Common Biology of Fatigue Across Immune-Inflammatory Diseases

This stream assembles evidence for the claim that pathological fatigue across autoimmune, autoinflammatory, infectious and malignant immune-activating conditions reflects a shared neuroimmune programme (cytokine-to-brain signalling / sickness behaviour), plus an immune-metabolic energetic conflict (“selfish brain” vs “selfish immune system”), and is mechanistically heterogeneous (multiple objective subtypes rather than one universal biomarker). The driving source is a social-media thread (hypothesis generator, not evidence); every embedded PMID was independently verified. Entries include the unifying cross-disease fatigue reviews, disease-specific fatigue prevalence/mechanism evidence, the human bioenergetic-stress studies, the checkpoint-inhibitor immune-activation signature, and the post-infectious prospective cohort.

1 Morris et al. 2016 — Neuro-Immune Pathophysiology of Fatigue Across Immune-Inflammatory Diseases

Full Citation:: Morris G, Berk M, Galecki P, Walder K, Maes M. The Neuro-Immune Pathophysiology of Central and Peripheral Fatigue in Systemic Immune-Inflammatory and Neuro-Immune Diseases. Molecular Neurobiology. 2016;53(2):1195–1219. (Morris et al. 2016) DOI:: 10.1007/s12035-015-9090-9 PMID:: 25598355 Study Design:: Narrative review Key Findings::

- Fatigue in depression, RA, SLE, Sjögren's, cancer, MS, stroke and ME/CFS converges on a shared set of mechanisms: pro-inflammatory cytokines (IL-1, IL-6, TNF-α, IFN-α), oxidative and nitrosative stress, TLR activation, altered glutamatergic and dopaminergic neurotransmission, mitochondrial dysfunction and Na/K-ATPase defects.
- Both central and peripheral fatigue are framed as consequences of interactions between multiple systemic and central pathways, not a single mediator.

Conclusion: The foundational source for the “shared neuroimmune fatigue programme” claim — it explicitly unifies central and peripheral fatigue across immune-inflammatory and neuro-immune diseases. Establishes the hypothesis the source thread repeats; does not itself provide pooled or controlled evidence. Limitations: Narrative, not systematic; no meta-analysis; broad disease list; no effect sizes. Certainty Assessment: 0.55 raw × 0.75 (general/mechanism) = discounted 0.41 (shared-programme review)

2 Arnett & Clark 2012 — Inflammatory Fatigue and Sickness Behaviour: Lessons for CFS

Full Citation:: Arnett SV, Clark IA. Inflammatory fatigue and sickness behaviour — lessons for the diagnosis and management of chronic fatigue syndrome. Journal of Affective Disorders. 2012;141(2–3):130–142. (Arnett and Clark 2012) DOI:: 10.1016/j.jad.2012.04.004 PMID:: 22578888 Study Design:: Narrative review Key Findings::

- A common inflammatory pathophysiology underlies fatigue in surgical trauma, infection, cancer, IBD, connective-tissue and autoimmune diseases.
- ME/CFS shows important pathophysiological similarities with cytokine-mediated sickness behaviour; lessons from sickness-behaviour biology can inform ME/CFS diagnosis and management.

Conclusion: Supplies the explicit conceptual bridge from the sickness-behaviour model to ME/CFS, seating ME/CFS within the shared immune-fatigue framework. Narrative review; causality and direction unresolved. Limitations: No primary data; no systematic search; does not establish that ME/CFS is a sickness-behaviour state rather than a phenocopy. Certainty Assessment: 0.50 raw × 0.75 (general/mechanism) = discounted 0.38 (conceptual bridge)

3 Kawka et al. 2021 — Fatigue in Systemic Lupus Erythematosus (67–90%)

Full Citation:: Kawka L, Schlencker A, Mertz P, Martin T, Arnaud L. Fatigue in Systemic Lupus Erythematosus: An Update on Its Impact, Determinants and Therapeutic Management. Journal of Clinical Medicine. 2021;10(17):3996. (Kawka et al. 2021) DOI:: 10.3390/jcm10173996 PMID:: 34501444 Study Design:: Narrative review Key Findings::

- Fatigue reported by 67–90% of SLE patients and described as the most bothersome symptom, impairing quality of life and driving employment disability.
- Multifactorial determinants (psychological factors, pain, reduced physical activity); the contribution of disease activity remains controversial.

