Energy Metabolism and Mitochondrial Dysfunction

1 Naviaux 2014 — Cell Danger Response

Full Citation:: Naviaux RK. Metabolic features of the cell danger response. Mitochondrion. 2014;16:7–17. (Naviaux 2014) DOI:: 10.1016/j.mito.2013.08.006 Key Findings::

- Foundational paper on cell danger response (CDR) via purinergic signaling
- ME/CFS hypothesised as persistent CDR state
- Links mitochondrial metabolic shifts to immune activation and chronic illness

Relevance to Part V:: Core theoretical framework for energy metabolism models; CDR provides a unifying mechanism for metabolic–immune coupling.

2 Naviaux et al. 2016 — Metabolic Features of CFS

Full Citation:: Naviaux RK, Naviaux JC, Li K, et al. Metabolic features of chronic fatigue syndrome. Proceedings of the National Academy of Sciences. 2016;113(37):E5472–E5480. (Naviaux et al. 2016) DOI:: 10.1073/pnas.1607571113 Key Findings::

- Targeted metabolomics revealed a hypometabolic state in ME/CFS
- 20 metabolic pathways affected; pattern consistent with a dauer-like hibernation response
- Abnormalities in sphingolipid, phospholipid, and purine metabolism

Relevance to Part V:: Empirical metabolomic data for parameterising energy metabolism models and CDR state transitions.

3 Dibble et al. 2020 — Genetic Risk Factors of ME/CFS: Critical Review

Full Citation:: Dibble JJ, McGrath SJ, Ponting CP. Genetic risk factors of ME/CFS: a critical review. Human Molecular Genetics. 2020;29(R1):R117–R124. (Dibble, McGrath, and Ponting 2020) DOI:: 10.1093/hmg/ddaa169 Key Findings::

- Heritability evidence mixed: UK Biobank SNP-based h² = 0.08 (low confidence); one study claimed high narrow-sense heritability; twin study inconclusive
- Clinically proven mtDNA variants do not commonly explain ME/CFS
- Intriguing observation: ME/CFS patients more likely to carry mtDNA lacking mildly deleterious variants (corroborated by Venter 2019)
- Most candidate gene associations lack replication; larger GWAS studies urgently needed

Conclusion:: No single genetic locus explains ME/CFS; polygenetic or gene-environment interaction model most consistent with evidence. mtDNA predisposition hypothesis not supported by pathogenic mutations but an anomalous variant distribution pattern warrants further investigation. Limitations:: Review covers literature to 2020; DecodeME GWAS results (2025) now available but post-date this review. Certainty:: 0.62 — high-quality critical review in Oxford journal; conclusions conservative and well-supported.

4 Albright et al. 2011 — Heritable Predisposition to CFS

Full Citation:: Albright F, Light K, Light A, Bateman L, Cannon-Albright LA. Evidence for a heritable predisposition to Chronic Fatigue Syndrome. BMC Neurology. 2011;11:62. (Albright et al. 2011) DOI:: 10.1186/1471-2377-11-62 Key Findings::

- Utah Population Database study, n = 811 CFS cases
- First-degree relatives: RR = 2.70 (95% CI 1.56–4.66, p = 0.001)
- Second-degree relatives: RR = 2.34 (p = 0.008); third-degree: RR = 1.93 (p = 0.009)
- Excess relatedness persisted when excluding close relatives, arguing against purely shared-environment explanation
- Does not distinguish maternal vs paternal inheritance; mitochondrial contribution indeterminate

Conclusion:: Strong population-level evidence for a heritable component to CFS predisposition. Molecular substrate unknown; provides the epidemiological foundation for exploring mitochondrial or nuclear genetic predisposition mechanisms. Limitations:: ICD-9 ascertainment only; Utah-specific cohort; cannot attribute heritability to maternal vs paternal lineage. Certainty:: 0.62 — robust methodology using validated genealogical tools; findings replicated in direction by other heritability studies.

