Final Report Summary - HSP/CMT GENETICS (Next-Generation Genetics of Axonopathies)
Development, maintenance and degeneration of neuronal processes is at the heart of a number of important neurodevelopmental and neurodegenerative diseases, including Autism, Multiple Sclerosis, Alzheimer’s and Parkinson’s disease. Molecular pathways governing these functions are essential to all neurons. Disturbances of these pathways affect neuronal processes in a length-dependent manner. Thus, neurons maintaining the longest axons in the central and peripheral nervous system including corticospinal tract motor neurons and motor and sensory neurons of the peripheral nervous system are a promising model to study key molecular pathways and key vulnerabilities of axon health that eventually apply to all neuronal cells.
Inherited human axonopathies, diseases of the long axons of the nervous systems, include the heterogeneous group of Hereditary Spastic Paraplegias (HSP) and Hereditary Motor and Sensory Neuropathies (HMSN), now better known as Charcot-Marie-Tooth disease (CMT). Studying monogenetic, Mendelian forms of these diseases offers the chance to identify key genes that determine the pathophysiology of axon degeneration. Such genes have turned out to encode completely unexpected factors in the past and have hugely enriched our understanding of the neuroscience of axon biology. Understanding the milestones of axon degeneration in these so-called dying-back axonopathies holds the potential of tracing the way back to axonal function and integrity, therefore providing a chance of therapy for many so far incurable diseases.
Taken together at least 65 genes are known to cause CMT or HSP, but new genes continue to be found. Mutations in known HSP and CMT genes explain only about 50% of the cases each, depending on the mode of inheritance.
In this project we aimed at the identification of novel genes for hereditary axonopathies to provide better diagnosis to patients and advance our understanding of the biology of axon degeneration in order to work towards better treatment options for these currently incurable diseases. We furthermore aimed at developing novel tools for more comprehensive stream-lined analysis of next generation sequencing data and advancing data sharing and collaboration opportunities in the scientific community.
COLLECTION OF A COHORT OF AXONOPATHY FAMILIES AND CASES
Collection of large, clinically well characterized cohorts is key in genetic studies of rare diseases. The two partnering institutions in this project – the Hertie Institute of Clinical Brain Research at the University of Tübingen (Tübingen, Germany) and the Hussman Institute for Human Genomics at University of Miami Miller School of Medicine (Miami, Florida) together have collected a unique cohort of families with axonopathies, each drawing from large, well established collaborative networks. From these cohorts, the most promising cases and families were selected for whole exome sequencing (WES) or whole genome sequencing (WGS).
Innovative genomic collaboration using the GENESIS (GEM.app) platform
With the advent of next generation sequencing (NGS) technology, discovery of novel genes for Mendelian disorders has reached an unprecedented pace. However, the new technology poses a number of novel challenges: 1) management of large exome or genome datasets is technically challenging especially for smaller labs; 2) interpretation of the multitude of resulting variants from NGS experiments requires large families or disease specific cohorts usually not available to individual researchers; 3) ‘disease experts’, namely clinicians and human genetics often lack direct ‘hands-on’ access to genomic data as data analysis requires advances computer science skills. We have therefore developed Genomes Management Application (GEM.app/Genesis) a software tool that analyses, annotates and visualises large genomic datasets [1, 2]. GEM.app/Genesis is cloud-based and allows users to directly process and analyse data through a user-friendly graphical user interface. Users can query their data in real-time, filtering for mode of inheritance and > 140 items of variant annotation provided by the system. GEM.app/Genesis currently has > 600 registered users; the community is spread over five continents. Data sharing and collaboration is actively encouraged by the system; individual datasets or whole collections of data can be shared with collaborators with a couple of mouse-clicks without necessitating the transfer of large volumes of data or shipping of hard drives. Overall, the platform has supported the discovery of > 50 Mendelian disease genes over the first three years of it’s existence [1].