Conclusion: Establishes very high fatigue prevalence in a prototypical systemic autoimmune disease, and dissociation from disease-activity measures — consistent with a central maintenance mechanism. Limitations: Review; wide prevalence range; determinants contested. Certainty Assessment: 0.50 raw × 1.00 (other disease cohort) = discounted 0.50 (disease-specific prevalence)

4 Tang et al. 2025 — Fatigue in Psoriatic Arthritis (~51%)

Full Citation:: Tang H, Chew TLT, Fong W. Prevalence and factors associated with fatigue in patients with psoriatic arthritis: a systematic review and meta-analysis. BMC Rheumatology. 2025;9(1):44. (Tang, Chew, and Fong 2025) DOI:: 10.1186/s41927-025-00498-8 PMID:: 40251651 Study Design:: Systematic review and meta-analysis (15 studies; n=6,482) Key Findings::

- Pooled fatigue prevalence 0.51 (95% CI 0.41–0.61) in psoriatic arthritis.
- Substantial heterogeneity (I²=97.4%); biologics use and geographic region identified as sources.

Conclusion: Quantifies fatigue burden in an immune-mediated arthritis at approximately half of patients. Robust pooled estimate; definition heterogeneity limits cross-disease comparison. Limitations: Cross-sectional constituent studies; fatigue definitions vary; I² very high. Certainty Assessment: 0.70 raw × 1.00 (other disease cohort) = discounted 0.70 (pooled prevalence)

5 Basta et al. 2018 — Fatigue in Systemic Sclerosis

Full Citation:: Basta F, Afeltra A, Margiotta DPE. Fatigue in systemic sclerosis: a systematic review. Clinical and Experimental Rheumatology. 2018;36 Suppl 113(4):150–160. (Basta, Afeltra, and Margiotta 2018) DOI:: 10.55563/clinexprheumatol/p8x98o PMID:: 29303706 Study Design:: Systematic review (43 records) Key Findings::

- Fatigue is among the most prevalent and debilitating symptoms in systemic sclerosis, with prevalence similar to other rheumatic diseases.
- Associated with depression, pain, sleep disorders, pulmonary and gastrointestinal involvement; relationship to disease-activity scores is uncertain.
- Pharmacological approaches broadly ineffective; physical activity and complementary approaches more encouraging.

Conclusion: Shows fatigue dominance in a fibrotic systemic autoimmune disease and its partial independence from disease activity, while therapeutic failure of anti-inflammatory approaches argues for a maintained, partly non-inflammatory mechanism. Limitations: No pooled estimate; heterogeneous instruments; systematic review of mostly observational studies. Certainty Assessment: 0.55 raw × 1.00 (other disease cohort) = discounted 0.55 (disease-specific review)

6 Harper et al. 2021 — Fatigue in ANCA-Associated Vasculitis Despite Remission

Full Citation:: Harper L, Hewitt CA, Litchfield I, et al. Management of fatigue with physical activity and behavioural change support in vasculitis: a feasibility study. Rheumatology (Oxford). 2021;60(9):4130–4140. (Harper et al. 2021) DOI:: 10.1093/rheumatology/keaa890 PMID:: 33369680 Study Design:: Single-centre open-label randomised feasibility study (43/134 eligible randomised) Key Findings::

- AAV patients in disease remission experienced high levels of fatigue, sufficient to justify a fatigue self-management trial (entry criterion MFI-20 general fatigue ≥14).
- Recruitment and protocol adherence were amber/amber; intervention acceptable to patients.

Conclusion: Demonstrates disabling fatigue persisting in the absence of active vasculitic inflammation — direct evidence for an inflammation-independent maintenance mechanism and for mechanistic heterogeneity. Limitations: Feasibility design, not powered for efficacy; single centre; no mechanistic sampling. Certainty Assessment: 0.55 raw × 1.00 (other disease cohort) = discounted 0.55 (remission-fatigue dissociation)

7 Tang et al. 2023 — Fatigue in Axial Spondyloarthritis (~56%)

Full Citation:: Tang H, Singh BSM, Fong W. Prevalence and factors associated with fatigue in patients with axial spondyloarthritis: a systematic review and meta-analysis. Rheumatology Advances in Practice. 2023;7(3):rkad084. (Tang, Singh, and Fong 2023) DOI:: 10.1093/rap/rkad084 PMID:: 37881507 Study Design:: Systematic review and meta-analysis (30 studies; n=7,893) Key Findings::

- Pooled fatigue prevalence 0.56 (95% CI 0.49–0.63) in axial spondyloarthritis.
- High heterogeneity (I²=94.6%); geographic region a significant source; poorer quality of life associated with more fatigue.

