Project description:Amyotrophic Lateral Sclerosis (ALS) is a complex syndrome with multiple genetic causes and wide variation in disease presentation. Despite this general heterogeneity, several common factors have been identified. For example, nearly all patients show pathological accumulations of phosphorylated TDP-43 protein in affected regions of the motor cortex and spinal cord. Moreover, large patient cohort studies have revealed that most patient samples can be grouped into a small number of ALS subtypes, as defined by their transcriptomic profiles. These ALS molecular subtypes can be grouped by whether postmortem motor cortex samples display signatures of: mitochondrial dysfunction and oxidative stress (ALS-Ox), microglial activation and neuroinflammation (ALS-Glia), or dense TDP-43 pathology and associated transposable element de-silencing (ALS-TE). In this study, we have built a deep layer ALS neural network classifier (DANcer) that has learned to accurately assign patient samples to these ALS subtypes, and which can be run on either bulk or single-cell datasets. Upon applying this classifier to an expanded ALS patient cohort from the NYGC ALS Consortium, we show that ALS Molecular Subtypes are robust across clinical centers, with no new subtypes appearing in a cohort that has quadrupled in size. Signatures from two of these molecular subtypes strongly correlate with disease duration: ALS-TE signatures in cortex and ALS-Glia signatures in spinal cord, revealing molecular correlates of clinical features. Finally, we use single nucleus RNA sequencing to reveal the cell type-specific contributions to ALS subtype, as determined by our single-cell classifier (scDANCer). Single-cell transcriptomes reveal that ALS molecular subtypes are recapitulated in neurons and glia, with both ALS-wide shared alterations in each cell type as well as ALS subtype- specific alterations. In summary, ALS molecular subtypes: (1) are robust across large cohorts of sporadic and familial ALS patient samples, (2) represent a combination of cellular, genetic, and pathological features, and (3) correlate with clinical features of ALS.

Project description:Aims: Loss of nuclear TDP-43 characterises sporadic and most familial forms of amyotrophic lateral sclerosis (ALS). TDP-43 (encoded by TARDBP) has multiple roles in RNA processing. We aimed to determine whether 1) RNA splicing dysregulation is present in lower motor neurons in ALS and in a motor neuron-like cell model, and 2) TARDBP mutations (mtTARDBP) are associated with aberrant RNA splicing using patient-derived fibroblasts. Methods: Affymetrix exon arrays were used to study mRNA expression and splicing in lower motor neurons obtained by laser capture microdissection of autopsy tissue from individuals with sporadic ALS and TDP-43 proteinopathy. Findings were confirmed by qRT-PCR and in NSC34 motor neuronal cells following shRNA-mediated TDP-43 depletion. Exon arrays and immunohistochemistry were used to study mRNA splicing and TDP-43 expression in fibroblasts from patients with mtTARDBP-associated, sporadic and mutant SOD1-associated ALS. Results: We found altered expression of spliceosome components in motor neurons and widespread aberrations of mRNA splicing that specifically affected genes involved in ribonucleotide binding. This was confirmed in TDP-43 depleted NSC34 cells. Fibroblasts with mtTARDBP showed loss of nuclear TDP-43 protein and demonstrated similar changes in splicing and gene expression, that were not present in fibroblasts from patients with sporadic or SOD1-related ALS. Conclusion: Loss of nuclear TDP-43 is associated with RNA processing abnormalities in ALS motor neurons, patient-derived cells with mtTARDBP, and following artificial TDP-43 depletion, suggesting that splicing dysregulation directly contributes to disease pathogenesis. Key functional pathways affected include those central to RNA metabolism. RNA was extracted from fibroblasts grown from neurologically healthy controls (n=6) and 3 groups of patients with ALS: 1) sporadic cases (n=6); 2) cases due to mutations of SOD1 (n=4); 3) cases due to mutations of TARDBP (n=3). The three ALS groups were compared to the controls.

Project description:Amyotrophic Lateral Sclerosis (ALS) is a complex syndrome with multiple genetic causes and wide variation in disease presentation. Despite this general heterogeneity, several common factors have been identified. For example, nearly all patients show pathological accumulations of phosphorylated TDP-43 protein in affected regions of the motor cortex and spinal cord. Moreover, large patient cohort studies have revealed that most patient samples can be grouped into a small number of ALS subtypes, as defined by their transcriptomic profiles. These ALS molecular subtypes can be grouped by whether postmortem motor cortex samples display signatures of: mitochondrial dysfunction and oxidative stress (ALS-Ox), microglial activation and neuroinflammation (ALS-Glia), or dense TDP-43 pathology and associated transposable element de-silencing (ALS-TE). In this study, we have built a deep layer ALS neural network classifier (DANcer) that has learned to accurately assign patient samples to these ALS subtypes, and which can be run on either bulk or single-cell datasets. Upon applying this classifier to an expanded ALS patient cohort from the NYGC ALS Consortium, we show that ALS Molecular Subtypes are robust across clinical centers, with no new subtypes appearing in a cohort that has quadrupled in size. Signatures from two of these molecular subtypes strongly correlate with disease duration: ALS-TE signatures in cortex and ALS-Glia signatures in spinal cord, revealing molecular correlates of clinical features. Finally, we use single nucleus RNA sequencing to reveal the cell type-specific contributions to ALS subtype, as determined by our single-cell classifier (scDANCer). Single-cell transcriptomes reveal that ALS molecular subtypes are recapitulated in neurons and glia, with both ALS-wide shared alterations in each cell type as well as ALS subtype- specific alterations. In summary, ALS molecular subtypes: (1) are robust across large cohorts of sporadic and familial ALS patient samples, (2) represent a combination of cellular, genetic, and pathological features, and (3) correlate with clinical features of ALS.

