Molecular subtypes of ALS are associated with differences in patient prognosis

Eshima, Jarrett; O'Connor, Samantha; Marschall, Ethan; Bowser, Robert; Plaisier, Christopher L.; Smith, Barbara S.

doi:10.1038/s41467-022-35494-w

Cited by 34 publications

(65 citation statements)

References 125 publications

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“…ALS is a very heterogenous disease 7 , and smaller cohort sizes cannot fully recapitulate its etiological diversity. However, only recently biobanks have been able collect enough samples to generate reports with dozens individuals 7,8 , we hope that the increase in samples availability and affordability of single-cell technology will allow a more comprehensive view of transcriptomic changes in ALS. A bigger cohort size would also allow a more stringent analysis of differentially expressed genes (such as by "pseudo-bulking") before nominating DEGs.…”

Section: Limitations Of This Studymentioning

confidence: 99%

“…Variants in genes associated with ALS can contribute to a related disorder, Frontotemporal Dementia (FTD), leading to the view of ALS and FTD as different clinical manifestations of shared molecular causes. Bulk RNA-sequencing of ALS post-mortem brains have identified differences 4,5 and similarities between sporadic and familial 6 cases and highlighted shared profiles independent of disease onset 7,8 . While they have provided valuable insights, these studies have had limited resolution on the cell types mostly altered by the disease.…”

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confidence: 99%

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Single-nucleus sequencing reveals enriched expression of genetic risk factors in Extratelencephalic Neurons sensitive to degeneration in ALS

Limone

Mordes

Couto

et al. 2021

Preprint

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Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disorder characterised by a progressive loss of motor function. While it is known that the eponymous spinal sclerosis observed upon autopsy is the result of Cortico-Spinal Motor Neuron (CSMN) degeneration, it remains unclear why this neuronal subtype is selectively affected. To understand the unique molecular properties that sensitise deep-layer CSMNs to ALS, we performed RNA sequencing of 79,169 single nuclei from the frontal cortex of patients and controls. In unaffected individuals, we found that expression of ALS risk genes was most significantly enriched only in THY1+ presumptive CSMNs and not in other cortical cell types. In patients, these genetic risk factors, as well as additional genes involved in protein homeostasis and stress responses, were significantly induced in THY1+ CSMNs and a wider collection of deep layer neurons, but not in neurons with more superficial identities. Examination of oligodendroglial and microglial nuclei also revealed patient-specific gene expression changes We show microglial alterations can in part be explained by interactions with degenerating neurons. Overall, our findings suggest the selective vulnerability of CSMNs is due to a "first over the line" mechanism by which their intrinsic molecular properties sensitise them to genetic and mechanistic contributors to degeneration.

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Section: Limitations Of This Studymentioning

confidence: 99%

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confidence: 99%

Single-nucleus sequencing reveals enriched expression of genetic risk factors in Extratelencephalic Neurons sensitive to degeneration in ALS

Limone

Mordes

Couto

et al. 2021

Preprint

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“…Our data would suggest that a combinatorial blood-based biomarker approach 75 , using circulating markers derived from a gene panel such as ours, validated across distinct ALS patient populations (as in Figure 5d), would be a more appropriate way to identify subgroups that would benefit from targeted therapies. Promising candidates are based on the 20 genes from our NPS-defining gene list that strongly delineate clusters in an independent, publicly available dataset (i.e., GRIN2B, RALB, BCL2L2, PINK1, MAP2K1, TBR1, PAK1, ATP6V1A, NEFL, GRIA1, CAMK4, MEF2C, CD47, MAPK10, RAB6B, PRKACB, RB1CC1, HOF1A, GCLC ) and two additional NPS-defining genes ( CD44 and TYROBP ) that also appear in a recently identified gene list defining a molecular subgroup relating to glial activation 61 . Molecular stratification, in the form of tissue derived and circulating biomarkers, is the mainstay of patient stratification for clinical trials in oncology 76 ; given the convergence of these studies with our data, molecular subtyping should be considered for future trials implementing targeted therapies in people with ALS.…”

Section: Discussionmentioning

confidence: 99%

“…The utility of transcriptome data for identifying molecular signatures that correlate with survival has been recently demonstrated identifying a subgroup of ALS patients with poorer survival with differential expression of genes relating to oxidative phosphorylation 60,61 . Here we identify BDNF expression as a clinical correlate of survival, highlighting the additional mechanistic insights afforded through our targeted approach.…”

Section: Discussionmentioning

confidence: 99%

Distinct neuroinflammatory signatures exist across genetic and sporadic ALS cohorts

