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Jahanbani F, Sing JC, Maynard RD, Jahanbani S, Dafoe J, Dafoe W, Jones N, Wallace KJ, Rastan A, Maecker HT, Röst HL, Snyder MP, Davis RW. Longitudinal cytokine and multi-modal health data of an extremely severe ME/CFS patient with HSD reveals insights into immunopathology, and disease severity. Front Immunol 2024; 15:1369295. [PMID: 38650940 PMCID: PMC11033372 DOI: 10.3389/fimmu.2024.1369295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Accepted: 03/18/2024] [Indexed: 04/25/2024] Open
Abstract
Introduction Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) presents substantial challenges in patient care due to its intricate multisystem nature, comorbidities, and global prevalence. The heterogeneity among patient populations, coupled with the absence of FDA-approved diagnostics and therapeutics, further complicates research into disease etiology and patient managment. Integrating longitudinal multi-omics data with clinical, health,textual, pharmaceutical, and nutraceutical data offers a promising avenue to address these complexities, aiding in the identification of underlying causes and providing insights into effective therapeutics and diagnostic strategies. Methods This study focused on an exceptionally severe ME/CFS patient with hypermobility spectrum disorder (HSD) during a period of marginal symptom improvements. Longitudinal cytokine profiling was conducted alongside the collection of extensive multi-modal health data to explore the dynamic nature of symptoms, severity, triggers, and modifying factors. Additionally, an updated severity assessment platform and two applications, ME-CFSTrackerApp and LexiTime, were introduced to facilitate real-time symptom tracking and enhance patient-physician/researcher communication, and evaluate response to medical intervention. Results Longitudinal cytokine profiling revealed the significance of Th2-type cytokines and highlighted synergistic activities between mast cells and eosinophils, skewing Th1 toward Th2 immune responses in ME/CFS pathogenesis, particularly in cognitive impairment and sensorial intolerance. This suggests a potentially shared underlying mechanism with major ME/CFS comorbidities such as HSD, Mast cell activation syndrome, postural orthostatic tachycardia syndrome (POTS), and small fiber neuropathy. Additionally, the data identified potential roles of BCL6 and TP53 pathways in ME/CFS etiology and emphasized the importance of investigating adverse reactions to medication and supplements and drug interactions in ME/CFS severity and progression. Discussion Our study advocates for the integration of longitudinal multi-omics with multi-modal health data and artificial intelligence (AI) techniques to better understand ME/CFS and its major comorbidities. These findings highlight the significance of dysregulated Th2-type cytokines in patient stratification and precision medicine strategies. Additionally, our results suggest exploring the use of low-dose drugs with partial agonist activity as a potential avenue for ME/CFS treatment. This comprehensive approach emphasizes the importance of adopting a patient-centered care approach to improve ME/CFS healthcare management, disease severity assessment, and personalized medicine. Overall, these findings contribute to our understanding of ME/CFS and offer avenues for future research and clinical practice.