Conclusion: Confirms fatigue in more than half of patients in a second major spondyloarthritis, supporting the cross-disease pattern. Robust pooled estimate; cross-sectional source studies. Limitations: Fatigue-definition heterogeneity; no mechanistic measures. Certainty Assessment: 0.70 raw × 1.00 (other disease cohort) = discounted 0.70 (pooled prevalence)

8 de Kleijn et al. 2009 — Fatigue in Sarcoidosis

Full Citation:: de Kleijn WPE, De Vries J, Lower EE, Elfferich MDP, Baughman RP, Drent M. Fatigue in sarcoidosis: a systematic review. Current Opinion in Pulmonary Medicine. 2009;15(5):499–506. Kleijn et al. (2009) DOI:: 10.1097/MCP.0b013e32832d0403 PMID:: 19458531 Study Design:: Systematic review Key Findings::

- Fatigue is a prominent, under-recognized complication of sarcoidosis, associated with impaired quality of life.
- Methodologically rigorous studies found no relationship between clinical parameters and fatigue; prednisone-treated patients reported more fatigue.
*Conclusion:* Fatigue in a granulomatous inflammatory disease is dissociated from clinical disease parameters, paralleling SLE/SSc and supporting a maintained central mechanism. Etiology unstudied; no pooled estimate.

Limitations: Heterogeneous instruments; no etiological studies; older review. Certainty Assessment: 0.50 raw × 1.00 (other disease cohort) = discounted 0.50 (disease-specific review)

9 Ricci et al. 2022 — Fatigue as a Common Signature of Inflammatory Myopathies

Full Citation:: Ricci G, Fontanelli L, Torri F, Schirinzi E, Siciliano G. Fatigue as a common signature of inflammatory myopathies: clinical aspects and care. Clinical and Experimental Rheumatology. 2022;40(2):425–432. (Ricci et al. 2022) DOI:: 10.55563/clinexprheumatol/p8x98o PMID:: 35225228 Study Design:: Narrative review Key Findings::

- Fatigue spans biological to behavioural dimensions in idiopathic inflammatory myopathies and greatly affects activities of daily living.
- Pathophysiology remains poorly understood; the review proposes clinical evaluation and management strategies.

Conclusion: Fatigue in a muscle-specific autoimmune disease is not explained solely by myocyte injury, supporting a central component. Narrative review; no prevalence pooling. Limitations: No primary data; no systematic search. Certainty Assessment: 0.45 raw × 1.00 (other disease cohort) = discounted 0.45 (disease-specific narrative)

10 Ruiter et al. 2020 — Fatigue vs Fatigability in Myasthenia Gravis

Full Citation:: Ruiter AM, Verschuuren JJGM, Tannemaat MR. Fatigue in patients with myasthenia gravis. A systematic review of the literature. Neuromuscular Disorders. 2020;30(8):631–639. (Ruiter, Verschuuren, and Tannemaat 2020) DOI:: 10.1016/j.nmd.2020.06.010 PMID:: 32718868 Study Design:: Systematic review (5 domains) Key Findings::

- Distinguishes peripheral fatigability (neuromuscular-junction dysfunction) from central fatigue (experienced lack of energy) in myasthenia gravis.
- Patient-reported fatigue prevalence 42–82%, significantly higher than controls, and highly prevalent even in ocular MG and patients in remission.
- Fatigue strongly associated with depressive symptoms, female gender and disease severity; treatable with physical/psychological training.

