Fecal metagenomic profiles in subgroups of patients with myalgic encephalomyelitis/chronic fatigue syndrome
Dorottya Nagy-Szakal, Brent L Williams, Nischay Mishra, Xiaoyu Che, Bohyun Lee, Lucinda Bateman, Nancy G Klimas, Anthony L Komaroff, Susan Levine, Jose G Montoya, Daniel L Peterson, Devi Ramanan, Komal Jain, Meredith L Eddy, Mady Hornig, W Ian Lipkin, Dorottya Nagy-Szakal, Brent L Williams, Nischay Mishra, Xiaoyu Che, Bohyun Lee, Lucinda Bateman, Nancy G Klimas, Anthony L Komaroff, Susan Levine, Jose G Montoya, Daniel L Peterson, Devi Ramanan, Komal Jain, Meredith L Eddy, Mady Hornig, W Ian Lipkin
Abstract
Background: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is characterized by unexplained persistent fatigue, commonly accompanied by cognitive dysfunction, sleeping disturbances, orthostatic intolerance, fever, lymphadenopathy, and irritable bowel syndrome (IBS). The extent to which the gastrointestinal microbiome and peripheral inflammation are associated with ME/CFS remains unclear. We pursued rigorous clinical characterization, fecal bacterial metagenomics, and plasma immune molecule analyses in 50 ME/CFS patients and 50 healthy controls frequency-matched for age, sex, race/ethnicity, geographic site, and season of sampling.
Results: Topological analysis revealed associations between IBS co-morbidity, body mass index, fecal bacterial composition, and bacterial metabolic pathways but not plasma immune molecules. IBS co-morbidity was the strongest driving factor in the separation of topological networks based on bacterial profiles and metabolic pathways. Predictive selection models based on bacterial profiles supported findings from topological analyses indicating that ME/CFS subgroups, defined by IBS status, could be distinguished from control subjects with high predictive accuracy. Bacterial taxa predictive of ME/CFS patients with IBS were distinct from taxa associated with ME/CFS patients without IBS. Increased abundance of unclassified Alistipes and decreased Faecalibacterium emerged as the top biomarkers of ME/CFS with IBS; while increased unclassified Bacteroides abundance and decreased Bacteroides vulgatus were the top biomarkers of ME/CFS without IBS. Despite findings of differences in bacterial taxa and metabolic pathways defining ME/CFS subgroups, decreased metabolic pathways associated with unsaturated fatty acid biosynthesis and increased atrazine degradation pathways were independent of IBS co-morbidity. Increased vitamin B6 biosynthesis/salvage and pyrimidine ribonucleoside degradation were the top metabolic pathways in ME/CFS without IBS as well as in the total ME/CFS cohort. In ME/CFS subgroups, symptom severity measures including pain, fatigue, and reduced motivation were correlated with the abundance of distinct bacterial taxa and metabolic pathways.
Conclusions: Independent of IBS, ME/CFS is associated with dysbiosis and distinct bacterial metabolic disturbances that may influence disease severity. However, our findings indicate that dysbiotic features that are uniquely ME/CFS-associated may be masked by disturbances arising from the high prevalence of IBS co-morbidity in ME/CFS. These insights may enable more accurate diagnosis and lead to insights that inform the development of specific therapeutic strategies in ME/CFS subgroups.
Keywords: Chronic fatigue syndrome; Irritable bowel syndrome; Metabolic pathway; Metagenomic; Microbiota-gut-brain axis; Myalgic encephalomyelitis; Topological data analysis.
Figures
References
- Institute of Medicine I . Beyond myalgic encephalomyelitis/chronic fatigue syndrome: redefining an illness. Washington: The National Academies Press; 2015.
- Jason LA, Benton MC, Valentine L, Johnson A, Torres-Harding S. The economic impact of ME/CFS: individual and societal costs. Dyn Med. 2008;7:6. doi: 10.1186/1476-5918-7-6.
- Evans M, Barry M, Im Y, Brown A, Jason LA. An investigation of symptoms predating CFS onset. J Prev Interv Community. 2015;43(1):54–61. doi: 10.1080/10852352.2014.973240.
