Gut microbiome and magnetic resonance spectroscopy study of subjects at ultra-high risk for psychosis may support the membrane hypothesis

European Psychiatry

Volumn 53, Issue , 2018, Pages 37-45

  He, Ying ^a,b   Kosciolek, Tomasz ^c   Tang, Jinsong ^a   Zhou, Yao ^a   Li, Zongchang ^a   Ma, Xiaoqian ^a   Zhu, Qiyun ^c   Yuan, Ning ^a   Yuan, Liu ^a   Li, Chunwang ^d   Jin, Ke ^d   Knight, Rob ^c   Tsuang, Ming T ^b,e   Chen, Xiaogang ^a,f,g,h  

^a CENTRAL SOUTH UNIVERSITY   (China)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c UNIVERSITY OF CALIFORNIA SAN DIEGO   (United States)

^d Institute of Clinical Medicine   (China)

^e HARVARD SCHOOL OF PUBLIC HEALTH   (United States)

^f CENTRAL SOUTH UNIVERSITY   (China)

^g China National Clinical Research Center for Mental Health Disorders   (China)

^h Chinese National Technology Institute on Mental Disorders   (China)

Author keywords

Magnetic resonance spectroscopy; Microbiome; Schizophrenia; Ultra high risk

Indexed keywords

CHOLINE; SHORT CHAIN FATTY ACID;

ADOLESCENT; ADULT; ANTERIOR CINGULATE; ARTICLE; BACTEROIDALES; CLOSTRIDIALES; CONTROLLED STUDY; FECES ANALYSIS; FEMALE; HIGH RISK POPULATION; HUMAN; HYPOTHESIS; INTESTINE FLORA; LACTOBACILLALES; MAJOR CLINICAL STUDY; MALE; MICROGLIA; NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY; OBSERVATIONAL STUDY; PRIORITY JOURNAL; PSYCHOSIS; SYMPTOMATOLOGY; YOUNG ADULT; CINGULATE GYRUS; DIAGNOSTIC IMAGING; METABOLISM; MICROBIOLOGY; NEUROIMAGING; PRODROMAL SYMPTOM; SCHIZOPHRENIA;

ADOLESCENT; ADULT; CHOLINE; FEMALE; GASTROINTESTINAL MICROBIOME; GYRUS CINGULI; HUMANS; MAGNETIC RESONANCE SPECTROSCOPY; MALE; NEUROIMAGING; PRODROMAL SYMPTOMS; PSYCHOTIC DISORDERS; SCHIZOPHRENIA; YOUNG ADULT;

EID: 85047787816     PISSN: 09249338     EISSN: 17783585     Source Type: Journal    
DOI: 10.1016/j.eurpsy.2018.05.011     Document Type: Article

References (82)

