Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

A collaborative knowledge base for cognitive phenomics

Abstract

The human genome project has stimulated development of impressive repositories of biological knowledge at the genomic level and new knowledge bases are rapidly being developed in a ‘bottom-up’ fashion. In contrast, higher-level phenomics knowledge bases are underdeveloped, particularly with respect to the complex neuropsychiatric syndrome, symptom, cognitive, and neural systems phenotypes widely acknowledged as critical to advance molecular psychiatry research. This gap limits informatics strategies that could improve both the mining and representation of relevant knowledge, and help prioritize phenotypes for new research. Most existing structured knowledge bases also engage a limited set of contributors, and thus fail to leverage recent developments in social collaborative knowledge-building. We developed a collaborative annotation database to enable representation and sharing of empirical information about phenotypes important to neuropsychiatric research (www.Phenowiki.org). As a proof of concept, we focused on findings relevant to ‘cognitive control’, a neurocognitive construct considered important to multiple neuropsychiatric syndromes. Currently this knowledge base tabulates empirical findings about heritabilities and measurement properties of specific cognitive task and rating scale indicators (n=449 observations). It is hoped that this new open resource can serve as a starting point that enables broadly collaborative knowledge-building, and help investigators select and prioritize endophenotypes for translational research.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Figure 1
Figure 2
Figure 3
Figure 4

Similar content being viewed by others

References

  1. Goh CS, Gianoulis TA, Liu Y, Li J, Paccanaro A, Lussier YA et al. Integration of curated databases to identify genotype–phenotype associations. BMC Genomics 2006; 7: 257.

    Article  Google Scholar 

  2. Korbel JO, Doerks T, Jensen LJ, Perez-Iratxeta C, Kaczanowski S, Hooper SD et al. Systematic association of genes to phenotypes by genome and literature mining. PLoS Biol 2005; 3: e134.

    Article  Google Scholar 

  3. Lussier YA, Liu Y . Computational approaches to phenotyping: high-throughput phenomics. Proc Am Thorac Soc 2007; 4: 18–25.

    Article  Google Scholar 

  4. van Driel MA, Bruggeman J, Vriend G, Brunner HG, Leunissen JA . A text-mining analysis of the human phenome. Eur J Hum Genet 2006; 14: 535–542.

    Article  CAS  Google Scholar 

  5. Craddock N, O’Donovan MC, Owen MJ . Symptom dimensions and the Kraepelinian dichotomy. Br J Psychiatry 2007; 190: 361; author reply 361–362.

    Article  CAS  Google Scholar 

  6. Craddock N, Owen MJ . Rethinking psychosis: the disadvantages of a dichotomous classification now outweigh the advantages. World Psychiatry 2007; 6: 20–27.

    Google Scholar 

  7. Haslam N, Kim H . Categories and continua: a review of taxometric research. Genet Soc Gen Psychol Monogr 2002; 128: 271–320.

    PubMed  Google Scholar 

  8. Bearden CE, Freimer NB . Endophenotypes for psychiatric disorders: ready for primetime? Trends Genet 2006; 22: 306–313.

    Article  CAS  Google Scholar 

  9. Freimer N, Sabatti C . The human phenome project. Nat Genet 2003; 34: 15–21.

    Article  CAS  Google Scholar 

  10. Gottesman II, Gould TD . The endophenotype concept in psychiatry: etymology and strategic intentions. Am J Psychiatry 2003; 160: 636–645.

    Article  Google Scholar 

  11. Almasy L, Blangero J . Endophenotypes as quantitative risk factors for psychiatric disease: rationale and study design. Am J Med Genet 2001; 105: 42–44.

    Article  CAS  Google Scholar 

  12. Nunnally JC . Introduction to Statistics for Psychology and Education. McGraw-Hill: New York, 1975.

    Google Scholar 

  13. Flint J, Munafo MR . The endophenotype concept in psychiatric genetics. Psychol Med 2007; 37: 163–180.

    Article  Google Scholar 

  14. Glahn DC, Almasy L, Blangero J, Burk GM, Estrada J, Peralta JM et al. Adjudicating neurocognitive endophenotypes for schizophrenia. Am J Med Genet B Neuropsychiatr Genet 2007; 144: 242–249.

    Article  Google Scholar 

  15. Noy NF, Crubezy M, Fergerson RW, Knublauch H, Tu SW, Vendetti J et al. Protege-2000: an open-source ontology-development and knowledge-acquisition environment. AMIA Annu Symp Proc 2003; 953.

  16. Hill H, Ott F, Herbert C, Weisbrod M . Response execution in lexical decision tasks obscures sex-specific lateralization effects in language processing: evidence from event-related potential measures during word reading. Cereb Cortex 2006; 16: 978–989.

    Article  Google Scholar 

  17. Lobmann R, Smid HG, Pottag G, Wagner K, Heinze HJ, Lehnert H . Impairment and recovery of elementary cognitive function induced by hypoglycemia in type-1 diabetic patients and healthy controls. J Clin Endocrinol Metab 2000; 85: 2758–2766.

    Article  CAS  Google Scholar 

  18. Smid HG, Trumper BG, Pottag G, Wagner K, Lobmann R, Scheich H et al. Differentiation of hypoglycaemia induced cognitive impairments. An electrophysiological approach. Brain 1997; 120 (Part 6): 1041–1056.

    Article  Google Scholar 

  19. Grachev ID, Kumar R, Ramachandran TS, Szeverenyi NM . Cognitive interference is associated with neuronal marker N-acetyl aspartate in the anterior cingulate cortex: an in vivo (1)H-MRS study of the Stroop Color-Word task. Mol Psychiatry 2001; 6: 496,529–539.

    Article  CAS  Google Scholar 

  20. Habel U, Klein M, Shah NJ, Toni I, Zilles K, Falkai P et al. Genetic load on amygdala hypofunction during sadness in nonaffected brothers of schizophrenia patients. Am J Psychiatry 2004; 161: 1806–1813.

    Article  Google Scholar 

  21. Kray J, Lindenberger U . Adult age differences in task switching. Psychol Aging 2000; 15: 126–147.

    Article  CAS  Google Scholar 

  22. Anokhin AP, Heath AC, Myers E . Genetics, prefrontal cortex, and cognitive control: a twin study of event-related brain potentials in a response inhibition task. Neurosci Lett 2004; 368: 314–318.

    Article  CAS  Google Scholar 

  23. Luciano M, Posthuma D, Wright MJ, de Geus EJ, Smith GA, Geffen GM et al. Perceptual speed does not cause intelligence, and intelligence does not cause perceptual speed. Biol Psychol 2005; 70: 1–8.

    Article  Google Scholar 

Download references

Acknowledgements

We thank Russ Poldrack, Tyrone Cannon and Nikki Kittur for comments and guidance in the development of this article. FW Sabb is currently supported by a T32 (MH014584; Nuechterlein, PI). This project was supported by the Consortium for Neuropsychiatric Phenomics (under P20 RR020750; Bilder, PI).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to R M Bilder.

Additional information

Supplementary Information accompanies the paper on the Molecular Psychiatry website (http://www.nature.com/mp)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Sabb, F., Bearden, C., Glahn, D. et al. A collaborative knowledge base for cognitive phenomics. Mol Psychiatry 13, 350–360 (2008). https://doi.org/10.1038/sj.mp.4002124

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/sj.mp.4002124

Keywords

This article is cited by

Search

Quick links