Metagenomic Sequencing ◽

Illumina Hiseq ◽

Fatigue Syndrome ◽

Q Fever 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, 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, and QFS patients show more of an inflammatory profile than CFS patients and 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 Actinobateria (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.

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A comparison of patients with Q fever fatigue syndrome and patients with chronic fatigue syndrome with a focus on inflammatory markers and possible fatigue perpetuating cognitions and behaviour

Journal of Psychosomatic Research ◽

10.1016/j.jpsychores.2015.07.005 ◽

2015 ◽

Vol 79 (4) ◽

pp. 295-302 ◽

Cited By ~ 15

Author(s):

Stephan P. Keijmel ◽

Johanna Saxe ◽

Jos W.M. van der Meer ◽

Stephanie Nikolaus ◽

Mihai G. Netea ◽

...

Keyword(s):

Chronic Fatigue Syndrome ◽

Inflammatory Markers ◽

Q Fever ◽

Chronic Fatigue ◽

Fatigue Syndrome ◽

Q Fever Fatigue Syndrome

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No signs of neuroinflammation in women with chronic fatigue syndrome or Q fever fatigue syndrome using the TSPO ligand [11C]-PK11195

10.21203/rs.3.rs-348289/v1 ◽

2021 ◽

Author(s):

Ruud Raijmakers ◽

Megan E. Roerink ◽

Stephan P. Keijmel ◽

Leo A.B. Joosten ◽

Mihai G. Netea ◽

...

Keyword(s):

Chronic Fatigue Syndrome ◽

Q Fever ◽

Chronic Fatigue ◽

Psychiatric Disease ◽

Binding Potential ◽

Healthy Controls ◽

Fatigue Syndrome ◽

Severity Scores ◽

Significant Difference ◽

Q Fever Fatigue Syndrome

Abstract Background The pathophysiology of chronic fatigue syndrome (CFS) and Q fever fatigue syndrome (QFS) remains elusive. Recent data suggest a role for neuroinflammation as defined by increased expression of translocator protein (TSPO). In the present study we investigated neuroinflammation in female CFS and QFS patients compared with healthy women, using Positron Emission Tomography (PET) with the TSPO ligand [11C]-PK11195. Methods The study population consisted of CFS patients (n = 9), QFS patients (n = 10), and healthy controls (n = 9). All subjects were women, matched for age (± 5 years) and neighbourhood, between 18 and 59 years of age, who did not use any medication other than paracetamol or oral contraceptives, and were not vaccinated in the last six months. None of the subjects reported substance abuse in the past 3 months or reported signs of underlying psychiatric disease on the Mini-International Neuropsychiatric Interview (MINI). All subjects underwent a [11C]-PK11195 PET scan and the [11C]-PK11195 binding potential (BPND) was calculated. Results No statistically significant differences in BPND were found for CFS patients or QFS patients when compared to healthy controls. BPND of [11C]-PK11195 positively correlated with symptom severity scores in QFS patients, but a negative correlation was found in CFS patients. Conclusions In contrast to what was previously reported for CFS, we found no significant difference in BPND of [11C]-PK11195 when comparing CFS or QFS patients to healthy neighbourhood controls. In this small series we were unable to find signs of neuroinflammation in patients with CFS and QFS. Trial registration EudraCT number: 2014-004448-37

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No Signs of Neuroinflammation in Women With Chronic Fatigue Syndrome or Q Fever Fatigue Syndrome Using the TSPO Ligand [11C]-PK11195

Neurology Neuroimmunology & Neuroinflammation ◽

10.1212/nxi.0000000000001113 ◽

2021 ◽

Vol 9 (1) ◽

pp. e1113

Author(s):

Ruud Raijmakers ◽

Megan Roerink ◽

Stephan Keijmel ◽

Leo Joosten ◽

Mihai Netea ◽

...

