Crowdsourced direct-to-consumer genomic analysis of a family quartet.

BACKGROUND: We describe the pioneering experience of a Spanish family pursuing the goal of understanding their own personal genetic data to the fullest possible extent using Direct to Consumer (DTC) tests. With full informed consent from the Corpas family, all genotype, exome and metagenome data from members of this family, are publicly available under a public domain Creative Commons 0 (CC0) license waiver. All scientists or companies analysing these data ("the Corpasome") were invited to return results to the family. METHODS: We released 5 genotypes, 4 exomes, 1 metagenome from the Corpas family via a blog and figshare under a public domain license, inviting scientists to join the crowdsourcing efforts to analyse the genomes in return for coauthorship or acknowldgement in derived papers. Resulting analysis data were compiled via social media and direct email. RESULTS: Here we present the results of our investigations, combining the crowdsourced contributions and our own efforts. Four companies offering annotations for genomic variants were applied to four family exomes: BIOBASE, Ingenuity, Diploid, and GeneTalk. Starting from a common VCF file and after selecting for significant results from company reports, we find no overlap among described annotations. We additionally report on a gut microbiome analysis of a member of the Corpas family. CONCLUSIONS: This study presents an analysis of a diverse set of tools and methods offered by four DTC companies. The striking discordance of the results mirrors previous findings with respect to DTC analysis of SNP chip data, and highlights the difficulties of using DTC data for preventive medical care. To our knowledge, the data and analysis results from our crowdsourced study represent the most comprehensive exome and analysis for a family quartet using solely DTC data generation to date.

Dissecting the genotype in syndromic intellectual disability using whole exome sequencing in addition to genome-wide copy number analysis.

When a known microimbalance affecting multiple genes is detected in a patient with syndromic intellectual disability, it is usually presumed causative for all observed features. Whole exome sequencing (WES) allows questioning this assumption. In this study of three families with children affected by unexplained syndromic intellectual disability, genome-wide copy number and subsequent analyses revealed a de novo maternal 1.1 Mb microdeletion in the 14q32 imprinted region causing a paternal UPD(14)-like phenotype, and two inherited 22q11.21 microduplications of 2.5 or 2.8 Mb. In patient 1 carrying the 14q32 microdeletion, tall stature and renal malformation were unexplained by paternal UPD(14), and there was no altered DLK1 expression or unexpected methylation status. By WES and filtering with a mining tool, a novel FBN1 missense variant was found in patient 1 and his mother, who both showed clinical features of Marfan syndrome by thorough anthropometric assessment, and a novel EYA1 missense variant as a probable cause of the renal malformation in the patient. In patient 2 with the 22q11.21 microduplication syndrome, skin hypo- and hyperpigmentation and two malignancies were only partially explained. By WES, compound heterozygous BLM stop founder mutations were detected causing Bloom syndrome. In male patient 3 carrying a 22q11.21 microduplication inherited from his unaffected father, WES identified a novel missense variant in the OPHN1 X-linked intellectual disability gene inherited from the unaffected mother as a possible additional cause for developmental delay. Thus, WES seems warranted in patients carrying microdeletions or microduplications, who have unexplained clinical features or microimbalances inherited from an unaffected parent.

Building a knowledge base for systems pathology.

Translating the exponentially growing amount of omics data into knowledge usable for a personalized medicine approach poses a formidable challenge. In this article-taking diabetes as a use case-we present strategies for developing data repositories into computer-accessible knowledge sources that can be used for a systemic view on the molecular causes of diseases, thus laying the foundation for systems pathology.

The BioPAX community standard for pathway data sharing.

Biological Pathway Exchange (BioPAX) is a standard language to represent biological pathways at the molecular and cellular level and to facilitate the exchange of pathway data. The rapid growth of the volume of pathway data has spurred the development of databases and computational tools to aid interpretation; however, use of these data is hampered by the current fragmentation of pathway information across many databases with incompatible formats. BioPAX, which was created through a community process, solves this problem by making pathway data substantially easier to collect, index, interpret and share. BioPAX can represent metabolic and signaling pathways, molecular and genetic interactions and gene regulation networks. Using BioPAX, millions of interactions, organized into thousands of pathways, from many organisms are available from a growing number of databases. This large amount of pathway data in a computable form will support visualization, analysis and biological discovery.

Integrating pathway data for systems pathology.

The HumanPSD database on the complete proteomes of human, mouse and rat has been integrated with the databases TRANSFAC on gene regulation and TRANSPATH on signal transduction to provide a comprehensive systems biological platform for these organisms. As a next step, integration with PathoDB and PathoSign on pathologically relevant mutations is planned together with an extension beyond the limits of the individual cell, towards intercellular networks, by integrating the database EndoNet on hormonal networks as well. The overall aim is to come up with a platform that is suitable to provide knowledge for systems pathology, i. e. a system-wide modeling of pathological states and their development.