Dr. Lapp on CFS versus FM: Twins, Cousins, or Just Acquaintances?

by Charles W. Lapp, MD
September 6, 2011

Ed Note: This article is reproduced with kind permission from Bruce Campbell’s CFIDS & Fibromyalgia Self-Help website (https://cfsselfhelp.org/). Dr. Lapp directed the Hunter-Hopkins Center in Charlotte, NC, one of the few medical practices in the US specializing in the treatment of ME/CFS and FM. [Dr. Lapp is now retired.]

Reprinted with the kind permission of Prohealth: 9/6/11

_______________________

Chronic Fatigue Syndrome is a disorder characterized by debilitating fatigue and recurrent flulike symptoms, such as muscle and joint aches, sore throat, swollen glands, and difficulty thinking. Fibromyalgia Syndrome is a disorder characterized by widespread muscle pain.

Can such different descriptions share anything in common?

Siamese Twins

Most experts agree that the symptoms of CFS and FM are so close that they are – for all intents – the same disorder. It’s a bit like Jekyll and Hyde, or perhaps like Chang and Eng Bunker, the Siamese twins made famous by P.T. Barnum. They were both the same “person” but had two different names, two similar but different personalities.

Assigning a Diagnosis

Patients who present to their primary care providers frequently relate a litany of complaints such as fatigue, vague aching, and trouble with memory or concentration.

Based on these complaints, the primary care doctor will most likely diagnose Chronic Fatigue Syndrome using the 1994 international case definition published by the Centers for Disease Control.

On the other hand,  the patient whose major complaint is pain will likely consult a rheumatologist who will ask, “Where does it hurt?” When it is determined that the patient hurts at the classical “tenderpoints” defined by the ACR [American College of Rheumatology] in 1990, the likely diagnosis will be Fibromyalgia.

Overlaps and Shadows

So one diagnosis is frequently given by primary care physicians and the other by rheumatologists. Both diagnoses have several features in common: exertional malaise [activity intensifying symptoms], cognitive difficulties, muscle pain (or myalgias) and a sleep disorder.

Both are frequently associated with “overlap disorders” or “shadow syndromes,” as I like to call them. The most common “shadow syndromes” are irritable bowel syndrome, irritable bladder, temperomandibular dysfunction, and mitral valve prolapse.

Others include premenstrual syndrome, primary dysmenorrhea, migraine, restless legs or periodic leg movements, Myofascial Pain Syndrome (MPS), chemical sensitivities, autonomic dysfunction (Neurally Mediated Hypotension and Postural Orthostatic Tachycardia Syndrome), Gulf War Syndrome, and possibly hyperextensibility, acne rosacea, Raynaud’s phenomenon, sicca complex (dry eyes and mouth) and vasomotor rhinitis (constant runny nose and congestion).

Note that the shadow syndromes occur predominantly in females, are defined clinically rather than by physical or laboratory findings, and many are associated with either pain or fatigue. It is likely that these disorders occur concurrently because they share a common biophysiological thread.

Fibromyalgia & CFS Compared

The symptoms are similar for both syndromes, including debilitating fatigue, post-exertional malaise, feverishness, sore throat, headache, joint aches, a feeling of generalized weakness, subjective swelling, non-radicular paresthesias (numbness or tingling that does not follow typical nerve patterns), memory loss, forgetfulness, confusion, irritability, and depressed mood.

There are some subtle differences, however. (See Table 1 at end of article.)  Historically, CFS is frequently triggered by a flulike or infectious illness, but sometimes occurs after trauma or surgery. FM, on the other hand, is frequently triggered by trauma, less often by an infectious process.

While there is a preponderance of women in both disorders, women are more likely to have FM (9:1) than CFS (7:3). The median age for both disorders is about 40 years, although all age groups are vulnerable, including children and seniors. Familial aggregations and overlapping HLA haplotypes are described for both disorders.

