White matter microstructural alterations across four major psychiatric disorders: mega-analysis study in 2937 individuals.


Journal

Molecular psychiatry
ISSN: 1476-5578
Titre abrégé: Mol Psychiatry
Pays: England
ID NLM: 9607835

Informations de publication

Date de publication:
04 2020
Historique:
received: 06 04 2019
accepted: 19 08 2019
revised: 20 07 2019
pubmed: 30 11 2019
medline: 18 2 2021
entrez: 30 11 2019
Statut: ppublish

Résumé

Identifying both the commonalities and differences in brain structures among psychiatric disorders is important for understanding the pathophysiology. Recently, the ENIGMA-Schizophrenia DTI Working Group performed a large-scale meta-analysis and reported widespread white matter microstructural alterations in schizophrenia; however, no similar cross-disorder study has been carried out to date. Here, we conducted mega-analyses comparing white matter microstructural differences between healthy comparison subjects (HCS; N = 1506) and patients with schizophrenia (N = 696), bipolar disorder (N = 211), autism spectrum disorder (N = 126), or major depressive disorder (N = 398; total N = 2937 from 12 sites). In comparison with HCS, we found that schizophrenia, bipolar disorder, and autism spectrum disorder share similar white matter microstructural differences in the body of the corpus callosum; schizophrenia and bipolar disorder featured comparable changes in the limbic system, such as the fornix and cingulum. By comparison, alterations in tracts connecting neocortical areas, such as the uncinate fasciculus, were observed only in schizophrenia. No significant difference was found in major depressive disorder. In a direct comparison between schizophrenia and bipolar disorder, there were no significant differences. Significant differences between schizophrenia/bipolar disorder and major depressive disorder were found in the limbic system, which were similar to the differences in schizophrenia and bipolar disorder relative to HCS. While schizophrenia and bipolar disorder may have similar pathological characteristics, the biological characteristics of major depressive disorder may be close to those of HCS. Our findings provide insights into nosology and encourage further investigations of shared and unique pathophysiology of psychiatric disorders.

Identifiants

pubmed: 31780770
doi: 10.1038/s41380-019-0553-7
pii: 10.1038/s41380-019-0553-7
pmc: PMC7156346
doi:

Types de publication

Journal Article Meta-Analysis Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

