Data_Sheet_1_Next-Generation Sequencing Based HLA Typing: Deciphering Immunogenetic Aspects of Sarcoidosis.docx

2018-10-25T11:55:47Z (GMT) by Amit Kishore Martin Petrek

Unraveling of the HLA-related immunogenetic basis of several immune disorders is complex due to the extensive HLA polymorphism and strong linkage-disequilibrium between HLA loci. A lack of in phase sequence information, a relative deficiency of high resolution genotyping including non-coding regions and ambiguous haplotype assignment make it difficult to compare findings across association studies and to attribute a causal role to specific HLA alleles/haplotypes in disease susceptibility and modification of disease phenotypes. Earlier, historical antibody and DNA-based methods of HLA typing, primarily of low resolution at antigen/alellic group levels, yielded “indicative” findings which were partially improved by high-resolution DNA-based typing. Only recently, next-generation sequencing (NGS) approaches based on deep-sequencing of the complete HLA genes combined with bioinformatics tools began to provide the access to complete information at an allelic level. Analyzing HLA with NGS approaches, therefore, promises to provide further insight in the etiopathogenesis of several immune disorders in which HLA associations have been implicated. These range from coeliac disease and rheumatological conditions to even more complex disorders, such as type-1 diabetes, systemic lupus erythematosus and sarcoidosis. A systemic disease of unknown etiology, sarcoidosis has previously been associated with numerous HLA variants and also other gene polymorphisms, often in linkage with the HLA region. To date, the biological significance of these associations has only partially been defined. Therefore, more precise assignments of HLA alleles/haplotypes using NGS approaches could help to elucidate the exact role of HLA variation in the multifaceted etiopathogenesis of sarcoidosis, including epigenetic mechanisms. NGS-based HLA analyses may be also relevant for defining variable clinical phenotypes and for predicting the disease course or the response to current/plausible novel therapies.