Conclusion: The clearest clinical dissociation between objective peripheral fatigability and central fatigue — high fatigue despite controlled neuromuscular transmission supports a distinct central mechanism. Questionnaire heterogeneity; pathophysiology unknown. Limitations: Varied assessment instruments; observational studies; no mechanistic data. Certainty Assessment: 0.60 raw × 1.00 (other disease cohort) = discounted 0.60 (fatigue/fatigability dissociation)

11 Khan et al. 2014 — Fatigue in Multiple Sclerosis (~80%)

Full Citation:: Khan F, Amatya B, Galea M. Management of fatigue in persons with multiple sclerosis. Frontiers in Neurology. 2014;5:177. (Khan, Amatya, and Galea 2014) DOI:: 10.3389/fneur.2014.00177 PMID:: 25309504 Study Design:: Systematic review of interventions Key Findings::

- Fatigue affects almost 80% of people with MS and remains the disabling symptom despite advances in treatment.
- Both pharmacological and non-pharmacological interventions are used in a multidisciplinary approach; the evidence body is growing but limited.

Conclusion: Documents very high fatigue prevalence in a central demyelinating autoimmune disease, reinforcing the cross-disease pattern. Prevalence cited rather than pooled; older review. Limitations: 2014; intervention-focused; no prevalence meta-analysis. Certainty Assessment: 0.55 raw × 1.00 (other disease cohort) = discounted 0.55 (disease-specific review)

12 D’Silva et al. 2022 — Fatigue in Inflammatory Bowel Disease (47%; 72% active)

Full Citation:: D’Silva A, Fox DE, Nasser Y, Vallance JK, Quinn RR, Ronksley PE, Raman M. Prevalence and Risk Factors for Fatigue in Adults With Inflammatory Bowel Disease: A Systematic Review With Meta-Analysis. Clinical Gastroenterology and Hepatology. 2022;20(5):995–1009.e7. (D’Silva et al. 2022) DOI:: 10.1016/j.cgh.2021.06.034 PMID:: 34216824 Study Design:: Systematic review and meta-analysis (20 studies) Key Findings::

- Pooled IBD fatigue prevalence 47% (95% CI 41–54); 72% in active disease versus 47% in remission.
- Sleep disturbance, anxiety, depression and anemia were the most commonly reported risk factors.

Conclusion: Provides a disease-state gradient (active greater than remission) while confirming substantial residual fatigue in remission — evidence that inflammation modulates but does not fully explain fatigue. High heterogeneity (I²=98%). Limitations: Definition-dependent prevalence; cross-sectional source studies. Certainty Assessment: 0.70 raw × 1.00 (other disease cohort) = discounted 0.70 (pooled prevalence)

13 Skjellerudsveen et al. 2019 — Fatigue in Coeliac Disease

Full Citation:: Skjellerudsveen BM, Omdal R, Grimstad T. Fatigue in celiac disease: A review of the literature. JGH Open. 2019;3(3):242–248. (Skjellerudsveen, Omdal, and Grimstad 2019) DOI:: 10.1002/jgh3.12134 PMID:: 31276043 Study Design:: Systematic review (18 articles) Key Findings::

- Fatigue was significantly greater in coeliac disease than in healthy controls; prevalence ranged 8–100% depending on instrument.
- Five of seven studies reported less fatigue on a gluten-free diet; two found no significant difference.

Conclusion: Fatigue in a dietary-antigen-driven immune disease is modifiable by removing the immune trigger in some patients, supporting an immune-fatigue link while showing wide inter-study inconsistency. Very wide prevalence range limits pooling. Limitations: Instrument heterogeneity; small diet-effect literature; no mechanistic data. Certainty Assessment: 0.50 raw × 1.00 (other disease cohort) = discounted 0.50 (disease-specific review)

14 Lynch et al. 2022 — Fatigue in Primary Biliary Cholangitis (Central vs Peripheral)

Full Citation:: Lynch EN, Campani C, Innocenti T, Dragoni G, Biagini MR, Forte P, Galli A. Understanding fatigue in primary biliary cholangitis: From pathophysiology to treatment perspectives. World Journal of Hepatology. 2022;14(6):1111–1119. (Lynch et al. 2022) DOI:: 10.4254/wjh.v14.i6.1111 PMID:: 35978669 Study Design:: Narrative review Key Findings::

- Fatigue affects over 50% of PBC patients, one in five severely; central fatigue (lack of self-motivation / lack of intention) is distinguished from peripheral fatigue (neuromuscular dysfunction / lack of ability).
- Fatigue is not related to disease progression except in end-stage liver disease; no licensed therapy exists.