883-895

Références

Cross-Disorder Group of the Psychiatric Genomics Consortium. Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis. Lancet. 2013;381:1371–9.
pmcid: 3714010 doi: 10.1016/S0140-6736(12)62129-1
Purcell SM, Wray NR, Stone JL, Visscher PM, O’Donovan MC, Sullivan PF, et al. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature. 2009;460:748–52.
pubmed: 19571811 doi: 10.1038/nature08185
Rapoport J, Chavez A, Greenstein D, Addington A, Gogtay N. Autism spectrum disorders and childhood-onset schizophrenia: clinical and biological contributions to a relation revisited. J Am Acad Child Adolesc Psychiatry. 2009;48:10–8.
pubmed: 19218893 pmcid: 2664646 doi: 10.1097/CHI.0b013e31818b1c63
Sullivan PF, Magnusson C, Reichenberg A, Boman M, Dalman C, Davidson M, et al. Family history of schizophrenia and bipolar disorder as risk factors for autism. Arch Gen Psychiatry. 2012;69:1099–03.
pubmed: 22752149 pmcid: 4187103 doi: 10.1001/archgenpsychiatry.2012.730
Autism Spectrum Disorders Working Group of The Psychiatric Genomics Consortium. Meta-analysis of GWAS of over 16,000 individuals with autism spectrum disorder highlights a novel locus at 10q24.32 and a significant overlap with schizophrenia. Mol Autism. 2017;8:21.
doi: 10.1186/s13229-017-0137-9
Crespi B, Stead P, Elliot M. Evolution in health and medicine Sackler colloquium: comparative genomics of autism and schizophrenia. Proc Natl Acad Sci USA. 2010;107 Suppl 1 :1736–41.
pubmed: 19955444 pmcid: 2868282 doi: 10.1073/pnas.0906080106
Chen G, Guo Y, Zhu H, Kuang W, Bi F, Ai H, et al. Intrinsic disruption of white matter microarchitecture in first-episode, drug-naive major depressive disorder: a voxel-based meta-analysis of diffusion tensor imaging. Prog Neuropsychopharmacol Biol Psychiatry. 2017;76:179–87.
pubmed: 28336497 doi: 10.1016/j.pnpbp.2017.03.011
Jiang J, Zhao YJ, Hu XY, Du MY, Chen ZQ, Wu M, et al. Microstructural brain abnormalities in medication-free patients with major depressive disorder: a systematic review and meta-analysis of diffusion tensor imaging. J Psychiatry Neurosci. 2017;42:150–63.
pubmed: 27780031 doi: 10.1503/jpn.150341
Ellison-Wright I, Bullmore E. Meta-analysis of diffusion tensor imaging studies in schizophrenia. Schizophr Res. 2009;108:3–10.
pubmed: 19128945 doi: 10.1016/j.schres.2008.11.021
Pettersson-Yeo W, Allen P, Benetti S, McGuire P, Mechelli A. Dysconnectivity in schizophrenia: where are we now? Neurosci Biobehav Rev. 2011;35:1110–24.
pubmed: 21115039 doi: 10.1016/j.neubiorev.2010.11.004
Kubicki M, McCarley R, Westin CF, Park HJ, Maier S, Kikinis R, et al. A review of diffusion tensor imaging studies in schizophrenia. J Psychiatr Res. 2007;41:15–30.
pubmed: 16023676 doi: 10.1016/j.jpsychires.2005.05.005
Zalesky A, Fornito A, Seal ML, Cocchi L, Westin CF, Bullmore ET, et al. Disrupted axonal fiber connectivity in schizophrenia. Biol Psychiatry. 2011;69:80–9.
pubmed: 21035793 doi: 10.1016/j.biopsych.2010.08.022
Kurumaji A, Itasaka M, Uezato A, Takiguchi K, Jitoku D, Hobo M, et al. A distinctive abnormality of diffusion tensor imaging parameters in the fornix of patients with bipolar II disorder. Psychiatry Res Neuroimaging. 2017;266:66–72.
pubmed: 28609689 doi: 10.1016/j.pscychresns.2017.06.005
Knochel C, Schmied C, Linden DE, Stablein M, Prvulovic D, de Ad CL, et al. White matter abnormalities in the fornix are linked to cognitive performance in SZ but not in BD disorder: an exploratory analysis with DTI deterministic tractography. J Affect Disord. 2016;201:64–78.
pubmed: 27177298 doi: 10.1016/j.jad.2016.03.015
Barysheva M, Jahanshad N, Foland-Ross L, Altshuler LL, Thompson PM. White matter microstructural abnormalities in bipolar disorder: a whole brain diffusion tensor imaging study. Neuroimage Clin. 2013;2:558–68.
pubmed: 24179807 pmcid: 3777761 doi: 10.1016/j.nicl.2013.03.016
