DNAscan2: a versatile, scalable, and user-friendly analysis pipeline for human next-generation sequencing data.

SUMMARY: The current widespread adoption of next-generation sequencing (NGS) in all branches of basic research and clinical genetics fields means that users with highly variable informatics skills, computing facilities and application purposes need to process, analyse, and interpret NGS data. In this landscape, versatility, scalability, and user-friendliness are key characteristics for an NGS analysis software. We developed DNAscan2, a highly flexible, end-to-end pipeline for the analysis of NGS data, which (i) can be used for the detection of multiple variant types, including SNVs, small indels, transposable elements, short tandem repeats, and other large structural variants; (ii) covers all standard steps of NGS analysis, from quality control of raw data and genome alignment to variant calling, annotation, and generation of reports for the interpretation and prioritization of results; (iii) is highly adaptable as it can be deployed and run via either a graphic user interface for non-bioinformaticians and a command line tool for personal computer usage; (iv) is scalable as it can be executed in parallel as a Snakemake workflow, and; (v) is computationally efficient by minimizing RAM and CPU time requirements. AVAILABILITY AND IMPLEMENTATION: DNAscan2 is implemented in Python3 and is available at https://github.com/KHP-Informatics/DNAscanv2.

The impact of age on genetic testing decisions in amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis (ALS) is a heterogeneous neurodegenerative syndrome. In up to 20% of cases, a family history is observed. Although Mendelian disease gene variants are found in apparently sporadic ALS, genetic testing is usually restricted to those with a family history or younger patients with sporadic disease. With the advent of therapies targeting genetic ALS, it is important that everyone treatable is identified. We therefore sought to determine the probability of a clinically actionable ALS genetic test result by age of onset, globally, but using the UK as an exemplar. Blood-derived DNA was sequenced for ALS genes, and the probability of a clinically actionable genetic test result estimated. For a UK subset, age- and sex-specific population incidence rates were used to determine the number of such results missed by restricting testing by age of onset according to UK's National Genomic Test Directory criteria. There were 6274 people with sporadic ALS, 1551 from the UK. The proportion with a clinically actionable genetic test result ranged between 0.21 [95% confidence interval (CI) 0.18-0.25] in the youngest age group to 0.15 (95% CI 0.13-0.17) in the oldest age group for a full gene panel. For the UK, the equivalent proportions were 0.23 (95% CI 0.13-0.33) in the youngest age group to 0.17 (95% CI 0.13-0.21) in the oldest age group. By limiting testing in those without a family history to people with onset below 40 years, 115 of 117 (98% of all, 95% CI 96%-101%) clinically actionable test results were missed. There is a significant probability of a clinically actionable genetic test result in people with apparently sporadic ALS at all ages. Although some countries limit testing by age, doing so results in a significant number of missed pathogenic test results. Age of onset and family history should not be a barrier to genetic testing in ALS.

Does genetic anticipation occur in familial Alexander disease?

Alexander Disease (AxD) is a rare leukodystrophy caused by missense mutations of glial fibrillary acidic protein (GFAP). Primarily seen in infants and juveniles, it can present in adulthood. We report a family with inherited AxD in which the mother presented with symptoms many years after her daughter. We reviewed the age of onset in all published cases of familial AxD and found that 32 of 34 instances of parent-offspring pairs demonstrated an earlier age of onset in offspring compared to the parent. We suggest that genetic anticipation occurs in familial AxD and speculate that genetic mosaicism could explain this phenomenon.

Detection of long repeat expansions from PCR-free whole-genome sequence data.

Identifying large expansions of short tandem repeats (STRs), such as those that cause amyotrophic lateral sclerosis (ALS) and fragile X syndrome, is challenging for short-read whole-genome sequencing (WGS) data. A solution to this problem is an important step toward integrating WGS into precision medicine. We developed a software tool called ExpansionHunter that, using PCR-free WGS short-read data, can genotype repeats at the locus of interest, even if the expanded repeat is larger than the read length. We applied our algorithm to WGS data from 3001 ALS patients who have been tested for the presence of the C9orf72 repeat expansion with repeat-primed PCR (RP-PCR). Compared against this truth data, ExpansionHunter correctly classified all (212/212, 95% CI [0.98, 1.00]) of the expanded samples as either expansions (208) or potential expansions (4). Additionally, 99.9% (2786/2789, 95% CI [0.997, 1.00]) of the wild-type samples were correctly classified as wild type by this method with the remaining three samples identified as possible expansions. We further applied our algorithm to a set of 152 samples in which every sample had one of eight different pathogenic repeat expansions, including those associated with fragile X syndrome, Friedreich's ataxia, and Huntington's disease, and correctly flagged all but one of the known repeat expansions. Thus, ExpansionHunter can be used to accurately detect known pathogenic repeat expansions and provides researchers with a tool that can be used to identify new pathogenic repeat expansions.

