Amyotrophic lateral sclerosis: an emerging era of collaborative gene discovery.

Amyotrophic lateral sclerosis (ALS) is the most common form of motor neuron disease (MND). It is currently incurable and treatment is largely limited to supportive care. Family history is associated with an increased risk of ALS, and many Mendelian causes have been discovered. However, most forms of the disease are not obviously familial. Recent advances in human genetics have enabled genome-wide analyses of single nucleotide polymorphisms (SNPs) that make it possible to study complex genetic contributions to human disease. Genome-wide SNP analyses require a large sample size and thus depend upon collaborative efforts to collect and manage the biological samples and corresponding data. Public availability of biological samples (such as DNA), phenotypic and genotypic data further enhances research endeavors. Here we discuss a large collaboration among academic investigators, government, and non-government organizations which has created a public repository of human DNA, immortalized cell lines, and clinical data to further gene discovery in ALS. This resource currently maintains samples and associated phenotypic data from 2332 MND subjects and 4692 controls. This resource should facilitate genetic discoveries which we anticipate will ultimately provide a better understanding of the biological mechanisms of neurodegeneration in ALS.

The Framingham Heart Study 100K SNP genome-wide association study resource: overview of 17 phenotype working group reports.

BACKGROUND: The Framingham Heart Study (FHS), founded in 1948 to examine the epidemiology of cardiovascular disease, is among the most comprehensively characterized multi-generational studies in the world. Many collected phenotypes have substantial genetic contributors; yet most genetic determinants remain to be identified. Using single nucleotide polymorphisms (SNPs) from a 100K genome-wide scan, we examine the associations of common polymorphisms with phenotypic variation in this community-based cohort and provide a full-disclosure, web-based resource of results for future replication studies. METHODS: Adult participants (n = 1345) of the largest 310 pedigrees in the FHS, many biologically related, were genotyped with the 100K Affymetrix GeneChip. These genotypes were used to assess their contribution to 987 phenotypes collected in FHS over 56 years of follow up, including: cardiovascular risk factors and biomarkers; subclinical and clinical cardiovascular disease; cancer and longevity traits; and traits in pulmonary, sleep, neurology, renal, and bone domains. We conducted genome-wide variance components linkage and population-based and family-based association tests. RESULTS: The participants were white of European descent and from the FHS Original and Offspring Cohorts (examination 1 Offspring mean age 32 +/- 9 years, 54% women). This overview summarizes the methods, selected findings and limitations of the results presented in the accompanying series of 17 manuscripts. The presented association results are based on 70,897 autosomal SNPs meeting the following criteria: minor allele frequency > or + 10%, genotype call rate > or = 80%, Hardy-Weinberg equilibrium p-value > or = 0.001, and satisfying Mendelian consistency. Linkage analyses are based on 11,200 SNPs and short-tandem repeats. Results of phenotype-genotype linkages and associations for all autosomal SNPs are posted on the NCBI dbGaP website at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007 webcite. CONCLUSION: We have created a full-disclosure resource of results, posted on the dbGaP website, from a genome-wide association study in the FHS. Because we used three analytical approaches to examine the association and linkage of 987 phenotypes with thousands of SNPs, our results must be considered hypothesis-generating and need to be replicated. Results from the FHS 100K project with NCBI web posting provides a resource for investigators to identify high priority findings for replication.

The NCBI dbGaP database of genotypes and phenotypes.

The National Center for Biotechnology Information has created the dbGaP public repository for individual-level phenotype, exposure, genotype and sequence data and the associations between them. dbGaP assigns stable, unique identifiers to studies and subsets of information from those studies, including documents, individual phenotypic variables, tables of trait data, sets of genotype data, computed phenotype-genotype associations, and groups of study subjects who have given similar consents for use of their data.

New models of collaboration in genome-wide association studies: the Genetic Association Information Network.

The Genetic Association Information Network (GAIN) is a public-private partnership established to investigate the genetic basis of common diseases through a series of collaborative genome-wide association studies. GAIN has used new approaches for project selection, data deposition and distribution, collaborative analysis, publication and protection from premature intellectual property claims. These demonstrate a new commitment to shared scientific knowledge that should facilitate rapid advances in understanding the genetics of complex diseases.

OMIA (Online Mendelian Inheritance in Animals): an enhanced platform and integration into the Entrez search interface at NCBI.

Online Mendelian Inheritance in Animals (OMIA) is a comprehensive, annotated catalogue of inherited disorders and other familial traits in animals other than humans and mice. Structured as a comparative biology resource, OMIA is a comprehensive resource of phenotypic information on heritable animal traits and genes in a strongly comparative context, relating traits to genes where possible. OMIA is modelled on and is complementary to Online Mendelian Inheritance in Man (OMIM). OMIA has been moved to a MySQL database at the Australian National Genomic Information Service (ANGIS) and can be accessed at http://omia.angis.org.au/. It has also been integrated into the Entrez search interface at the National Center for Biotechnology Information (NCBI; http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=omia). Curation of OMIA data by researchers working on particular species and disorders has also been enabled.

PlasmoDB: the Plasmodium genome resource. A database integrating experimental and computational data.

PlasmoDB (http://PlasmoDB.org) is the official database of the Plasmodium falciparum genome sequencing consortium. This resource incorporates the recently completed P. falciparum genome sequence and annotation, as well as draft sequence and annotation emerging from other Plasmodium sequencing projects. PlasmoDB currently houses information from five parasite species and provides tools for intra- and inter-species comparisons. Sequence information is integrated with other genomic-scale data emerging from the Plasmodium research community, including gene expression analysis from EST, SAGE and microarray projects and proteomics studies. The relational schema used to build PlasmoDB, GUS (Genomics Unified Schema) employs a highly structured format to accommodate the diverse data types generated by sequence and expression projects. A variety of tools allow researchers to formulate complex, biologically-based, queries of the database. A stand-alone version of the database is also available on CD-ROM (P. falciparum GenePlot), facilitating access to the data in situations where internet access is difficult (e.g. by malaria researchers working in the field). The goal of PlasmoDB is to facilitate utilization of the vast quantities of genomic-scale data produced by the global malaria research community. The software used to develop PlasmoDB has been used to create a second Apicomplexan parasite genome database, ToxoDB (http://ToxoDB.org).

Molecular analysis of spinal muscular atrophy and modification of the phenotype by SMN2.

PURPOSE: This study describes SMN1 deletion frequency, carrier studies, and the effect of the modifying SMN2 gene on the spinal muscular atrophy (SMA) phenotype. A novel allele-specific intragenic mutation panel increases the sensitivity of SMN1 testing. METHODS: From 1995 to 2001, 610 patients were tested for SMN1 deletions and 399 relatives of probands have been tested for carrier status. SMN2 copy number was compared between 52 type I and 90 type III patients, and between type I and type III patients with chimeric SMN genes. A fluorescent allele-specific polymerase chain reaction (PCR) -based strategy detected intragenic mutations in potential compound heterozygotes and was used on 366 patients. RESULTS: Less than half of the patients tested were homozygously deleted for SMN1. A PCR-based panel detected the seven most common intragenic mutations. SMN2 copy number was significantly different between mild and severely affected patients. CONCLUSIONS: SMN1 molecular testing is essential for the diagnosis of SMA and allows for accurate carrier testing. Screening for intragenic mutations in SMN1 increases the sensitivity of diagnostic testing. Finally, SMN2 copy number is conclusively shown to ameliorate the phenotype and provide valuable prognostic information.