Conclusion: The central-fatigue construct in PBC (“lack of intention”) closely parallels ME/CFS fatigue and is dissociated from disease progression. Narrative review; pathophysiology unresolved. Limitations: No primary data; no pooled prevalence. Certainty Assessment: 0.50 raw × 1.00 (other disease cohort) = discounted 0.50 (disease-specific review)

15 Newton et al. 2007 — Autonomic Dysfunction and Fatigue in Primary Biliary Cirrhosis (40% vs 6%)

Full Citation:: Newton JL, Hudson M, Tachtatzis P, Sutcliffe K, Pairman J, Burt JA, Jones DEJ. Population prevalence and symptom associations of autonomic dysfunction in primary biliary cirrhosis. Hepatology. 2007;45(6):1496–1505. (Newton et al. 2007) DOI:: 10.1002/hep.21609 PMID:: 17538969 Study Design:: Cross-sectional, geographically defined representative cohort Key Findings::

- Moderate-or-worse orthostatic symptoms in 40% of PBC patients versus 6% of matched controls (P less than 0.0001; mean OGS 3.2±3.4 vs 1.3±1.9, P less than 0.005).
- Autonomic symptom severity independently associated with both fatigue severity and cognitive symptoms (both r²=0.3, P less than 0.0001); objective BP dysregulation on dynamic testing in 13/20 with OGS greater than 4.

Conclusion: Links a non-inflammatory autonomic axis to fatigue in an autoimmune disease — objective blood-pressure dysregulation substantiates the link, and the association with cognitive symptoms mirrors ME/CFS. Cross-sectional; single geographic region. Limitations: Observational; OGS is symptom-based for the prevalence figure; causality unestablished. Certainty Assessment: 0.65 raw × 1.00 (other disease cohort) = discounted 0.65 (autonomic-fatigue link)

16 Al Maqbali et al. 2021 — Cancer-Related Fatigue (49%; N=71,568)

Full Citation:: Al Maqbali M, Al Sinani M, Al Naamani Z, Al Badi K, Tanash MI. Prevalence of Fatigue in Patients With Cancer: A Systematic Review and Meta-Analysis. Journal of Pain and Symptom Management. 2021;61(1):167–189.e14. (Al Maqbali et al. 2021) DOI:: 10.1016/j.jpainsymman.2020.07.037 PMID:: 32768552 Study Design:: Systematic review and meta-analysis (129 studies; N=71,568) Key Findings::

- Overall cancer fatigue prevalence 49% (95% CI 45–53); 62% during treatment and 60.6% in advanced disease.
- Prevalence declined from 64% (1996–2000) to 43% (2016–2020); female gender a significant moderator.

Conclusion: The largest pooled estimate of fatigue in an immune-relevant malignant disease; the secular decline and treatment-stage gradient indicate fatigue is modulated by immune/treatment factors and is not a fixed tumour property. Very high heterogeneity (I²=98.9%). Limitations: Heterogeneous instruments and populations; no mechanism data. Certainty Assessment: 0.75 raw × 1.00 (other disease cohort) = discounted 0.75 (pooled prevalence)

17 Hickie et al. 2006 — Dubbo Infection Outcomes Study (Post-Infective Fatigue, 11% CFS)

Full Citation:: Hickie I, Davenport T, Wakefield D, Vollmer-Conna U, Cameron B, Vernon SD, Reeves WC, Lloyd A; Dubbo Infection Outcomes Study Group. Post-infective and chronic fatigue syndromes precipitated by viral and non-viral pathogens: prospective cohort study. BMJ. 2006;333(7568):575. (Hickie et al. 2006) DOI:: 10.1136/bmj.38933.585764.AE PMID:: 16950834 Study Design:: Prospective cohort (n=253), enrolled at acute infection and followed 12 months Key Findings::

- Prolonged disabling fatigue illness in 29/253 (12%) at six months; 28 (11%) met CFS diagnostic criteria.
- The post-infective fatigue syndrome was stereotyped and occurred at similar incidence after EBV, Coxiella burnetii (Q fever) and Ross River virus.
- The syndrome was predicted by severity of the acute illness, not by demographic, psychological or microbiological factors.