Rifai

O’Shaughnessy

Dando

et al. 2023

Preprint

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Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterised by progressive loss of upper and lower motor neurons. ALS is on a pathogenetic disease spectrum with frontotemporal dementia (FTD), with patients sometimes experiencing elements of both conditions (ALS-FTSD). For mutations associated with ALS-FTSD, such as the C9orf72 hexanucleotide repeat expansion (HRE), the factors influencing where an individual may lie on this spectrum require further characterisation. Here, using NanoString molecular barcoding with a panel of 770 neuroinflammatory genes, we interrogate inflammatory dysregulation at the level of gene expression. We identified 20 dysregulated neuroinflammatory genes in the motor cortex of deeply clinically phenotyped C9-ALS post-mortem cases, with enrichment of microglial and inflammatory response gene sets. Our analyses also revealed two distinct ALS-related neuroinflammatory panel signatures (NPS), NPS1 and NPS2, delineated by the direction of expression of proinflammatory, axonal transport and synaptic signalling pathways. Two genes with significant correlations to available clinical metrics were selected for validation: FKBP5 and BDNF. FKBP5 and its signalling partner, NF-κB, appeared to have a cell-type-specific staining distribution, with activated (i.e., nuclear) NF-κB immunoreactivity in C9-ALS. Expression of BDNF, a correlate of disease duration, was confirmed to be higher in individuals with long compared to short disease duration using BaseScope(TM) in situ hybridisation. Finally, we compared NPS between C9-ALS cases and those from deeply clinically phenotyped sporadic ALS (sALS) and SOD1-ALS cohorts, with NPS1 and NPS2 appearing across all cohorts. A subset of these signatures was also detected in publicly available RNA-sequencing data from independent C9-ALS and sALS cohorts, underscoring the relevance of these pathways across cohorts. Our findings highlight the importance of tailoring therapeutic approaches based on distinct molecular signatures that exist between and within genetic and sporadic cohorts.

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“…ML has previously been applied to brain expression data to stratify people with SALS into molecular subgroups [8][9][10][11] and has led to valuable insights into the genomic heterogeneity of ALS. However, some of these studies integrated samples from different brain regions to generate clusters and characterise their molecular architectures [10][11][12] . This design would not reflect motor neuron-specific ALS pathogenesis.…”

Section: Introductionmentioning

confidence: 99%

Unsupervised machine learning identifies distinct molecular and phenotypic ALS subtypes in post-mortem motor cortex and blood expression data

Marriott

Kabiljo

Hunt

et al. 2023

Preprint

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Background: Amyotrophic lateral sclerosis (ALS) displays considerable clinical, genetic and molecular heterogeneity. Machine learning approaches have shown potential to disentangle complex disease landscapes and they have been utilised for patient stratification in ALS. However, lack of independent validation in different populations and in pre-mortem tissue samples have greatly limited their use in clinical and research settings. We overcame such issues by performing a large-scale study of over 600 post-mortem brain and blood samples of people with ALS from four independent datasets from the UK, Italy, the Netherlands and the US. Methods: Hierarchical clustering was performed on the 5000 most variably expressed autosomal genes identified from post-mortem motor cortex expression data of people with sporadic ALS from the KCL BrainBank (N=112). The molecular architectures of each cluster were investigated with gene enrichment, network and cell composition analysis. Methylation and genetic data were also used to assess if other omics measures differed between individuals. Validation of these clusters was achieved by applying linear discriminant analysis models based on the KCL BrainBank to the TargetALS US motor cortex (N=93), as well as Italian (N=15) and Dutch (N=397) blood expression datasets. Phenotype analysis was also performed to assess cluster-specific differences in clinical outcomes. Results: We identified three molecular phenotypes, which reflect the proposed major mechanisms of ALS pathogenesis: synaptic and neuropeptide signalling, excitotoxicity and oxidative stress, and neuroinflammation. Known ALS risk genes were identified among the informative genes of each cluster, suggesting potential for genetic profiling of the molecular phenotypes. Cell types which are known to be associated with specific molecular phenotypes were found in higher proportions in those clusters. These molecular phenotypes were validated in independent motor cortex and blood datasets. Phenotype analysis identified distinct cluster-related outcomes associated with progression, survival and age of death. We developed a public webserver (https://alsgeclustering.er.kcl.ac.uk) that allows users to stratify samples with our model by uploading their expression data. Conclusions: We have identified three molecular phenotypes, driven by different cell types, which reflect the proposed major mechanisms of ALS pathogenesis. Our results support the hypothesis of biological heterogeneity in ALS where different mechanisms underly ALS pathogenesis in a subgroup of patients that can be identified by a specific expression signature. These molecular phenotypes show potential for stratification of clinical trials, the development of biomarkers and personalised treatment approaches.

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Molecular subtypes of ALS are associated with differences in patient prognosis

Cited by 34 publications

References 125 publications

Single-nucleus sequencing reveals enriched expression of genetic risk factors in Extratelencephalic Neurons sensitive to degeneration in ALS

Single-nucleus sequencing reveals enriched expression of genetic risk factors in Extratelencephalic Neurons sensitive to degeneration in ALS

Distinct neuroinflammatory signatures exist across genetic and sporadic ALS cohorts

Unsupervised machine learning identifies distinct molecular and phenotypic ALS subtypes in post-mortem motor cortex and blood expression data

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