Tag: pathophysiology

The Role of Leptin and Inflammatory Related Biomarkers in Individuals with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Purpose: Leptin is a member of the cytokine family; its receptor (LEPR-b) is the longest form receptor expressed in cells of the immune system; wherein LEPR-b deficiency causes a decrease in CD4+ cells. LEPR-b is located in hypothalamic and brain stem nuclei, and it primarily regulates energy status. As well, leptin indirectly regulates widespread pain and exercise tolerance by decreasing circulating cortisol.

Hyperinsulinemia increases leptin production in adipocytes on a diurnal rhythm; however, the precise relationship between insulin, leptin and pro-inflammatory markers remains uncertain. In clinical settings, high-sensitivity C-reactive protein (hsCRP) has been widely used, as an inflammatory predictor for leptin-related cardiometabolic outcomes and chronic inflammatory symptoms.

Leptin-related metabolic and inflammation dysregulations have been clinically reported in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS), but not fully elucidated. We examined the association of plasma insulin, leptin, and hsCRP levels with ME/CFS self-reported symptom severity.

Methods: Prospective analyses were conducted on ME/CFS patients who met Fukuda/CDC criteria at Birmingham hospital, Alabama, U.S.A. The independent variables were hyperinsulinemia (>174 μIU/mL), hyperleptinemia/hypoleptinemia (>18.3/<3.3 ng/mL), residual inflammation risk (hsCRP ≥2 and ≠26.2 mg/L) and within-individual-variability (WIV) for each biomarker.

WIV was defined for each individual as standard deviation/sample residuals adjusting for time and calculated from once-daily random plasma samples over 10–12 weeks.

The primary outcomes were:

(1) ME/CFS symptom score trends [generalized pain, persistent fatigue, sleep disturbance, impairment of concentration and memory (brain fog), and post-exertional malaise (PEM)] calculated from the MFI-20 questionnaire with anchors from 0 to 100 and recorded once daily over a matching 12–14 weeks, and

(2) dichotomized symptom severity, with severe symptoms defined as scores > 60/100. After adjusting for age and time, we reported: (1) standard errors (SEM) and p-values for symptom trends using multivariable mixed-effect linear regression models, and (2) odds ratios for severe symptoms using multivariable alternating logistic regression models.

Results: We included 29 ME/CFS patients. All were females and >18 years old. Hyperinsulinemia, hyperleptinemia/hypoleptinemia, and residual inflammation risk were 7%, 80%/7%, and 74%, respectively.

The medians of insulin-WIV, leptin-WIV and hsCRP-WIV were [(0.24; IQR 0.15–0.38), (0.25; IQR 0.15–0.40), (0.33; IQR 0.18–0.51)] respectively. On average, hyperleptinemic patients had the highest leptin-WIV and 50% of them had residual inflammation risk.

Severe (fatigue, pain, brain fog, sleep disturbance, and PEM) were reported in 50%, 29%, 41%, 30%, and 57% of patients, respectively. In the adjusted analysis, worse fatigue scores (7.49; SEM, 2.23; p = 0.002) were associated with higher insulin-WIV.

Hyperleptinemia (OR 1.54; 95% CI 1.13–2.09) compared to hypoleptinemia, and residual inflammation risk (OR 1.65; 95% CI 1.21–2.25) were associated with higher odds of severe fatigue. Worse pain scores (7.17; SEM, 2.30; p = 0.005) were associated with higher leptin-WIV, and (8.45; SEM, 2.25; p = 0.0009) higher hsCRP-WIV, and residual inflammation risk (OR 1.75; 95% CI 1.34–2.29) was associated with higher odds of severe pain.

Severe brain fog scores (9.20; SEM, 2.44; p = 0.0008) were associated with higher insulin-WIV, higher leptin-WIV (4.73; SEM, 2.12; p = 0.03). Residual inflammation risk (OR 1.40; 95% CI 1.16–1.77) was associated with higher odds of severe brain fog.