Conclusion: The strongest prospective evidence that a conserved, pathogen-nonspecific post-infectious fatigue pathway exists, and the canonical model for one route into ME/CFS. Geographic restriction (rural Australia); one diagnostic era (Fukuda). Limitations: Single region; six-month outcome; no mechanistic sampling; Fukuda criteria. Certainty Assessment: 0.75 raw × 0.85 (post-viral fatigue) = discounted 0.64 (post-infectious cohort)

18 Kealy et al. 2020 — Acute Inflammation Alters Brain Energy Metabolism (Mouse + Human)

Full Citation:: Kealy J, Murray C, Griffin EW, Lopez-Rodriguez AB, Healy D, Tortorelli LS, Lowry JP, Watne LO, Cunningham C. Acute Inflammation Alters Brain Energy Metabolism in Mice and Humans: Role in Suppressed Spontaneous Activity, Impaired Cognition, and Delirium. Journal of Neuroscience. 2020;40(29):5681–5696. (Kealy et al. 2020) DOI:: 10.1523/JNEUROSCI.2876-19.2020 PMID:: 32513828 Study Design:: Mouse experiments + human CSF corroboration Key Findings::

- LPS induced hypoglycemia and reduced CSF glucose; suppression of locomotor activity correlated with blood glucose, was mitigated by exogenous glucose and exacerbated by 2-deoxyglucose.
- Acute cognitive impairments were mimicked by insulin and mitigated by glucose, selectively in animals with existing neurodegeneration.
- Hip-fracture patients with delirium showed elevated CSF lactate and pyruvate, consistent with altered brain energy metabolism.

Conclusion: Provides the mechanistic core of the “selfish immune system” claim — immune activation reduces brain glucose, and the resulting bioenergetic stress drives suppressed spontaneous activity. Mouse model with human CSF corroboration; not ME/CFS; translation gap remains. Limitations: Primary evidence is murine; human arm is delirium, not fatigue; single immune stimulus. Certainty Assessment: 0.65 raw × 0.50 (animal model) = discounted 0.33 (bioenergetic mechanism)

19 Titlestad et al. 2024 — Impaired Brain Glucose Utilization in Human Delirium

Full Citation:: Titlestad I, Watne LO, Caplan GA, et al. Impaired glucose utilization in the brain of patients with delirium following hip fracture. Brain. 2024;147(1):215–223. (Titlestad et al. 2024) DOI:: 10.1093/brain/awad296 PMID:: 37658825 Study Design:: Prospective human cohort (406 hip-fracture patients, mean age 81), serum and CSF targeted metabolic profiling Key Findings::

- Delirium was associated with impaired glucose utilization in the brain, measured by targeted CSF/serum metabolite profiling.
- Human confirmation that acute systemic inflammation/injury is accompanied by objective central energy-metabolism impairment.

Conclusion: The human counterpart to Kealy 2020 — central energy-metabolism impairment is measurable in patients during an inflammation-associated neuropsychiatric state. Elderly surgical population; delirium phenotype, not ME/CFS. Limitations: Not ME/CFS; elderly hip-fracture cohort; association not causation. Certainty Assessment: 0.65 raw × 0.75 (general-population patients) = discounted 0.49 (human bioenergetic evidence)

20 Li et al. 2025 — Immune-Activation Signature of ICI-Related Fatigue (Th1, Effector CD8)

Full Citation:: Li HL, Charmsaz S, Nakazawa M, et al. Immune Activation Signatures Associated with Fatigue in Cancer Patients Undergoing Immune Checkpoint Inhibitor Therapy. Cancer Research Communications. 2025;5(10):1738–1746. (Li et al. 2025) DOI:: 10.1158/2767-9764.CRC-25-0240 PMID:: 40952384 Study Design:: Prospective cohort (n=53 solid-tumour patients on ICI), serial blood sampling Key Findings::

- 31/53 (58.5%) reported worsening fatigue during ICI therapy.
- Fatigued patients showed broad early-treatment cytokine elevations, most prominently the Th1 cluster (IFN-γ, IL-2, IL-12), with expansion of cytotoxic effector CD8+ T-cell clusters.
- Fatigue was not associated with objective tumour response or with other immune-related adverse events.