1. McGrath, J., Saha, S., Chant, D., Welham, J., Schizophrenia A concise overview of incidence, prevalence, and mortality. Epidemiol Rev 30 (2008), 67–76, 10.1093/epirev/mxn001.
2. Cardno, A.G., Marshall, E.J., Coid, B., Macdonald, A.M., Ribchester, T.R., Davies, N.J., et al. Heritability estimates for psychotic disorders: the Maudsley Twin psychosis series. Arch Gen Psychiatry 56 (1999), 162–168, 10.1001/archpsyc.56.2.162.
3. Clemente, C.J., Ursell, K.L., Parfrey, W.L., Knight, R., The impact of the gut microbiota on human health: an integrative view. Cell 148 (2012), 1258–1270.
4. Li, J., Jia, H., Cai, X., Zhong, H., Feng, Q., Sunagawa, S., et al. An integrated catalog of reference genes in the human gut microbiome. Nat Biotechnol 32 (2014), 834–841, 10.1038/nbt.2942.
5. Lloyd-Price, J., Mahurkar, A., Rahnavard, G., Crabtree, J., Orvis, J., Hall, A.B., et al. Strains, functions and dynamics in the expanded Human Microbiome Project. Nature 550 (2017), 61–66, 10.1038/nature23889.
6. Qin, J., Li, R., Raes, J., Arumugam, M., Burgdorf, S.K., Manichanh, C., et al. A human gut microbial gene catalogue established by metagenomic sequencing. Nature 464 (2010), 59–65.
7. Sender, R., Fuchs, S., Milo, R., Revised estimate for the number of human and bacterial cells in the body. BioRvix 14 (2016), 1–21, 10.1101/036103.
8. Rhee, S.H., Pothoulakis, C., Mayer, E.A., Principles and clinical implications of the brain-gut-enteric microbiota axis. Nat Rev Gastroenterol Hepatol 6 (2009), 306–314, 10.1038/nrgastro.2009.35.
9. Dinan, T.G., Cryan, J.F., The impact of gut microbiota on brain and behaviour: implications for psychiatry. Curr Opin Clin Nutr Metab Care 18 (2015), 552–558, 10.1097/MCO.0000000000000221.
10. Smith, A.P., The tantalizing links between gut microbes and the brain. Nature 526 (2015), 312–314.
11. Carlsson, A., Lindqvist, M., Effect of chlorpromazine or haloperidol on formation of 3methoxytyramine and normetanephrine in mouse brain. Acta Pharmacol Toxicol (Copenh), 196020, 2016, 140.
12. Woolley, D.W., Weil-Malherbe, H., The biochemical bases of psychoses. J Nerv Ment Dis, 138, 1964, 92, 10.1097/00005053-196401000-00014.
13. Kim, J.S., Kornhuber, H.H., Schmid-Burgk, W., Holzmüller, B., Low cerebrospinal fluid glutamate in schizophrenic patients and a new hypothesis on schizophrenia. Neurosci Lett 20 (1980), 379–382, 10.1016/0304-3940(80)90178-0.
14. Horrobin, D.F., Glen, A.I.M., Vaddadi, K., The membrane hypothesis of schizophrenia. Schizophr Res 13 (1994), 195–207, 10.1016/0920-9964(94)90043-4.
15. Dinan, T.G., Stilling, R.M., Stanton, C., Cryan, J.F., Collective unconscious: how gut microbes shape human behavior. J Psychiatr Res, 6, 2015, 3, 10.1016/j.jpsychires.2015.02.021.
16. Gershon, M.D., Tack, J., The serotonin signaling system: from basic understanding to drug development for functional GI disorders. Gastroenterology 132 (2007), 397–414, 10.1053/j.gastro.2006.11.002.
17. Yano, J.M., Yu, K., Donaldson, G.P., Shastri, G.G., Ann, P., Ma, L., et al. Indigenous bacteria from the gut microbiota regulate host serotonin biosynthesis. Cell 161 (2015), 264–276, 10.1016/j.cell.2015.02.047.
18. Kemp van der, W.J.M., Explorations into the membrane hypothesis of schizophrenia. 2011.
19. Shutter, L., Tong, K.A., Holshouser, B.A., Proton MRS in acute traumatic brain injury: role for glutamate/glutamine and choline for outcome prediction. J Neurotrauma 21 (2004), 1693–1705, 10.1089/neu.2004.21.1693.