Hyperleptinemia (OR 0.60; 95% CI 0.43–1.19) was associated with lower odds of severe PEM compared to hypoleptinemia, and better sleep quality was associated (6.07; SEM, 1.70; p = 0.001) with higher insulin-WIV, and (3.37; SEM, 1.47; p = 0.03) higher leptin-WIV.

Conclusions: In patients with ME/CFS, symptoms severity was associated with hyperleptinemia, inflammation and within-individual-variability of these biomarkers. Leptin and hsCRP may be clinically useful in predicting symptom severity.

Larger clinical trials are needed to further examine the prediction and causality of these biomarkers in the development of ME/CFS diagnosis. The efficacy and safety of anti-inflammatory therapies may be evaluated in sub-clusters of ME/CFS with metabolic responses and inflammation dysregulations to improve patient-reported symptoms.

Source: Rahaf Al Assil and Jarred W Younger. “The Role of Leptin and Inflammatory Related Biomarkers in Individuals with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome” in Karandrea S, Agarwal N, Organizing Committee of Cardiometabolic Health Congress. Report from the Scientific Poster Session at the 16th Annual Cardiometabolic Health Congress in National Harbor, USA, 14–17 October 2021. Proceedings. 2022; 80(1):6. https://doi.org/10.3390/proceedings2022080006 (Full text)

Genetic risk factors for ME/CFS identified using combinatorial analysis

Abstract:

Background:Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating chronic disease that lacks known pathogenesis, distinctive diagnostic criteria, and effective treatment options. Understanding the genetic (and other) risk factors associated with the disease would begin to help to alleviate some of these issues for patients.

Methods: We applied both GWAS and the PrecisionLife combinatorial analytics platform to analyze ME/CFS cohorts from UK Biobank, including the Pain Questionnaire cohort, in a case-control design with 1,000 cycles of fully random permutation. Results from this study were supported by a series of replication and cohort comparison experiments, including use of disjoint Verbal Interview CFS, post-viral fatigue syndrome and fibromyalgia cohorts also derived from UK Biobank, and results compared for overlap and reproducibility.

Results: Combinatorial analysis revealed 199 SNPs mapping to 14 genes, that were significantly associated with 91% of the cases in the ME/CFS population. These SNPs were found to stratify by shared cases into 15 clusters (communities) made up of 84 high-order combinations of between 3-5 SNPs. p-values for these communities range from 2.3 × 10−10 to 1.6 × 10−72. Many of the genes identified are linked to the key cellular mechanisms hypothesized to underpin ME/CFS, including vulnerabilities to stress and/or infection, mitochondrial dysfunction, sleep disturbance and autoimmune development. We identified 3 of the critical SNPs replicated in the post-viral fatigue syndrome cohort and 2 SNPs replicated in the fibromyalgia cohort. We also noted similarities with genes associated with multiple sclerosis and long COVID, which share some symptoms and potentially a viral infection trigger with ME/CFS.

Conclusions: This study provides the first detailed genetic insights into the pathophysiological mechanisms underpinning ME/CFS and offers new approaches for better diagnosis and treatment of patients

Source: Sayoni Das, Krystyna Taylor, James Kozubek, Jason Sardell, Steve Gardner. Genetic Risk Factors for ME/CFS Identified using Combinatorial Analysis. medRxiv 2022.09.09.22279773; doi: https://doi.org/10.1101/2022.09.09.22279773  https://www.medrxiv.org/content/10.1101/2022.09.09.22279773v2.full-text (Full text)

Fatigue in ANCA-associated vasculitis (AAV) and systemic sclerosis (SSc): similarities with Myalgic encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS). A critical review of the literature

Abstract:

Introduction: Persistent debilitating fatigue is a frequent complaint in patients with systemic autoimmune rheumatic diseases (SARDs). Fatigue is, however, frequently overlooked in the clinic, and patients who successfully achieve remission of their disease, often still have a lowered quality of life due to its persistence. How similar is this fatigue to Myalgic encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS), what is this fatigue associated with, and what tools/approaches (if any), have resulted in the improvement of fatigue in these patients is poorly defined.