Barnea-Goraly N, Chang KD, Karchemskiy A, Howe ME, Reiss AL. Limbic and corpus callosum aberrations in adolescents with bipolar disorder: a tract-based spatial statistics analysis. Biol Psychiatry. 2009;66:238–44.
pubmed: 19389661 doi: 10.1016/j.biopsych.2009.02.025
Oertel-Knochel V, Reinke B, Alves G, Jurcoane A, Wenzler S, Prvulovic D, et al. Frontal white matter alterations are associated with executive cognitive function in euthymic bipolar patients. J Affect Disord. 2014;155:223–33.
pubmed: 24295601 doi: 10.1016/j.jad.2013.11.004
Vederine FE, Wessa M, Leboyer M, Houenou J. A meta-analysis of whole-brain diffusion tensor imaging studies in bipolar disorder. Prog Neuropsychopharmacol Biol Psychiatry. 2011;35:1820–26.
pubmed: 21624424 doi: 10.1016/j.pnpbp.2011.05.009
Nortje G, Stein DJ, Radua J, Mataix-Cols D, Horn N. Systematic review and voxel-based meta-analysis of diffusion tensor imaging studies in bipolar disorder. J Affect Disord. 2013;150:192–200.
pubmed: 23810479 doi: 10.1016/j.jad.2013.05.034
Di X, Azeez A, Li X, Haque E, Biswal BB. Disrupted focal white matter integrity in autism spectrum disorder: a voxel-based meta-analysis of diffusion tensor imaging studies. Prog Neuropsychopharmacol Biol Psychiatry. 2018;82:242–8.
pubmed: 29128446 doi: 10.1016/j.pnpbp.2017.11.007
Aoki Y, Yoncheva YN, Chen B, Nath T, Sharp D, Lazar M, et al. Association of white matter structure with autism spectrum disorder and attention-deficit/hyperactivity disorder. JAMA Psychiatry. 2017;74:1120–8.
pubmed: 28877317 pmcid: 5710226 doi: 10.1001/jamapsychiatry.2017.2573
Nickel K, Tebartz van Elst L, Perlov E, Endres D, Muller GT, Riedel A, et al. Altered white matter integrity in adults with autism spectrum disorder and an IQ >100: a diffusion tensor imaging study. Acta Psychiatr Scand. 2017;135:573–83.
pubmed: 28407202 doi: 10.1111/acps.12731
Ameis SH, Fan J, Rockel C, Soorya L, Wang AT, Anagnostou E. Altered cingulum bundle microstructure in autism spectrum disorder. Acta Neuropsychiatr. 2013;25:275–82.
pubmed: 25287727 doi: 10.1017/neu.2013.2
Travers BG, Adluru N, Ennis C, Tromp do PM, Destiche D, Doran S, et al. Diffusion tensor imaging in autism spectrum disorder: a review. Autism Res. 2012;5:289–313.
pubmed: 22786754 pmcid: 3474893 doi: 10.1002/aur.1243
Barnea-Goraly N, Kwon H, Menon V, Eliez S, Lotspeich L, Reiss AL. White matter structure in autism: preliminary evidence from diffusion tensor imaging. Biol Psychiatry. 2004;55:323–6.
pubmed: 14744477 doi: 10.1016/j.biopsych.2003.10.022
Jou RJ, Jackowski AP, Papademetris X, Rajeevan N, Staib LH, Volkmar FR. Diffusion tensor imaging in autism spectrum disorders: preliminary evidence of abnormal neural connectivity. Aust N Z J Psychiatry. 2011;45:153–62.
pubmed: 21128874 doi: 10.3109/00048674.2010.534069
Jou RJ, Mateljevic N, Kaiser MD, Sugrue DR, Volkmar FR, Pelphrey KA. Structural neural phenotype of autism: preliminary evidence from a diffusion tensor imaging study using tract-based spatial statistics. AJNR Am J Neuroradiol. 2011;32:1607–13.
pubmed: 21799040 pmcid: 7965377 doi: 10.3174/ajnr.A2558
Kumar A, Sundaram SK, Sivaswamy L, Behen ME, Makki MI, Ager J, et al. Alterations in frontal lobe tracts and corpus callosum in young children with autism spectrum disorder. Cereb Cortex. 2010;20:2103–13.
pubmed: 20019145 doi: 10.1093/cercor/bhp278
Lee JE, Chung MK, Lazar M, DuBray MB, Kim J, Bigler ED, et al. A study of diffusion tensor imaging by tissue-specific, smoothing-compensated voxel-based analysis. Neuroimage. 2009;44:870–83.
pubmed: 18976713 doi: 10.1016/j.neuroimage.2008.09.041
Noriuchi M, Kikuchi Y, Yoshiura T, Kira R, Shigeto H, Hara T, et al. Altered white matter fractional anisotropy and social impairment in children with autism spectrum disorder. Brain Res. 2010;1362:141–9.
pubmed: 20858472 doi: 10.1016/j.brainres.2010.09.051
Pardini M, Garaci FG, Bonzano L, Roccatagliata L, Palmieri MG, Pompili E, et al. White matter reduced streamline coherence in young men with autism and mental retardation. Eur J Neurol. 2009;16:1185–90.
