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Gene family information facilitates variant interpretation and identification of disease-associated genes in neurodevelopmental disorders

Authors :
Dennis Lal
Patrick May
Eduardo Perez-Palma
Kaitlin E. Samocha
Jack A. Kosmicki
Elise B. Robinson
Rikke S. Møller
Roland Krause
Peter Nürnberg
Sarah Weckhuysen
Peter De Jonghe
Renzo Guerrini
Lisa M. Niestroj
Juliana Du
Carla Marini
EuroEPINOMICS-RES Consortium
James S. Ware
Mitja Kurki
Padhraig Gormley
Sha Tang
Sitao Wu
Saskia Biskup
Annapurna Poduri
Bernd A. Neubauer
Bobby P. C. Koeleman
Katherine L. Helbig
Yvonne G. Weber
Ingo Helbig
Amit R. Majithia
Aarno Palotie
Mark J. Daly
Source :
Genome Medicine, Vol 12, Iss 1, Pp 1-12 (2020)
Publication Year :
2020
Publisher :
BMC, 2020.

Abstract

Abstract Background Classifying pathogenicity of missense variants represents a major challenge in clinical practice during the diagnoses of rare and genetic heterogeneous neurodevelopmental disorders (NDDs). While orthologous gene conservation is commonly employed in variant annotation, approximately 80% of known disease-associated genes belong to gene families. The use of gene family information for disease gene discovery and variant interpretation has not yet been investigated on a genome-wide scale. We empirically evaluate whether paralog-conserved or non-conserved sites in human gene families are important in NDDs. Methods Gene family information was collected from Ensembl. Paralog-conserved sites were defined based on paralog sequence alignments; 10,068 NDD patients and 2078 controls were statistically evaluated for de novo variant burden in gene families. Results We demonstrate that disease-associated missense variants are enriched at paralog-conserved sites across all disease groups and inheritance models tested. We developed a gene family de novo enrichment framework that identified 43 exome-wide enriched gene families including 98 de novo variant carrying genes in NDD patients of which 28 represent novel candidate genes for NDD which are brain expressed and under evolutionary constraint. Conclusion This study represents the first method to incorporate gene family information into a statistical framework to interpret variant data for NDDs and to discover new NDD-associated genes.

Details

Language :
English
ISSN :
1756994X
Volume :
12
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Genome Medicine
Publication Type :
Academic Journal
Accession number :
edsdoj.45a19bc663e847f68db119e08f35c85f
Document Type :
article
Full Text :
https://doi.org/10.1186/s13073-020-00725-6