20. Shen, Y., Xu, J., Li, Z., Huang, Y., Yuan, Y., Wang, J., et al. Analysis of gut microbiota diversity and auxiliary diagnosis as a biomarker in patients with schizophrenia: a cross-sectional study. Schizophr Res, 2018, 10.1016/j.schres.2018.01.002.
21. Schwarz, E., Maukonen, J., Hyytiäinen, T., Kieseppä T., Orešič M., Sabunciyan, S., et al. Analysis of microbiota in first episode psychosis identifies preliminary associations with symptom severity and treatment response. Schizophr Res, 2017, 10.1016/j.schres.2017.04.017.
22. APA, Diagnostic and statistical manual of mental disorders. Am Psychiatr Assoc, 2000.
23. McGlashan, H.T., Miller, J.T., Woods, W.S., Rosen, L.J., Hoffman, E.R., Davidson, L., Structured interview for prodromal syndromes. PRIME Res Clin Yale Sch Med N Hav CT, 1997.
24. Hall, R., Global assessment of functioning: a modified scale. Psychosomatics, 3, 1995, 6, 10.1016/S0033-3182(95)71666-8.
25. Callahan, J.B., McMurdie, J.P., Rosen, J.M., Han, W.A., Johnson, A.A.J., Holmes, P.S., DADA2. High-resolution sample inference from Illumina amplicon data. Nat Methods 13 (2016), 581–583.
26. Caporaso, J.G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F.D., Costello, E.K., et al. QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7 (2010), 335–336, 10.1038/nmeth.f.303.
27. Segata, N., Izard, J., Waldron, L., Gevers, D., Miropolsky, L., Garrett, W.S., et al. Metagenomic biomarker discovery and explanation. Genome Biol, 1, 2011, 2, 10.1186/gb-2011-12-6-r60.
28. Langille, I.M.G., Zaneveld, J., Caporaso, G.J., McDonald, D., Knights, D., Reyes, A.J., et al. Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nat Biotechnol 31 (2013), 814–821.
29. Parks, D.H., Tyson, G.W., Hugenholtz, P., Beiko RG. STAMP. Statistical analysis of taxonomic and functional profiles. Bioinformatics 30 (2014), 3123–3124, 10.1093/bioinformatics/btu494.
30. Lance, N.G., Williams, T.W., Mixed-Data classificatory programs I – agglomerative systems. Aust Comput J, 1963, 1.
31. Stilling, R.M., van de Wouw, M., Clarke, G., Stanton, C., Dinan, T.G., Cryan, J.F., The neuropharmacology of butyrate: the bread and butter of the microbiota-gut-brain axis?. Neurochem Int 99 (2016), 110–132, 10.1016/j.neuint.2016.06.011.
32. Macfarlane, S., Macfarlane, G.T., Regulation of short-chain fatty acid production. Proc Nutr Soc 62 (2003), 67–72, 10.1079/PNS2002207.
33. Adams, J.B., Johansen, L.J., Powell, L.D., Quig, D., Rubin, R.A., Gastrointestinal flora and gastrointestinal status in children with autism − comparisons to typical children and correlation with autism severity. BMC Gastroenterol, 11, 2011, 22, 10.1186/1471-230X-11-22.
34. Strati, F., Cavalieri, D., Albanese, D., De Felice, C., Donati, C., Hayek, J., et al. New evidences on the altered gut microbiota in autism spectrum disorders. Microbiome, 5, 2017, 24, 10.1186/s40168-017-0242-1.
35. Tomova, A., Husarova, V., Lakatosova, S., Bakos, J., Vlkova, B., Babinska, K., et al. Gastrointestinal microbiota in children with autism in Slovakia. Physiol Behav 138 (2015), 179–187.
36. Angelis, M., Piccolo, M., Vannini, L., Siragusa, S., Giacomo, A., Serrazzanetti, D., et al. Fecal microbiota and metabolome of children with autism and pervasive developmental disorder not otherwise specified. PLoS One, 2013, 8, 10.1371/journal.pone.0076993.
37. Finegold, S.M., Molitoris, D., Song, Y., Liu, C., Vaisanen, M., Bolte, E., et al. Gastrointestinal microflora studies in late-onset autism. Clin Infect Dis 35 (2002), S6–16, 10.1086/341914.