pubmed: 19538216 doi: 10.1111/j.1468-1331.2009.02699.x
Thakkar KN, Polli FE, Joseph RM, Tuch DS, Hadjikhani N, Barton JJ, et al. Response monitoring, repetitive behaviour and anterior cingulate abnormalities in autism spectrum disorders (ASD). Brain. 2008;131:2464–78.
pubmed: 18550622 pmcid: 2525446 doi: 10.1093/brain/awn099
Melicher T, Horacek J, Hlinka J, Spaniel F, Tintera J, Ibrahim I, et al. White matter changes in first episode psychosis and their relation to the size of sample studied: a DTI study. Schizophr Res. 2015;162:22–8.
pubmed: 25660467 doi: 10.1016/j.schres.2015.01.029
Kelly S, Jahanshad N, Zalesky A, Kochunov P, Agartz I, Alloza C, et al. Widespread white matter microstructural differences in schizophrenia across 4322 individuals: results from the ENIGMA Schizophrenia DTI Working Group. Mol Psychiatry. 2018;23:1261–9.
Jahanshad N, Kochunov PV, Sprooten E, Mandl RC, Nichols TE, Almasy L, et al. Multi-site genetic analysis of diffusion images and voxelwise heritability analysis: a pilot project of the ENIGMA-DTI working group. Neuroimage. 2013;81:455–69.
pubmed: 23629049 doi: 10.1016/j.neuroimage.2013.04.061
Kochunov P, Jahanshad N, Sprooten E, Nichols TE, Mandl RC, Almasy L, et al. Multi-site study of additive genetic effects on fractional anisotropy of cerebral white matter: comparing meta and megaanalytical approaches for data pooling. Neuroimage. 2014;95:136–50.
pubmed: 24657781 doi: 10.1016/j.neuroimage.2014.03.033
Kochunov P, Jahanshad N, Marcus D, Winkler A, Sprooten E, Nichols TE, et al. Heritability of fractional anisotropy in human white matter: a comparison of Human Connectome Project and ENIGMA-DTI data. Neuroimage. 2015;111:300–11.
pubmed: 25747917 doi: 10.1016/j.neuroimage.2015.02.050
Morita K, Miura K, Fujimoto M, Shishido E, Shiino T, Takahashi J, et al. Abnormalities of eye movement are associated with work hours in schizophrenia. Schizophr Res. 2018;202:420–2.
Koshiyama D, Fukunaga M, Okada N, Yamashita F, Yamamori H, Yasuda Y, et al. Role of subcortical structures on cognitive and social function in schizophrenia. Sci Rep. 2018;8:1183.
pubmed: 29352126 pmcid: 5775279 doi: 10.1038/s41598-017-18950-2
Koshiyama D, Fukunaga M, Okada N, Morita K, Nemoto K, Yamashita F, et al. Role of frontal white matter and corpus callosum on social function in schizophrenia. Schizophr Res. 2018;202:180–7.
Koshiyama D, Fukunaga M, Okada N, Yamashita F, Yamamori H, Yasuda Y, et al. Subcortical association with memory performance in schizophrenia: a structural magnetic resonance imaging study. Transl Psychiatry. 2018;8:20.
pubmed: 29317603 pmcid: 5802568 doi: 10.1038/s41398-017-0069-3
Okada N, Fukunaga M, Yamashita F, Koshiyama D, Yamamori H, Ohi K, et al. Abnormal asymmetries in subcortical brain volume in schizophrenia. Mol Psychiatry. 2016;21:1460–6.
pubmed: 26782053 pmcid: 5030462 doi: 10.1038/mp.2015.209
Morita K, Miura K, Fujimoto M, Yamamori H, Yasuda Y, Iwase M, et al. Eye movement as a biomarker of schizophrenia: Using an integrated eye movement score. Psychiatry Clin Neurosci. 2017;71:104–14.
pubmed: 27673731 doi: 10.1111/pcn.12460
Fan S, van den Heuvel OA, Cath DC, van der Werf YD, de Wit SJ, de Vries FE, et al. Mild white matter changes in un-medicated obsessive-compulsive disorder patients and their unaffected siblings. Front Neurosci. 2015;9:495.
pubmed: 26793045
Wolfers T, Doan NT, Kaufmann T, Alnaes D, Moberget T, Agartz I, et al. Mapping the heterogeneous phenotype of schizophrenia and bipolar disorder using normative models. JAMA Psychiatry. 2018;75:1146–55.
pubmed: 30304337 pmcid: 6248110 doi: 10.1001/jamapsychiatry.2018.2467
Brugger SP, Howes OD. Heterogeneity and homogeneity of regional brain structure in schizophrenia: a meta-analysis. JAMA Psychiatry. 2017;74:1104–11.
pubmed: 28973084 pmcid: 5669456 doi: 10.1001/jamapsychiatry.2017.2663
Kochunov P, Williamson DE, Lancaster J, Fox P, Cornell J, Blangero J, et al. Fractional anisotropy of water diffusion in cerebral white matter across the lifespan. Neurobiol Aging. 2012;33:9–20.
