Genome-wide identification of the genetic basis of amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a complex disease that leads to motor neuron death. Despite heritability estimates of 52%, genome-wide association studies (GWASs) have discovered relatively few loci. We developed a machine learning approach called RefMap, which integrates functional genomics...

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Published inNeuron (Cambridge, Mass.) Vol. 110; no. 6; pp. 992 - 1008.e11
Main Authors Zhang, Sai, Cooper-Knock, Johnathan, Weimer, Annika K., Shi, Minyi, Moll, Tobias, Marshall, Jack N.G., Harvey, Calum, Nezhad, Helia Ghahremani, Franklin, John, Souza, Cleide dos Santos, Ning, Ke, Wang, Cheng, Li, Jingjing, Dilliott, Allison A., Farhan, Sali, Elhaik, Eran, Pasniceanu, Iris, Livesey, Matthew R., Eitan, Chen, Hornstein, Eran, Kenna, Kevin P., Blair, Ian, Wray, Naomi R., Kiernan, Matthew, Mitne Neto, Miguel, Chio, Adriano, Cauchi, Ruben, Robberecht, Wim, van Damme, Philip, Corcia, Philippe, Couratier, Philippe, Hardiman, Orla, McLaughin, Russell, Gotkine, Marc, Drory, Vivian, Ticozzi, Nicola, Silani, Vincenzo, Veldink, Jan H., van den Berg, Leonard H., de Carvalho, Mamede, Mora Pardina, Jesus S., Povedano, Monica, Andersen, Peter, Weber, Markus, Başak, Nazli A., Al-Chalabi, Ammar, Shaw, Chris, Shaw, Pamela J., Morrison, Karen E., Landers, John E., Glass, Jonathan D., Ferraiuolo, Laura, Snyder, Michael P.
Format Journal Article
LanguageEnglish
Published United States Elsevier Inc 16.03.2022
Subjects
Online AccessGet full text
ISSN0896-6273
1097-4199
1097-4199
DOI10.1016/j.neuron.2021.12.019

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Abstract Amyotrophic lateral sclerosis (ALS) is a complex disease that leads to motor neuron death. Despite heritability estimates of 52%, genome-wide association studies (GWASs) have discovered relatively few loci. We developed a machine learning approach called RefMap, which integrates functional genomics with GWAS summary statistics for gene discovery. With transcriptomic and epigenetic profiling of motor neurons derived from induced pluripotent stem cells (iPSCs), RefMap identified 690 ALS-associated genes that represent a 5-fold increase in recovered heritability. Extensive conservation, transcriptome, network, and rare variant analyses demonstrated the functional significance of candidate genes in healthy and diseased motor neurons and brain tissues. Genetic convergence between common and rare variation highlighted KANK1 as a new ALS gene. Reproducing KANK1 patient mutations in human neurons led to neurotoxicity and demonstrated that TDP-43 mislocalization, a hallmark pathology of ALS, is downstream of axonal dysfunction. RefMap can be readily applied to other complex diseases. •Machine learning method identifies risk genes by integrating GWASs and epigenetic data•Discovered ALS risk genes lead to a 5-fold increase in recovered heritability•Genetic and experimental support for initiation of ALS pathogenesis in the distal axon•Convergent genetic and experimental data establish KANK1 as a new ALS gene Zhang et al. develop a new machine learning method that integrates epigenetic profiling with GWAS summary statistics for gene discovery. Application to ALS identifies 690 risk genes with 5-fold increase in recovered heritability. Leading candidate KANK1 is reproduced in human neurons leading to TDP-43 mislocalization, a hallmark pathology of ALS.
AbstractList Amyotrophic lateral sclerosis (ALS) is a complex disease that leads to motor neuron death. Despite heritability estimates of 52%, genome-wide association studies (GWASs) have discovered relatively few loci. We developed a machine learning approach called RefMap, which integrates functional genomics with GWAS summary statistics for gene discovery. With transcriptomic and epigenetic profiling of motor neurons derived from induced pluripotent stem cells (iPSCs), RefMap identified 690 ALS-associated genes that represent a 5-fold increase in recovered heritability. Extensive conservation, transcriptome, network, and rare variant analyses demonstrated the functional significance of candidate genes in healthy and diseased motor neurons and brain tissues. Genetic convergence between common and rare variation highlighted KANK1 as a new ALS gene. Reproducing KANK1 patient mutations in human neurons led to neurotoxicity and demonstrated that TDP-43 mislocalization, a hallmark pathology of ALS, is downstream of axonal dysfunction. RefMap can be readily applied to other complex diseases.