38. Parracho, H.M.R.T., Bingham, M.O., Gibson, G.R., McCartney, A.L., Differences between the gut microflora of children with autistic spectrum disorders and that of healthy children. J Med Microbiol 54 (2005), 987–991, 10.1099/jmm.0.46101-0.
39. Song, Y., Liu, C., Finegold, S.M., Real-time PCR quantitation of clostridia in feces of autistic children. Appl Environ Microbiol 70 (2004), 6459–6465, 10.1128/AEM.70.11.6459-6465.2004.
40. Castro-Nallar, E., Bendall, M.L., Pérez-Losada, M., Composition, taxonomy and functional diversity of the oropharynx microbiome in individuals with schizophrenia and controls. PeerJ, 2015.
41. Yolken, R.H., Severance, E.G., Sabunciyan, S., Gressitt, K.L., Chen, O., Stallings, C., et al. Metagenomic sequencing indicates that the oropharyngeal phageome of individuals with schizophrenia differs from that of controls. Schizophr Bull 41 (2015), 1153–1161, 10.1093/schbul/sbu197.
42. de Theije, C.G.M., Wopereis, H., Ramadan, M., van Eijndthoven, T., Lambert, J., Knol, J., et al. Altered gut microbiota and activity in a murine model of autism spectrum disorders. Brain Behav Immun 37 (2014), 197–206, 10.1016/j.bbi.2013.12.005.
43. Taweechotipatr, M., Iyer, C., Spinler, K.J., Versalovic, J., Tumwasorn, S., Lactobacillus saerimneri and Lactobacillus ruminis: novel human-derived probiotic strains with immunomodulatory activities. FEMS Microbiol Lett 293 (2009), 65–72.
44. Wood, J.S., Berger, G., Velakoulis, D., Phillips, J.L., McGorry, D.P., Yung, R.A., et al. Proton magnetic resonance spectroscopy in first episode psychosis and ultra high-risk individuals. Schizophr Bull, 29, 2001, 831.
45. Copolov, D., Velakoulis, D., Mcgorry, P., Mallard, C., Yung, A., Rees, S., et al. Neurobiological findings in early phase schizophrenia 1. Brain Res Rev 31 (2000), 157–165.
46. O'Neill, J., Levitt, J., Caplan, R., Asarnow, R., McCracken, T.J., Toga, W.A., et al. 1H MRSI evidence of metabolic abnormalities in childhood-onset schizophrenia. Neuroimage 21 (2004), 1781–1789.
47. Tandon, N., Bolo, N.R., Sanghavi, K., Mathew, I.T., Francis, A.N., Stanley, J.A., et al. Brain metabolite alterations in young adults at familial high risk for schizophrenia using proton magnetic resonance spectroscopy. Schizophr Res 148 (2013), 59–66, 10.1016/j.schres.2013.05.024.
48. Chiu, P.W., Lui, S.S.Y., Hung, K.S.Y., Chan, R.C.K., Chan, Q., Sham, P.C., et al. In vivo gamma-aminobutyric acid and glutamate levels in people with first-episode schizophrenia: a proton magnetic resonance spectroscopy study. Schizophr Res, 2017, 10.1016/j.schres.2017.07.021.
49. Cordes, J.S., Mathiak, K.A., Dyck, M., Alawi, E.M., Gaber, T.J., Zepf, F.D., et al. Cognitive and neural strategies during control of the anterior cingulate cortex by fMRI neurofeedback in patients with schizophrenia. Front Behav Neurosci, 2015, 9, 10.3389/fnbeh.2015.00169.
50. Plitman, E., de la Fuente-Sandoval, C., Reyes-Madrigal, F., Chavez, S., Gómez-Cruz, G., León-Ortiz, P., et al. Elevated myo-inositol, choline, and glutamate levels in the associative striatum of antipsychotic-naive patients with first-episode psychosis: a proton magnetic resonance spectroscopy study with implications for glial dysfunction. Schizophr Bull 42 (2016), 415–424, 10.1093/schbul/sbv118.
51. Monji, A., Kato, T., Kanba, S., Cytokines and schizophrenia. Microglia hypothesis of schizophrenia. Psychiatry Clin Neurosci 63 (2009), 257–265.