pubmed: 20122755 doi: 10.1016/j.neurobiolaging.2010.01.014
Faul F, Erdfelder E, Lang AG, Buchner A. G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007;39:175–91.
pubmed: 17695343 doi: 10.3758/BF03193146
Chang M, Womer FY, Edmiston EK, Bai C, Zhou Q, Jiang X, et al. Neurobiological commonalities and distinctions among three major psychiatric diagnostic categories: a structural MRI study. Schizophr Bull. 2018;44:65–74.
pubmed: 29036668 doi: 10.1093/schbul/sbx028
Lovblad KO, Schaller K, Vargas MI. The fornix and limbic system. Semin Ultrasound CT MR. 2014;35:459–73.
pubmed: 25217299 doi: 10.1053/j.sult.2014.06.005
Paul LK, Lautzenhiser A, Brown WS, Hart A, Neumann D, Spezio M, et al. Emotional arousal in agenesis of the corpus callosum. Int J Psychophysiol. 2006;61:47–56.
pubmed: 16759726 doi: 10.1016/j.ijpsycho.2005.10.017
Gazzaniga MS. Cerebral specialization and interhemispheric communication: does the corpus callosum enable the human condition? Brain. 2000;123:1293–326.
pubmed: 10869045 doi: 10.1093/brain/123.7.1293
Aoki Y, Abe O, Nippashi Y, Yamasue H. Comparison of white matter integrity between autism spectrum disorder subjects and typically developing individuals: a meta-analysis of diffusion tensor imaging tractography studies. Mol Autism. 2013;4:25.
pubmed: 23876131 pmcid: 3726469 doi: 10.1186/2040-2392-4-25
Bora E, Fornito A, Radua J, Walterfang M, Seal M, Wood SJ, et al. Neuroanatomical abnormalities in schizophrenia: a multimodal voxelwise meta-analysis and meta-regression analysis. Schizophr Res. 2011;127:46–57.
pubmed: 21300524 doi: 10.1016/j.schres.2010.12.020
van Erp TGM, Walton E, Hibar DP, Schmaal L, Jiang W, Glahn DC, et al. Cortical brain abnormalities in 4474 individuals with schizophrenia and 5098 control subjects via the Enhancing Neuro Imaging Genetics through Meta Analysis (ENIGMA) consortium. Biol Psychiatry. 2018;84:644–54.
pubmed: 29960671 pmcid: 6177304 doi: 10.1016/j.biopsych.2018.04.023
Haijma SV, Van Haren N, Cahn W, Koolschijn PC, Hulshoff Pol HE, Kahn RS. Brain volumes in schizophrenia: a meta-analysis in over 18000 subjects. Schizophr Bull. 2013;39:1129–38.
pubmed: 23042112 doi: 10.1093/schbul/sbs118
Arts B, Jabben N, Krabbendam L, van Os J. Meta-analyses of cognitive functioning in euthymic bipolar patients and their first-degree relatives. Psychol Med. 2008;38:771–85.
pubmed: 17922938 doi: 10.1017/S0033291707001675
Bora E, Yucel M, Pantelis C. Neurocognitive markers of psychosis in bipolar disorder: a meta-analytic study. J Affect Disord. 2010;127:1–9.
pubmed: 20231037 doi: 10.1016/j.jad.2010.02.117
Lee J, Altshuler L, Glahn DC, Miklowitz DJ, Ochsner K, Green MF. Social and nonsocial cognition in bipolar disorder and schizophrenia: relative levels of impairment. Am J Psychiatry. 2013;170:334–41.
pubmed: 23450289 doi: 10.1176/appi.ajp.2012.12040490
Fujino H, Sumiyoshi C, Yasuda Y, Yamamori H, Fujimoto M, Fukunaga M, et al. Estimated cognitive decline in patients with schizophrenia: a multicenter study. Psychiatry Clin Neurosci. 2017;71:294–300.
pubmed: 27804186 doi: 10.1111/pcn.12474
American psychiatric association. Diagnostic and statistical manual of mental disorders: DSM-5. Arlington: American Psychiatric Publishing, Inc; 2013.
doi: 10.1176/appi.books.9780890425596
Picchioni MM, Rijsdijk F, Toulopoulou T, Chaddock C, Cole JH, Ettinger U, et al. Familial and environmental influences on brain volumes in twins with schizophrenia. J Psychiatry Neurosci. 2017;42:122–30.
pubmed: 28245176 doi: 10.1503/jpn.140277
Clarke MC, Harley M, Cannon M. The role of obstetric events in schizophrenia. Schizophr Bull. 2006;32:3–8.
pubmed: 16306181 doi: 10.1093/schbul/sbj028
Cannon M, Jones PB, Murray RM. Obstetric complications and schizophrenia: historical and meta-analytic review. Am J Psychiatry. 2002;159:1080–92.
pubmed: 12091183 doi: 10.1176/appi.ajp.159.7.1080