Project description:Amyotrophic Lateral Sclerosis (ALS) is a complex syndrome with multiple genetic causes and wide variation in disease presentation. Despite this general heterogeneity, several common factors have been identified. For example, nearly all patients show pathological accumulations of phosphorylated TDP-43 protein in affected regions of the motor cortex and spinal cord. Moreover, large patient cohort studies have revealed that most patient samples can be grouped into a small number of ALS subtypes, as defined by their transcriptomic profiles. These ALS molecular subtypes can be grouped by whether postmortem motor cortex samples display signatures of: mitochondrial dysfunction and oxidative stress (ALS-Ox), microglial activation and neuroinflammation (ALS-Glia), or dense TDP-43 pathology and associated transposable element de-silencing (ALS-TE). In this study, we have built a deep layer ALS neural network classifier (DANcer) that has learned to accurately assign patient samples to these ALS subtypes, and which can be run on either bulk or single-cell datasets. Upon applying this classifier to an expanded ALS patient cohort from the NYGC ALS Consortium, we show that ALS Molecular Subtypes are robust across clinical centers, with no new subtypes appearing in a cohort that has quadrupled in size. Signatures from two of these molecular subtypes strongly correlate with disease duration: ALS-TE signatures in cortex and ALS-Glia signatures in spinal cord, revealing molecular correlates of clinical features. Finally, we use single nucleus RNA sequencing to reveal the cell type-specific contributions to ALS subtype, as determined by our single-cell classifier (scDANCer). Single-cell transcriptomes reveal that ALS molecular subtypes are recapitulated in neurons and glia, with both ALS-wide shared alterations in each cell type as well as ALS subtype-specific alterations. In summary, ALS molecular subtypes: (1) are robust across large cohorts of sporadic and familial ALS patient samples, (2) represent a combination of cellular, genetic, and pathological features, and (3) correlate with clinical features of ALS.

Project description:Aims: Loss of nuclear TDP-43 characterises sporadic and most familial forms of amyotrophic lateral sclerosis (ALS). TDP-43 (encoded by TARDBP) has multiple roles in RNA processing. We aimed to determine whether 1) RNA splicing dysregulation is present in lower motor neurons in ALS and in a motor neuron-like cell model, and 2) TARDBP mutations (mtTARDBP) are associated with aberrant RNA splicing using patient-derived fibroblasts. Methods: Affymetrix exon arrays were used to study mRNA expression and splicing in lower motor neurons obtained by laser capture microdissection of autopsy tissue from individuals with sporadic ALS and TDP-43 proteinopathy. Findings were confirmed by qRT-PCR and in NSC34 motor neuronal cells following shRNA-mediated TDP-43 depletion. Exon arrays and immunohistochemistry were used to study mRNA splicing and TDP-43 expression in fibroblasts from patients with mtTARDBP-associated, sporadic and mutant SOD1-associated ALS. Results: We found altered expression of spliceosome components in motor neurons and widespread aberrations of mRNA splicing that specifically affected genes involved in ribonucleotide binding. This was confirmed in TDP-43 depleted NSC34 cells. Fibroblasts with mtTARDBP showed loss of nuclear TDP-43 protein and demonstrated similar changes in splicing and gene expression, that were not present in fibroblasts from patients with sporadic or SOD1-related ALS. Conclusion: Loss of nuclear TDP-43 is associated with RNA processing abnormalities in ALS motor neurons, patient-derived cells with mtTARDBP, and following artificial TDP-43 depletion, suggesting that splicing dysregulation directly contributes to disease pathogenesis. Key functional pathways affected include those central to RNA metabolism. RNA was extracted from lower motor neurons obtained by laser capture microdissection from autopsy material from neurologically healthy controls (n=6) and cases of sporadic ALS (n=3) and ALS due to C9ORF72 mutations (n=3).

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Postmortem Cortex Samples Identify Distinct Molecular Subtypes of ALS: Retrotransposon Activation, Oxidative Stress, and Activated Glia [motor cortex]

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