5 Billing-Ross et al. 2016 — mtDNA Variants and ME/CFS Symptoms

Full Citation:: Billing-Ross P, Germain A, Ye K, Keinan A, Gu Z, Hanson MR. Mitochondrial DNA variants correlate with symptoms in myalgic encephalomyelitis/chronic fatigue syndrome. Journal of Translational Medicine. 2016;14:19. (Billing-Ross et al. 2016) DOI:: 10.1186/s12967-016-0771-6 Key Findings::

- Complete mitochondrial genome sequencing; n = 193 ME/CFS, 196 controls
- Null susceptibility finding: no association between mtDNA variants and ME/CFS onset
- Haplogroups J, U, H and 8 SNPs significantly associated with symptom severity (joint pain, bloating, post-exertional "feeling dead")
- Heteroplasmy levels low and comparable between cases and controls

Conclusion:: Inherited mtDNA variants do not predispose to ME/CFS onset, but modulate symptom expression once disease is established. Distinction between susceptibility and symptom-modifying effects is critical for predisposition model framing. Limitations:: Predominantly European descent cohort; replication in independent cohort required; multiple testing correction applied but symptom associations should be treated cautiously. Certainty:: 0.55 — adequate sample size, rigorous sequencing, but symptom associations unreplicated.

6 Venter et al. 2019 — MtDNA Population Variation in ME/CFS: Two Cohorts

Full Citation:: Venter M, Tomas C, Pienaar IS, et al. MtDNA population variation in Myalgic encephalomyelitis/Chronic fatigue syndrome in two populations: a study of mildly deleterious variants. Scientific Reports. 2019;9:2914. (Venter et al. 2019) DOI:: 10.1038/s41598-019-39060-1 Key Findings::

- Two independent cohorts: UK (n = 118 patients, 64 controls), South Africa (n = 143 patients, 98 controls)
- No clinically proven pathogenic mtDNA mutations in either cohort
- ME/CFS patients had significantly fewer mildly deleterious variants than controls (UK: 55% vs 27%, p = 0.0008; SA: 56% vs 41%, p = 0.03)
- Unexpected cross-cohort replication of the "fewer deleterious variants" pattern

Conclusion:: ME/CFS patients carry mitochondrial genomes that are — paradoxically — less burdened with mildly deleterious variants than controls. Mechanism unclear; could reflect altered selection pressures or immune-mitochondrial interaction thresholds. Does not support a simple “damaged mtDNA = predisposition” model. Limitations:: Computational MutPred scoring (threshold > 0.5) for variant deleteriousness; biological significance of “mildly deleterious” classification uncertain; larger cohorts needed. Certainty:: 0.52 — cross-cohort replication is a strength; interpretive uncertainty is high.

7 Germain et al. 2020 — Circulatory Metabolomics in ME/CFS

Full Citation:: Germain A, Barupal DK, Levine SM, Hanson MR. Comprehensive Circulatory Metabolomics in ME/CFS Reveals Disrupted Metabolism of Acyl Carnitines and Fatty Acids. Metabolites. 2020;10(1):34. (Germain et al. 2020) DOI:: 10.3390/metabo10010034 Key Findings::

- Disrupted acyl carnitine and fatty acid metabolism
- Identified distinct ME/CFS metabotypes suggesting patient subgroups

Relevance to Part V:: Supports metabolic subtyping in predictive models; fatty acid oxidation parameters for energy models.

8 CastroMarrero et al. 2021 — CoQ10 + NADH RCT

Full Citation:: Castro-Marrero J, Cordero MD, Segundo MJ, et al. Effect of coenzyme Q10 plus nicotinamide adenine dinucleotide supplementation on maximum heart rate after exercise testing in chronic fatigue syndrome — A randomized, controlled, double-blind trial. Clinical Nutrition. 2021;40(5):2898–2906. (Castro-Marrero et al. 2021) DOI:: 10.1016/j.clnu.2021.03.012 Key Findings::

- RCT of CoQ10 + NADH supplementation in CFS
- Improved maximum heart rate after exercise testing

Relevance to Part V:: Treatment parameter data for mitochondrial supplement models and exercise response modeling.