- Aaron LA, Herrell R, Ashton S, Belcourt M, Schmaling K, Goldberg J, Buchwald D. Comorbid clinical conditions in chronic fatigue: a co-twin control study. J Gen Intern Med. 2001;16(1):24–31.
- Hausteiner-Wiehle C, Henningsen P. Irritable bowel syndrome: relations with functional, mental, and somatoform disorders. World J Gastroenterol. 2014;20(20):6024–6030. doi: 10.3748/wjg.v20.i20.6024.
- Kim SE, Chang L. Overlap between functional GI disorders and other functional syndromes: what are the underlying mechanisms? Neurogastroenterol Motil. 2012;24(10):895–913. doi: 10.1111/j.1365-2982.2012.01993.x.
- Dinan TG, Cryan JF. Microbes, immunity, and behavior: psychoneuroimmunology meets the microbiome. Neuropsychopharmacology. 2017;42(1):178–92. doi: 10.1038/npp.2016.103.
- Mayer EA. Gut feelings: the emerging biology of gut-brain communication. Nat Rev Neurosci. 2011;12(8):453–466. doi: 10.1038/nrn3071.
- O’Malley D. Immunomodulation of enteric neural function in irritable bowel syndrome. World J Gastroenterol. 2015;21(24):7362–7366. doi: 10.3748/wjg.v21.i24.7362.
- Yarandi SS, Peterson DA, Treisman GJ, Moran TH, Pasricha PJ. Modulatory effects of gut microbiota on the central nervous system: how gut could play a role in neuropsychiatric health and diseases. J Neurogastroenterol Motil. 2016;22(2):201–212. doi: 10.5056/jnm15146.
- Reigstad CS, Kashyap PC. Beyond phylotyping: understanding the impact of gut microbiota on host biology. Neurogastroenterol Motil. 2013;25(5):358–372. doi: 10.1111/nmo.12134.
- Giloteaux L, Goodrich JK, Walters WA, Levine SM, Ley RE, Hanson MR. Reduced diversity and altered composition of the gut microbiome in individuals with myalgic encephalomyelitis/chronic fatigue syndrome. Microbiome. 2016;4(1):30. doi: 10.1186/s40168-016-0171-4.
- Fremont M, Coomans D, Massart S, De Meirleir K. High-throughput 16S rRNA gene sequencing reveals alterations of intestinal microbiota in myalgic encephalomyelitis/chronic fatigue syndrome patients. Anaerobe. 2013;22:50–56. doi: 10.1016/j.anaerobe.2013.06.002.
- Sheedy JR, Wettenhall REH, Scanlon D, Gooley PR, Lewis DP, Mcgregor N, Stapleton DI, Butt HL, De Meirleir KL. Increased D-lactic acid intestinal bacteria in patients with chronic fatigue syndrome. In Vivo. 2009;23(4):621–628.
- Yamano E, Sugimoto M, Hirayama A, Kume S, Yamato M, Jin G, Tajima S, Goda N, Iwai K, Fukuda S, et al. Index markers of chronic fatigue syndrome with dysfunction of TCA and urea cycles. Sci Rep. 2016;6:34990. doi: 10.1038/srep34990.
- Naviaux RK, Naviaux JC, Li K, Bright AT, Alaynick WA, Wang L, Baxter A, Nathan N, Anderson W, Gordon E. Metabolic features of chronic fatigue syndrome. Proc Natl Acad Sci U S A. 2016;113(37):E5472–5480. doi: 10.1073/pnas.1607571113.
- Fukuda K, Straus SE, Hickie I, Sharpe MC, Dobbins JG, Komaroff A. The chronic fatigue syndrome: a comprehensive approach to its definition and study. International Chronic Fatigue Syndrome Study Group. Ann Intern Med. 1994;121(12):953–959. doi: 10.7326/0003-4819-121-12-199412150-00009.
- Carruthers BM, Jain AK, DeMeirleir KL, Peterson DL, Klimas NG, Lerner AM, Bested AC, Flor-Henry P, Joshi P, Powles ACP, et al. Myalgic encephalomyelitis/chronic fatigue syndrome: clinical working case definition, diagnostic and treatments protocols. J Chronic Fatigue Syndr. 2003;11:7–115. doi: 10.1300/J092v11n01_02.