Relationship between smoking and ALS: Mendelian randomisation interrogation of causality.

OBJECTIVE: Smoking has been widely studied as a susceptibility factor for amyotrophic lateral sclerosis (ALS), but results are conflicting and at risk of confounding bias. We used the results of recently published large genome-wide association studies and Mendelian randomisation methods to reduce confounding to assess the relationship between smoking and ALS. METHODS: Two genome-wide association studies investigating lifetime smoking (n=463 003) and ever smoking (n=1 232 091) were identified and used to define instrumental variables for smoking. A genome-wide association study of ALS (20 806 cases; 59 804 controls) was used as the outcome for inverse variance weighted Mendelian randomisation, and four other Mendelian randomisation methods, to test whether smoking is causal for ALS. Analyses were bidirectional to assess reverse causality. RESULTS: There was no strong evidence for a causal or reverse causal relationship between smoking and ALS. The results of Mendelian randomisation using the inverse variance weighted method were: lifetime smoking OR 0.94 (95% CI 0.74 to 1.19), p value 0.59; ever smoking OR 1.10 (95% CI 1 to 1.23), p value 0.05. CONCLUSIONS: Using multiple methods, large sample sizes and sensitivity analyses, we find no evidence with Mendelian randomisation techniques that smoking causes ALS. Other smoking phenotypes, such as current smoking, may be suitable for future Mendelian randomisation studies.

Younger age of onset in familial amyotrophic lateral sclerosis is a result of pathogenic gene variants, rather than ascertainment bias.

OBJECTIVE: Amyotrophic lateral sclerosis (ALS) is a rapidly progressive neurodegenerative disease of motor neurons with a median survival of 2 years. Familial ALS has a younger age of onset than apparently sporadic ALS. We sought to determine whether this younger age of onset is a result of ascertainment bias or has a genetic basis. METHODS: Samples from people with ALS were sequenced for 13 ALS genes. To determine the effect of genetic variation, age of onset was compared in people with sporadic ALS carrying a pathogenic gene variant and those who do not; to determine the effect of family history, we compared those with genetic sporadic ALS and familial ALS. RESULTS: There were 941 people with a diagnosis of ALS, 100 with familial ALS. Of 841 with apparently sporadic ALS, 95 carried a pathogenic gene variant. The mean age of onset in familial ALS was 5.3 years younger than for apparently sporadic ALS (p=6.0×10-5, 95% CI 2.8 to 7.8 years). The mean age of onset of genetic sporadic ALS was 2.9 years younger than non-genetic sporadic ALS (p=0.011, 95% CI 0.7 to 5.2 years). There was no difference between the mean age of onset in genetic sporadic ALS and familial ALS (p=0.097). CONCLUSIONS: People with familial ALS have an age of onset about 5 years younger than those with apparently sporadic ALS, and we have shown that this is a result of Mendelian gene variants lowering the age of onset, rather than ascertainment bias.

A comprehensive analysis of rare genetic variation in amyotrophic lateral sclerosis in the UK.

Amyotrophic lateral sclerosis is a progressive neurodegenerative disease of motor neurons. About 25 genes have been verified as relevant to the disease process, with rare and common variation implicated. We used next generation sequencing and repeat sizing to comprehensively assay genetic variation in a panel of known amyotrophic lateral sclerosis genes in 1126 patient samples and 613 controls. About 10% of patients were predicted to carry a pathological expansion of the C9orf72 gene. We found an increased burden of rare variants in patients within the untranslated regions of known disease-causing genes, driven by SOD1, TARDBP, FUS, VCP, OPTN and UBQLN2. We found 11 patients (1%) carried more than one pathogenic variant (P = 0.001) consistent with an oligogenic basis of amyotrophic lateral sclerosis. These findings show that the genetic architecture of amyotrophic lateral sclerosis is complex and that variation in the regulatory regions of associated genes may be important in disease pathogenesis.

Analysis of non-motor symptoms in amyotrophic lateral sclerosis.