Amyotrophic lateral sclerosis (ALS) is a complex disease that leads to motor neuron death. Despite heritability estimates of 52%, genome-wide association studies (GWASs) have discovered relatively few loci. We developed a machine learning approach called RefMap, which integrates functional genomics with GWAS summary statistics for gene discovery. With transcriptomic and epigenetic profiling of motor neurons derived from induced pluripotent stem cells (iPSCs), RefMap identified 690 ALS-associated genes that represent a 5-fold increase in recovered heritability. Extensive conservation, transcriptome, network, and rare variant analyses demonstrated the functional significance of candidate genes in healthy and diseased motor neurons and brain tissues. Genetic convergence between common and rare variation highlighted KANK1 as a new ALS gene. Reproducing KANK1 patient mutations in human neurons led to neurotoxicity and demonstrated that TDP-43 mislocalization, a hallmark pathology of ALS, is downstream of axonal dysfunction. RefMap can be readily applied to other complex diseases.Amyotrophic lateral sclerosis (ALS) is a complex disease that leads to motor neuron death. Despite heritability estimates of 52%, genome-wide association studies (GWASs) have discovered relatively few loci. We developed a machine learning approach called RefMap, which integrates functional genomics with GWAS summary statistics for gene discovery. With transcriptomic and epigenetic profiling of motor neurons derived from induced pluripotent stem cells (iPSCs), RefMap identified 690 ALS-associated genes that represent a 5-fold increase in recovered heritability. Extensive conservation, transcriptome, network, and rare variant analyses demonstrated the functional significance of candidate genes in healthy and diseased motor neurons and brain tissues. Genetic convergence between common and rare variation highlighted KANK1 as a new ALS gene. Reproducing KANK1 patient mutations in human neurons led to neurotoxicity and demonstrated that TDP-43 mislocalization, a hallmark pathology of ALS, is downstream of axonal dysfunction. RefMap can be readily applied to other complex diseases.
Amyotrophic lateral sclerosis (ALS) is a complex disease that leads to motor neuron death. Despite heritability estimates of 52%, genome-wide association studies (GWASs) have discovered relatively few loci. We developed a machine learning approach called RefMap, which integrates functional genomics with GWAS summary statistics for gene discovery. With transcriptomic and epigenetic profiling of motor neurons derived from induced pluripotent stem cells (iPSCs), RefMap identified 690 ALS-associated genes that represent a 5-fold increase in recovered heritability. Extensive conservation, transcriptome, network, and rare variant analyses demonstrated the functional significance of candidate genes in healthy and diseased motor neurons and brain tissues. Genetic convergence between common and rare variation highlighted KANK1 as a new ALS gene. Reproducing KANK1 patient mutations in human neurons led to neurotoxicity and demonstrated that TDP-43 mislocalization, a hallmark pathology of ALS, is downstream of axonal dysfunction. RefMap can be readily applied to other complex diseases. •Machine learning method identifies risk genes by integrating GWASs and epigenetic data•Discovered ALS risk genes lead to a 5-fold increase in recovered heritability•Genetic and experimental support for initiation of ALS pathogenesis in the distal axon•Convergent genetic and experimental data establish KANK1 as a new ALS gene Zhang et al. develop a new machine learning method that integrates epigenetic profiling with GWAS summary statistics for gene discovery. Application to ALS identifies 690 risk genes with 5-fold increase in recovered heritability. Leading candidate KANK1 is reproduced in human neurons leading to TDP-43 mislocalization, a hallmark pathology of ALS.
Amyotrophic lateral sclerosis (ALS) is a complex disease leading to motor neuron death. Despite heritability estimates of 52%, genome-wide association studies (GWAS) have discovered relatively few loci. We developed a machine learning approach called RefMap which integrates functional genomics with GWAS summary statistics for gene discovery. With transcriptomic and epigenetic profiling of motor neurons derived from induced pluripotent stem cells (iPSCs), RefMap identified 690 ALS-associated genes which represents a 5-fold increase in recovered heritability. Extensive conservation, transcriptome, network, and rare variant analyses demonstrated the functional significance of candidate genes in healthy and diseased motor neurons and brain tissues. Genetic convergence between common and rare variation highlighted KANK1 as a new ALS gene. Reproducing KANK1 patient mutations in human neurons led to neurotoxicity and demonstrated that TDP-43 mislocalization, a hallmark pathology of ALS, is downstream of axonal dysfunction. RefMap can be readily applied to other complex diseases. Zhang et al. develop a new machine learning method which integrates epigenetic profiling with GWAS summary statistics for gene discovery. Application to ALS identifies 690 risk genes with 5-fold increase in recovered heritability. Leading candidate KANK1 is reproduced in human neurons leading to TDP-43 mislocalization, a hallmark pathology of ALS.
Author Shaw, Pamela J.
Veldink, Jan H.
Eitan, Chen
Kiernan, Matthew
Moll, Tobias
Povedano, Monica
McLaughin, Russell
Wray, Naomi R.
Snyder, Michael P.
Mora Pardina, Jesus S.
Livesey, Matthew R.
Başak, Nazli A.
Shaw, Chris
Mitne Neto, Miguel
Morrison, Karen E.