- Mojtahed A, Khanna R, Sandborn WJ, D’Haens GR, Feagan BG, Shackelton LM, Baker KA, Dubcenco E, Valasek MA, Geboes K, et al. Assessment of histologic disease activity in Crohn’s disease: a systematic review. Inflamm Bowel Dis. 2014;20(11):2092–103. doi: 10.1097/MIB.0000000000000155.
- Gyorffy H, Holczbauer A, Nagy P, Szabo Z, Kupcsulik P, Paska C, Papp J, Schaff Z, Kiss A. Claudin expression in Barrett’s esophagus and adenocarcinoma. Virchows Arch. 2005;447(6):961–968. doi: 10.1007/s00428-005-0045-9.
- Hollister EB, Riehle K, Luna RA, Weidler EM, Rubio-Gonzales M, Mistretta TA, Raza S, Doddapaneni HV, Metcalf GA, Muzny DM, et al. Structure and function of the healthy pre-adolescent pediatric gut microbiome. Microbiome. 2015;3:36. doi: 10.1186/s40168-015-0101-x.
- Shukla SK, Cook D, Meyer J, Vernon SD, Le T, Clevidence D, Robertson CE, Schrodi SJ, Yale S, Frank DN. Changes in gut and plasma microbiome following exercise challenge in myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) PLoS One. 2015;10(12):e0145453. doi: 10.1371/journal.pone.0145453.
- Daniels J, Brigden A, Kacorova A. Anxiety and depression in chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME): examining the incidence of health anxiety in CFS/ME. Psychol Psychother. 2017. [Epub ahead of print].
- Sibelli A, Chalder T, Everitt H, Workman P, Windgassen S, Moss-Morris R. A systematic review with meta-analysis of the role of anxiety and depression in irritable bowel syndrome onset. Psychol Med. 2016;46(15):3065–3080. doi: 10.1017/S0033291716001987.
- Klem F, Wadhwa A, Prokop L, Sundt W, Farrugia G, Camilleri M, Singh S, Grover M. Prevalence, risk factors, and outcomes of irritable bowel syndrome after infectious enteritis: a systematic review and meta-analysis. Gastroenterology: 2017.
- Hickie I, Davenport T, Wakefield D, Vollmer-Conna U, Cameron B, Vernon SD, Reeves WC, Lloyd A. Post-infective and chronic fatigue syndromes precipitated by viral and non-viral pathogens: prospective cohort study. BMJ. 2006;333(7568):575. doi: 10.1136/.
- Wensaas KA, Langeland N, Hanevik K, Morch K, Eide GE, Rortveit G. Irritable bowel syndrome and chronic fatigue 3 years after acute giardiasis: historic cohort study. Gut. 2012;61(2):214–219. doi: 10.1136/gutjnl-2011-300220.
- Simren M, Svedlund J, Posserud I, Bjornsson ES, Abrahamsson H. Predictors of subjective fatigue in chronic gastrointestinal disease. Aliment Pharmacol Ther. 2008;28(5):638–647. doi: 10.1111/j.1365-2036.2008.03770.x.
- Lind R, Berstad A, Hatlebakk J, Valeur J. Chronic fatigue in patients with unexplained self-reported food hypersensitivity and irritable bowel syndrome: validation of a Norwegian translation of the Fatigue Impact Scale. Clin Exp Gastroenterol. 2013;6:101–107.
- Miquel S, Martin R, Lashermes A, Gillet M, Meleine M, Gelot A, Eschalier A, Ardid D, Bermudez-Humaran LG, Sokol H, et al. Anti-nociceptive effect of Faecalibacterium prausnitzii in non-inflammatory IBS-like models. Sci Rep. 2016;6:19399. doi: 10.1038/srep19399.
- Malinen E, Krogius-Kurikka L, Lyra A, Nikkila J, Jaaskelainen A, Rinttila T, Vilpponen-Salmela T, von Wright AJ, Palva A. Association of symptoms with gastrointestinal microbiota in irritable bowel syndrome. World J Gastroenterol. 2010;16(36):4532–4540. doi: 10.3748/wjg.v16.i36.4532.
- Kelly JR, Kennedy PJ, Cryan JF, Dinan TG, Clarke G, Hyland NP. Breaking down the barriers: the gut microbiome, intestinal permeability and stress-related psychiatric disorders. Front Cell Neurosci. 2015;9:392.