Conclusion: A human, temporally resolved link between a defined immune-activation signature (Th1/effector CD8) and fatigue, positioning fatigue as a clinical surrogate of immune activation. Single-centre, modest n; causality not established. Limitations: Solid-tumour/ICI population; n=53; single centre; correlational. Certainty Assessment: 0.65 raw × 1.00 (other disease cohort) = discounted 0.65 (immune-activation signature)

21 Fencková 2024 — When the ‘Selfish’ Brain and ‘Selfish’ Immune System Clash

Full Citation:: Fencková M. When the ‘selfish’ brain and the ‘selfish’ immune system clash. Nature Reviews Neuroscience. 2024;26:140. (Fenckova 2024) DOI:: 10.1038/s41583-024-00900-3 PMID:: — Study Design:: Journal research highlight (editorial) Key Findings::

- Frames the "selfish brain" versus "selfish immune system" energetic conflict: during immune activation the brain's energy supply is compromised, with behavioral and cognitive consequences.
- Cites Kealy 2020 and Titlestad 2024 as the supporting primary evidence.

Conclusion: A concise statement of the shared energetic-conflict framing used by the source thread; included for provenance of the “selfish brain vs selfish immune” phrase, not as evidence. Highlight, not a study. Limitations: Editorial; no primary data; two references. Certainty Assessment: 0.35 raw × 0.75 (general/mechanism) = discounted 0.26 (framing source)

References

Al Maqbali, Mohammed, Mallak Al Sinani, Zahra Al Naamani, Khalid Al Badi, and Murad I Tanash. 2021. “Prevalence of Fatigue in Patients with Cancer: A Systematic Review and Meta-Analysis.” Journal of Pain and Symptom Management 61 (1): 167–189.e14. https://doi.org/10.1016/j.jpainsymman.2020.07.037.

Arnett, Simon V, and Ian A Clark. 2012. “Inflammatory Fatigue and Sickness Behaviour - Lessons for the Diagnosis and Management of Chronic Fatigue Syndrome.” Journal of Affective Disorders 141 (2-3): 130–42. https://doi.org/10.1016/j.jad.2012.04.004.

Basta, Fabio, Antonella Afeltra, and Domenico Paolo Emanuele Margiotta. 2018. “Fatigue in Systemic Sclerosis: A Systematic Review.” Clinical and Experimental Rheumatology 36 Suppl 113 (4): 150–60.

D’Silva, Adrijana, Danielle E Fox, Yasmin Nasser, Jeff K Vallance, Robert R Quinn, Paul E Ronksley, and Maitreyi Raman. 2022. “Prevalence and Risk Factors for Fatigue in Adults with Inflammatory Bowel Disease: A Systematic Review with Meta-Analysis.” Clinical Gastroenterology and Hepatology 20 (5): 995–1009.e7. https://doi.org/10.1016/j.cgh.2021.06.034.

Fenckova, Michaela. 2024. “When the ’Selfish’ Brain and the ’Selfish’ Immune System Clash.” Nature Reviews Neuroscience 26: 140. https://doi.org/10.1038/s41583-024-00900-3.

Harper, Lorraine, Catherine A Hewitt, Ian Litchfield, Matthew D Morgan, Dimitrios Chanouzas, Hannah K Caulfield, Laura Coughlan, et al. 2021. “Management of Fatigue with Physical Activity and Behavioural Change Support in Vasculitis: A Feasibility Study.” Rheumatology (Oxford) 60 (9): 4130–40. https://doi.org/10.1093/rheumatology/keaa890.

Hickie, Ian, Tracey Davenport, Denis Wakefield, Ute Vollmer-Conna, Barbara Cameron, Suzanne D Vernon, William C Reeves, and Andrew Lloyd. 2006. “Post-Infective and Chronic Fatigue Syndromes Precipitated by Viral and Non-Viral Pathogens: Prospective Cohort Study.” BMJ 333 (7568): 575. https://doi.org/10.1136/bmj.38933.585764.AE.

Kawka, Lou, Aurelien Schlencker, Philippe Mertz, Thierry Martin, and Laurent Arnaud. 2021. “Fatigue in Systemic Lupus Erythematosus: An Update on Its Impact, Determinants and Therapeutic Management.” Journal of Clinical Medicine 10 (17): 3996. https://doi.org/10.3390/jcm10173996.

Kealy, John, Carol Murray, Eoin W Griffin, Ana Belen Lopez-Rodriguez, Daire Healy, Lucas Silva Tortorelli, John P Lowry, Leiv Otto Watne, and Colm Cunningham. 2020. “Acute Inflammation Alters Brain Energy Metabolism in Mice and Humans: Role in Suppressed Spontaneous Activity, Impaired Cognition, and Delirium.” Journal of Neuroscience 40 (29): 5681–96. https://doi.org/10.1523/JNEUROSCI.2876-19.2020.

