Systematic identification and modeling of rare and common genetic risk factors for sarcoidosis

• Applicant: Professor Dr. David Ellinghaus, Ph.D., since 11/2017
• Subject Area: Human Genetics
• Term: from 2013 to 2020
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 239536609

In the past years, a reasonable number of common genetic risk variants for sarcoidosis have been discovered by genome-wide association studies, in its majority by the principle investigator of the applied project. However, few is known on the role of these variants in the disease process, and a large proportion of the heritability of sarcoidosis remains to be unexplained. Therefore, the applied project approaches the to-date most comprehensive investigation of the genetic basis of sarcoidosis, including the systemic identification of rare variants and a detailed genetic analysis of the HLA region. In order to translate genetic findings to pathogenic mechanism and to clinical application, a detailed investigation of the functional properties and modeling of associated variants will be applied.The applicant has acquired a multinational sample collection of unprecedented size, which is critical for the identification of rare risk variants. It comprises genome-wide genotype datasets of >4,400 sarcoidosis patients and >10,500 control individuals for variant discovery and DNA samples of >4,600 sarcoidosis patients and >8,800 controls for confirmation of the findings.A strength of this project is the availability of i) the largest genotype dataset of sarcoidosis patients and controls worldwide for screening ii) a unique multi-national collection of sarcoidosis patients and controls for replication and iii) all required technology on-site. This provides an excellent basis to reach the following project aims:-Detection of associations of HLA genotypes and -haplotypes with sarcoidosis -Identification of additional common risk variants for sarcoidosis-Identification of novel rare risk variants for sarcoidosis-Compilation of a sarcoidosis eQTL database -Identification of proteins potentially affected by risk variants-Protein network construction for a refined model of disease pathogenesis-Evaluation of the predictive value of the risk variantsTo achieve these objectives extensive genome-wide genotype datasets will be re-analyzed with a focus on HLA associations and rare variants. In addition, a meta-analysis with an US-American case-control dataset will be performed. Candidate risk variants from these analyses will be subjected to replication in six independent sarcoidosis populations of European origin. In order to bridge the gap between genetic studies and cellular processes, novel and known genetic risk factors will be subjected to detailed in silico analyses, using public available tools as well as a sarcoidosis specific eQTV database, which will be compiled by the applicant. The obtained functional hypotheses will be integrated in a refined model of sarcoidosis pathogenesis based on genetic interaction as well as protein-protein-interaction. These results are expected to provide important insights on the interaction of genetic factors in the disease processes and will further be used for patient classification and risk estimation.

• DFG Programme: Research Grants
• International Connection: Czech Republic, Sweden, USA
• Participating Persons: Dr. Burkhard Bewig; Dr. Daniel Culver; Professor Dr. Andre Franke; Professor Dr. Christian Grohé; Professor Johan Grunewald; Professor Dr. Stefan H.E. Kaufmann; Professor Dr. Michael Krawczak; Jeroen Maertzdorf; Courtney-Gray Montgomery; Professor Dr. Joachim Müller-Quernheim; Dr. Leonid Padykov; Professor Dr. Martin Petrek; Professor Dr. Stefan Schreiber; Privatdozent Dr. Martin Schürmann; Professorin Mary-Jane Thomassen
• Ehemalige Antragstellerin: Dr. Annegret Fischer, until 10/2017