Targeted massively parallel sequencing panel to diagnose genetic endocrine disorders in a tertiary hospital.

OBJECTIVES: To analyze the efficiency of a multigenic targeted massively parallel sequencing panel related to endocrine disorders for molecular diagnosis of patients assisted in a tertiary hospital involved in the training of medical faculty. MATERIAL AND METHODS: Retrospective analysis of the clinical diagnosis and genotype obtained from 272 patients in the Endocrine unit of a tertiary hospital was performed using a custom panel designed with 653 genes, most of them already associated with the phenotype (OMIM) and some candidate genes that englobes developmental, metabolic and adrenal diseases. The enriched DNA libraries were sequenced in NextSeq 500. Variants found were then classified according to ACMG/AMP criteria, with Varsome and InterVar. RESULTS: Three runs were performed; the mean coverage depth of the targeted regions in panel sequencing data was 249×, with at least 96.3% of the sequenced bases being covered more than 20-fold. The authors identified 66 LP/P variants (24%) and 27 VUS (10%). Considering the solved cases, 49 have developmental diseases, 12 have metabolic and 5 have adrenal diseases. CONCLUSION: The application of a multigenic panel aids the training of medical faculty in an academic hospital by showing the picture of the molecular pathways behind each disorder. This may be particularly helpful in developmental disease cases. A precise genetic etiology provides an improvement in understanding the disease, guides decisions about prevention or treatment, and allows genetic counseling.

Targeted massively parallel sequencing panel to diagnose genetic endocrine disorders in a tertiary hospital

Abstract Objectives To analyze the efficiency of a multigenic targeted massively parallel sequencing panel related to endocrine disorders for molecular diagnosis of patients assisted in a tertiary hospital involved in the training of medical faculty. Material and methods Retrospective analysis of the clinical diagnosis and genotype obtained from 272 patients in the Endocrine unit of a tertiary hospital was performed using a custom panel designed with 653 genes, most of them already associated with the phenotype (OMIM) and some candidate genes that englobes developmental, metabolic and adrenal diseases. The enriched DNA libraries were sequenced in NextSeq 500. Variants found were then classified according to ACMG/AMP criteria, with Varsome and InterVar. Results Three runs were performed; the mean coverage depth of the targeted regions in panel sequencing data was 249×, with at least 96.3% of the sequenced bases being covered more than 20-fold. The authors identified 66 LP/P variants (24%) and 27 VUS (10%). Considering the solved cases, 49 have developmental diseases, 12 have metabolic and 5 have adrenal diseases. Conclusion The application of a multigenic panel aids the training of medical faculty in an academic hospital by showing the picture of the molecular pathways behind each disorder. This may be particularly helpful in developmental disease cases. A precise genetic etiology provides an improvement in understanding the disease, guides decisions about prevention or treatment, and allows genetic counseling.

Genetic diagnosis of congenital hypopituitarism by a target gene panel: novel pathogenic variants in GLI2, OTX2 and GHRHR.

AIM: Congenital hypopituitarism has an incidence of 1:3500-10,000 births and is defined by the impaired production of pituitary hormones. Early diagnosis has an impact on management and genetic counselling. The clinical and genetic heterogeneity of hypopituitarism poses difficulties to select the order of genes to analyse. The objective of our study is to screen hypopituitarism genes (candidate and previously related genes) simultaneously using a target gene panel in patients with congenital hypopituitarism. METHODS: Screening of 117 subjects with congenital hypopituitarism for pathogenic variants in 26 genes associated with congenital hypopituitarism by massively parallel sequencing using a customized target gene panel. RESULTS: We found three novel pathogenic variants in OTX2 c.295C>T:p.Gln99*, GLI2 c.1681G>T:p.Glu561* and GHRHR c.820_821insC:p.Asp274Alafs*113, and the previously reported variants in GHRHR c.57+1G>A and PROP1 [c.301_302delAG];[c.109+1G>A]. CONCLUSIONS: Our results indicate that a custom-designed panel is an efficient method to screen simultaneously variants of biological and clinical relevance for congenital GH deficiency. A genetic diagnosis was possible in 5 out of 117 (4%) patients of our cohort. We identified three novel pathogenic variants in GHRHR, OTX2 and GLI2 expanding the spectrum of variants associated with congenital hypopituitarism.