Areas covered: Similarities between the pathophysiology of ME/CFS, systemic sclerosis (SSc) and primary systemic vasculitides (PSV) are discussed, followed by an in-depth review of the prevalence and correlates of fatigue in these diseases. The authors reviewed literature from MEDLINE, APA PsycInfo, Embase, and CINAHL.

Expert opinion: Persistent fatigue is a prominent feature in SARDs and may not be associated with components commonly associated with disease activity and/or progression. Immune and metabolic commonalities exist between ME/CFS, SSc, and PSVs – suggesting that common pathways inherent to the diseases and fatigue may be present. We suggest that patients with features of ME/CFS need to be identified by treating physicians, as they may require alternative approaches to therapy to improve their quality of life.

Source: van Eeden C, Osman MS, Cohen Tervaert JW. Fatigue in ANCA-associated vasculitis (AAV) and systemic sclerosis (SSc): similarities with Myalgic encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS). A critical review of the literature. Expert Rev Clin Immunol. 2022 Aug 31:1-22. doi: 10.1080/1744666X.2022.2116002. Epub ahead of print. PMID: 36045606. https://pubmed.ncbi.nlm.nih.gov/36045606/

Role of Gut Microbiota and Probiotic in Chronic Fatigue Syndrome

Abstract:

Chronic fatigue syndrome (CFS) is a combination of complex illness characterized by tiredness or intense fatigue that may worsen with too much exertion. Among the wide range of neuropsychological symptoms, 97% CFS patients have been reported with neuronal disorders such as headaches and symptoms in the emotional realm.

Patients with CFS also show noticeable alterations in microflora, lowering level of  Lactobacilli and Bifidobacterium.

Recent researches explain that probiotics in the gastrointestinal tract (GIT) can greatly influence the neuronal pathways and central nervous system (CNS) to modulate behavior.

Various studies expressed the benefit of probiotic therapy in normalizing fatigue patients and also restored mitochondrial electron transport function in patients with CFS.

In this chapter, we provided a historical skeleton, bidirectional communication pathophysiology, selection criteria of probiotics, CFS treatment, and clinical implications of gut–brain connections. In summary, various aspects concerning the potential and safety of probiotics in the management of chronic fatigue syndrome are discussed in this chapter.

Source: Sharma A., Wakode S., Sharma S., Fayaz F. (2022) Role of Gut Microbiota and Probiotic in Chronic Fatigue Syndrome. In: Kaur I.P., Deol P.K., Sandhu S.K. (eds) Probiotic Research in Therapeutics. Springer, Singapore. https://doi.org/10.1007/978-981-16-6760-2_9 

Long COVID or post-COVID-19 syndrome: putative pathophysiology, risk factors, and treatments

Abstract:

Long COVID or post-COVID-19 syndrome first gained widespread recognition among social support groups and later in scientific and medical communities. This illness is poorly understood as it affects COVID-19 survivors at all levels of disease severity, even younger adults, children, and those not hospitalized. While the precise definition of long COVID may be lacking, the most common symptoms reported in many studies are fatigue and dyspnoea that last for months after acute COVID-19. Other persistent symptoms may include cognitive and mental impairments, chest and joint pains, palpitations, myalgia, smell and taste dysfunctions, cough, headache, and gastrointestinal and cardiac issues. Presently, there is limited literature discussing the possible pathophysiology, risk factors, and treatments in long COVID, which the current review aims to address.

In brief, long COVID may be driven by long-term tissue damage (e.g. lung, brain, and heart) and pathological inflammation (e.g. from viral persistence, immune dysregulation, and autoimmunity). The associated risk factors may include female sex, more than five early symptoms, early dyspnoea, prior psychiatric disorders, and specific biomarkers (e.g. D-dimer, CRP, and lymphocyte count), although more research is required to substantiate such risk factors. While preliminary evidence suggests that personalized rehabilitation training may help certain long COVID cases, therapeutic drugs repurposed from other similar conditions, such as myalgic encephalomyelitis or chronic fatigue syndrome, postural orthostatic tachycardia syndrome, and mast cell activation syndrome, also hold potential. In sum, this review hopes to provide the current understanding of what is known about long COVID.