52. Kinney, K.D., Hintz, K., Shearer, M.E., Barch, H.D., Riffin, C., Whitley, K., et al. A unifying hypothesis of schizophrenia: abnormal immune system development may help explain roles of prenatal hazards, post-pubertal onset, stress, genes, climate, infections, and brain dysfunction. Med Hypotheses 74 (2010), 555–563.
53. da Fonseca, A.C.C., Matias, D., Garcia, C., Amaral, R., Geraldo, L.H., Freitas, C., et al. The impact of microglial activation on blood-brain barrier in brain diseases. Front Cell Neurosci, 8, 2014, 362, 10.3389/fncel.2014.00362.
54. Minghetti, L., Ajmone-Cat, M.A., De Berardinis, M.A., De Simone, R., Microglial activation in chronic neurodegenerative diseases: roles of apoptotic neurons and chronic stimulation. Brain Res Rev 48 (2005), 251–256, 10.1016/j.brainresrev.2004.12.015.
55. Paolicelli, R.C., Bolasco, G., Pagani, F., Maggi, L., Scianni, M., Panzanelli, P., et al. Synaptic pruning by microglia is necessary for normal brain development. Science 333 (2011), 1456–1458, 10.1126/science.1202529.
56. Streit, W.J., Mrak, R.E., Griffin, W.S.T., Microglia and neuroinflammation. A pathological perspective. J Neuroinflammation, 2004, 1, 10.1186/1742-2094-1-14.
57. Bayer, T.A., Buslei, R., Havas, L., Falkai, P., Evidence for activation of microglia in patients with psychiatric illnesses. Neurosci Lett 271 (1999), 126–128.
58. Radewicz, K., Garey, L.J., Gentleman, S.M., Reynolds, R., Increase in HLA-DR immunoreactive microglia in frontal and temporal cortex of chronic schizophrenics. J Neuropathol Exp Neurol 59 (2000), 137–150, 10.1093/jnen/59.2.137.
59. Bloomfield, S.P., Selvaraj, S., Veronese, M., Rizzo, G., Bertoldo, A., Owen, R.D., et al. Microglial activity in people at ultra high risk of psychosis and in schizophrenia: an [(11)C]PBR28 PET brain imaging study. Am J Psychiatry 173 (2016), 44–52.
60. Sekar, A., Bialas, A.R., De Rivera, H., Davis, A., Hammond, T.R., Kamitaki, N., et al. Schizophrenia risk from complex variation of complement component 4. Nature 530 (2016), 177–183, 10.1038/nature16549.
61. Houser, M.C., Tansey, M.G., The gut-brain axis: is intestinal inflammation a silent driver of Parkinson's disease pathogenesis?. Npj Park Dis, 2017, 3, 10.1038/s41531-016-0002-0.
62. Tumanov, S., Bulusu, V., Kamphorst, J.J., Methods in enzymology. Methods Enzymol 561 (2015), 197–217, 10.1016/bs.mie.2015.05.017.
63. Vadder, F., Petia, K.-D., Goncalves, D., Vinera, J., Zitoun, C., Duchampt, A., et al. Microbiota-generated metabolites promote metabolic benefits via gut-brain neural circuits. Cell 156 (2014), 84–96, 10.1016/j.cell.2013.12.016.
64. Sherwin, E., Sandhu, K.V., Dinan, T.G., Cryan, J.F., May the force Be with you: the light and dark sides of the microbiota–gut–brain axis in neuropsychiatry. CNS Drugs 30 (2016), 1019–1041, 10.1007/s40263-016-0370-3.
65. Vinolo, M.A.R., Rodrigues, H.G., Nachbar, R.T., Curi, R., Regulation of inflammation by short chain fatty acids. Nutrients 3 (2011), 858–876, 10.3390/nu3100858.
66. Pender, L.S., Quinn, J.J., Sanderson, R.I., MacDonald, T.T., Butyrate upregulates stromelysin-1 production by intestinal mesenchymal cells. Am J Physiol Gastrointest Liver Physiol 279 (2000), G918–24.
67. Sampson, T.R., Debelius, J.W., Thron, T., Janssen, S., Shastri, G.G., Ilhan, Z.E., et al. Gut microbiota regulate motor deficits and neuroinflammation in a model of parkinson's disease. Cell 167 (2016), 1469–1480, 10.1016/j.cell.2016.11.018 e12.
68. Wang, L., Christophersen, C.T., Sorich, M.J., Gerber, J.P., Angley, M.T., Conlon, M.A., Elevated fecal short chain fatty acid and ammonia concentrations in children with autism spectrum disorder. Dig Dis Sci 57 (2012), 2096–2102, 10.1007/s10620-012-2167-7.