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Affiliation(s)
- Fereshteh Jahanbani
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, United States
| | - Justin Cyril Sing
- Department of Molecular Genetics, Donnelly Center, University of Toronto, Toronto, ON, Canada
| | - Rajan Douglas Maynard
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, United States
| | - Shaghayegh Jahanbani
- Division of Immunology and Rheumatology, Stanford University School of Medicine, Veterans Affairs (VA) Palo Alto Health Care System, Palo Alto, CA, United States
| | - Janet Dafoe
- ME/CFS Collaborative Research Center at Stanford, Stanford Genome Technology Center, Stanford University School of Medicine, Palo Alto, CA, United States
| | - Whitney Dafoe
- ME/CFS Collaborative Research Center at Stanford, Stanford Genome Technology Center, Stanford University School of Medicine, Palo Alto, CA, United States
| | - Nathan Jones
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, United States
| | - Kelvin J. Wallace
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, United States
| | - Azuravesta Rastan
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, United States
| | - Holden T. Maecker
- Sean N. Parker Center for Allergy and Asthma Research at Stanford University, Pulmonary and Critical Care Medicine, Institute of Immunity, Transplantation, and Infectious Diseases, Stanford University, Palo Alto, CA, United States
| | - Hannes L. Röst
- Department of Molecular Genetics, Donnelly Center, University of Toronto, Toronto, ON, Canada
| | - Michael P. Snyder
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, United States
| | - Ronald W. Davis
- ME/CFS Collaborative Research Center at Stanford, Stanford Genome Technology Center, Stanford University School of Medicine, Palo Alto, CA, United States
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Trevisan G, Bonin S, Ruscio M. A Practical Approach to the Diagnosis of Lyme Borreliosis: From Clinical Heterogeneity to Laboratory Methods. Front Med (Lausanne) 2020; 7:265. [PMID: 32793606 PMCID: PMC7390863 DOI: 10.3389/fmed.2020.00265] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Accepted: 05/14/2020] [Indexed: 12/05/2022] Open
Abstract
Clinical evaluation of Lyme Borreliosis (LB) is the starting point for its diagnosis. The patient's medical history and clinical symptoms are fundamental for disease recognition. The heterogeneity in clinical manifestations of LB can be related to different causes, including the different strains of Borrelia, possible co-infection with other tick transmitted pathogens, and its interactions with the human host. This review aims at describing the heterogeneous symptoms of Lyme Borreliosis, as well as offering a practical approach for recognition of the disease, both in terms of clinical features and diagnostic/research tools.
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Affiliation(s)
- Giusto Trevisan
- DSM-Department of Medical Sciences, University of Trieste, Trieste, Italy
| | - Serena Bonin
- DSM-Department of Medical Sciences, University of Trieste, Trieste, Italy
| | - Maurizio Ruscio
- ASU GI-Azienda Sanitaria Universitaria Giuliano Isontina, Trieste, Italy
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DeLong A, Hsu M, Kotsoris H. Estimation of cumulative number of post-treatment Lyme disease cases in the US, 2016 and 2020. BMC Public Health 2019; 19:352. [PMID: 31014314 PMCID: PMC6480773 DOI: 10.1186/s12889-019-6681-9] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2018] [Accepted: 03/19/2019] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Lyme disease (LD) is an infectious multi-system illness caused by the bacterial genus Borrelia and spread by bites of infected ticks. Although most patients are successfully treated by timely antibiotic therapy, it is broadly accepted that a sizeable number of patients experience treatment failure and continue to suffer long-term, debilitating symptoms, including pain, fatigue, cognitive dysfunction and other symptoms. This is known as post-treatment LD (PTLD), for which diagnosis is not standardized and treatment remains controversial. The prevalence and societal burden of PTLD is unknown. METHODS In an effort to help characterize the LD landscape, we estimated the number of PTLD cases in the US in 2016 and 2020 using Monte-Carlo simulation techniques, publically-available demographic datasets, uncertainty in the inputs and realistic assumptions about incidence and treatment failure rates. RESULTS Depending on the input assumptions, PTLD prevalence estimates for 2016 ranged from 69,011 persons (95% CI 51,796 to 89,312) to 1,523,869 (CI 1,268,634 to 1,809,416). Prevalence in 2020 is predicted to be higher than 2016, and may be as high as 1,944,189 (CI 1,619,988 to 2,304,147) cases. CONCLUSIONS The cumulative prevalence of PLTD in the United States is estimated to be high and continues to increase. These findings will be of interest to epidemiologists and health economists studying disease burden in the US and elsewhere, and justify funding to study PTLD diagnosis and treatment.
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Affiliation(s)
- Allison DeLong
- Center for Statistical Sciences, School of Public Health, Brown University, Providence, RI, 02912, USA.
| | - Mayla Hsu
- Global Lyme Alliance, Stamford, CT, USA
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