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Genome-wide Identification of the Genetic Basis of Amyotrophic Lateral Sclerosis

Sai Zhang, Johnathan Cooper-Knock, Annika K. Weimer, Minyi Shi, Tobias Moll, Calum Harvey, Helia Ghahremani Nezhad, John Franklin, Cleide dos Santos Souza, Cheng Wang, Jingjing Li, Chen Eitan, Eran Hornstein, Kevin P. Kenna, Project MinE Sequencing Consortium, Jan Veldink, Laura Ferraiuolo, Pamela J. Shaw, Michael P. Snyder
doi: https://doi.org/10.1101/2020.11.14.382606
Sai Zhang
1Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
2Center for Genomics and Personalized Medicine, Stanford University School of Medicine, Stanford, CA, USA
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Johnathan Cooper-Knock
3Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, UK
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Annika K. Weimer
1Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
2Center for Genomics and Personalized Medicine, Stanford University School of Medicine, Stanford, CA, USA
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Minyi Shi
1Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
2Center for Genomics and Personalized Medicine, Stanford University School of Medicine, Stanford, CA, USA
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Tobias Moll
3Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, UK
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Calum Harvey
3Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, UK
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Helia Ghahremani Nezhad
3Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, UK
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John Franklin
3Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, UK
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Cleide dos Santos Souza
3Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, UK
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Cheng Wang
4Department of Neurology, School of Medicine, University of California, San Francisco, CA, USA
5Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA, USA
6Bakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA
7Parker Institute for Cancer Immunotherapy, University of California, San Francisco, CA, USA
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Jingjing Li
4Department of Neurology, School of Medicine, University of California, San Francisco, CA, USA
5Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, CA, USA
6Bakar Computational Health Sciences Institute, University of California, San Francisco, CA, USA
7Parker Institute for Cancer Immunotherapy, University of California, San Francisco, CA, USA
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Chen Eitan
8Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel
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Eran Hornstein
8Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel
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Kevin P. Kenna
9Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
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Jan Veldink
9Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
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Laura Ferraiuolo
3Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, UK
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Pamela J. Shaw
3Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, UK
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Michael P. Snyder
1Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
2Center for Genomics and Personalized Medicine, Stanford University School of Medicine, Stanford, CA, USA
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  • For correspondence: mpsnyder@stanford.edu
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ABSTRACT

Amyotrophic lateral sclerosis (ALS) is an archetypal complex disease centered on progressive death of motor neurons. Despite heritability estimates of 52%, GWAS studies have discovered only seven genome-wide significant hits, which are relevant to <10% of ALS patients. To increase the power of gene discovery, we integrated motor neuron functional genomics with ALS genetics in a hierarchical Bayesian model called RefMap. Comprehensive transcriptomic and epigenetic profiling of iPSC-derived motor neurons enabled RefMap to systematically fine-map genes and pathways associated with ALS. As a significant extension of the known genetic architecture of ALS, we identified a group of 690 candidate ALS genes, which is enriched with previously discovered risk genes. Extensive conservation, transcriptome and network analyses demonstrated the functional significance of these candidate genes in motor neurons and disease progression. In particular, we observed a genetic convergence on the distal axon, which supports the prevailing view of ALS as a distal axonopathy. Of the new ALS genes we discovered, we further characterized KANK1 that is enriched with coding and noncoding, common and rare ALS-associated genetic variation. Modelling patient mutations in human neurons reduced KANK1 expression and produced neurotoxicity with disruption of the distal axon. RefMap can be applied broadly to increase the discovery power in genetic association studies of human complex traits and diseases.

Competing Interest Statement

The authors have declared no competing interest.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Genome-wide Identification of the Genetic Basis of Amyotrophic Lateral Sclerosis
Sai Zhang, Johnathan Cooper-Knock, Annika K. Weimer, Minyi Shi, Tobias Moll, Calum Harvey, Helia Ghahremani Nezhad, John Franklin, Cleide dos Santos Souza, Cheng Wang, Jingjing Li, Chen Eitan, Eran Hornstein, Kevin P. Kenna, Project MinE Sequencing Consortium, Jan Veldink, Laura Ferraiuolo, Pamela J. Shaw, Michael P. Snyder
bioRxiv 2020.11.14.382606; doi: https://doi.org/10.1101/2020.11.14.382606
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Genome-wide Identification of the Genetic Basis of Amyotrophic Lateral Sclerosis
Sai Zhang, Johnathan Cooper-Knock, Annika K. Weimer, Minyi Shi, Tobias Moll, Calum Harvey, Helia Ghahremani Nezhad, John Franklin, Cleide dos Santos Souza, Cheng Wang, Jingjing Li, Chen Eitan, Eran Hornstein, Kevin P. Kenna, Project MinE Sequencing Consortium, Jan Veldink, Laura Ferraiuolo, Pamela J. Shaw, Michael P. Snyder
bioRxiv 2020.11.14.382606; doi: https://doi.org/10.1101/2020.11.14.382606

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