Which genes to assess in the NGS diagnostics of intellectual disability? The case for a consensus database-driven and expert-curated approach

Florian Erger; Christian P Schaaf; Christian Netzer

doi:10.1016/j.mcp.2019.03.006

Which genes to assess in the NGS diagnostics of intellectual disability? The case for a consensus database-driven and expert-curated approach

Mol Cell Probes. 2019 Jun:45:84-88. doi: 10.1016/j.mcp.2019.03.006. Epub 2019 Mar 23.

Authors

Florian Erger¹, Christian P Schaaf², Christian Netzer³

Affiliations

¹ Institute of Human Genetics, University Hospital Cologne, Kerpener Str. 34, 50931, Cologne, Germany; Center for Molecular Medicine Cologne, University of Cologne, Robert-Koch-Str. 21, 50931, Cologne, Germany; Cologne Center for Genomics (CCG), University of Cologne, Cologne, Germany. Electronic address: florian.erger@uk-koeln.de.
² Institute of Human Genetics, University Hospital Cologne, Kerpener Str. 34, 50931, Cologne, Germany; Center for Molecular Medicine Cologne, University of Cologne, Robert-Koch-Str. 21, 50931, Cologne, Germany; Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, 1250 Moursund Street, Houston, TX, 77030, USA; Baylor College of Medicine, Department of Molecular and Human Genetics, One Baylor Plaza, Houston, TX, 77030, USA.
³ Institute of Human Genetics, University Hospital Cologne, Kerpener Str. 34, 50931, Cologne, Germany.

PMID: 30914295
DOI: 10.1016/j.mcp.2019.03.006

Abstract

When deciding on which genes to assess in larger Next-Generation Sequencing (NGS) datasets for the molecular genetic diagnosis of intellectual disability (ID), geneticists today have a variety of gene-phenotype databases and expert-curated gene lists available. To quantify their respective completeness, we compare an ID gene selection auto-generated from the Human Phenotype Ontology gene-phenotype association database and expert-curated ID gene lists from three reputable sources (sysID, the DDD consortium and Genomics England) and analyse some of their differences. We give examples of what we regard as genuine gaps ("missing ID genes") for each of these and conclude that a complementary or consensus approach is needed to maximise diagnostic yield in ID patients. We propose several consensus gene lists with ID-associated genes of different confidence levels.

Keywords: Gene panel; Human phenotype ontology; Intellectual disability; NGS; Neurodevelopmental delay.

MeSH terms

Computational Biology / methods*
Consensus
Data Curation
Databases, Genetic
Gene Regulatory Networks*
Genetic Predisposition to Disease
High-Throughput Nucleotide Sequencing / methods*
Humans
Intellectual Disability / genetics*
Sequence Analysis, DNA