Physiologically, both disorders have in common reduced midbrain and cortical blood flow; autonomic dysfunction such as symptomatic orthostatic tachycardia and neurally mediated hypotension;  suppression of the hypothalamic pituitary axis; disturbed Stage 4 sleep; reduced serum or CSF serotonin levels; and suppression of growth hormone, somatomedin C, or IGF1. (Similarities are summarized in Table 2.)

Substance P, a neurotransmitter responsible for the transmission of pain is elevated in persons with FM (but not CFS); and RNaseL, a cellular antiviral enzyme is frequently elevated in CFS (but not in FM). These differences may reflect why pain is a key symptom in FM, and viral symptoms predominate in CFS.

Treatment

The treatment of CFS and FM is hampered by the absence of a known cause and pathophysiology. In such instances, treatment is generally limited to supportive care and symptomatic therapy. Thus a prudent diet, basic supplementation, and traditional management of sleep disruption, pain, and autonomic symptoms are the standard course.

Counseling is helpful in coping with chronic illness and stress, and study after study has extolled the virtues of low level progressive exercise. Activity must be approached cautiously, however.

“Pure cases” of FM seem to respond with increased endurance and improved well-being to a progressive exercise program, while “pure cases” of CFS are more likely to respond with increased cognitive and flulike symptoms to a similar regimen. Thus, persons with CFS may have to start at a lower level and progress more slowly.

Pure Cases

There are certainly cases of “pure CFS” or “pure FM.” When there is no significant complaint of muscle pain, the patient would be diagnosed as having “pure CFS,” mostly characterized by fatigue, cognitive dysfunction, sleep disruption, and flu-like symptoms including vague muscular aching during relapses.

When cognitive symptoms are minimal and widespread muscle pain is the major complaint, the patient is thought to have “pure FM.” These make up a minority of the cases,  however, since about 70% of persons with CFS meet criteria for FM, and about 70% of persons with FM also meet criteria for CFS.

In most aspects Fibromyalgia and CFS are almost identical. There are subtle differences in biochemistry, prevalence, and perhaps response to exercise that separate them ever so slightly. CFS and FM may represent the extreme ends of a spectrum of multisystem disorders characterized by fatigue, pain, and female predominance.

* * * *

Table 1: Differences
CFS                                 FM
Trigger                    Flulike > trauma        Trauma > flulike

Female to Male      7 to 3                          9 to 1
Predominance

Prevalence             400-800 per 100K    2,000 per 100K

Substance P           Normal                       Increased

RNaseL                  Increased                     Normal

Exercise
Intolerance              +++                            +

Table 2: Similarities

• Reduced cerebral blood flow in cortex and midbrain
• HPG Axis suppression
• Non-restorative sleep
• Reduced serum and/or CSF serotonin
• Low growth hormone
• Familial aggregation / haplotypes

___

ProHealth Note – have you visited:

The Treating CFS & FM website (www.treatcfsfm.org). Dr. Lapp and Dr. Campbell are long-time collaborators who have also pooled their knowledge to create this website. It is a guide that can take you step-by-step through creation of a personal treatment plan.

Disclaimer: This material is posted for informational and educational purposes only and is not intended to substitute for medical or other professional advice. Consult your physician or other health care provider regarding your symptoms and medical needs.

 

Extracellular Vesicle Protein and MiRNA Signatures as Biomarkers for Post-Infectious ME/CFS Patients

Abstract:

Post-infectious Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a chronic disease with unresolved pathophysiology and limited diagnostic options. Extracellular vesicles (EVs) carry disease-specific protein and miRNA signatures and may enable improved disease profiling. We aimed to identify novel protein and miRNA markers as potential biomarkers in plasma EVs from female ME/CFS patients, including post-COVID-19 ME/CFS and post-infectious ME/CFS of other origins, compared with healthy controls.