DISCOVERY OF NOVEL DISEASE GENES AND PROGRESS ON THE BIOLOGY OF AXONOPATHIES
Availability of a clinically well characterized cohort of axonopathy cases and families for whole exome sequencing on the one hand, and the powerful GEM.app/Genesis analysis workflow on the other hand have allowed us to speed up the gene discovery process. Over the course of the three-year project we were involved in the discovery of at least eight novel axonopathy disease genes, including
− ATP13AS (SPG78), a gene previously associated with juvenile-onset parkinsonism, [3]
− KCNA2 which we demonstrated not only to cause epileptic encephalopathy but also autosomal dominant hereditary spastic paraplegia, [4] [5]
− SCYL1, mutations in which cause a unique phenotype with recurrent episodes of acute liver failure in early infancy, followed by a progressive ataxia – neuropathy phenotype, [6]
− SLC25A46, the human Ugo1 orthologue, that is associated with hereditary axonal neuropathy and optic atrophy and is involved in mitochondrial dynamics, [7]
− DNAJC3 which we showed to cause juvenile onset diabetes, ataxia, pyramidal damage and peripheral neuropathy, thus linking monogenetic diabetes mellitus to neurodegeneration, [8]
− PNPLA6, mutations in which explain several distinct clinically defined syndromes, including Boucher-Neuhauser syndrome, Godron Holmes syndrome and hereditary spastic paraplegia with axonal motor neuropathy, [9]
− WWOX, a novel gene linking tonic-clonic epilepsy, mental retardation, ataxia and pyramidal dysfunction, [10]
− KIF1C (SPG58), the third kinesin involved in the pathogenesis of hereditary spastic paraplegia, which causes spastic paraplegia complicated by cerebellar ataxia and variable extrapyramidal features [11]
GENOTYPE-PHENOTYPE CORRELATIONS AND RE-DEFINITION OF DISEASE SPECTRA
By combining the genomic results from this project with our previously established clinical database (‘HSP registry’), a multicentric database that captures detailed cross-sectional and longitudinal data on HSP and related disorders in a harmonized and standardized way, we were furthermore able to delineate and broaden the mutational and phenotypic spectrum associated with a multitude of established axonopathy genes[12], including among many others SYNE1 [13, 14], DYNC1H1 [15], BICD2 [16], STUB1 [17], and OPA1 [18].
LESSONS LEARNED
Traditionally, disease entities are defined clinically or based on common pathological features. As next generation sequencing technology allows to perform phenotypically comparatively unbiased exome- or genome-wide screens we realize that these pre-defined clinical syndromes often do not correspond with the underlying genetic etiology. By classifying cases prematurely into diagnostic categories like hereditary spastic paraplegia, hereditary neuropathy or others, we fail to appreciate the immense overlap that exists between these diagnostic categories and potentially hamper timely and effective genetic diagnosis. Next generation genomics teaches us that we need to move away from strict diagnostic categories to a more modular descriptive approach to a phenotype that can be analysed in unison with the genomic data available from whole exome or genome sequencing experiments. To appreciate the complex relationship between genotype and phenotype that becomes increasingly complex even in rare Mendelian disorders as disease modifiers enter the picture, clinicians and scientists need to collaborate on a global scale to share and jointly analyse data.
REFERENCES
1. Gonzalez, M., et al., Innovative genomic collaboration using the GENESIS (GEM.app) platform. Hum Mutat, 2015. 36(10): p. 950-6.
2. Gonzalez, M.A. et al., GEnomes Management Application (GEM.app): a new software tool for large-scale collaborative genome analysis. Hum Mutat, 2013. 34(6): p. 842-6.
3. Estrada-Cuzcano, A., et al., Loss-of-function mutations in the ATP13A2/PARK9 gene cause complicated hereditary spastic paraplegia (SPG78). Brain, 2016. in press.
4. Helbig, K.L. et al., A recurrent mutation in KCNA2 as a novel cause of hereditary spastic paraplegia and ataxia. Ann Neurol, 2016. 80(4).
5. Syrbe, S., et al., De novo loss- or gain-of-function mutations in KCNA2 cause epileptic encephalopathy. Nat Genet, 2015. 47(4): p. 393-9.
