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NeuroSCORE: A Genome-wide Omics-Based Model to Identify Candidate Disease Genes of the Central Nervous System

View ORCID ProfileKyle W. Davis, View ORCID ProfileColleen G. Bilancia, View ORCID ProfileMegan Martin, View ORCID ProfileRena Vanzo, Megan Rimmasch, Yolanda Hom, Mohammed Uddin, View ORCID ProfileMoises Serrano
doi: https://doi.org/10.1101/2021.02.04.429640
Kyle W. Davis
1Bionano Genomics, Lineagen Division, Inc., San Diego, CA, USA
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  • For correspondence: kdavis@lineagen.com
Colleen G. Bilancia
1Bionano Genomics, Lineagen Division, Inc., San Diego, CA, USA
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  • ORCID record for Colleen G. Bilancia
Megan Martin
1Bionano Genomics, Lineagen Division, Inc., San Diego, CA, USA
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Rena Vanzo
1Bionano Genomics, Lineagen Division, Inc., San Diego, CA, USA
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Megan Rimmasch
1Bionano Genomics, Lineagen Division, Inc., San Diego, CA, USA
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Yolanda Hom
1Bionano Genomics, Lineagen Division, Inc., San Diego, CA, USA
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Mohammed Uddin
2Mohammed Bin Rashid University of Medicine and Health Sciences, College of Medicine, Dubai, UAE
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Moises Serrano
1Bionano Genomics, Lineagen Division, Inc., San Diego, CA, USA
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  • ORCID record for Moises Serrano
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Abstract

To identify and prioritize candidate disease genes of the central nervous system (CNS) we created the Neurogenetic Systematic Correlation of Omics-Related Evidence (NeuroSCORE). We used five genome-wide metrics highly associated with neurological phenotypes to score 19,598 protein-coding genes. Genes scored one point per metric, resulting in a range of scores from 0-5. Approximately 13,000 genes were then paired with phenotype data from the Online Mendelian Inheritance in Man (OMIM) database. We used logistic regression to determine the odds ratio of each metric and compared genes scoring 1+ to cause a known CNS-related phenotype compared to genes that scored zero. We tested NeuroSCORE using microarray copy number variants (CNVs) in case-control cohorts, mouse model phenotype data, and gene ontology (GO) and pathway analyses. NeuroSCORE identified 8,296 genes scored ≥1, of which 1,580 are “high scoring” genes (scores ≥3). High scoring genes are significantly associated with CNS phenotypes (OR=5.5, p<2×10−16), enriched in case CNVs, and enriched in mouse ortholog genes associated with behavioral and nervous system abnormalities. GO and pathway analyses showed high scoring genes were enriched in chromatin remodeling, mRNA splicing, dendrite development, and neuron projection. OMIM has no phenotype for 1,062 high scoring genes (67%). Top scoring genes include ANKRD17, CCAR1, CLASP1, DOCK9, EIF4G2, G3BP2, GRIA1, MAP4K4, MARK2, PCBP2, RNF145, SF1, SYNCRIP, TNPO2, and ZSWIM8. NeuroSCORE identifies and prioritizes CNS-disease candidate genes, many not yet associated with any phenotype in OMIM. These findings can help direct future research and improve molecular diagnostics for individuals with neurological conditions.

Competing Interest Statement

Kyle W. Davis, Megan Martin, Rena Vanzo, Dr. Colleen G. Bilancia, and Dr. Moises Serrano all are employees of and hold stock options in Bionano Genomics, Inc. Megan Rimmasch was previously employed by Bionano Genomics, Inc. Dr. Mohammed Uddin is listed as an inventor on a patent application for his work on critical exon indexing (upon which the Index gene metric is based); the patent is held by Toronto Hospital for Sick Children and licensed by Lineagen Inc, a Bionano Genomics Company. Yolanda Hom has declared no competing interests.

Footnotes

  • Co-author email addresses: cbilancia{at}lineagen.com, mmartin{at}lineagen.com, rvanzo{at}lineagen.com, megrimmasch{at}gmail.com, yolandahom{at}gmail.com, mohammed.uddin{at}mbru.ac.ae, mserrano{at}lineagen.com

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted February 06, 2021.
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NeuroSCORE: A Genome-wide Omics-Based Model to Identify Candidate Disease Genes of the Central Nervous System
Kyle W. Davis, Colleen G. Bilancia, Megan Martin, Rena Vanzo, Megan Rimmasch, Yolanda Hom, Mohammed Uddin, Moises Serrano
bioRxiv 2021.02.04.429640; doi: https://doi.org/10.1101/2021.02.04.429640
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NeuroSCORE: A Genome-wide Omics-Based Model to Identify Candidate Disease Genes of the Central Nervous System
Kyle W. Davis, Colleen G. Bilancia, Megan Martin, Rena Vanzo, Megan Rimmasch, Yolanda Hom, Mohammed Uddin, Moises Serrano
bioRxiv 2021.02.04.429640; doi: https://doi.org/10.1101/2021.02.04.429640

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