Shi, Minyi
Weber, Markus
Landers, John E.
Li, Jingjing
Blair, Ian
Cauchi, Ruben
Marshall, Jack N.G.
Ferraiuolo, Laura
Drory, Vivian
Weimer, Annika K.
Ticozzi, Nicola
de Carvalho, Mamede
Ning, Ke
Pasniceanu, Iris
Robberecht, Wim
Corcia, Philippe
Nezhad, Helia Ghahremani
Cooper-Knock, Johnathan
Al-Chalabi, Ammar
Gotkine, Marc
Franklin, John
Wang, Cheng
van Damme, Philip
Elhaik, Eran
Andersen, Peter
Dilliott, Allison A.
Couratier, Philippe
Zhang, Sai
Farhan, Sali
Hornstein, Eran
Glass, Jonathan D.
Harvey, Calum
van den Berg, Leonard H.
Souza, Cleide dos Santos
Silani, Vincenzo
Kenna, Kevin P.
Chio, Adriano
Hardiman, Orla
AuthorAffiliation 7 Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht 3584 CX, Netherlands
5 Department of Biology, Lund University, Lund 223 62, Sweden
1 Department of Genetics, Center for Genomics and Personalized Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
2 Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield S10 2HQ, UK
9 Lead contact
6 Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 7610001, Israel
3 The Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, the Bakar Computational Health Sciences Institute, the Parker Institute for Cancer Immunotherapy, and the Department of Neurology, School of Medicine, University of California, San Francisco, CA 94143, USA
8 These authors contributed equally
4 Department of Neurology and Neurosurgery, the Montreal Neurological Institute, McGill University, Montreal, QC H3A 1A1, Canada
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BackLink https://www.ncbi.nlm.nih.gov/pubmed/35045337$$D View this record in MEDLINE/PubMed
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Keywords motor neurons
genetics
gene discovery
iPSC
ALS
multiomics
TDP-43 mislocalization
axonal dysfunction
machine learning
epigenetics
Language English
License This is an open access article under the CC BY-NC-ND license.
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AUTHOR CONTRIBUTIONS
S.Z., J.C.-K. and M.P.S. conceived and designed the study. S.Z. designed and implemented RefMap. S.Z., J.C.-K., A.K.W., M.S., T.M., J.N.G.M., I.P., M.R.L., C.H., H.G.N., J.F., C.S.S., K.N., S.F., A.A.D., J.V., L.F., P.J.S. and M.P.S. were responsible for data acquisition. S.Z., J.C.-K., A.K.W., M.S., T.M., J.N.G.M., C.H., H.G.N., J.F., C.S.S., K.N., C.W., J.L., S.F., A.A.D., E.E., I.P., M.R.L., C.E., E.H., J.V., L.F., P.J.S. and M.P.S. were responsible for analysis of data. S.Z., J.C.-K., A.K.W., T.M., J.N.G.M., C.H., H.G.N., J.F., C.S.S., K.N., C.W., J.L., S.F., A.A.D., E.E., I.P., M.R.L., C.E., E.H., K.P.K., J.V., L.F., P.J.S. and M.P.S. were responsible for interpretation of data. The Project MinE ALS Sequencing Consortium was involved in data acquisition and analysis. S.Z., J.C.-K. and M.P.S. prepared the manuscript with assistance from all authors. All authors meet the four ICMJE authorship criteria, and were responsible for revising the manuscript, approving the final version for publication, and for accuracy and integrity of the work.
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Snippet Amyotrophic lateral sclerosis (ALS) is a complex disease that leads to motor neuron death. Despite heritability estimates of 52%, genome-wide association...
Amyotrophic lateral sclerosis (ALS) is a complex disease leading to motor neuron death. Despite heritability estimates of 52%, genome-wide association studies...
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SubjectTerms Adaptor Proteins, Signal Transducing - genetics
ALS
Amyotrophic Lateral Sclerosis - genetics
Amyotrophic Lateral Sclerosis - pathology
axonal dysfunction
Basic Medicine
Cell Death - genetics
Cytoskeletal Proteins - genetics
epigenetics
gene discovery
genetics
Genome-Wide Association Study
Humans
Induced Pluripotent Stem Cells - pathology
iPSC
machine learning
Medical and Health Sciences
Medical Genetics and Genomics (including Gene Therapy)
Medicin och hälsovetenskap
Medicinsk genetik och genomik (Här ingår: Genterapi)
Medicinska och farmaceutiska grundvetenskaper
motor neurons
Motor Neurons - pathology
multiomics
TDP-43 mislocalization
Title Genome-wide identification of the genetic basis of amyotrophic lateral sclerosis
URI https://dx.doi.org/10.1016/j.neuron.2021.12.019
https://www.ncbi.nlm.nih.gov/pubmed/35045337
https://www.proquest.com/docview/2621657615
https://pubmed.ncbi.nlm.nih.gov/PMC9017397
Volume 110
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