Next-generation sequencing of 32 genes associated with hereditary aortopathies and related disorders of connective tissue in a cohort of 199 patients

Purpose: Heritable factors play an important etiologic role in connective tissue disorders (CTD) with vascular involvement, and a genetic diagnosis is getting increasingly important for gene-tailored, personalized patient management. Methods: We analyzed 32 disease-associated genes by using targeted next-generation sequencing and exome sequencing in a clinically relevant cohort of 199 individuals. We classified and refined sequence variants according to their likelihood for pathogenicity. Results: We identified 1 pathogenic variant (PV; in FBN1 or SMAD3) in 15 patients (7.5%) and >= 1 likely pathogenic variant (LPV; in COL3A1, FBN1, FBN2, LOX, MYH11, SMAD3, TGFBR1, or TGFBR2) in 19 individuals (9.6%), together resulting in 17.1% diagnostic yield. Thirteen PV/LPV were novel. Of PV/LPV-negative patients 47 (23.6%) showed >= 1 variant of uncertain significance (VUS). Twenty-five patients had concomitant variants. In-depth evaluation of reported/calculated variant classes resulted in reclassification of 19.8% of variants. Conclusion: Variant classification and refinement are essential for shaping mutational spectra of disease genes, thereby improving clinical sensitivity. Obligate stringent multigene analysis is a powerful tool for identifying genetic causes of clinically related CTDs. Nonetheless, the relatively high rate of PV/LPV/VUS-negative patients underscores the existence of yet unknown disease loci and/or oligogenic/polygenic inheritance

Cancer gene discovery in mouse and man

The elucidation of the human and mouse genome sequence and developments in high-throughput genome analysis, and in computational tools, have made it possible to profile entire cancer genomes. In parallel with these advances mouse models of cancer have evolved into a powerful tool for cancer gene discovery. Here we discuss the approaches that may be used for cancer gene identification in both human and mouse and discuss how a cross-species ‘oncogenomics’ approach to cancer gene discovery represents a powerful strategy for finding genes that drive tumourigenesis