Source: Yong SJ. Long COVID or post-COVID-19 syndrome: putative pathophysiology, risk factors, and treatments. Infect Dis (Lond). 2021 May 22:1-18. doi: 10.1080/23744235.2021.1924397. Epub ahead of print. PMID: 34024217. https://pubmed.ncbi.nlm.nih.gov/34024217/

Changes in DNA methylation profiles of myalgic encephalomyelitis/chronic fatigue syndrome patients reflect systemic dysfunctions

Abstract:

Background: Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a lifelong debilitating disease with a complex pathology not yet clearly defined. Susceptibility to ME/CFS involves genetic predisposition and exposure to environmental factors, suggesting an epigenetic association. Epigenetic studies with other ME/CFS cohorts have used array-based technology to identify differentially methylated individual sites. Changes in RNA quantities and protein abundance have been documented in our previous investigations with the same ME/CFS cohort used for this study.

Results: DNA from a well-characterised New Zealand cohort of 10 ME/CFS patients and 10 age-/sex-matched healthy controls was isolated from peripheral blood mononuclear (PBMC) cells, and used to generate reduced genome-scale DNA methylation maps using reduced representation bisulphite sequencing (RRBS). The sequencing data were analysed utilising the DMAP analysis pipeline to identify differentially methylated fragments, and the MethylKit pipeline was used to quantify methylation differences at individual CpG sites. DMAP identified 76 differentially methylated fragments and Methylkit identified 394 differentially methylated cytosines that included both hyper- and hypo-methylation. Four clusters were identified where differentially methylated DNA fragments overlapped with or were within close proximity to multiple differentially methylated individual cytosines. These clusters identified regulatory regions for 17 protein encoding genes related to metabolic and immune activity. Analysis of differentially methylated gene bodies (exons/introns) identified 122 unique genes. Comparison with other studies on PBMCs from ME/CFS patients and controls with array technology showed 59% of the genes identified in this study were also found in one or more of these studies. Functional pathway enrichment analysis identified 30 associated pathways. These included immune, metabolic and neurological-related functions differentially regulated in ME/CFS patients compared to the matched healthy controls.

Conclusions: Major differences were identified in the DNA methylation patterns of ME/CFS patients that clearly distinguished them from the healthy controls. Over half found in gene bodies with RRBS in this study had been identified in other ME/CFS studies using the same cells but with array technology. Within the enriched functional immune, metabolic and neurological pathways, a number of enriched neurotransmitter and neuropeptide reactome pathways highlighted a disturbed neurological pathophysiology within the patient group.

Source: Helliwell AM, Sweetman EC, Stockwell PA, Edgar CD, Chatterjee A, Tate WP. Changes in DNA methylation profiles of myalgic encephalomyelitis/chronic fatigue syndrome patients reflect systemic dysfunctions. Clin Epigenetics. 2020 Nov 4;12(1):167. doi: 10.1186/s13148-020-00960-z. PMID: 33148325; PMCID: PMC7641803. https://clinicalepigeneticsjournal.biomedcentral.com/articles/10.1186/s13148-020-00960-z  (Full study)

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A Comprehensive Review

Abstract:

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating chronic disease of unknown aetiology that is recognized by the World Health Organization (WHO) and the United States Center for Disease Control and Prevention (US CDC) as a disorder of the brain. The disease predominantly affects adults, with a peak age of onset of between 20 and 45 years with a female to male ratio of 3:1. Although the clinical features of the disease have been well established within diagnostic criteria, the diagnosis of ME/CFS is still of exclusion, meaning that other medical conditions must be ruled out.

The pathophysiological mechanisms are unclear but the neuro-immuno-endocrinological pattern of CFS patients gleaned from various studies indicates that these three pillars may be the key point to understand the complexity of the disease. At the moment, there are no specific pharmacological therapies to treat the disease, but several studies’ aims and therapeutic approaches have been described in order to benefit patients’ prognosis, symptomatology relief, and the recovery of pre-existing function.