EVs were isolated from plasma by size-exclusion chromatography and characterized for number, size, morphology, and surface marker expression. Flow cytometry showed that small EVs strongly expressed tetraspanins, with only minor differences between ME/CFS patients and healthy donors. Proteomic profiling of EVs from ME/CFS patients identified altered cargo proteins, including hemoglobin subunit alpha and insulin-like growth factor-binding protein acid labile subunit compared with healthy controls (n ≤ 10/cohort). Small RNA sequencing followed by qPCR revealed significant downregulation of hsa-let-7b-5p in EVs from post-COVID-19 ME/CFS patients (n = 12) versus healthy controls (n = 15). Reduced hsa-let-7b-5p expression correlated with impaired physical functioning and increased fatigue, pain, and immune activation.

These findings indicate that EV cargo differences, particularly hemoglobin subunit alpha and insulin-like growth factor-binding protein acid labile subunit, as well as hsa-let-7b-5p, represent promising candidates for ME/CFS diagnosis and patient stratification.

Source: Seifert M, Schäfers J, Douglas FF, Schwarzburg C, Boristowski D, Birke A, Klein O, Sotzny F, Rubarth K, Windzio L, Beez CM, Peters CK, Wittke K, Scheibenbogen C, Greco A. Extracellular Vesicle Protein and MiRNA Signatures as Biomarkers for Post-Infectious ME/CFS Patients. Int J Mol Sci. 2026 Feb 28;27(5):2314. doi: 10.3390/ijms27052314. PMID: 41828537. https://www.mdpi.com/1422-0067/27/5/2314 (Full text)

ACHTSAM study protocol: outreach diagnostics and assessment of tolerability in severe ME/CFS-a pilot study

Abstract:

Introduction: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a severe, multisystem condition that often emerges after viral infections and affects physical and cognitive function. Severely affected patients are underrepresented in research due to immobility and exertional intolerance.

Methods: This is a prospective, non-interventional observational study investigating the feasibility and tolerability of home-based diagnostics in patients with severe and very severe ME/CFS. Phase 1 includes remote identification using validated questionnaires. Phase 2 involves home visits for physiological, cognitive and biological assessments. The primary outcome is feasibility; secondary outcomes include tolerability and methodological barriers.

Ethics/dissemination: The study protocol was approved by the Ethics Committee of the University of Freiburg (No. 25-1031-S1). Written informed consent is obtained from all participants. Results will be disseminated via peer-reviewed publications and patient support groups.

Trial registration number: DRKS00035231; FRKS005506.

Source: Fricke C, Deibert P, Maier P, Kern W, Krumnau O, Barsch F. ACHTSAM study protocol: outreach diagnostics and assessment of tolerability in severe ME/CFS-a pilot study. BMJ Open. 2026 Mar 6;16(3):e113095. doi: 10.1136/bmjopen-2025-113095. PMID: 41791789. https://bmjopen.bmj.com/content/16/3/e113095 (Full text)

ICD-10 Diagnoses prior to ME/CFS diagnosis in children and young people suggest potential early diagnostic indicators

Abstract:

To identify ICD-10-GM codes recorded in the year preceding a Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) diagnosis, we conducted a 1:5 matched case–control study using statutory health insurance data of 6–27-year-olds with ME/CFS (ICD-10-GM: G93.3, 2020–2022). Cases (n = 6,077) were matched 1:5 to controls by birth year, sex, and postal code. ICD-10-GM codes from the preceding year were analyzed using multivariable conditional logistic regression, reporting odds ratios (OR) and 95% confidence intervals. Most cases were female and aged 18–27 years.

