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Research Article

Metabolic features of chronic fatigue syndrome

Robert K. Naviaux, Jane C. Naviaux, Kefeng Li, A. Taylor Bright, William A. Alaynick, Lin Wang, Asha Baxter, Neil Nathan, Wayne Anderson, and Eric Gordon
PNAS September 13, 2016 113 (37) E5472-E5480; first published August 29, 2016; https://doi.org/10.1073/pnas.1607571113
Robert K. Naviaux
aThe Mitochondrial and Metabolic Disease Center, University of California, San Diego School of Medicine, San Diego, CA 92103-8467;
bDepartment of Medicine, University of California, San Diego School of Medicine, San Diego, CA 92103-8467;
cDepartment of Pediatrics, University of California, San Diego School of Medicine, San Diego, CA 92103-8467;
dDepartment of Pathology, University of California, San Diego School of Medicine, San Diego, CA 92103-8467;
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  • For correspondence: rnaviaux@ucsd.edu
Jane C. Naviaux
aThe Mitochondrial and Metabolic Disease Center, University of California, San Diego School of Medicine, San Diego, CA 92103-8467;
eDepartment of Neurosciences, University of California, San Diego School of Medicine, San Diego, CA 92103-8467;
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Kefeng Li
aThe Mitochondrial and Metabolic Disease Center, University of California, San Diego School of Medicine, San Diego, CA 92103-8467;
bDepartment of Medicine, University of California, San Diego School of Medicine, San Diego, CA 92103-8467;
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A. Taylor Bright
aThe Mitochondrial and Metabolic Disease Center, University of California, San Diego School of Medicine, San Diego, CA 92103-8467;
bDepartment of Medicine, University of California, San Diego School of Medicine, San Diego, CA 92103-8467;
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William A. Alaynick
aThe Mitochondrial and Metabolic Disease Center, University of California, San Diego School of Medicine, San Diego, CA 92103-8467;
bDepartment of Medicine, University of California, San Diego School of Medicine, San Diego, CA 92103-8467;
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Lin Wang
aThe Mitochondrial and Metabolic Disease Center, University of California, San Diego School of Medicine, San Diego, CA 92103-8467;
bDepartment of Medicine, University of California, San Diego School of Medicine, San Diego, CA 92103-8467;
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Asha Baxter
fGordon Medical Associates, Santa Rosa, CA 95403
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Neil Nathan
fGordon Medical Associates, Santa Rosa, CA 95403
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Wayne Anderson
fGordon Medical Associates, Santa Rosa, CA 95403
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Eric Gordon
fGordon Medical Associates, Santa Rosa, CA 95403
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  1. Edited by Ronald W. Davis, Stanford University School of Medicine, Stanford, CA, and approved July 13, 2016 (received for review May 11, 2016)

This article has a Correction and Letters. Please see:

  • Metabolic features of chronic fatigue syndrome revisited - November 03, 2016
  • Metabolome of chronic fatigue syndrome - January 26, 2017
  • Correction for Naviaux et al., Metabolic features of chronic fatigue syndrome - April 24, 2017

See related content:

  • Metabolomics and chronic fatigue syndrome
    - Nov 03, 2016
  • Metabolome of chronic fatigue syndrome
    - Jan 26, 2017
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Significance

Chronic fatigue syndrome is a multisystem disease that causes long-term pain and disability. It is difficult to diagnose because of its protean symptoms and the lack of a diagnostic laboratory test. We report that targeted, broad-spectrum metabolomics of plasma not only revealed a characteristic chemical signature but also revealed an unexpected underlying biology. Metabolomics showed that chronic fatigue syndrome is a highly concerted hypometabolic response to environmental stress that traces to mitochondria and was similar to the classically studied developmental state of dauer. This discovery opens a fresh path for the rational development of new therapeutics and identifies metabolomics as a powerful tool to identify the chemical differences that contribute to health and disease.