OBJECTIVE: We investigated non-motor symptoms in ALS using sequential questionnaires; here we report the findings of the second questionnaire. METHODS: A social media platform (Twitter, now known as X) was used to publicize the questionnaires. Data were downloaded from SurveyMonkey and analyzed by descriptive statistics, comparison of means, and regression models. RESULTS: There were 182 people with ALS and 57 controls. The most important non-motor symptoms were cold limbs (60.4% cases, 14% controls, p = 9.67 x 10-10) and appetite loss (29.7% cases, 5.3% controls, p = 1.6 x 10-4). The weaker limb was most likely to feel cold (p = 9.67 x 10-10), and symptoms were more apparent in the evening and night. Appetite loss was reported as due to feeling full and the time taken to eat. People with ALS experienced medium-intensity pain, more usually shock-like pain than burning or cold-like pain, although the most prevalent type of pain was non-differentiated. CONCLUSIONS: Non-motor symptoms are an important feature of ALS. Further investigation is needed to understand their physiological basis and whether they represent phenotypic differences useful for subtyping ALS.

Non-motor symptoms in amyotrophic lateral sclerosis.

OBJECTIVE: While motor symptoms are well-known in ALS, non-motor symptoms are often under-reported and may have a significant impact on quality of life. In this study, we aimed to examine the nature and extent of non-motor symptoms in ALS. METHODS: A 20-item questionnaire was developed covering the domains of autonomic function, sleep, pain, gastrointestinal disturbance, and emotional lability, posted online and shared on social media platforms to target people with ALS and controls. RESULTS: A total of 1018 responses were received, of which 927 were complete from 506 people with ALS and 421 unaffected individuals. Cold limbs (p 1.66 × 10-36), painful limbs (p 6.14 × 10-28), and urinary urgency (p 4.70 × 10-23) were associated with ALS. People with ALS were more likely to report autonomic symptoms, pain, and psychiatric symptoms than controls (autonomic symptoms B = 0.043, p 6.10 × 10-5, pain domain B = 0.18, p 3.72 × 10-11 and psychiatric domain B = 0.173, p 1.32 × 10-4). CONCLUSIONS: Non-motor symptoms in ALS are common. The identification and management of non-motor symptoms should be integrated into routine clinical care for people with ALS. Further research is warranted to investigate the relationship between non-motor symptoms and disease progression, as well as to develop targeted interventions to improve the quality of life for people with ALS.

Investigating the impact of socioeconomic status on amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by the gradual death of motor neurons in the brain and spinal cord, leading to fatal paralysis. Socioeconomic status (SES) is a measure of an individual's shared economic and social status, which has been shown to have an association with health outcomes. Understanding the impact of SES on health conditions is crucial, as it can influence and be influenced by health-related variables. The role of socioeconomic status in influencing the risk and progression of ALS has not been established, and understanding the various factors that impact ALS is important in developing strategies for treatment and prevention. To investigate this relationship, we recruited 413 participants with definite, probable, or possible ALS according to the El Escorial criteria, from three tertiary centers in London, Sheffield, and Birmingham. Logistic regression was used to examine the association between case-control status, socioeconomic criteria, and ALS risk. Linear regression was used to examine the association between age of onset and socioeconomic variables. Two sensitivity analyses were performed, one using an alternative occupational classifier, and the other using Mendelian Randomization analysis to examine association. There was no significant relationship between any variables and ALS risk. We found an inverse relationship between mean lifetime salary and age of ALS onset (Beta = -0.157, p = 0.011), but no effect of education or occupation on the age of onset. The finding was confirmed in both sensitivity analyses and in Mendelian Randomization. We find that a higher salary is associated with a younger age of ALS onset taking into account sex, occupation, years of education, and clinical presentation.

C9orf72 Repeat Expansion Discordance in 6 Multigenerational Kindreds.