6. Schmidt, W.M. et al., Disruptive SCYL1 Mutations Underlie a Syndrome Characterized by Recurrent Episodes of Liver Failure, Peripheral Neuropathy, Cerebellar Atrophy, and Ataxia. Am J Hum Genet, 2015. 97(6): p. 855-61.
7..
8. Synofzik, M., et al., Absence of BiP co-chaperone DNAJC3 causes diabetes mellitus and multisystemic neurodegeneration. Am J Hum Genet, 2014. 95(6): p. 689-97.
9. Synofzik, M., et al., PNPLA6 mutations cause Boucher-Neuhauser and Gordon Holmes syndromes as part of a broad neurodegenerative spectrum. Brain, 2014. 137(Pt 1): p. 69-77.
10. Mallaret, M., et al., The tumour suppressor gene WWOX is mutated in autosomal recessive cerebellar ataxia with epilepsy and mental retardation. Brain, 2014. 137(Pt 2): p. 411-9.
11. Caballero Oteyza, A., et al., Motor protein mutations cause a new form of hereditary spastic paraplegia. Neurology, 2014. 82(22): p. 2007-16.
12. Schule, R., et al., Hereditary spastic paraplegia: Clinicogenetic lessons from 608 patients. Ann Neurol, 2016. 79(4): p. 646-58.
13. Mademan, I., et al., Multisystemic SYNE1 ataxia: confirming the high frequency and extending the mutational and phenotypic spectrum. Brain, 2016. 139(Pt 8): p. e46.
14. Synofzik, M., et al., SYNE1 ataxia is a common recessive ataxia with major non-cerebellar features: a large multi-centre study. Brain, 2016. 139(Pt 5): p. 1378-93.
15. Strickland, A.V. et al., Mutation screen reveals novel variants and expands the phenotypes associated with DYNC1H1. J Neurol, 2015. 262(9): p. 2124-34.
16. Rossor, A.M. et al., Phenotypic and molecular insights into spinal muscular atrophy due to mutations in BICD2. Brain, 2015. 138(Pt 2): p. 293-310.
17. Synofzik, M., et al., Phenotype and frequency of STUB1 mutations: next-generation screenings in Caucasian ataxia and spastic paraplegia cohorts. Orphanet J Rare Dis, 2014. 9(1): p. 57.
18. Bonifert, T., et al., Pure and syndromic optic atrophy explained by deep intronic OPA1 mutations and an intralocus modifier. Brain, 2014. 137(Pt 8): p. 2164-77.
Inherited human axonopathies, diseases of the long axons of the nervous systems, include the heterogeneous group of Hereditary Spastic Paraplegias (HSP) and Hereditary Motor and Sensory Neuropathies (HMSN), now better known as Charcot-Marie-Tooth disease (CMT). Studying monogenetic, Mendelian forms of these diseases offers the chance to identify key genes that determine the pathophysiology of axon degeneration. Such genes have turned out to encode completely unexpected factors in the past and have hugely enriched our understanding of the neuroscience of axon biology. Understanding the milestones of axon degeneration in these so-called dying-back axonopathies holds the potential of tracing the way back to axonal function and integrity, therefore providing a chance of therapy for many so far incurable diseases.
Taken together at least 65 genes are known to cause CMT or HSP, but new genes continue to be found. Mutations in known HSP and CMT genes explain only about 50% of the cases each, depending on the mode of inheritance.
In this project we aimed at the identification of novel genes for hereditary axonopathies to provide better diagnosis to patients and advance our understanding of the biology of axon degeneration in order to work towards better treatment options for these currently incurable diseases. We furthermore aimed at developing novel tools for more comprehensive stream-lined analysis of next generation sequencing data and advancing data sharing and collaboration opportunities in the scientific community.
COLLECTION OF A COHORT OF AXONOPATHY FAMILIES AND CASES
Collection of large, clinically well characterized cohorts is key in genetic studies of rare diseases. The two partnering institutions in this project – the Hertie Institute of Clinical Brain Research at the University of Tübingen (Tübingen, Germany) and the Hussman Institute for Human Genomics at University of Miami Miller School of Medicine (Miami, Florida) together have collected a unique cohort of families with axonopathies, each drawing from large, well established collaborative networks. From these cohorts, the most promising cases and families were selected for whole exome sequencing (WES) or whole genome sequencing (WGS).