Abstract

More than 2 million people in the United States have myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). We performed targeted, broad-spectrum metabolomics to gain insights into the biology of CFS. We studied a total of 84 subjects using these methods. Forty-five subjects (n = 22 men and 23 women) met diagnostic criteria for ME/CFS by Institute of Medicine, Canadian, and Fukuda criteria. Thirty-nine subjects (n = 18 men and 21 women) were age- and sex-matched normal controls. Males with CFS were 53 (±2.8) y old (mean ± SEM; range, 21–67 y). Females were 52 (±2.5) y old (range, 20–67 y). The Karnofsky performance scores were 62 (±3.2) for males and 54 (±3.3) for females. We targeted 612 metabolites in plasma from 63 biochemical pathways by hydrophilic interaction liquid chromatography, electrospray ionization, and tandem mass spectrometry in a single-injection method. Patients with CFS showed abnormalities in 20 metabolic pathways. Eighty percent of the diagnostic metabolites were decreased, consistent with a hypometabolic syndrome. Pathway abnormalities included sphingolipid, phospholipid, purine, cholesterol, microbiome, pyrroline-5-carboxylate, riboflavin, branch chain amino acid, peroxisomal, and mitochondrial metabolism. Area under the receiver operator characteristic curve analysis showed diagnostic accuracies of 94% [95% confidence interval (CI), 84–100%] in males using eight metabolites and 96% (95% CI, 86–100%) in females using 13 metabolites. Our data show that despite the heterogeneity of factors leading to CFS, the cellular metabolic response in patients was homogeneous, statistically robust, and chemically similar to the evolutionarily conserved persistence response to environmental stress known as dauer.

  • chronic fatigue syndrome
  • metabolomics
  • mitochondria
  • dauer
  • cell danger response

Footnotes

  • ↵1To whom correspondence should be addressed. Email: rnaviaux{at}ucsd.edu.
  • ↵2Present address: Redwood Valley Clinic, 8501 West Road, Redwood Valley, CA, 95470.

  • Author contributions: R.K.N., N.N., W.A., and E.G. designed research; R.K.N., J.C.N., K.L., A.T.B., L.W., A.B., N.N., W.A., and E.G. performed research; R.K.N., J.C.N., K.L., A.T.B., W.A.A., and L.W. contributed new reagents/analytic tools; R.K.N. wrote and managed the human subjects protocol; J.C.N. recruited subjects and developed methods; K.L. developed methods; A.T.B. created the pathway database and developed new bioinformatic methods; W.A.A. prepared the Cytoscape pathway visualizations; A.B. coordinated patient recruitment, medical histories, and clinical data; N.N., W.A., and E.G. identified and recruited patients; R.K.N., J.C.N., K.L., A.T.B., N.N., and E.G. analyzed data; and R.K.N., J.C.N., K.L., A.T.B., and W.A.A. wrote the paper.

  • The authors declare no conflict of interest.

  • This article is a PNAS Direct Submission.

  • Data deposition: The data reported in this paper have been deposited in the NIH Metabolomics Data Repository and Coordinating Center (DRCC) (accession no. ST000450).

  • This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1607571113/-/DCSupplemental.

Freely available online through the PNAS open access option.

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Metabolic features of chronic fatigue syndrome
Robert K. Naviaux, Jane C. Naviaux, Kefeng Li, A. Taylor Bright, William A. Alaynick, Lin Wang, Asha Baxter, Neil Nathan, Wayne Anderson, Eric Gordon
Proceedings of the National Academy of Sciences Sep 2016, 113 (37) E5472-E5480; DOI: 10.1073/pnas.1607571113

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Metabolic features of chronic fatigue syndrome
Robert K. Naviaux, Jane C. Naviaux, Kefeng Li, A. Taylor Bright, William A. Alaynick, Lin Wang, Asha Baxter, Neil Nathan, Wayne Anderson, Eric Gordon
Proceedings of the National Academy of Sciences Sep 2016, 113 (37) E5472-E5480; DOI: 10.1073/pnas.1607571113
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