Background and Objectives: A hexanucleotide repeat expansion in the noncoding region of the C9orf72 gene is the most common genetically identifiable cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia in populations of European ancestry. Pedigrees associated with this expansion exhibit phenotypic heterogeneity and incomplete disease penetrance, the basis of which is poorly understood. Relatives of those carrying the C9orf72 repeat expansion exhibit a characteristic cognitive endophenotype independent of carrier status. To examine whether additional shared genetic or environmental risks within kindreds could compel this observation, we have conducted a detailed cross-sectional study of the inheritance within multigenerational Irish kindreds carrying the C9orf72 repeat expansion. Methods: One hundred thirty-one familial ALS pedigrees, 59 of which carried the C9orf72 repeat expansion (45.0% [95% CI 36.7-53.5]), were identified through the Irish population-based ALS register. C9orf72 genotyping was performed using repeat-primed PCR with amplicon fragment length analysis. Pedigrees were further investigated using SNP, targeted sequencing data, whole-exome sequencing, and whole-genome sequencing. Results: We identified 21 kindreds where at least 1 family member with ALS carried the C9orf72 repeat expansion and from whom DNA was available from multiple affected family members. Of these, 6 kindreds (28.6% [95% CI 11.8-48.3]) exhibited discordant segregation. The C9orf72 haplotype was studied in 2 families and was found to segregate with the C9orf72-positive affected relative but not the C9orf72-negative affected relative. No other ALS pathogenic variants were identified within these discordant kindreds. Discussion: Family members of kindreds associated with the C9orf72 repeat expansion may carry an increased risk of developing ALS independent of their observed carrier status. This has implications for assessment and counseling of asymptomatic individuals regarding their genetic risk.

Harnessing transcriptomic signals for amyotrophic lateral sclerosis to identify novel drugs and enhance risk prediction.

Introduction: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease. This study integrates common genetic association results from the latest ALS genome-wide association study (GWAS) summary statistics with functional genomic annotations with the aim of providing mechanistic insights into ALS risk loci, inferring drug repurposing opportunities, and enhancing prediction of ALS risk and clinical characteristics. Methods: Genes associated with ALS were identified using GWAS summary statistic methodology including SuSiE SNP-based fine-mapping, and transcriptome- and proteome-wide association study (TWAS/PWAS) analyses. Using several approaches, gene associations were integrated with the DrugTargetor drug-gene interaction database to identify drugs that could be repurposed for the treatment of ALS. Furthermore, ALS gene associations from TWAS were combined with observed blood expression in two external ALS case-control datasets to calculate polytranscriptomic scores and evaluate their utility for prediction of ALS risk and clinical characteristics, including site of onset, age at onset, and survival. Results: SNP-based fine-mapping, TWAS and PWAS identified 118 genes associated with ALS, with TWAS and PWAS providing novel mechanistic insights. Drug repurposing analyses identified six drugs significantly enriched for interactions with ALS associated genes, though directionality could not be determined. Additionally, drug class enrichment analysis showed gene signatures linked to calcium channel blockers may reduce ALS risk, whereas antiepileptic drugs may increase ALS risk. Across the two observed expression target samples, ALS polytranscriptomic scores significantly predicted ALS risk (R 2 = 5.1 %; p-value = 3.2 × 10-27) and clinical characteristics. Conclusions: Functionally-informed analyses of ALS GWAS summary statistics identified novel mechanistic insights into ALS aetiology, highlighted several therapeutic research avenues, and enabled statistically significant prediction of ALS risk.

predicTTE: An accessible and optimal tool for time-to-event prediction in neurological diseases.

Time-to-event prediction is a key task for biological discovery, experimental medicine, and clinical care. This is particularly true for neurological diseases where development of reliable biomarkers is often limited by difficulty visualising and sampling relevant cell and molecular pathobiology. To date, much work has relied on Cox regression because of ease-of-use, despite evidence that this model includes incorrect assumptions. We have implemented a set of deep learning and spline models for time-to-event modelling within a fully customizable 'app' and accompanying online portal, both of which can be used for any time-to-event analysis in any disease by a non-expert user. Our online portal includes capacity for end-users including patients, Neurology clinicians, and researchers, to access and perform predictions using a trained model, and to contribute new data for model improvement, all within a data-secure environment. We demonstrate a pipeline for use of our app with three use-cases including imputation of missing data, hyperparameter tuning, model training and independent validation. We show that predictions are optimal for use in downstream applications such as genetic discovery, biomarker interpretation, and personalised choice of medication. We demonstrate the efficiency of an ensemble configuration, including focused training of a deep learning model. We have optimised a pipeline for imputation of missing data in combination with time-to-event prediction models. Overall, we provide a powerful and accessible tool to develop, access and share time-to-event prediction models; all software and tutorials are available at www.predictte.org.