Innovative genomic collaboration using the GENESIS (GEM.app) platform
With the advent of next generation sequencing (NGS) technology, discovery of novel genes for Mendelian disorders has reached an unprecedented pace. However, the new technology poses a number of novel challenges: 1) management of large exome or genome datasets is technically challenging especially for smaller labs; 2) interpretation of the multitude of resulting variants from NGS experiments requires large families or disease specific cohorts usually not available to individual researchers; 3) ‘disease experts’, namely clinicians and human genetics often lack direct ‘hands-on’ access to genomic data as data analysis requires advances computer science skills. We have therefore developed Genomes Management Application (GEM.app/Genesis) a software tool that analyses, annotates and visualises large genomic datasets [1, 2]. GEM.app/Genesis is cloud-based and allows users to directly process and analyse data through a user-friendly graphical user interface. Users can query their data in real-time, filtering for mode of inheritance and > 140 items of variant annotation provided by the system. GEM.app/Genesis currently has > 600 registered users; the community is spread over five continents. Data sharing and collaboration is actively encouraged by the system; individual datasets or whole collections of data can be shared with collaborators with a couple of mouse-clicks without necessitating the transfer of large volumes of data or shipping of hard drives. Overall, the platform has supported the discovery of > 50 Mendelian disease genes over the first three years of it’s existence [1].
DISCOVERY OF NOVEL DISEASE GENES AND PROGRESS ON THE BIOLOGY OF AXONOPATHIES
Availability of a clinically well characterized cohort of axonopathy cases and families for whole exome sequencing on the one hand, and the powerful GEM.app/Genesis analysis workflow on the other hand have allowed us to speed up the gene discovery process. Over the course of the three-year project we were involved in the discovery of at least eight novel axonopathy disease genes, including
− ATP13AS (SPG78), a gene previously associated with juvenile-onset parkinsonism, [3]
− KCNA2 which we demonstrated not only to cause epileptic encephalopathy but also autosomal dominant hereditary spastic paraplegia, [4] [5]
− SCYL1, mutations in which cause a unique phenotype with recurrent episodes of acute liver failure in early infancy, followed by a progressive ataxia – neuropathy phenotype, [6]
− SLC25A46, the human Ugo1 orthologue, that is associated with hereditary axonal neuropathy and optic atrophy and is involved in mitochondrial dynamics, [7]
− DNAJC3 which we showed to cause juvenile onset diabetes, ataxia, pyramidal damage and peripheral neuropathy, thus linking monogenetic diabetes mellitus to neurodegeneration, [8]
− PNPLA6, mutations in which explain several distinct clinically defined syndromes, including Boucher-Neuhauser syndrome, Godron Holmes syndrome and hereditary spastic paraplegia with axonal motor neuropathy, [9]
− WWOX, a novel gene linking tonic-clonic epilepsy, mental retardation, ataxia and pyramidal dysfunction, [10]
− KIF1C (SPG58), the third kinesin involved in the pathogenesis of hereditary spastic paraplegia, which causes spastic paraplegia complicated by cerebellar ataxia and variable extrapyramidal features [11]
GENOTYPE-PHENOTYPE CORRELATIONS AND RE-DEFINITION OF DISEASE SPECTRA
By combining the genomic results from this project with our previously established clinical database (‘HSP registry’), a multicentric database that captures detailed cross-sectional and longitudinal data on HSP and related disorders in a harmonized and standardized way, we were furthermore able to delineate and broaden the mutational and phenotypic spectrum associated with a multitude of established axonopathy genes[12], including among many others SYNE1 [13, 14], DYNC1H1 [15], BICD2 [16], STUB1 [17], and OPA1 [18].