- Maes M, Kubera M, Leunis JC, Berk M. Increased IgA and IgM responses against gut commensals in chronic depression: further evidence for increased bacterial translocation or leaky gut. J Affect Disord. 2012;141(1):55–62. doi: 10.1016/j.jad.2012.02.023.
- Heap LC, Peters TJ, Wessely S. Vitamin B status in patients with chronic fatigue syndrome. J Roy Soc Med. 1999;92(4):183–185.
- Vermeulen RCW, Kurk RM, Visser FC, Sluiter W, Scholte HR. Patients with chronic fatigue syndrome performed worse than controls in a controlled repeated exercise study despite a normal oxidative phosphorylation capacity. J Transl Med. 2010;8.
- Li H, Nowak-Wegrzyn A, Charlop-Powers Z, Shreffler W, Chehade M, Thomas S, Roda G, Dahan S, Sperber K, Berin MC. Transcytosis of IgE-antigen complexes by CD23a in human intestinal epithelial cells and its role in food allergy. Gastroenterology. 2006;131(1):47–58. doi: 10.1053/j.gastro.2006.03.044.
- Maes M, Mihaylova I, Leunis JC. In chronic fatigue syndrome, the decreased levels of omega-3 poly-unsaturated fatty acids are related to lowered serum zinc and defects in T cell activation. Neuroendocrinol Lett. 2005;26(6):745–751.
- Leonard B, Maes M. Mechanistic explanations how cell-mediated immune activation, inflammation and oxidative and nitrosative stress pathways and their sequels and concomitants play a role in the pathophysiology of unipolar depression. Neurosci Biobehav R. 2012;36(2):764–785. doi: 10.1016/j.neubiorev.2011.12.005.
- Puri BK. Long-chain polyunsaturated fatty acids and the pathophysiology of myalgic encephalomyelitis (chronic fatigue syndrome) J Clin Pathol. 2007;60(2):122–124. doi: 10.1136/jcp.2006.042424.
- Takayama K, Wang C, Besra GS. Pathway to synthesis and processing of mycolic acids in Mycobacterium tuberculosis. Clin Microbiol Rev. 2005;18(1):81–101. doi: 10.1128/CMR.18.1.81-101.2005.
- Tapiero H, Mathe G, Couvreur P, Tew KD. Dossier: Free amino acids in human health and pathologies - I Arginine. Biomed Pharmacother. 2002;56(9):439–445. doi: 10.1016/S0753-3322(02)00284-6.
- Cheng IS, Wang YW, Chen IF, Hsu GS, Hsueh CF, Chang CK. The supplementation of branched-chain amino acids, arginine, and citrulline improves endurance exercise performance in two consecutive days. J Sports Sci Med. 2016;15(3):509–515.
- LeBlanc JG, Milani C, de Giori GS, Sesma F, van Sinderen D, Ventura M. Bacteria as vitamin suppliers to their host: a gut microbiota perspective. Curr Opin Biotechnol. 2013;24(2):160–168. doi: 10.1016/j.copbio.2012.08.005.
- Wikoff WR, Anfora AT, Liu J, Schultz PG, Lesley SA, Peters EC, Siuzdak G. Metabolomics analysis reveals large effects of gut microflora on mammalian blood metabolites. Proc Natl Acad Sci U S A. 2009;106(10):3698–3703. doi: 10.1073/pnas.0812874106.
- Marcobal A, Yusufaly T, Higginbottom S, Snyder M, Sonnenburg JL, Mias GI. Metabolome progression during early gut microbial colonization of gnotobiotic mice. Sci Rep. 2015;5:11589. doi: 10.1038/srep11589.
- Antunes LC, Han J, Ferreira RB, Lolic P, Borchers CH, Finlay BB. Effect of antibiotic treatment on the intestinal metabolome. Antimicrob Agents Chemother. 2011;55(4):1494–1503. doi: 10.1128/AAC.01664-10.
- Hornig M, Montoya JG, Klimas NG, Levine S, Felsenstein D, Bateman L, Peterson DL, Gottschalk CG, Schultz AF, Che X, et al. Distinct plasma immune signatures in ME/CFS are present early in the course of illness. Sci Adv. 2015;1(1):e1400121. doi: 10.1126/sciadv.1400121.
