Dataset Information

Enhancing rare variant interpretation in inherited arrhythmias through quantitative analysis of consortium disease cohorts and population controls.

ABSTRACT:

Purpose

Stringent variant interpretation guidelines can lead to high rates of variants of uncertain significance (VUS) for genetically heterogeneous disease like long QT syndrome (LQTS) and Brugada syndrome (BrS). Quantitative and disease-specific customization of American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines can address this false negative rate.

Methods

We compared rare variant frequencies from 1847 LQTS (KCNQ1/KCNH2/SCN5A) and 3335 BrS (SCN5A) cases from the International LQTS/BrS Genetics Consortia to population-specific gnomAD data and developed disease-specific criteria for ACMG/AMP evidence classes-rarity (PM2/BS1 rules) and case enrichment of individual (PS4) and domain-specific (PM1) variants.

Results

Rare SCN5A variant prevalence differed between European (20.8%) and Japanese (8.9%) BrS patients (p?=?5.7?×?10^-18) and diagnosis with spontaneous (28.7%) versus induced (15.8%) Brugada type 1 electrocardiogram (ECG) (p?=?1.3?×?10^-13). Ion channel transmembrane regions and specific N-terminus (KCNH2) and C-terminus (KCNQ1/KCNH2) domains were characterized by high enrichment of case variants and >95% probability of pathogenicity. Applying the customized rules, 17.4% of European BrS and 74.8% of European LQTS cases had (likely) pathogenic variants, compared with estimated diagnostic yields (case excess over gnomAD) of 19.2%/82.1%, reducing VUS prevalence to close to background rare variant frequency.

Conclusion

Large case-control data sets enable quantitative implementation of ACMG/AMP guidelines and increased sensitivity for inherited arrhythmia genetic testing.

SUBMITTER: Walsh R

PROVIDER: S-EPMC7790744 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Enhancing rare variant interpretation in inherited arrhythmias through quantitative analysis of consortium disease cohorts and population controls.

Walsh Roddy R Lahrouchi Najim N Tadros Rafik R Kyndt Florence F Glinge Charlotte C Postema Pieter G PG Amin Ahmad S AS Nannenberg Eline A EA Ware James S JS Whiffin Nicola N Mazzarotto Francesco F Škorić-Milosavljević Doris D Krijger Christian C Arbelo Elena E Babuty Dominique D Barajas-Martinez Hector H Beckmann Britt M BM Bézieau Stéphane S Bos J Martijn JM Breckpot Jeroen J Campuzano Oscar O Castelletti Silvia S Celen Candan C Clauss Sebastian S Corveleyn Anniek A Crotti Lia L Dagradi Federica F de Asmundis Carlo C Denjoy Isabelle I Dittmann Sven S Ellinor Patrick T PT Ortuño Cristina Gil CG Giustetto Carla C Gourraud Jean-Baptiste JB Hazeki Daisuke D Horie Minoru M Ishikawa Taisuke T Itoh Hideki H Kaneko Yoshiaki Y Kanters Jørgen K JK Kimoto Hiroki H Kotta Maria-Christina MC Krapels Ingrid P C IPC Kurabayashi Masahiko M Lazarte Julieta J Leenhardt Antoine A Loeys Bart L BL Lundin Catarina C Makiyama Takeru T Mansourati Jacques J Martins Raphaël P RP Mazzanti Andrea A Mörner Stellan S Napolitano Carlo C Ohkubo Kimie K Papadakis Michael M Rudic Boris B Molina Maria Sabater MS Sacher Frédéric F Sahin Hatice H Sarquella-Brugada Georgia G Sebastiano Regina R Sharma Sanjay S Sheppard Mary N MN Shimamoto Keiko K Shoemaker M Benjamin MB Stallmeyer Birgit B Steinfurt Johannes J Tanaka Yuji Y Tester David J DJ Usuda Keisuke K van der Zwaag Paul A PA Van Dooren Sonia S Van Laer Lut L Winbo Annika A Winkel Bo G BG Yamagata Kenichiro K Zumhagen Sven S Volders Paul G A PGA Lubitz Steven A SA Antzelevitch Charles C Platonov Pyotr G PG Odening Katja E KE Roden Dan M DM Roberts Jason D JD Skinner Jonathan R JR Tfelt-Hansen Jacob J van den Berg Maarten P MP Olesen Morten S MS Lambiase Pier D PD Borggrefe Martin M Hayashi Kenshi K Rydberg Annika A Nakajima Tadashi T Yoshinaga Masao M Saenen Johan B JB Kääb Stefan S Brugada Pedro P Robyns Tomas T Giachino Daniela F DF Ackerman Michael J MJ Brugada Ramon R Brugada Josep J Gimeno Juan R JR Hasdemir Can C Guicheney Pascale P Priori Silvia G SG Schulze-Bahr Eric E Makita Naomasa N Schwartz Peter J PJ Shimizu Wataru W Aiba Takeshi T Schott Jean-Jacques JJ Redon Richard R Ohno Seiko S Probst Vincent V Behr Elijah R ER Barc Julien J Bezzina Connie R CR

