On 9 June 2008, at 12 noon, Eastern U.S. time, Fred Sabb and Bob Bilder of UCLA, and Deanna Barch of Washington University, St. Louis, led an online discussion focusing on two elements of the burgeoning effort to measure and treat cognitive deficits in schizophrenia"the CNTRICS initiative and the Phenowiki knowledge base. We invite you to read their background text below, and we suggest as background reading two recent papers: on CNTRICS, Carter and colleagues in Biological Psychiatry (Carter et al., 2008), and on Phenowiki, Sabb and colleagues in Molecular Psychiatry (Sabb et al., 2008). [Editor's note: We thank the Society for Biological Psychiatry and Elsevier for permission to post a full copy of the CNTRICS paper, and Molecular Psychiatry and Nature Journals for providing open access to the Phenowiki article for one month.]
References: Carter CS, Barch DM, Buchanan RW, Bullmore E, Krystal JH, Cohen J, Geyer M, Green M, Nuechterlein KH, Robbins T, Silverstein S, Smith EE, Strauss M, Wykes T, Heinssen R. Identifying Cognitive Mechanisms Targeted for Treatment Development in Schizophrenia: An Overview of the First Meeting of the Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia Initiative. Biol Psychiatry. 2008 May 6. Copyright Society of Biological Psychiatry (2008) Abstract
Sabb FW, Bearden CE, Glahn DC, Parker DS, Freimer N, Bilder RM. A collaborative knowledge base for cognitive phenomics. Mol Psychiatry. 2008 Apr ; 13(4):350-60. Abstract
Background Text By Fred Sabb, Bob Bilder, and Deanna Barch
Over the past decade and a half there has been a growing awareness of the importance of impaired cognition in schizophrenia as a critical "glass ceiling" that limits functional outcome for people with the illness. For example, many people with schizophrenia continue to have problems with memory and problem solving, along with difficulties living and working independently, despite the fact that their hallucinations and delusions may be well controlled by their current antipsychotic medications. During the 1990s there was initial enthusiasm that second-generation antipsychotic drugs would confer significant advantages over first-generation agents for this aspect of the illness. However, it has now become clear that the data are disappointing in this regard. This understanding has resulted in a growing awareness of an urgent need for the discovery and development of new treatments for schizophrenia that will enhance cognitive functioning in the illness and improve functional outcome. In order to do so it is important to have reliable and valid measurements of cognitive function that are clearly linked to the neural systems that we would wish to target with pharmacological or psychological interventions.
Topic A"CNTRICS The Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophrenia (CNTRICS) initiative was created to translate successful basic animal and human cognitive neuroscience into useful clinical research in schizophrenia. This initiative followed on the heels of the Measurement and Treatment Research to Improve Cognition in Schizophrenia program (MATRICS), which was also designed to enhance the development of treatments designed to improve cognition in schizophrenia. Because of the laudable speed with which MATRICS developed a standardized battery for use in such clinical trials, the measures selected were primarily well standardized and psychometrically sound measures stemming from traditional clinical neuropsychology approach, and not necessarily from advances in basic cognitive neuroscience. CNTRICS was designed to address this issues by facilitating and promoting research that would translate paradigms from basic cognitive neuroscience into versions useable in clinical trials.
Why might translating paradigms from cognitive neuroscience help us to design and evaluate treatments for cognitive impairment in schizophrenia? If appropriate paradigms can be translated from basic cognitive neuroscience for use in clinical trials, the opportunity for bridging translational research from "bench to bedside" may be dramatically enhanced. Currently, development of new tools in drug development has outpaced our capacity to identify the most relevant targets of treatment. Thus we have unprecedented capacity to design new molecules, but lack understanding of how these molecules impact cellular and neural systems level functions in ways that can be meaningfully related to the cognitive and symptomatic dimensions that are the ultimate hallmarks of efficacy and effectiveness.
Why is it important to use bioinformatics approaches in the design and interpretation of studies on cognitive enhancement in schizophrenia? Informatics strategies may help bridge the currently wide gap between our understanding of basic molecular mechanisms and higher level neural systems, cognitive, and syndromal dimensions. There are already major resources developed for genomics and proteomics that are revolutionizing discovery processes in these disciplines. Similar strategies are under development to link repositories of biological knowledge to higher level systems and clinical knowledge. Ultimately it will be possible to connect information about drugs, via the systems in which these drugs act, to the ultimate clinical endpoints that are used in clinical trials. Informatics systems capable of relating molecular to behavioral knowledge need major development, primarily at the behavioral level. There is increasing consensus, achieved via initiatives like MATRICS and CNTRICS, about the important dimensions of behavior and relevant measurement methods. Informatics strategies can model results of these consensus processes and the evidence that supports or conflicts with these results.
How, then, will researchers select the most appropriate paradigms? The Consortium for Neuropsychiatric Phenomics (CNP) has been developing informatics procedures and tools to assist researchers in the development of hypotheses that span multiple levels of scientific inquiry, using literature association techniques, and now also in an online knowledge-base of quantitative data from published articles. Phenowiki is the entry point for phenotype annotation for the CNP tools (Sabb et al., 2008)A concrete example is offered by the CNTRICS process, where a set of cognitive dimensions and measurement approaches has been arrived at via consensus meetings. Data supporting these decisions are now being assembled, and a collaborative knowledgebase will be used to provide an initial scaffold for entry of data regarding the reliability and validity of specific measurement methods considered most relevant to the cognitive dimensions. These data can then be subjected to modeling approaches that can help identify more clearly which paradigms, and which parameter modifications within paradigms, may best relate to specific cognitive dimensions, neural systems activity, drug effects, and diagnostic effects. This knowledgebase can support objective decision making about paradigm selection and refinement for future research.
Figure: Entrez Knowledge Base components and their current sizes and connections.
What is Phenowiki good for?
Annotation of quantitative data in published articles for hypothesis modeling (i.e., do people want to lay out their hypotheses with quantitative effect sizes)?
Connection to other knowledge bases (i.e., how important would it be to link to other Entrez components, e.g., gene, protein, SNP, OMIM, GEO"see figure)
Literature search/retrieval (via PubMed)?
Genetics research (e.g., heritability data, demonstrated genetic associations)?
Psychopharm research (e.g., demonstrated drug effects, reliability statistics, test durations)?
Meta-Analysis & Ontology development - through interaction with other CNP tools
Voting rights for related concepts, and class hierarchies?
Empirical data suggesting validity of constructs by covariance structure analysis?
Who might contribute?
Faculty level scholars?
Funded consortium of annotators?
What incentive structures might work?
Burning desire to know the truth?
Collection of private hypotheses?
Publication of hypotheses (i.e., is there interest in an on-line journal of meta-analytically supported multi-level hypotheses)?