SUN-710 Custom Panel to Diagnosis Genetic Endocrine Disorders in a Tertiary Academic Hospital

Next-generation sequencing (NGS) has been transforming the endocrine diagnostic methodology allowing the genetic testing to assume an exploratory role rather than only a confirmatory one. This is possible due to lower costs and increased yield of information. A way to further increase efficiency and sensitivity for variant detection is the use of a sequencing custom panel selecting specific genes for screening. In endocrine disorders, the complex and intricate genotype-phenotype relations and occurrence of diverse comorbidities made the diagnosis challenging. Our aim is to analyze the efficiency of a multigenic panel for molecular diagnosis of endocrine disorders in patients assisted in a tertiary academic hospital, as well as to train academic and medical faculties in the use of molecular tools. Genomic DNA from 282 patients was extracted from blood sample using standard procedures. Sanger method was previously used to screen some candidate genes in half of the patients. The custom panel was designed with 651 genes using the SureDesign tool (Agilent technologies), either associated with the phenotype (OMIM) or candidate genes that englobes developmental (DD), metabolic (MD), and adrenal (AD) disorders. Libraries were prepared with SureSelect(XT) Target Enrichment kit (Agilent Technologies). The enriched DNA libraries were sequenced in NextSeq 500 (Illumina) with High Output V2 kit (2 x 150 bp). The raw data was aligned to hg19 with BWA-MEM, variant calling was performed using FreeBayes and annotated with ANNOVAR. Filtering took into consideration the rarity (≤1%) of variants in population databases and those in exonic or splice site regions. Variants found were then classified according ACMG/AMP criteria. The categories of Pathogenic (P) and Likely Pathogenic (LP) were considered for molecular diagnosis, while variants of uncertain significance (VUS) were only reported. The average result of 3 runs was: 159Kmm(2) of cluster density, 76.5 % of Q30 and 76.6 Gb of data were generated. The mean coverage depth of the targeted regions in panel sequencing data was 237x (SD±110x), with at least 96.3% of the sequenced bases being covered more than 20-fold. Out of the 282 patients, we identified 65 LP/P variants (23%), 22 VUS (8%) and 195 remained undiagnosed (69%). Considering the solved cases, 54 (19.1%) have DD, 6 (2.1%) have MD and 5 (1.8%) have AD. Taking into account that half of the patients had already been previously screened, the data enable new findings in known genes. The application of a multigenic panel aids the training of medical faculty in an academic hospital by showing the big picture of the molecular pathways behind each disorder. This may be particularly helpful considering the higher diagnosis of DD cases. A precise genetic etiology provides improvement in understanding the disease, guides decisions about prevention or treatment, and brings comfort to the affected families.