Keyword(s):

Chronic Fatigue Syndrome ◽

Q Fever ◽

Chronic Fatigue ◽

Psychiatric Disease ◽

Binding Potential ◽

Fatigue Syndrome ◽

Small Series ◽

Severity Scores ◽

Significant Difference ◽

Q Fever Fatigue Syndrome

Background and ObjectivesThe pathophysiology of chronic fatigue syndrome (CFS) and Q fever fatigue syndrome (QFS) remains elusive. Recent data suggest a role for neuroinflammation as defined by increased expression of translocator protein (TSPO). In the present study, we investigated whether there are signs of neuroinflammation in female patients with CFS and QFS compared with healthy women, using PET with the TSPO ligand 11C-(R)-(2-chlorophenyl)-N-methyl-N-(1-methylpropyl)-3-isoquinoline-carbox-amide ([11C]-PK11195).MethodsThe study population consisted of patients with CFS (n = 9), patients with QFS (n = 10), and healthy subjects (HSs) (n = 9). All subjects were women, matched for age (±5 years) and neighborhood, aged between 18 and 59 years, who did not use any medication other than paracetamol or oral contraceptives, and were not vaccinated in the last 6 months. None of the subjects reported substance abuse in the past 3 months or reported signs of underlying psychiatric disease on the Mini-International Neuropsychiatric Interview. All subjects underwent a [11C]-PK11195 PET scan, and the [11C]-PK11195 binding potential (BPND) was calculated.ResultsNo statistically significant differences in BPND were found for patients with CFS or patients with QFS compared with HSs. BPND of [11C]-PK11195 correlated with symptom severity scores in patients with QFS, but a negative correlation was found in patients with CFS.DiscussionIn contrast to what was previously reported for CFS, we found no significant difference in BPND of [11C]-PK11195 when comparing patients with CFS or QFS with healthy neighborhood controls. In this small series, we were unable to find signs of neuroinflammation in patients with CFS and QFS.Trial Registration InformationEudraCT number 2014-004448-37.

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A possible role for mitochondrial-derived peptides humanin and MOTS-c in patients with Q fever fatigue syndrome and chronic fatigue syndrome

Journal of Translational Medicine ◽

10.1186/s12967-019-1906-3 ◽

2019 ◽

Vol 17 (1) ◽

Cited By ~ 5

Author(s):

Ruud P. H. Raijmakers ◽

Anne F. M. Jansen ◽

Stephan P. Keijmel ◽

Rob ter Horst ◽

Megan E. Roerink ◽

...

Keyword(s):

Chronic Fatigue Syndrome ◽

Q Fever ◽

Chronic Fatigue ◽

Fatigue Syndrome ◽

Q Fever Fatigue Syndrome

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COVID-19 and post-infectious myalgic encephalomyelitis/chronic fatigue syndrome: a narrative review

Therapeutic Advances in Infectious Disease ◽

10.1177/20499361211009385 ◽

2021 ◽

Vol 8 ◽

pp. 204993612110093

Author(s):

Sonia Poenaru ◽

Sara J. Abdallah ◽

Vicente Corrales-Medina ◽

Juthaporn Cowan

Keyword(s):

Chronic Fatigue Syndrome ◽

Sleep Disturbances ◽

Q Fever ◽

Orthostatic Intolerance ◽

Chronic Fatigue ◽

Myalgic Encephalomyelitis ◽

Exercise Intolerance ◽

Laboratory Findings ◽

Fatigue Syndrome ◽

Post Infectious

Coronavirus disease 2019 (COVID-19) is a viral infection which can cause a variety of respiratory, gastrointestinal, and vascular symptoms. The acute illness phase generally lasts no more than 2–3 weeks. However, there is increasing evidence that a proportion of COVID-19 patients experience a prolonged convalescence and continue to have symptoms lasting several months after the initial infection. A variety of chronic symptoms have been reported including fatigue, dyspnea, myalgia, exercise intolerance, sleep disturbances, difficulty concentrating, anxiety, fever, headache, malaise, and vertigo. These symptoms are similar to those seen in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), a chronic multi-system illness characterized by profound fatigue, sleep disturbances, neurocognitive changes, orthostatic intolerance, and post-exertional malaise. ME/CFS symptoms are exacerbated by exercise or stress and occur in the absence of any significant clinical or laboratory findings. The pathology of ME/CFS is not known: it is thought to be multifactorial, resulting from the dysregulation of multiple systems in response to a particular trigger. Although not exclusively considered a post-infectious entity, ME/CFS has been associated with several infectious agents including Epstein–Barr Virus, Q fever, influenza, and other coronaviruses. There are important similarities between post-acute COVID-19 symptoms and ME/CFS. However, there is currently insufficient evidence to establish COVID-19 as an infectious trigger for ME/CFS. Further research is required to determine the natural history of this condition, as well as to define risk factors, prevalence, and possible interventional strategies.

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