The SOD1-mediated ALS phenotype shows a decoupling between age of symptom onset and disease duration

Opie-Martin, Sarah; Iacoangeli, Alfredo; Topp, Simon; Abel, Olubunmi; Mayl, Keith; Mehta, Pritesh; Shatunov, Aleksey; Fogh, Isabella; Bowles, Harry; Limbachiya, Naomi; Spargo, Thomas P; Khleifat, Ahmad Al; Williams, Kelly L.; Jockel-Balsarotti, Jennifer; Bali, Taha; Self, Wade; Henden, Lyndal; Nicholson, Garth A.; Ticozzi, Nicola; McKenna‐Yasek, Diane; Tang, Lu; Shaw, Pamela J.; Chiò, Adriano; Ludolph, Albert L.; Weishaupt, Jochen H.; Landers, John E.; Glass, Jonathan D.; Mora, Jesús; Robberecht, Wim; Damme, Philip Van; McLaughlin, Russell L.; Hardiman, Orla; Berg, Leonard van den; Veldink, Jan H.; Corcia, Phillippe; Stević, Zorica; Siddique, Nailah; Silani, Vincenzo; Blair, Ian P.; Esselin, Florence; Cruz, Elisa De La; Camu, William; Başak, Nazlı; Siddique, Teepu; Miller, Timothy M.; Brown, Robert H.; Al‐Chalabi, Ammar

doi:10.1038/s41467-022-34620-y

Cited by 26 publications

(19 citation statements)

References 35 publications

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“…In order to investigate whether WTL and MBR variants associate with different clinical outcomes, we collected clinical data of patients carrying the variants investigated in this study. We were able to retrieve clinical data of 489 ALS patients with A4V, G37R, L38V, G93R, I113T, H46R, H80R, G85R and D125H (see details of individual variants in Table 4) [34]. Cox proportional hazard analysis (Figure 10) showed that patients with MBR variants presented a longer survival time (approximately 6 years median difference, p < 0.001) than patients with WTL variants, while no difference (p = 0.19) was observed for the age of onset (details in Table 4).…”

Section: Phenotype Analysis Of Wtl and Mbr Variantsmentioning

confidence: 99%

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Molecular dynamics analysis of Superoxide Dismutase 1 mutations suggests decoupling between mechanisms underlying ALS onset and progression

Kalia

Miotto

Ness

et al. 2022

Preprint

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Mutations in the superoxide dismutase 1 (SOD1) gene are the second most common known cause of ALS. SOD1 variants express high phenotypic variability and over 200 have been reported in people with ALS. Investigating how different SOD1 variants affect the protein dynamics might help in understanding their pathogenic mechanism and explaining their heterogeneous clinical presentation. It was previously proposed that variants can be broadly classified in two groups, "wild-type like" (WTL) and "metal binding region" (MBR) variants, based on their structural location and biophysical properties. MBR variants are associated with a loss of SOD1 enzymatic activity. In this study we used molecular dynamics and large clinical datasets to characterise the differences in the structural and dynamic behaviour of WTL and MBR variants with respect to the wild-type SOD1, and how such differences influence the ALS clinical phenotype. Our study identified marked structural differences, some of which are observed in both variant groups, while others are group specific. Moreover, applying graph theory to a network representation of the proteins, we identified differences in the intramolecular contacts of the two classes of variants. Finally, collecting clinical data of approximately 500 SOD1 ALS patients carrying variants from both classes, we showed that the survival time of patients carrying an MBR variant is generally longer (~6 years median difference, p < 0.001) with respect to patients with a WTL variant. In conclusion, our study highlights key differences in the dynamic behaviour of the WTL and MBR SOD1 variants, and wild-type SOD1 at an atomic and molecular level. We identified interesting structural features that could be further investigated to explain the associated phenotypic variability. Our results support the hypothesis of a decoupling between mechanisms of onset and progression of SOD1 ALS, and an involvement of loss-of-function of SOD1 with the disease progression.

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Section: Phenotype Analysis Of Wtl and Mbr Variantsmentioning

confidence: 99%

“…Our results suggested that the structural and dynamic behaviour differences between WTL and MBR variants could be linked to the ALS clinical phenotype. To explore this hypothesis, we collected a large clinical dataset of SOD1 ALS patients [34] and performed survival and age of onset analyses in the patients carrying WTL and MBR variants.…”

Section: Introductionmentioning

confidence: 99%

Molecular dynamics analysis of Superoxide Dismutase 1 mutations suggests decoupling between mechanisms underlying ALS onset and progression

Kalia

Miotto

Ness

et al. 2022

Preprint

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“…This design would not reflect motor neuron-specific ALS pathogenesis. Other studies adopted a case-control framework 8,9,11 , which could lead to reduced power given the potential decoupling between mechanisms underlying risk and clinical presentation [13][14][15] . Furthermore, previous work has not been validated in independent datasets or in different populations and did not investigate whether molecular subtypes identified in post-mortem brains are reflected in other tissues available pre-mortem.…”

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

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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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“…As well as affecting ALS risk, some of these variants have distinct effects on clinical features such as age of onset of motor symptoms and disease duration. For example, p.A5V and p.H44R have a marked effect on disease duration while p.G38R is associated with an early onset 10,12-14 . Being able to characterise how genetic variants affect the clinical phenotype is essential for optimal development and design of healthcare, treatments, and trial stratification.…”

Section: Introductionmentioning

confidence: 99%

SOD1-ALS-Browser: a web-utility for investigating the clinical phenotype inSOD1amyotrophic lateral sclerosis

Spargo

Opie-Martin

Hunt

et al. 2023

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ObjectiveVariants in the superoxide dismutase (SOD1) gene are among the most common genetic causes of amyotrophic lateral sclerosis. Reflecting the wide spectrum of putatively deleterious variants that have been reported to date, it has become clear thatSOD1-linked ALS presents a highly variable age at symptom onset and disease duration.MethodsHere we describe an open access web-tool for comparative phenotype analysis in ALS:https://sod1-als-browser.rosalind.kcl.ac.uk/. The tool contains a built-in dataset of clinical information from 1,383 people with ALS harbouring aSOD1variant resulting in one of 162 unique amino acid sequence alterations, and from a non-SOD1comparator ALS cohort of 13,469 individuals. We present two examples of analyses possible with this tool, testing how the ALS phenotype relates toSOD1variants which alter amino acid residue hydrophobicity, and distinct variants at the 94thresidue of SOD1 which has six variants sampled at the same position.Results and conclusionsThe tool provides immediate access to the datasets and enables bespoke analysis of phenotypic trends associated with different gene variants, including the option for users to upload their own datasets for integration with the server data. The tool can be used to studySOD1-ALS as well as an analytical framework to study the differences between other user-uploaded ALS groups and our large reference database ofSOD1and non-SOD1ALS. The tool is designed to be useful for clinicians and researchers, including those without programming expertise, and is highly flexible in the analyses that can be conducted.

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The SOD1-mediated ALS phenotype shows a decoupling between age of symptom onset and disease duration

Cited by 26 publications

References 35 publications

Molecular dynamics analysis of Superoxide Dismutase 1 mutations suggests decoupling between mechanisms underlying ALS onset and progression

Molecular dynamics analysis of Superoxide Dismutase 1 mutations suggests decoupling between mechanisms underlying ALS onset and progression

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

SOD1-ALS-Browser: a web-utility for investigating the clinical phenotype inSOD1amyotrophic lateral sclerosis

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