Auteurs

Daisuke Koshiyama (D)

Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.

Masaki Fukunaga (M)

Division of Cerebral Integration, National Institute for Physiological Sciences, Aichi, Japan.

Naohiro Okada (N)

Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
International Research Center for Neurointelligence (WPI-IRCN), UTIAS, The University of Tokyo, Tokyo, Japan.

Kentaro Morita (K)

Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.

Kiyotaka Nemoto (K)

Department of Psychiatry, Division of Clinical Medicine, Faculty of Medicine, University of Tsukuba, Tsukuba, Japan.

Kaori Usui (K)

Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.

Hidenaga Yamamori (H)

Department of Psychiatry, Osaka University Graduate School of Medicine, Suita, Japan.

Yuka Yasuda (Y)

Life Grow Brilliant Mental Clinic, Medical Corporation Foster, Osaka, Japan.
Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan.

Michiko Fujimoto (M)

Department of Psychiatry, Osaka University Graduate School of Medicine, Suita, Japan.

Noriko Kudo (N)

Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan.

Hirotsugu Azechi (H)

Molecular Research Center for Children's Mental Development, United Graduate School of Child Development, Osaka University, Osaka, Japan.

Yoshiyuki Watanabe (Y)

Diagnostic and Interventional Radiology, Osaka University Graduate School of Medicine, Osaka, Japan.

Naoki Hashimoto (N)

Department of Psychiatry, Hokkaido University Graduate School of Medicine, Hokkaido, Japan.

Hisashi Narita (H)

Department of Psychiatry, Hokkaido University Graduate School of Medicine, Hokkaido, Japan.

Ichiro Kusumi (I)

Department of Psychiatry, Hokkaido University Graduate School of Medicine, Hokkaido, Japan.

Kazutaka Ohi (K)

Department of Neuropsychiatry, Kanazawa Medical University, Ishikawa, Japan.
Medical Research Institute, Kanazawa Medical University, Ishikawa, Japan.

Takamitsu Shimada (T)

Department of Neuropsychiatry, Kanazawa Medical University, Ishikawa, Japan.

Yuzuru Kataoka (Y)

Department of Neuropsychiatry, Kanazawa Medical University, Ishikawa, Japan.

Maeri Yamamoto (M)

Department of Psychiatry, Nagoya University, Graduate School of Medicine, Aichi, Japan.

Norio Ozaki (N)

Department of Psychiatry, Nagoya University, Graduate School of Medicine, Aichi, Japan.

Go Okada (G)

Department of Psychiatry and Neurosciences, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan.

Yasumasa Okamoto (Y)

Department of Psychiatry and Neurosciences, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan.

Kenichiro Harada (K)

Division of Neuropsychiatry, Department of Neuroscience, Yamaguchi University Graduate School of Medicine, Yamaguchi, Japan.

Koji Matsuo (K)

Department of Psychiatry, Faculty of Medicine, Saitama Medical University, Saitama, Japan.

Hidenori Yamasue (H)

Department of Psychiatry, Hamamatsu University School of Medicine, Shizuoka, Japan.

Osamu Abe (O)

Department of Radiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.

Ryuichiro Hashimoto (R)

Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan.

Tsutomu Takahashi (T)

Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan.

Tomoki Hori (T)

Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan.

Masahito Nakataki (M)

Department of Psychiatry, Tokushima University Hospital, Tokushima, Japan.

Toshiaki Onitsuka (T)

Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.

Laurena Holleran (L)

Center for Neuroimaging and Cognitive Genomics (NICOG), School of Psychology, National University of Ireland Galway, Galway, Ireland.

Neda Jahanshad (N)

Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA.

Theo G M van Erp (TGM)

Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA.

Jessica Turner (J)

Psychology and Neuroscience, Georgia State University, Atlanta, GA, USA.

Gary Donohoe (G)

Center for Neuroimaging and Cognitive Genomics (NICOG), School of Psychology, National University of Ireland Galway, Galway, Ireland.

Paul M Thompson (PM)

Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA.

Kiyoto Kasai (K)

Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
International Research Center for Neurointelligence (WPI-IRCN), UTIAS, The University of Tokyo, Tokyo, Japan.

Ryota Hashimoto (R)

Department of Psychiatry, Osaka University Graduate School of Medicine, Suita, Japan. ryotahashimoto55@ncnp.go.jp.
Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, Japan. ryotahashimoto55@ncnp.go.jp.
Molecular Research Center for Children's Mental Development, United Graduate School of Child Development, Osaka University, Osaka, Japan. ryotahashimoto55@ncnp.go.jp.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH