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

Morgan, Sarah; Shatunov, Aleksey; Sproviero, William; Jones, Ashley; Shoai, Maryam; Hughes, Deborah; Khleifat, Ahmad Al; Malaspina, Andrea; Morrison, Karen; Shaw, Pamela J.; Shaw, Christopher E.; Sidle, Katie; Orrell, Richard W.; Fratta, Pietro; Hardy, John; Pittman, Alan; Al‐Chalabi, Ammar

doi:10.1093/brain/awx082

Cited by 79 publications

(64 citation statements)

References 39 publications

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“…After reading the full text, we excluded 20 out of 34 studies clearly not meeting our inclusion criteria (Table ). Finally, 14 papers 35‐48 met the inclusion criteria and were included in our evaluation (Figure 1). Of the selected papers, only 2 studies 39,48 aimed to evaluate the primary research question of determining whether NGS is more accurate than Sanger sequencing to identify pathological mutations of ALS‐associated genes.…”

Section: Resultsmentioning

confidence: 99%

“…At baseline, age of onset ranged from 18 to 87 years, and site of onset was bulbar for 245 (10.5%) patients, spinal for 675 (29%) patients, with these data being unspecified for the remaining 60.5% of patients. Seven studies 36,40,41,43‐45,47 analysed also healthy samples as control. Characteristics of included studies are summarized in Table 1.…”

Section: Resultsmentioning

confidence: 99%

“…In the first study, 35 there were no false positive results; in the second one, 44 the false positive rate was 26.4%. Finally, five studies 35,37,39,43,44 evaluated the oligogenic features of the disease and reported that 37 out 1,880 patients (2%) harboured 2 or more potentially pathological mutations.…”

Section: Resultsmentioning

confidence: 99%

“…In 13 studies, 35‐47 NGS allowed to identify already known mutations in 21 genes, and new or rare variants in 27 genes (Figure 3). Identified variants were nonsense or missense mutations leading to a frameshift mutation resulting in a truncated protein and a loss of protein function.…”

Section: Resultsmentioning

confidence: 99%

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The NGS technology for the identification of genes associated with the ALS. A systematic review

Pecoraro

Mandrioli

Carone

et al. 2020

Eur J Clin Investigation

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Background: More than 30 causative genes have been identified in familial and sporadic amyotrophic lateral sclerosis (ALS). The next-generation sequencing (NGS) is a powerful and groundbreaking tool to identify disease-associated variants. Despite documented advantages of NGS, its diagnostic reliability needs to be addressed in order to use this technology for specific routine diagnosis. Material and Methods: Literature database was explored to identify studies comparing NGS and Sanger sequencing for the detection of variants causing ALS. We collected data about patients' characteristics, disease type and duration, NGS and Sanger properties. Results: More than 200 bibliographic references were identified, of which only 14 studies matching our inclusion criteria. Only 2 out of 14 studies compared results of NGS analysis with the Sanger sequencing. Twelve studies screened causative genes associated to ALS using NGS technologies and confirmed the identified variants with Sanger sequencing. Overall, data about more 2,000 patients were analysed. The number of genes that were investigated in each study ranged from 1 to 32, the most frequent being FUS, OPTN, SETX and VCP. NGS identified already known mutations in 21 genes, and new or rare variants in 27 genes. Conclusions: NGS seems to be a promising tool for the diagnosis of ALS in routine clinical practice. Its advantages are represented by an increased speed and a lowest sequencing cost, but patients' counselling could be problematic due to the discovery of frequent variants of unknown significance. K E Y W O R D S amyothrophic lateral sclerosis, evidence, gene detection, next-generation sequencing, systematic review 2 of 16 | PECORARO Et Al. 4 of 16 | PECORARO Et Al.duration, site of onset); (d) characteristics of NGS technologies; (e) investigated outcomes as defined above.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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The NGS technology for the identification of genes associated with the ALS. A systematic review

Pecoraro

Mandrioli

Carone

et al. 2020

Eur J Clin Investigation

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“…Using DNAscan in Fast mode, we analysed real DNA sequence data from two ALS patients (case A and case B). Case A carries a non-synonymous mutation in the FUS gene [46] (variant C1561T, AA change R521C, variant dbSNP id rs121909670 [47]) known to be a cause of ALS (ClinVar id RCV000017609.27,RCV000017611.25). Case B is a confirmed C9orf72 expansion carrier (see Methods), this repeat expansion is known to be strongly associated with ALS [48].…”

Section: Als Miseq and Whole-genome-seq Test Casesmentioning

confidence: 99%

DNAscan: a fast, computationally and memory efficient bioinformatics pipeline for the analysis of DNA next-generation-sequencing data

Iacoangeli

Khleifat

Sproviero

et al. 2018

Preprint

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The generation of DNA Next Generation Sequencing (NGS) data is a commonly applied approach for studying the genetic basis of biological processes, including diseases, and underpins the aspirations of precision medicine. However, there are significant challenges when dealing with NGS data. A huge number of bioinformatics tools exist and it is therefore challenging to design an analysis pipeline; NGS analysis is computationally intensive, requiring expensive infrastructure which can be problematic given that many medical and research centres do not have adequate high performance computing facilities and the use of cloud computing facilities is not always possible due to privacy and ownership issues. We have therefore developed a fast and efficient bioinformatics pipeline that allows for the analysis of DNA sequencing data, while requiring little computational effort and memory usage. We achieved this by exploiting state-of-the-art bioinformatics tools. DNAscan can analyse raw, 40x whole genome NGS data in 8 hours, using as little as 8 threads and 16 Gbs of RAM, while guaranteeing a high performance. DNAscan can look for SNVs, small indels, SVs, repeat expansions and viral genetic material (or any other organism). Its results are annotated using a customisable variety of databases including ClinVar, Exac and dbSNP, and a local deployment of the gene.iobio platform is available for an on-the-fly result visualisation.

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Genetic Basis of ALS

Ross

Rouleau

2021

Spectrums of Amyotrophic Lateral Sclerosis

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

Cited by 79 publications

References 39 publications

The NGS technology for the identification of genes associated with the ALS. A systematic review

The NGS technology for the identification of genes associated with the ALS. A systematic review

DNAscan: a fast, computationally and memory efficient bioinformatics pipeline for the analysis of DNA next-generation-sequencing data

Genetic Basis of ALS

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