- Hornig M, Gottschalk G, Peterson DL, Knox KK, Schultz AF, Eddy ML, Che X, Lipkin WI. Cytokine network analysis of cerebrospinal fluid in myalgic encephalomyelitis/chronic fatigue syndrome. Mol Psychiatry. 2016;21(2):261–269. doi: 10.1038/mp.2015.29.
- Klimas N, Ironson G, Carter A, Balbin E, Bateman L, Felsenstein D, Levine S, Peterson D, Chiu K, Allen A, et al. Findings from a clinical and laboratory database developed for discovery of pathogenic mechanisms in myalgic encephalomyelitis/chronic fatigue syndrome. Fatigue. 2015;3:75–96.
- Alter HJ, Mikovits JA, Switzer WM, Ruscetti FW, Lo SC, Klimas N, Komaroff AL, Montoya JG, Bateman L, Levine S, et al. A multicenter blinded analysis indicates no association between chronic fatigue syndrome/myalgic encephalomyelitis and either xenotropic murine leukemia virus-related virus or polytropic murine leukemia virus. MBio. 2012;3(5):e00266–12. doi: 10.1128/mBio.00266-12.
- Ware JE, Jr, Sherbourne CD. The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Med Care. 1992;30(6):473–483. doi: 10.1097/00005650-199206000-00002.
- Smets EM, Garssen B, Bonke B, De Haes JC. The Multidimensional Fatigue Inventory (MFI) psychometric qualities of an instrument to assess fatigue. J Psychosom Res. 1995;39(3):315–325. doi: 10.1016/0022-3999(94)00125-O.
- Martins TB. Development of internal controls for the Luminex instrument as part of a multiplex seven-analyte viral respiratory antibody profile. Clin Diagn Lab Immunol. 2002;9(1):41–45.
- Vignali DA. Multiplexed particle-based flow cytometric assays. J Immunol Methods. 2000;243(1-2):243–255. doi: 10.1016/S0022-1759(00)00238-6.
- Grus J. Data science from scratch. Sebastopol: O’Reilly; 2015. pp. 99–100.
- Hinks T, Zhou X, Staples K, Dimitrov B, Manta A, Petrossian T, Lum P, Smith C, Ward J, Howarth P, et al. Multidimensional endotypes of asthma: topological data analysis of cross-sectional clinical, pathological, and immunological data. Lancet. 2015;385(Suppl 1):S42. doi: 10.1016/S0140-6736(15)60357-9.
- Benjamini Y, Hochberg Y. Controlling the false discovery rate—a practical and powerful approach to multiple testing. J R Stat Soc B. 1995;57(1):289–300.
- Tibshirani R. Regression shrinkage and selection via the lasso. J R Stat Soc Series B. 1996;58:267–288.
- Breiman L. Random forests. Mach Learn. 2001;45:5–32. doi: 10.1023/A:1010933404324.
- Eckburg PB, Bik EM, Bernstein CN, Purdom E, Dethlefsen L, Sargent M, Gill SR, Nelson KE, Relman DA. Diversity of the human intestinal microbial flora. Science. 2005;308(5728):1635–1638. doi: 10.1126/science.1110591.
- Segata N, Izard J, Waldron L, Gevers D, Miropolsky L, Garrett WS, Huttenhower C. Metagenomic biomarker discovery and explanation. Genome Biol. 2011;12(6):R60. doi: 10.1186/gb-2011-12-6-r60.
- Hulsen T, de Vlieg J, Alkema W. BioVenn—a web application for the comparison and visualization of biological lists using area-proportional Venn diagrams. BMC Genomics. 2008;9:488. doi: 10.1186/1471-2164-9-488.
- Krzywinski M, Schein J, Birol I, Connors J, Gascoyne R, Horsman D, Jones SJ, Marra MA. Circos: an information aesthetic for comparative genomics. Genome Res. 2009;19(9):1639–1645. doi: 10.1101/gr.092759.109.
- Poritz LS, Harris LR, 3rd, Kelly AA, Koltun WA. Increase in the tight junction protein claudin-1 in intestinal inflammation. Dig Dis Sci. 2011;56(10):2802–9. doi: 10.1007/s10620-011-1688-9.
Source: PubMed