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An integrative, translational approach to understanding rare and orphan genetically based diseases.

ABSTRACT: PhenomeNet is an approach for integrating phenotypes across species and identifying candidate genes for genetic diseases based on the similarity between a disease and animal model phenotypes. In contrast to 'guilt-by-association' approaches, PhenomeNet relies exclusively on the comparison of phenotypes to suggest candidate genes, and can, therefore, be applied to study the molecular basis of rare and orphan diseases for which the molecular basis is unknown. In addition to disease phenotypes from the Online Mendelian Inheritance in Man (OMIM) database, we have now integrated the clinical signs from Orphanet into PhenomeNet. We demonstrate that our approach can efficiently identify known candidate genes for genetic diseases in Orphanet and OMIM. Furthermore, we find evidence that mutations in the HIP1 gene might cause Bassoe syndrome, a rare disorder with unknown genetic aetiology. Our results demonstrate that integration and computational analysis of human disease and animal model phenotypes using PhenomeNet has the potential to reveal novel insights into the pathobiology underlying genetic diseases.

SUBMITTER: Hoehndorf R

PROVIDER: S-EPMC3638468 | biostudies-literature | 2013 Apr

REPOSITORIES: biostudies-literature

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An integrative, translational approach to understanding rare and orphan genetically based diseases.

Hoehndorf Robert R Schofield Paul N PN Gkoutos Georgios V GV

Interface focus 20130401 2

PhenomeNet is an approach for integrating phenotypes across species and identifying candidate genes for genetic diseases based on the similarity between a disease and animal model phenotypes. In contrast to 'guilt-by-association' approaches, PhenomeNet relies exclusively on the comparison of phenotypes to suggest candidate genes, and can, therefore, be applied to study the molecular basis of rare and orphan diseases for which the molecular basis is unknown. In addition to disease phenotypes from ...[more]

PMID: 23853703

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Project description:According to global annual estimates hunger/malnutrition is the major cause of death (36 of 62 million). Cardiovascular diseases and cancer (5.44 of 13.43 million) are the major causes of death in developed countries, while lower respiratory tract infections, human immunodeficiency virus infection/acquired immunodeficiency syndrome, diarrhoeal disease, malaria and tuberculosis (10.88 of 27.12 million) are the major causes of death in developing countries with more than 70% of deaths occurring in children. The majority of approximately 800 million people with other rare diseases, including 100000 children born with thalassaemia annually receive no treatment. There are major ethical dilemmas in dealing with global health issues such as poverty and the treatment of orphan and rare diseases. Of approximately 50000 drugs about 10% are orphan drugs, with annual sales of the latter approaching 100 billion USD. In comparison, the annual revenue in 2009 from the top 12 pharmaceutical companies in Western countries was 445 billion USD and the top drug, atorvastatin, reached 100 billion USD. In the same year, the total government expenditure for health in the developing countries was 410 billion USD with only 6%-7% having been received as aid from developed countries. Drugs cost the National Health Service in the United Kingdom more than 20 billion USD or 10% of the annual health budget. Uncontrollable drug prices and marketing policies affect global health budgets, clinical practice, patient safety and survival. Fines of 5.3 billion USD were imposed on two pharmaceutical companies in the United States, the regulatory authority in France was replaced and clinicians were charged with bribery in order to overcome recent illegal practises affecting patient care. High expenditure for drug development is mainly related to marketing costs. However, only 2 million USD was spent developing the drug deferiprone (L1) for thalassaemia up to the stage of multicentre clinical trials. The criteria for drug development, price levels and use needs to be readdressed to improve drug safety and minimise costs. New global health policies based on cheaper drugs can help the treatment of many categories of orphan and rare diseases and millions of orphan patients in developing and developed countries.

Project description:BackgroundGenotype-phenotype analyses of rare diseases often suffer from a lack of power, due to small sample size, which makes identifying significant associations difficult. Sinusoidal obstruction syndrome (SOS) of the liver is a rare but life-threatening complication of hematopoietic stem cell transplantation (HSCT). The alkylating agent busulfan is commonly used in HSCT and known to trigger SOS. We developed a novel pipeline to identify genetic determinants in rare diseases by combining in vitro information with clinical whole-exome sequencing (WES) data and applied it in SOS patients and controls.MethodsFirst, we analysed differential gene expression in six lymphoblastoid cell lines (LCLs) before and after incubation with busulfan. Second, we used WES data from 87 HSCT patients and estimated the association with SOS at the SNP and the gene levels. We then combined the results of the expression and the association analyses into an association statistic at the gene level. We used an over-representation analysis to functionally characterize the genes that were associated with a significant combined test statistic.ResultsAfter treatment of LCLs with busulfan, 1708 genes were significantly up-, and 1385 down-regulated. The combination of the expression experiment and the association analysis of WES data into a single test statistic revealed 35 genes associated with the outcome. These genes are involved in various biological functions and processes, such as "Cell growth and death", "Signalling molecules and interaction", "Cancer", and "Infectious disease".ConclusionsThis novel data analysis pipeline integrates two independent omics datasets and increases statistical power for identifying genotype-phenotype associations. The analysis of the transcriptomics profile of cell lines treated with busulfan and WES data from HSCT patients allowed us to identify potential genetic contributors to SOS. Our pipeline could be useful for identifying genetic contributors to other rare diseases where limited power renders genome-wide analyses unpromising.Trial registrationFor the clinical dataset: Clinicaltrials.gov: NCT01257854. https://clinicaltrials.gov/ct2/history/NCT01257854.

Dataset Information

An integrative, translational approach to understanding rare and orphan genetically based diseases.

Publications

An integrative, translational approach to understanding rare and orphan genetically based diseases.

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