This review presents a pathophysiological approach to understanding the essential concepts of ME/CFS, with an emphasis on the population, clinical, and genetic concepts associated with ME/CFS.

Source: Cortes Rivera M, Mastronardi C, Silva-Aldana CT, Arcos-Burgos M, Lidbury BA. Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A Comprehensive Review. Diagnostics (Basel). 2019 Aug 7;9(3). pii: E91. doi: 10.3390/diagnostics9030091. https://www.ncbi.nlm.nih.gov/pubmed/31394725

The chronic fatigue syndrome: a comparative pathway analysis

Abstract:

In this paper, we introduce a method to detect pathological pathways of a disease. We aim to identify biological processes rather than single genes affected by the chronic fatigue syndrome (CFS). So far, CFS has neither diagnostic clinical signals nor abnormalities that could be diagnosed by laboratory examinations. It is also unclear if the CFS represents one disease or can be subdivided in different categories. We use information from clinical trials, the gene ontology (GO) database as well as gene expression data to identify undirected dependency graphs (UDGs) representing biological processes according to the GO database. The structural comparison of UDGs of sick versus non-sick patients allows us to make predictions about the modification of pathways due to pathogenesis.

 

Source: Emmert-Streib F. The chronic fatigue syndrome: a comparative pathway analysis. J Comput Biol. 2007 Sep;14(7):961-72. https://www.ncbi.nlm.nih.gov/pubmed/17803373

 

Orthostatic intolerance in the chronic fatigue syndrome

Abstract:

This study aims to investigate the prevalence and pathophysiology of orthostatic intolerance (OI) and its potential contribution to symptoms of a group of unselected patients with chronic fatigue syndrome (CFS).

Seventy five patients (65 women, 10 men) with CFS were evaluated. During an initial visit, a clinical suspicion as to the likelihood of observing laboratory evidence of OI was assigned. Laboratory investigation consisted of beat-to-beat recordings of heart rate, blood pressure (Finapres), and stroke volume (impedance cardiograph) while supine and during 80 degrees head-up tilt (HUT), during rhythmic deep breathing (6 breaths/min) and during the Valsalva maneuver. The responses of 48 age-matched healthy controls who had no history of OI were used to define the range of normal responses to these three maneuvers.

Forty percent of patients with CFS had OI during head-up tilt. Sixteen exhibited neurally-mediated syncope alone, seven tachycardia (> 35 bpm averaged over the whole of the head-up tilt) and six a mixture of tachycardia and syncope. Eight of 48 controls exhibited neurally-mediated syncope. The responses to the Valsalva maneuver and to deep breathing were similar in controls and patients. On average, the duration of disease and patient age were significantly less and the onset of symptoms was more often subacute in patients with OI than in those without OI.

We conclude that there exists a clinically identifiable subgroup of patients with CFS and OI that differs from control subjects and from those with CFS without OI for whom treatment specifically aimed at improving orthostatic tolerance may be indicated.

 

Source: Schondorf R, Benoit J, Wein T, Phaneuf D. Orthostatic intolerance in the chronic fatigue syndrome. J Auton Nerv Syst. 1999 Feb 15;75(2-3):192-201. http://www.ncbi.nlm.nih.gov/pubmed/10189122

 

Chronic fatigue syndrome

Abstract:

Chronic fatigue syndrome (CFS) is a medically unexplained illness characterized by chronic, disabling fatigue, impaired concentration, muscle pain, and other somatic symptoms. The conceptual difficulties associated with all medically unexplained illnesses contribute to the controversy surrounding CFS, which has centered around whether it is best regarded as a medical or as a psychiatric condition. Clinically, such an approach is not helpful, and current research suggests that both pathophysiologic changes and psychosocial factors are important. Pragmatic management based on a detailed assessment of the individual is outlined.

 

Source: Sharpe M. Chronic fatigue syndrome. Psychiatr Clin North Am. 1996 Sep;19(3):549-73. http://www.ncbi.nlm.nih.gov/pubmed/8856816