Khan, Fary, Bhasker Amatya, and Mary Galea. 2014. “Management of Fatigue in Persons with Multiple Sclerosis.” Frontiers in Neurology 5: 177. https://doi.org/10.3389/fneur.2014.00177.

Kleijn, Willemien P E de, Jolanda De Vries, Elyse E Lower, Marjon D P Elfferich, Robert P Baughman, and Marjolein Drent. 2009. “Fatigue in Sarcoidosis: A Systematic Review.” Current Opinion in Pulmonary Medicine 15 (5): 499–506. https://doi.org/10.1097/MCP.0b013e32832d0403.

Li, Han Ling, Soren Charmsaz, Mark Nakazawa, Sarah L Alden, Marco Brancati, James M Leatherman, Elizabeth Griffin, et al. 2025. “Immune Activation Signatures Associated with Fatigue in Cancer Patients Undergoing Immune Checkpoint Inhibitor Therapy.” Cancer Research Communications 5 (10): 1738–46. https://doi.org/10.1158/2767-9764.CRC-25-0240.

Lynch, Erica N, Claudia Campani, Tommaso Innocenti, Gabriele Dragoni, Maria Rosa Biagini, Paolo Forte, and Andrea Galli. 2022. “Understanding Fatigue in Primary Biliary Cholangitis: From Pathophysiology to Treatment Perspectives.” World Journal of Hepatology 14 (6): 1111–19. https://doi.org/10.4254/wjh.v14.i6.1111.

Morris, Gerwyn, Michael Berk, Piotr Galecki, Ken Walder, and Michael Maes. 2016. “The Neuro-Immune Pathophysiology of Central and Peripheral Fatigue in Systemic Immune-Inflammatory and Neuro-Immune Diseases.” Molecular Neurobiology 53 (2): 1195–1219. https://doi.org/10.1007/s12035-015-9090-9.

Newton, Julia L, Mark Hudson, Phaedra Tachtatzis, Kathryn Sutcliffe, Jessie Pairman, Jennifer A Burt, and David E J Jones. 2007. “Population Prevalence and Symptom Associations of Autonomic Dysfunction in Primary Biliary Cirrhosis.” Hepatology 45 (6): 1496–1505. https://doi.org/10.1002/hep.21609.

Ricci, Giulia, Lorenzo Fontanelli, Francesca Torri, Erika Schirinzi, and Gabriele Siciliano. 2022. “Fatigue as a Common Signature of Inflammatory Myopathies: Clinical Aspects and Care.” Clinical and Experimental Rheumatology 40 (2): 425–32. https://doi.org/10.55563/clinexprheumatol/p8x98o.

Ruiter, Anika M, Jan J G M Verschuuren, and Martijn R Tannemaat. 2020. “Fatigue in Patients with Myasthenia Gravis. A Systematic Review of the Literature.” Neuromuscular Disorders 30 (8): 631–39. https://doi.org/10.1016/j.nmd.2020.06.010.

Skjellerudsveen, Berit M, Roald Omdal, and Tore Grimstad. 2019. “Fatigue in Celiac Disease: A Review of the Literature.” JGH Open 3 (3): 242–48. https://doi.org/10.1002/jgh3.12134.

Tang, Hong, Ting Loon Teo Chew, and Warren Fong. 2025. “Prevalence and Factors Associated with Fatigue in Patients with Psoriatic Arthritis: A Systematic Review and Meta-Analysis.” BMC Rheumatology 9 (1): 44. https://doi.org/10.1186/s41927-025-00498-8.

Tang, Hong, Bernard S M Singh, and Warren Fong. 2023. “Prevalence and Factors Associated with Fatigue in Patients with Axial Spondyloarthritis: A Systematic Review and Meta-Analysis.” Rheumatology Advances in Practice 7 (3): rkad084. https://doi.org/10.1093/rap/rkad084.

Titlestad, Ingrid, Leiv Otto Watne, Gideon A Caplan, Adrian McCann, Per Magne Ueland, Bjorn Erik Neerland, Marius Myrstad, et al. 2024. “Impaired Glucose Utilization in the Brain of Patients with Delirium Following Hip Fracture.” Brain 147 (1): 215–23. https://doi.org/10.1093/brain/awad296.