LESSONS LEARNED
Traditionally, disease entities are defined clinically or based on common pathological features. As next generation sequencing technology allows to perform phenotypically comparatively unbiased exome- or genome-wide screens we realize that these pre-defined clinical syndromes often do not correspond with the underlying genetic etiology. By classifying cases prematurely into diagnostic categories like hereditary spastic paraplegia, hereditary neuropathy or others, we fail to appreciate the immense overlap that exists between these diagnostic categories and potentially hamper timely and effective genetic diagnosis. Next generation genomics teaches us that we need to move away from strict diagnostic categories to a more modular descriptive approach to a phenotype that can be analysed in unison with the genomic data available from whole exome or genome sequencing experiments. To appreciate the complex relationship between genotype and phenotype that becomes increasingly complex even in rare Mendelian disorders as disease modifiers enter the picture, clinicians and scientists need to collaborate on a global scale to share and jointly analyse data.
REFERENCES
1. Gonzalez, M., et al., Innovative genomic collaboration using the GENESIS (GEM.app) platform. Hum Mutat, 2015. 36(10): p. 950-6.
2. Gonzalez, M.A. et al., GEnomes Management Application (GEM.app): a new software tool for large-scale collaborative genome analysis. Hum Mutat, 2013. 34(6): p. 842-6.
3. Estrada-Cuzcano, A., et al., Loss-of-function mutations in the ATP13A2/PARK9 gene cause complicated hereditary spastic paraplegia (SPG78). Brain, 2016. in press.
4. Helbig, K.L. et al., A recurrent mutation in KCNA2 as a novel cause of hereditary spastic paraplegia and ataxia. Ann Neurol, 2016. 80(4).
5. Syrbe, S., et al., De novo loss- or gain-of-function mutations in KCNA2 cause epileptic encephalopathy. Nat Genet, 2015. 47(4): p. 393-9.
6. Schmidt, W.M. et al., Disruptive SCYL1 Mutations Underlie a Syndrome Characterized by Recurrent Episodes of Liver Failure, Peripheral Neuropathy, Cerebellar Atrophy, and Ataxia. Am J Hum Genet, 2015. 97(6): p. 855-61.
7.
8. Synofzik, M., et al., Absence of BiP co-chaperone DNAJC3 causes diabetes mellitus and multisystemic neurodegeneration. Am J Hum Genet, 2014. 95(6): p. 689-97.
9. Synofzik, M., et al., PNPLA6 mutations cause Boucher-Neuhauser and Gordon Holmes syndromes as part of a broad neurodegenerative spectrum. Brain, 2014. 137(Pt 1): p. 69-77.
10. Mallaret, M., et al., The tumour suppressor gene WWOX is mutated in autosomal recessive cerebellar ataxia with epilepsy and mental retardation. Brain, 2014. 137(Pt 2): p. 411-9.
11. Caballero Oteyza, A., et al., Motor protein mutations cause a new form of hereditary spastic paraplegia. Neurology, 2014. 82(22): p. 2007-16.
12. Schule, R., et al., Hereditary spastic paraplegia: Clinicogenetic lessons from 608 patients. Ann Neurol, 2016. 79(4): p. 646-58.
13. Mademan, I., et al., Multisystemic SYNE1 ataxia: confirming the high frequency and extending the mutational and phenotypic spectrum. Brain, 2016. 139(Pt 8): p. e46.
14. Synofzik, M., et al., SYNE1 ataxia is a common recessive ataxia with major non-cerebellar features: a large multi-centre study. Brain, 2016. 139(Pt 5): p. 1378-93.
15. Strickland, A.V. et al., Mutation screen reveals novel variants and expands the phenotypes associated with DYNC1H1. J Neurol, 2015. 262(9): p. 2124-34.
16. Rossor, A.M. et al., Phenotypic and molecular insights into spinal muscular atrophy due to mutations in BICD2. Brain, 2015. 138(Pt 2): p. 293-310.
17. Synofzik, M., et al., Phenotype and frequency of STUB1 mutations: next-generation screenings in Caucasian ataxia and spastic paraplegia cohorts. Orphanet J Rare Dis, 2014. 9(1): p. 57.
18. Bonifert, T., et al., Pure and syndromic optic atrophy explained by deep intronic OPA1 mutations and an intralocus modifier. Brain, 2014. 137(Pt 8): p. 2164-77.