Genetics in medicine : official journal of the American College of Medical Genetics 20200907 1

<h4>Purpose</h4>Stringent variant interpretation guidelines can lead to high rates of variants of uncertain significance (VUS) for genetically heterogeneous disease like long QT syndrome (LQTS) and Brugada syndrome (BrS). Quantitative and disease-specific customization of American College of Medical Genetics and Genomics/Association for Molecular Pathology (ACMG/AMP) guidelines can address this false negative rate.<h4>Methods</h4>We compared rare variant frequencies from 1847 LQTS (KCNQ1/KCNH2/S ...[more]

PMID: 32893267

Similar Datasets

Project description:The acceleration of DNA sequencing in samples from patients and population studies has resulted in extensive catalogues of human genetic variation, but the interpretation of rare genetic variants remains problematic. A notable example of this challenge is the existence of disruptive variants in dosage-sensitive disease genes, even in apparently healthy individuals. Here, by manual curation of putative loss-of-function (pLoF) variants in haploinsufficient disease genes in the Genome Aggregation Database (gnomAD)1, we show that one explanation for this paradox involves alternative splicing of mRNA, which allows exons of a gene to be expressed at varying levels across different cell types. Currently, no existing annotation tool systematically incorporates information about exon expression into the interpretation of variants. We develop a transcript-level annotation metric known as the 'proportion expressed across transcripts', which quantifies isoform expression for variants. We calculate this metric using 11,706 tissue samples from the Genotype Tissue Expression (GTEx) project2 and show that it can differentiate between weakly and highly evolutionarily conserved exons, a proxy for functional importance. We demonstrate that expression-based annotation selectively filters 22.8% of falsely annotated pLoF variants found in haploinsufficient disease genes in gnomAD, while removing less than 4% of high-confidence pathogenic variants in the same genes. Finally, we apply our expression filter to the analysis of de novo variants in patients with autism spectrum disorder and intellectual disability or developmental disorders to show that pLoF variants in weakly expressed regions have similar effect sizes to those of synonymous variants, whereas pLoF variants in highly expressed exons are most strongly enriched among cases. Our annotation is fast, flexible and generalizable, making it possible for any variant file to be annotated with any isoform expression dataset, and will be valuable for the genetic diagnosis of rare diseases, the analysis of rare variant burden in complex disorders, and the curation and prioritization of variants in recall-by-genotype studies.

Dataset Information

Enhancing rare variant interpretation in inherited arrhythmias through quantitative analysis of consortium disease cohorts and population controls.

Purpose

Methods

Results

Conclusion

Publications

Enhancing rare variant interpretation in inherited arrhythmias through quantitative analysis of consortium disease cohorts and population controls.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets