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 Research & Giving News Article  New Web Tool Enables Schizophrenia Researchers to Assess Genetic Risk Markers The field of schizophrenia genetics is booming. Roughly 1,000 papers on the subject have appeared to date in peer-reviewed scientific and medical journals. In the last decade, literally hundreds of reports have been published claiming or refuting claims of genetic association between putative schizophrenia genes and disease risk, onset age, or other characteristics of the illness. Despite the mass of data generated by these studies, their results, considered as a whole, have been largely inconclusive. In mid-2006 Lars Bertram, M.D., Ph.D., of Harvard Medical School and Massachusetts General Hospital, and several colleagues including tech assistant Nicole C. Allen, undertook to address this problem. They began development of a web-based resource that would provide members of the research community and interested members of the general public an overview of the state of current knowledge about the genetics of schizophrenia, one that would be comprehensive, continuously updated, and fully objective. The online resource, called SchizophreniaGene, went live on February 9, hosted by an innovative website for the schizophrenia research community called the Schizophrenia Research Forum, or SRF (www.schizophreniaforum.org/res/sczgene). Both SRF and the SchizophreniaGene resource owe their existence to the great success of the Alzheimer Research Forum, which features a resource called AlzGene (www.alzforum.org/res/com/gen/alzgene) that was developed by Dr. Bertram several years ago and is the model for SchizophreniaGene. In 2002, armed with the donation of the powerful and elegant Alzforum software, veteran science writer and editor Hakon Heimer, one of whose siblings has schizophrenia, set out to find support for a Schizophrenia Research Forum, eventually gaining funding from the National Institute of Mental Health and administrative and technical support from NARSAD. SRF, which offers news, links to new research papers, information about drugs in clinical trials, forums about research hypotheses and other features, began making its mark on the web in late 2005, stitching together a vibrant virtual community of scientists and others interested in the illness. “It was key fi9nancial support from NARSAD,” Heimer says, “that originally enabled us to launch SRF, and now to add the SchizophreniaGene resource to the SRF site. This is the feature that schizophrenia researchers who were familiar with Alzforum and AlzGene most often requested, so we are very happy to have it up and running.” At the heart of SchizophreniaGene is a meticulously compiled database, assembled from data extracted from peer-reviewed papers identified through systematic searches of publicly available scientific literature databases (e.g., NCBI's “PubMed”), as well as the table of contents of journals in genetics, neurology and psychiatry. “We’ve taken the data from the published literature and put it through what might be described as a statistical analysis machine,” Dr. Bertram explains. Most of the data are derived from genetic association studies, that is, studies examining specific genetic markers for a possible link to schizophrenia risk. Most of the markers consist of single-letter variations of the genetic code, called SNPs, at specific sites on the chromosomes. A typical gene association study will examine a distinctive allele -- a particular version of a SNP -- among a study population consisting of persons diagnosed with schizophrenia and persons who do not have the illness. “Such studies, which typically consist of several hundreds of schizophrenia patients and a like number of controls, usually do not themselves have the power to reliably determine whether there is a significant effect in the sample,” Dr. Bertram says. The solution, in statistical terms, is straightforward: to increase sample size, and in so doing, “increase the power to make an assertion” about whether or to what degree the data for specific markers are significant. When the total universe of useful studies are reflected in the SchizophreniaGene online database – data from more than 300 papers remains to be entered – roughly 300 to 400 distinct genes will be represented. The significance of specific markers on these implicated genes will be analyzed and displayed via meta-analysis, an established statistical procedure that quantitatively summarizes data across a set of studies on a given marker by combining their data and thereby effectively increasing sample size. A “digest” of meta-analyses for all genes implicated in the schizophrenia phenotype will appear on the right side of the SchizophreniaGene homepage when the project of data input is complete, perhaps three months hence. By scanning this digest, researchers will have a powerful tool not previously available, based on over 100 separate meta-analyses of the published literature. The database and the digest of meta-analyses are constantly updated as new studies and meta-analyses for specific markers are published. Prospective users will include the geneticist interested in determining which gene or genes to study next; the pharmaceutical scientist interested in knowing what the best drug targets are for new candidate compounds designed to treat schizophrenia; and the basic researcher, seeking to learn more about the mechanism of the disease: how a given allele, or gene variant, is implicated in the disease, how variations in letters of the genetic code affect the gene’s expression profile, and whether or how the protein produced upon instructions from the variant gene differs in function from that produced by the corresponding gene in someone unaffected by schizophrenia. The site’s database also can be searched either by gene/protein name or alias, chromosomal location, polymorphism name, a paper’s first author and year of publication, as well as specific keywords. For each gene, summary overviews are provided displaying key characteristics for each publication (e.g., study design, population of origin, ethnicity, sample size, onset age), including the reported genotype distributions of the polymorphisms studied. |
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