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Neuroscience Bulletin

, Volume 35, Issue 2, pp 277–282 | Cite as

The Stanley Neuropathology Consortium Integrative Database (SNCID) for Psychiatric Disorders

  • Sanghyeon Kim
  • Maree J. WebsterEmail author
Perspective

The Stanley Medical Research Institute (SMRI) is a non-profit organization with a primary mission to fund research on the cause and treatment of severe mental illnesses. The SMRI also supports a brain bank as part of the mission to facilitate research into mental illness. The SMRI brain bank distributes postmortem samples from individuals with serious mental illness, free of charge, to scientists around the world. The SMRI brain bank is recognized for the unique way it is set up, organized, and administered. Cohorts of demographically-matched groups of patients with schizophrenia, bipolar disorder (BP), or major depression (DEP) and unaffected controls are organized such that all researchers applying for tissue received samples from the same cohort. The SMRI was the first to include multiple diagnostic categories in the cohorts as well as the first to include a large number (N) of cases in each group. The Stanley Neuropathology Consortium (SNC) was the first cohort established and...

Notes

Acknowledgements

We thank all the investigators who generated the data in the SNCID (http://sncid.stanleyresearch.org). We also thank Jonathan Cohen for technical support.

Conflicts of interest

The authors declare that they have no conflict of interest.

Supplementary material

12264_2018_314_MOESM1_ESM.pdf (227 kb)
Supplementary material 1 (PDF 226 kb)

References

  1. 1.
    Torrey EF, Webster M, Knable M, Johnston N, Yolken RH. The stanley foundation brain collection and neuropathology consortium. Schizophr Res 2000, 44: 151–155.CrossRefGoogle Scholar
  2. 2.
    Webster MJ. Tissue preparation and banking. Prog Brain Res 2006, 158: 3–14.CrossRefGoogle Scholar
  3. 3.
    Yan X, Mai L, Lin C, He W, Yin G, Yu J, et al. CSF-based analysis for identification of potential serum biomarkers of neural tube defects. Neurosci Bull 2017, 33: 436–444.CrossRefGoogle Scholar
  4. 4.
    Kim S, Webster MJ. The stanley neuropathology consortium integrative database: a novel, web-based tool for exploring neuropathological markers in psychiatric disorders and the biological processes associated with abnormalities of those markers. Neuropsychopharmacology 2010, 35: 473–482.CrossRefGoogle Scholar
  5. 5.
    Huitinga I, Webster MJ. Brain Banking. Elsevier, 2018.Google Scholar
  6. 6.
    Kim S, Webster MJ. Integrative genome-wide association analysis of cytoarchitectural abnormalities in the prefrontal cortex of psychiatric disorders. Mol Psychiatry 2011, 16: 452–461.CrossRefGoogle Scholar
  7. 7.
    Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics 2008, 9: 559.CrossRefGoogle Scholar
  8. 8.
    Jo Y, Kim S, Lee D. Identification of common coexpression modules based on quantitative network comparison. BMC Bioinformatics 2018, 19: 213.CrossRefGoogle Scholar
  9. 9.
    Kim S, Cho H, Lee D, Webster MJ. Association between SNPs and gene expression in multiple regions of the human brain. Transl Psychiatry 2012, 2: e113.CrossRefGoogle Scholar
  10. 10.
    Schizophrenia Working Group of the Psychiatric Genomics Consortium. Biological insights from 108 schizophrenia-associated genetic loci. Nature 2014, 511: 421–427.CrossRefGoogle Scholar
  11. 11.
    Harrison PJ. Recent genetic findings in schizophrenia and their therapeutic relevance. J Psychopharmacol 2015, 29: 85–96.CrossRefGoogle Scholar
  12. 12.
    Cascante A, Klum S, Biswas M, Antolin-Fontes B, Barnabe-Heider F, Hermanson O. Gene-specific methylation control of H3K9 and H3K36 on neurotrophic BDNF versus astroglial GFAP genes by KDM4A/C regulates neural stem cell differentiation. J Mol Biol 2014, 426: 3467–3477.CrossRefGoogle Scholar
  13. 13.
    Howes OD, Kapur S. The dopamine hypothesis of schizophrenia: version III–the final common pathway. Schizophr Bull 2009, 35: 549–562.CrossRefGoogle Scholar
  14. 14.
    Seeman P. Targeting the dopamine D2 receptor in schizophrenia. Expert Opin Ther Targets 2006, 10: 515–531.CrossRefGoogle Scholar
  15. 15.
    Coyle JT. The glutamatergic dysfunction hypothesis for schizophrenia. Harv Rev Psychiatry 1996, 3: 241–253.CrossRefGoogle Scholar

Copyright information

© Shanghai Institutes for Biological Sciences, CAS and Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Stanley Brain Research LaboratoryStanley Medical Research InstituteRockvilleUSA

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