Forty-four ICD-10-GM code classes were associated with increased and four with decreased odds, spanning 13 diagnostic chapters. Most associations were in chapters F (mental/behavioral disorders), R (respiratory diseases), and M (musculoskeletal disorders). Frequent conditions included fatigue, depression, pain disorders, and somatoform disorders (≥ 10% in cases; ORs 1.11–2.19. Rare diagnoses (≤ 1% prevalence), such as fibromyalgia (OR 2.08, 95% CI: 1.20–3.59) and mild cognitive impairment (2.93, 1.21–7.10), were strongly associated. Four COVID-19 or vaccination-related code classes were identified, with post-COVID-19 condition showing the highest OR (3.84, 2.97–4.98). Several ICD-10-GM codes, including COVID-19 related codes, were associated with later ME/CFS diagnoses.

Prospective studies should clarify timing relative to ME/CFS onset, and distinguish between pre-existing conditions, comorbidities, early manifestations, or misdiagnoses.

Source:Wirth M, Haastert B, Linnenkamp U, Andrich S, Icks A, Pricoco R, Behrends U, De Bock F. ICD-10 Diagnoses prior to ME/CFS diagnosis in children and young people suggest potential early diagnostic indicators. Sci Rep. 2026 Feb 26. doi: 10.1038/s41598-026-40848-1. Epub ahead of print. PMID: 41741569. https://www.nature.com/articles/s41598-026-40848-1 (Full text)

Diagnosis of chronic fatigue syndrome using beat-to-beat autonomic measurements

Abstract:

Background: An artificial intelligence (AI) pipeline was used to differentiate patients suffering from Chronic Fatigue Syndrome (CFS) from healthy controls (HC) based on high-frequency, large-scale data obtained using beat-to-beat measurement of the autonomic nervous system (ANS) and cardiovascular function.

Methods: This prospective, case-control study included a cohort of 112 CFS patients and 61 HCs examined. Heart rate (HR), high-frequency R-to-R interval (HF RRI), diastolic blood pressure (dBP), stroke volume (SV), and SV index (SV/FFM) were measured using the Task Force Monitor. A novel sequential learning approach was applied: first, a Transformer model was trained, followed by an XGBoost classifier that learned from the errors of the Transformer. Matthews correlation coefficient (MCC), accuracy, and Area Under the Receiver Operating Characteristic Curve (ROC AUC) were assessed. Model classifications were explained globally.

Results: The applied classifier achieved a subject-level accuracy of 0.89, an MCC of 0.79, and an AUC of 1.00. Lower values of beat-to-beat difference in HR and raw HF RRI (indicating reduced cardiac vagal tone) and higher values of dBP difference (more beat-to-beat increases, indicating higher sympathetic vascular tone) were related to being more likely classified as CFS patients. Low values of SV difference and low values of SV/FFM (both indicating less effective cardiac hemodynamics) were related to being more likely classified as CFS patients.

Conclusions: The AI-driven classifier demonstrates remarkable proficiency in distinguishing between patients with CFS and HC. By leveraging this automated pipeline, beat-to-beat measurements of the ANS can significantly enhance the objective assessment of CFS diagnosis.

Source: Kujawski S, Tabisz H, Morten KJ, Modlińska A, Słomko J, Zalewski P. Diagnosis of chronic fatigue syndrome using beat-to-beat autonomic measurements. J Transl Med. 2025 Dec 23;23(1):1413. doi: 10.1186/s12967-025-07433-y. PMID: 41437251; PMCID: PMC12729017. https://pmc.ncbi.nlm.nih.gov/articles/PMC12729017/ (Full text)

Assessment of symptoms in myalgic encephalomyelitis/chronic fatigue syndrome: a comparative study of existing scales

Abstract:

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a multifaceted disorder characterized by persistent fatigue, post-exertional malaise (PEM), cognitive dysfunction, sleep disturbance, pain, psychological distress, orthostatic intolerance, and impaired multidimensional health status and functioning. In the absence of reliable biomarkers, standardized symptom assessment is essential for accurate diagnosis and comparability across studies.

This narrative literature review synthesized studies identified through PubMed and Web of Science up to June 2024, covering assessment instruments across major ME/CFS symptom domains. Tools were evaluated for their psychometric validity, clinical applicability, and key limitations.

Overall, existing scales demonstrate acceptable reliability but vary in sensitivity and disease specificity. Harmonized, multidimensional, and digitally or objectively validated measures are needed to improve diagnostic precision, longitudinal monitoring, and clinical translation in ME/CFS.

Source: Lu J, Sun W, Li S, Qu Y, Liu T, Guo S, Feng C, Yang T. Assessment of symptoms in myalgic encephalomyelitis/chronic fatigue syndrome: a comparative study of existing scales. Front Neurol. 2025 Nov 18;16:1618272. doi: 10.3389/fneur.2025.1618272. PMID: 41341517; PMCID: PMC12668935. https://pmc.ncbi.nlm.nih.gov/articles/PMC12668935/ (Full text)

Approach to nursing diagnoses of people with myalgic encephalomyelitis / chronic fatigue syndrome: a qualitative meta-synthesis

Abstract:

Objective: To identify human responses (diagnostic foci) that shape the experience of living with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and how they manifest throughout the course of the illness.

Methods: A qualitative meta-synthesis was conducted. Original studies exploring the experience of living with ME/CFS in adults with a confirmed diagnosis, published in English or Spanish between 1994 and June 2024, were included. The literature search was carried out in Medline/Medline In-Process, Embase, CINAHL, PsycINFO, SCI-EXPANDED, SSCI, SciELO, Lilacs, and Cuiden. Data analysis was based on the human responses (diagnostic foci) from the NANDA-I Nursing Diagnoses Classification, 2021–2023, with findings structured according to Fennell’s Four-Phase Model.

Results: A total of 42 articles were selected. Twenty human responses (diagnostic foci) and three classes of the NANDA-I Nursing Diagnoses Classification were identified, interwoven across the different phases of the model. Some responses were present throughout all phases, while others, such as Energy Balance and Health Self-Management, became particularly relevant from Phase 2 onwards. Phases 3 and 4 were characterised by losses and processes of subjective reconstruction, with diagnostic foci such as Sorrow, Spiritual Distress, and Personal Identity being predominant.

Conclusions: The identified human responses (diagnostic foci) highlight how the contested and chronic nature of ME/CFS profoundly shapes the lived experience of those affected. The model derived from this review provides a structured framework for targeted nursing interventions, aligned with the phase each individual is experiencing.

Source: Oter-Quintana, C., Esteban-Hernandez, J., Cuellar-Pompa, L., Gil-Carballo, C., Brito-Brito, P. R., Martín-García, A., … Alameda-Cuesta, A. (2025). Approach to nursing diagnoses of people with myalgic encephalomyelitis / chronic fatigue syndrome: a qualitative meta-synthesis. Fatigue: Biomedicine, Health & Behavior, 1–32. https://doi.org/10.1080/21641846.2025.2522028 https://www.tandfonline.com/doi/full/10.1080/21641846.2025.2522028

Biomarkers over Time: From Visual Contrast Sensitivity to Transcriptomics in Differentiating Chronic Inflammatory Response Syndrome and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Abstract:

Chronic inflammatory response syndrome (CIRS) and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) are debilitating multisystem illnesses that share overlapping symptoms and molecular patterns, including immune dysregulation, mitochondrial impairment, and vascular dysfunction. This review provides a chronological synthesis of biomarker development in CIRS, tracing its evolution from early functional tests such as visual contrast sensitivity (VCS) to advanced transcriptomic profiling.

Drawing on peer-reviewed studies spanning two decades, we examine the layered integration of neuroendocrine, immunologic, metabolic, and genomic markers that collectively support a multisystem model of innate immune activation specific to environmentally acquired illness. Particular focus is given to the Gene Expression: Inflammation Explained (GENIE) platform’s use of transcriptomics to classify disease stages and distinguish CIRS from other fatiguing conditions.

