Reference : Reassessment Of Lesion-Associated Gene And Variant Pathogenicity In Focal Human Epilepsies
E-prints/Working papers : Already available on another site
Life sciences : Genetics & genetic processes
Systems Biomedicine
http://hdl.handle.net/10993/31044
Reassessment Of Lesion-Associated Gene And Variant Pathogenicity In Focal Human Epilepsies
English
Neupert, Lisa Marie [> >]
Nothnagel, Michael [> >]
May, Patrick mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) >]
Palotie, Aarno [> >]
Daly, Mark [> >]
Nürnberg, Peter [> >]
Blümcke, Ingmar [> >]
Lal, Dennis [> >]
2017
Cold Spring Harbor Labs Journals
No
[en] Purpose: Increasing availability of surgically resected brain tissue from Focal Cortical Dysplasia and low-grade epilepsy-associated tumor patients fostered large-scale genetic examination. However, assessment of germline and somatic variant pathogenicity remains difficult. Methods: Here, we critically reevaluated the pathogenicity for all neuropathology-associated variants reported to date in the PubMed and ClinVar databases, including 12 disease-related genes and 88 neuropathology-associated missense variants. We (1) assessed evolutionary gene constraint using the pLI and missense z scores, (2) applied guidelines by the American College of Medical Genetics and Genomics (ACMG), and (3) predicted pathogenicity by using PolyPhen-2, CADD, and GERP. Results: Constraint analysis classified only seven out of 12 genes to be likely disease-associated, while 35 (40\%) of those 88 variants were classified as being variants of unknown significance (VUS) and 53 (60\%) as being likely pathogenic (LPII). Pathogenicity prediction yielded discrimination between neuropathology-associated variants (LPII and VUS) and rare variant scores obtained from individuals present in the Genome Aggregation Database (gnomAD). Conclusion: We conclude that several VUS are likely disease-associated and will be reclassified by future molecular evidence. In summary, interpretation of lesion-associated gene variants remains complex while the application of current ACMG guidelines including bioinformatic pathogenicity prediction will help improving interpretation and prediction.
Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group)
http://hdl.handle.net/10993/31044
10.1101/130203
http://biorxiv.org/content/early/2017/04/24/130203
http://biorxiv.org/content/early/2017/04/24/130203

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