69. Ossenkopp, K.P., Foley, K.A., Gibson, J., Fudge, M.A., Kavaliers, M., Cain, D.P., et al. Systemic treatment with the enteric bacterial fermentation product, propionic acid, produces both conditioned taste avoidance and conditioned place avoidance in rats. Behav Brain Res 227 (2012), 134–141, 10.1016/j.bbr.2011.10.045.
70. Shultz, S.R., MacFabe, D.F., Martin, S., Jackson, J., Taylor, R., Boon, F., et al. Intracerebroventricular injections of the enteric bacterial metabolic product propionic acid impair cognition and sensorimotor ability in the Long-Evans rat: further development of a rodent model of autism. Behav Brain Res 200 (2009), 33–41, 10.1016/j.bbr.2008.12.023.
71. Adkison, D.K., Shen, D., Uptake of vaiproic acid into rat brain is mediated fatty acid transporter. J Pharmacol Exp Ther 276 (1996), 1189–1200.
72. Banks, W.A., Kastin, A.J., Broadwell, R.D., Passage of cytokines across the blood-Brain barrier. Neuroimmunomodulation 2 (1996), 241–248, 10.1159/000097202.
73. Tsao, N., Hsu, H.P.P., Liu, C.M.M., Liu, C.C.C., Lei, H.Y.Y., Wu, C.M.M., et al. Tumour necrosis factor-(causes an increase in blood-brain barrier permeability during sepsis. J Med Microbiol 50 (2001), 812–821, 10.1099/0022-1317-50-9-812.
74. Klapal, L., Igelhorst, B.A., Dietzel-Meyer, I.D., Changes in neuronal excitability by activated microglia: differential Na + current upregulation in pyramid-shaped and bipolar neurons by TNF-α and IL-18. Front Neurol, 2016, 7, 10.3389/fneur.2016.00044.
75. Morris, G., Berk, M., Carvalho, A., Caso, J.R., Sanz, Y., Walder, K., et al. The role of the microbial metabolites including tryptophan catabolites and short chain fatty acids in the pathophysiology of immune-Inflammatory and neuroimmune disease. Mol Neurobiol 54 (2017), 4432–4451, 10.1007/s12035-016-0004-2.
76. Downs, R., Perna, J., Vitelli, A., Cook, D., Dhurjati, P., Model-based hypothesis of gut microbe populations and gut/brain barrier permeabilities in the development of regressive autism. Med Hypotheses 83 (2014), 649–655, 10.1016/j.mehy.2014.09.005.
77. Huang, S.-H., Jong, A.Y., Cellular mechanisms of microbial proteins contributing to invasion of the blood-brain barrier. {MicroReview}. Cell Microbiol 3 (2001), 277–287, 10.1046/j.1462-5822.2001.00116.x.
78. Janda, J.M., Abbott, S.L., 16S rRNA gene sequencing for bacterial identification in the diagnostic laboratory: pluses, perils, and pitfalls. J Clin Microbiol 45 (2007), 2761–2764, 10.1128/JCM.01228-07.
79. Caporaso, J.G., Lauber, C.L., Walters, W.A., Berg-Lyons, D., Lozupone, C.A., Turnbaugh, P.J., et al. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc Natl Acad Sci 108 (2011), 4516–4522, 10.1073/pnas.1000080107.
80. Mi, H., Muruganujan, A., Thomas, P.D., PANTHER in 2013: Modeling the evolution of gene function, and other gene attributes, in the context of phylogenetic trees. Nucleic Acids Res, 4, 2013, 1, 10.1093/nar/gks1118.
81. Suzek, B.E., Wang, Y., Huang, H., McGarvey, P.B., Wu, C.H., UniRef clusters: a comprehensive and scalable alternative for improving sequence similarity searches. Bioinformatics 31 (2015), 926–932, 10.1093/bioinformatics/btu739.
82. Jiang, Y., Oron, T.R., Clark, W.T., Bankapur, A.R., D'Andrea, D., Lepore, R., et al. An expanded evaluation of protein function prediction methods shows an improvement in accuracy. Genome Biol, 17, 2016, 184, 10.1186/s13059-016-1037-6.