While ME/CFS research continues to explore overlapping pathophysiologic features, it has yet to establish a unified diagnostic model with validated biomarkers or exposure-linked mechanisms. As a result, many patients labeled with ME/CFS may, in fact, represent unrecognized CIRS cases.

This review underscores the importance of structured biomarker timelines in improving differential diagnosis and guiding treatment in complex chronic illness and highlights the reproducibility of the CIRS framework in contrast to the diagnostic ambiguity surrounding ME/CFS.

Source: Dooley M. Biomarkers over Time: From Visual Contrast Sensitivity to Transcriptomics in Differentiating Chronic Inflammatory Response Syndrome and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome. Int J Mol Sci. 2025 Jul 28;26(15):7284. doi: 10.3390/ijms26157284. PMID: 40806417. https://www.mdpi.com/1422-0067/26/15/7284 (Full text)

Circulating cell-free RNA signatures for the characterization and diagnosis of myalgic encephalomyelitis/chronic fatigue syndrome

Abstract:

People living with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) experience heterogeneous and debilitating symptoms that lack sufficient biological explanation, compounded by the absence of accurate, noninvasive diagnostic tools. To address these challenges, we explored circulating cell-free RNA (cfRNA) as a blood-borne bioanalyte to monitor ME/CFS. cfRNA is released into the bloodstream during cellular turnover and reflects dynamic changes in gene expression, cellular signaling, and tissue-specific processes.

We profiled cfRNA in plasma by RNA sequencing for 93 ME/CFS cases and 75 healthy sedentary controls, then applied machine learning to develop diagnostic models and advance our understanding of ME/CFS pathobiology. A generalized linear model with least absolute shrinkage selector operator regression trained on condition-specific signatures achieved a test-set AUC of 0.81 and an accuracy of 77%.

Immune cfRNA deconvolution revealed differences in platelet-derived cfRNA between cases and controls, as well as elevated levels of plasmacytoid dendritic, monocyte, and T cell-derived cfRNA in ME/CFS. Biological network analysis further implicated immune dysfunction in ME/CFS, with signatures of cytokine signaling and T cell exhaustion. These findings demonstrate the utility of RNA liquid biopsy as a minimally invasive tool for unraveling the complex biology behind chronic illnesses.

Source: Gardella AE, Eweis-LaBolle D, Loy CJ, Belcher ED, Lenz JS, Franconi CJ, Scofield SY, Grimson A, Hanson MR, De Vlaminck I. Circulating cell-free RNA signatures for the characterization and diagnosis of myalgic encephalomyelitis/chronic fatigue syndrome. Proc Natl Acad Sci U S A. 2025 Aug 19;122(33):e2507345122. doi: 10.1073/pnas.2507345122. Epub 2025 Aug 11. PMID: 40789036. https://pubmed.ncbi.nlm.nih.gov/40789036/

Differential diagnosis between “chronic fatigue” and “chronic fatigue syndrome”

Introduction:

Fatigue is a common complaint experienced by most of subjects during lifetime, which affects approximately 30–50% of general population as point prevalence. According to the fatigue-lasting duration, it is classified as acute (<1 month), prolonged (>1 month, <6 months), and chronic fatigue (≥6 months), respectively. Acute fatigue is generally disappears after taking a rest or treating the causative diseases, while uncontrolled prolonged and chronic fatigue limit the physical and social activities. Especially, medically unexplained chronic fatigue is a debilitating status, such as idiopathic chronic fatigue (ICF) and chronic fatigue syndrome (CFS).

Source: Son CG. Differential diagnosis between “chronic fatigue” and “chronic fatigue syndrome”. Integr Med Res. 2019 Jun;8(2):89-91. doi: 10.1016/j.imr.2019.04.005. Epub 2019 Apr 12. PMID: 31193269; PMCID: PMC6522773. https://pmc.ncbi.nlm.nih.gov/articles/PMC6522773/ (Full text)