Rare and common genetic determinants of mitochondrial function determine severity but not risk of amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease involving selective vulnerability of energy-intensive motor neurons (MNs). It has been unclear whether mitochondrial function is an upstream driver or a downstream modifier of neurotoxicity. We separated upstream genetic determinants of mitochondrial function, including genetic variation within the mitochondrial genome or autosomes; from downstream changeable factors including mitochondrial DNA copy number (mtCN). Across three cohorts including 6,437 ALS patients, we discovered that a set of mitochondrial haplotypes, chosen because they are linked to measurements of mitochondrial function, are a determinant of ALS survival following disease onset, but do not modify ALS risk. One particular haplotype appeared to be neuroprotective and was significantly over-represented in two cohorts of long-surviving ALS patients. Causal inference for mitochondrial function was achievable using mitochondrial haplotypes, but not autosomal SNPs in traditional Mendelian randomization (MR). Furthermore, rare loss-of-function genetic variants within, and reduced MN expression of, ACADM and DNA2 lead to ∼50 % shorter ALS survival; both proteins are implicated in mitochondrial function. Both mtCN and cellular vulnerability are linked to DNA2 function in ALS patient-derived neurons. Finally, MtCN responds dynamically to the onset of ALS independently of mitochondrial haplotype, and is correlated with disease severity. We conclude that, based on the genetic measures we have employed, mitochondrial function is a therapeutic target for amelioration of disease severity but not prevention of ALS.

Mutations in the tail and rod domains of the neurofilament heavy-chain gene increase the risk of ALS.

OBJECTIVE: Neurofilament heavy-chain gene (NEFH) variants are associated with multiple neurodegenerative diseases, however, their relationship with ALS has not been robustly explored. Still, NEFH is commonly included in genetic screening panels worldwide. We therefore aimed to determine if NEFH variants modify ALS risk. METHODS: Genetic data of 11,130 people with ALS and 7,416 controls from the literature and Project MinE were analysed. We performed meta-analyses of published case-control studies reporting NEFH variants, and variant analysis of NEFH in Project MinE whole-genome sequencing data. RESULTS: Fixed-effects meta-analysis found that rare (MAF <1%) missense variants in the tail domain of NEFH increase ALS risk (OR 4.55, 95% CI 2.13-9.71, p < 0.0001). In Project MinE, ultrarare NEFH variants increased ALS risk (OR 1.37 95% CI 1.14-1.63, p = 0.0007), with rod domain variants (mostly intronic) appearing to drive the association (OR 1.45 95% CI 1.18-1.77, pMadsen-Browning = 0.0007, pSKAT-O = 0.003). While in the tail domain, ultrarare (MAF <0.1%) pathogenic missense variants were also associated with higher risk of ALS (OR 1.94, 95% CI 0.86-4.37, pMadsen-Browning = 0.039), supporting the meta-analysis results. Finally, several tail in-frame deletions were also found to affect disease risk, however, both protective and pathogenic deletions were found in this domain, highlighting an intricate architecture that requires further investigation. INTERPRETATION: We showed that NEFH tail missense and in-frame deletion variants, and intronic rod variants are risk factors for ALS. However, they are not variants of large effect, and their functional impact needs to be clarified in further studies. Therefore, their inclusion in routine genetic screening panels should be reconsidered.

Mechanism-free repurposing of drugs for C9orf72-related ALS/FTD using large-scale genomic data.

Repeat expansions in the C9orf72 gene are the most common genetic cause of (ALS) and frontotemporal dementia (FTD). Like other genetic forms of neurodegeneration, pinpointing the precise mechanism(s) by which this mutation leads to neuronal death remains elusive, and this lack of knowledge hampers the development of therapy for C9orf72-related disease. We used an agnostic approach based on genomic data (n = 41,273 ALS and healthy samples, and n = 1,516 C9orf72 carriers) to overcome these bottlenecks. Our drug-repurposing screen, based on gene- and expression-pattern matching and information about the genetic variants influencing onset age among C9orf72 carriers, identified acamprosate, a γ-aminobutyric acid analog, as a potentially repurposable treatment for patients carrying C9orf72 repeat expansions. We validated its neuroprotective effect in cell models and showed comparable efficacy to riluzole, the current standard of care. Our work highlights the potential value of genomics in repurposing drugs in situations where the underlying pathomechanisms are inherently complex. VIDEO ABSTRACT.

Non-motor symptoms in amyotrophic lateral sclerosis: lessons from Parkinson's disease.

