Metabolic features of chronic fatigue syndrome

Robert Naviaux

Jane Naviaux

Kefeng Li

A Bright

Supplementary Material

Supplementary File

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^{The Mitochondrial and Metabolic Disease Center, University of California, San Diego School of Medicine, San Diego, CA, 92103-8467;}

^{Department of Medicine, University of California, San Diego School of Medicine, San Diego, CA, 92103-8467;}

^{Department of Pediatrics, University of California, San Diego School of Medicine, San Diego, CA, 92103-8467;}

^{Department of Pathology, University of California, San Diego School of Medicine, San Diego, CA, 92103-8467;}

^{Department of Neurosciences, University of California, San Diego School of Medicine, San Diego, CA, 92103-8467;}

^{Gordon Medical Associates, Santa Rosa, CA, 95403}

^{To whom correspondence should be addressed. Email:}ude.dscu@xuaivanr.

Edited by Ronald W. Davis, Stanford University School of Medicine, Stanford, CA, and approved July 13, 2016 (received for review May 11, 2016)

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.

^{Present address: Redwood Valley Clinic, 8501 West Road, Redwood Valley, CA, 95470.}

Edited by Ronald W. Davis, Stanford University School of Medicine, Stanford, CA, and approved July 13, 2016 (received for review May 11, 2016)

Freely available online through the PNAS open access option.

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.

Keywords: chronic fatigue syndrome, metabolomics, mitochondria, dauer, cell danger response

Significance

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.

Abstract

Chronic fatigue syndrome (CFS) is a complex, multiorgan system disease for which no single diagnostic test yet exists. The disease is characterized by profound fatigue and disability lasting for at least 6 mo, episodes of cognitive dysfunction, sleep disturbance, autonomic abnormalities, chronic or intermittent pain syndromes, microbiome abnormalities (1), cerebral cytokine dysregulation (2), natural killer cell dysfunction (3), and other symptoms that are made worse by exertion of any kind (4). The Institute of Medicine (IOM) recently published an update of the diagnostic criteria recommended for CFS (4). These are listed in Box 1.

Box 1

Complex diseases like CFS are often difficult and expensive to diagnose. Although individual tests may be affordable and possibly covered by medical insurance, many patients undergo a diagnostic odyssey that results in substantial personal expenditures that can exceed $100,000 over years of searching, absence from the workplace, and significant reductions in quality of life. The societal cost of CFS is estimated to be up to $24 billion annually (4). Health care professionals are also frustrated by the lack of an objective technology that can assist with diagnosis. Attempts to use a small number of biomarkers, whether analytes in blood, cerebrospinal fluid, or a handful of genetic loci, have not yielded diagnostically useful tests for CFS.

Metabolomics has several advantages over genomics for the diagnosis of complex chronic disease and for the growing interest in precision medicine (5). First, fewer than 2,000 metabolites constitute the majority of the parent molecules in the blood that are used for cell-to-cell communication and metabolism, compared with 6 billion bases in the diploid human genome. Second, metabolites reflect the current functional state of the individual. Collective cellular chemistry represents the functional interaction of genes and environment. This is metabolism. In contrast, the genome represents an admixture of ancestral genotypes that were selected for fitness in ancestral environments. The metabolic state of an individual at the time of illness is produced by both current conditions, age, and the aggregate history, timing, and magnitude of exposures to physical and emotional stress, trauma, diet, exercise, infections, and the microbiome recorded as metabolic memory (6, 7). Analysis of metabolites may provide a more technically and bioinformatically tractable, physiologically relevant, chemically comprehensive, and cost-effective method of diagnosis of complex chronic diseases. In addition, because metabolomics provides direct small-molecule information, the results can provide immediately actionable treatment information using readily available small-molecule nutrients, cofactors, and lifestyle interventions. Our results show that CFS has an objectively identifiable chemical signature in both men and women and that targeted metabolomics can be used to uncover biological insights that may prove useful for both diagnosis and personalized treatment.

n = 18 control males and 22 CFS males, and n = 21 control females and 23 CFS females.

Acknowledgments

R.K.N. thanks the patients and families who donated their time and effort in helping to make this study possible. The authors thank Carla-Rae Lukens for assistance with clinical coordination. We thank Dr. Paul Cheney for guidance, critical comments, and observations. We thank Dr. Phil Morgan and Jon Gangoiti for critical review and comments on the manuscript. R.K.N. thanks all the individuals and the foundations who helped make this project possible with their support. This work was supported in part by the UCSD Christini Fund, The Wright Family Foundation, The Lennox Foundation, The It Takes Guts Foundation, The UCSD Mitochondrial Disease Research Fund, and gifts from Mr. Tom Eames and Ms. Tonye Marie Castenada. Funding for the mass spectrometers used in this study was provided by a gift from the Jane Botsford Johnson Foundation.

Acknowledgments

Footnotes

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.

Footnotes

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