9 Newton et al. 2007 — Fatigue Comparison with Sj"{ogren’s}

Full Citation:: Newton JL, Harte AL, Man W, Jones DE, Pyke DA, Deary IJ, Ng W-F. Fatigue in primary Sjögren’s syndrome: A comparison with chronic fatigue syndrome. Rheumatology. 2007;46(12):1817–1821. (Newton et al. 2007) DOI:: 10.1093/rheumatology/kem235 Key Findings::

- CFS and primary Sjögren's show overlapping fatigue profiles
- Suggests shared pathophysiological mechanisms for fatigue across autoimmune conditions

Relevance to Part V:: Cross-disease comparison for model generalization and shared fatigue pathway identification.

References

Albright, Frederick, Kathleen Light, Alan Light, Lucinda Bateman, and Lisa A Cannon-Albright. 2011. “Evidence for a Heritable Predisposition to Chronic Fatigue Syndrome.” BMC Neurology 11: 62. https://doi.org/10.1186/1471-2377-11-62.

Billing-Ross, Paul, Arnaud Germain, Ketian Ye, Alon Keinan, Zhenglong Gu, and Maureen R Hanson. 2016. “Mitochondrial DNA Variants Correlate with Symptoms in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome.” Journal of Translational Medicine 14: 19. https://doi.org/10.1186/s12967-016-0771-6.

Castro-Marrero, Jesús, Mario D Cordero, María J Segundo, Naia Sáez-Francàs, Natalia Calvo, Lorena Román-Malo, Luis Aliste, Tomás Fernández de Sevilla, and José Alegre. 2021. “Effect of Coenzyme Q10 Plus Nicotinamide Adenine Dinucleotide Supplementation on Maximum Heart Rate After Exercise Testing in Chronic Fatigue Syndrome - a Randomized, Controlled, Double-Blind Trial.” Clinical Nutrition 40 (5): 2898–2906. https://doi.org/10.1016/j.clnu.2021.03.012.

Dibble, Joshua J, Simon J McGrath, and Chris P Ponting. 2020. “Genetic Risk Factors of ME/CFS: A Critical Review.” Human Molecular Genetics 29 (R1): R117–24. https://doi.org/10.1093/hmg/ddaa169.

Germain, Arnaud, Dinesh K Barupal, Susan M Levine, and Maureen R Hanson. 2020. “Comprehensive Circulatory Metabolomics in ME/CFS Reveals Disrupted Metabolism of Acyl Carnitines and Fatty Acids.” Metabolites 10 (1): 34. https://doi.org/10.3390/metabo10010034.

Naviaux, Robert K. 2014. “Metabolic Features of the Cell Danger Response.” Mitochondrion 16: 7–17. https://doi.org/10.1016/j.mito.2013.08.006.

Naviaux, Robert K., Jane C. Naviaux, Kefeng Li, A. Taylor Bright, William A. Alaynick, Lin Wang, Asha Baxter, Neil Nathan, Wayne Anderson, and Eric Gordon. 2016. “Metabolic Features of Chronic Fatigue Syndrome.” Proceedings of the National Academy of Sciences 113 (37): E5472–80. https://doi.org/10.1073/pnas.1607571113.

Newton, Julia L, Alison L Harte, Winnifred Man, David E Jones, David A Pyke, Ian J Deary, and Wan-Fai Ng. 2007. “Fatigue in Primary Sjögren’s Syndrome: A Comparison with Chronic Fatigue Syndrome.” Rheumatology 46 (12): 1817–21. https://doi.org/10.1093/rheumatology/kem235.

Venter, Mareke, Cara Tomas, Ilse S Pienaar, Victoria Strassheim, Engela Erasmus, Wan-Fai Ng, Neil Howell, Julia L Newton, Francois H van der Westhuizen, and Joanna L Elson. 2019. “MtDNA Population Variation in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome in Two Populations: A Study of Mildly Deleterious Variants.” Scientific Reports 9: 2914. https://doi.org/10.1038/s41598-019-39060-1.