Amyotrophic lateral sclerosis and Parkinson's disease are neurodegenerative diseases of the motor system which are now recognized also to affect non-motor pathways. Non-motor symptoms have been acknowledged as important determinants of quality of life in Parkinson's disease, and there is increasing interest in understanding the extent and role of non-motor symptoms in amyotrophic lateral sclerosis. We therefore reviewed what is known about non-motor symptoms in amyotrophic lateral sclerosis, using lessons from Parkinson's disease.

VariantSurvival: a tool to identify genotype-treatment response.

Motivation: For a number of neurological diseases, such as Alzheimer's disease, amyotrophic lateral sclerosis, and many others, certain genes are known to be involved in the disease mechanism. A common question is whether a structural variant in any such gene may be related to drug response in clinical trials and how this relationship can contribute to the lifecycle of drug development. Results: To this end, we introduce VariantSurvival, a tool that identifies changes in survival relative to structural variants within target genes. VariantSurvival matches annotated structural variants with genes that are clinically relevant to neurological diseases. A Cox regression model determines the change in survival between the placebo and clinical trial groups with respect to the number of structural variants in the drug target genes. We demonstrate the functionality of our approach with the exemplary case of the SETX gene. VariantSurvival has a user-friendly and lightweight graphical user interface built on the shiny web application package.

Harnessing Transcriptomic Signals for Amyotrophic Lateral Sclerosis to Identify Novel Drugs and Enhance Risk Prediction.

Introduction: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease. This study integrates the latest ALS genome-wide association study (GWAS) summary statistics with functional genomic annotations with the aim of providing mechanistic insights into ALS risk loci, inferring drug repurposing opportunities, and enhancing prediction of ALS risk and clinical characteristics. Methods: Genes associated with ALS were identified using GWAS summary statistic methodology including SuSiE SNP-based fine-mapping, and transcriptome- and proteome-wide association study (TWAS/PWAS) analyses. Using several approaches, gene associations were integrated with the DrugTargetor drug-gene interaction database to identify drugs that could be repurposed for the treatment of ALS. Furthermore, ALS gene associations from TWAS were combined with observed blood expression in two external ALS case-control datasets to calculate polytranscriptomic scores and evaluate their utility for prediction of ALS risk and clinical characteristics, including site of onset, age at onset, and survival. Results: SNP-based fine-mapping, TWAS and PWAS identified 117 genes associated with ALS, with TWAS and PWAS providing novel mechanistic insights. Drug repurposing analyses identified five drugs significantly enriched for interactions with ALS associated genes, with directional analyses highlighting α-glucosidase inhibitors may exacerbate ALS pathology. Additionally, drug class enrichment analysis showed calcium channel blockers may reduce ALS risk. Across the two observed expression target samples, ALS polytranscriptomic scores significantly predicted ALS risk (R2 = 4%; p-value = 2.1×10-21). Conclusions: Functionally-informed analyses of ALS GWAS summary statistics identified novel mechanistic insights into ALS aetiology, highlighted several therapeutic research avenues, and enabled statistically significant prediction of ALS risk.

Comparison Of King's Clinical Staging In Multinational Amyotrophic Lateral Sclerosis Cohorts.

Background: Amyotrophic lateral sclerosis (ALS) shows considerable clinical heterogeneity, which affects clinical trials. A clinical staging system has been proposed for ALS with potential applications in patient care, research, trial design and health economic analyses. The King's system consists of five stages. We have previously shown that progressive clinical stages were reached at predictable proportions through the disease course, but this needs to be validated in other independent samples. Objectives: We aimed to compare King's clinical staging in ALS in four patient groups, located in different regions and countries and using different health care systems from the original study population in South London. Methods: Clinical data were extracted from two European phase 3 randomized controlled trials (MitoTarget and LiCALS) and from two databases predominately from the United States: the PRO-ACT Consortium Database and a database of patients from the PatientsLikeMe website. Clinical stage was estimated using an algorithm, and standardized time to each clinical stage was calculated in deceased patients. Results: 8,796 patients were included, of whom 1,959 had died by the end of follow-up. Stages occurred in the same order as in the original study for all cohorts. Median standardized times to stages (interquartile range) were Stage 2: 0.61 (0.47-0.75), Stage 3: 0.68 (0.56-0.81), Stage 4A: 0.82 (0.71-0.91), Stage 4B: 0.82 (0.69-0.92) and Stage 4 0.80 (0.67-0.91). Discussion: Timings for all stages were similar to those reported in the original study, except Stage 2 which occurred later in the clinical trial databases due to recruitment occurring after diagnosis.