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

Superoxide dismutase (SOD1) gene variants may cause amyotrophic lateral sclerosis, some of which are associated with a distinct phenotype. Most studies assess limited variants or sample sizes. In this international, retrospective observational study, we compare phenotypic and demographic characteristics between people with SOD1-ALS and people with ALS and no recorded SOD1 variant. We investigate which variants are associated with age at symptom onset and time from onset to death or censoring using Cox proportional-hazards regression. The SOD1-ALS dataset reports age of onset for 1122 and disease duration for 883 people; the comparator population includes 10,214 and 9010 people respectively. Eight variants are associated with younger age of onset and distinct survival trajectories; a further eight associated with younger onset only and one with distinct survival only. Here we show that onset and survival are decoupled in SOD1-ALS. Future research should characterise rarer variants and molecular mechanisms causing the observed variability.

Development of a Smartphone App for a Genetics Website: The Amyotrophic Lateral Sclerosis Online Genetics Database (ALSoD)

Background

The ALS Online Genetics Database (ALSoD) website holds mutation, geographical, and phenotype data on genes implicated in amyotrophic lateral sclerosis (ALS) and links to bioinformatics resources, publications, and tools for analysis. On average, there are 300 unique visits per day, suggesting a high demand from the research community. To enable wider access, we developed a mobile-friendly version of the website and a smartphone app.

Objective

We sought to compare data traffic before and after implementation of a mobile version of the website to assess utility.

Methods

We identified the most frequently viewed pages using Google Analytics and our in-house analytic monitoring. For these, we optimized the content layout of the screen, reduced image sizes, and summarized available information. We used the Microsoft .NET framework mobile detection property (HttpRequest.IsMobileDevice in the Request.Browser object in conjunction with HttpRequest.UserAgent), which returns a true value if the browser is a recognized mobile device. For app development, we used the Eclipse integrated development environment with Android plug-ins. We wrapped the mobile website version with the WebView object in Android. Simulators were downloaded to test and debug the applications.

Results

The website automatically detects access from a mobile phone and redirects pages to fit the smaller screen. Because the amount of data stored on ALSoD is very large, the available information for display using smartphone access is deliberately restricted to improve usability. Visits to the website increased from 2231 to 2820, yielding a 26% increase from the pre-mobile to post-mobile period and an increase from 103 to 340 visits (230%) using mobile devices (including tablets). The smartphone app is currently available on BlackBerry and Android devices and will be available shortly on iOS as well.

Conclusions

Further development of the ALSoD website has allowed access through smartphones and tablets, either through the website or directly through a mobile app, making genetic data stored on the database readily accessible to researchers and patients across multiple devices.

Residual association at C9orf72 suggests an alternative amyotrophic lateral sclerosis-causing hexanucleotide repeat

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease of motor neurons. Single-nucleotide polymorphism rs3849942 is associated with ALS, tagging a hexanucleotide repeat mutation in the C9orf72 gene. It is possible that there is more than 1 disease-causing genetic variation at this locus, in which case association might remain after removal of cases carrying the mutation. DNA from patients with ALS was therefore tested for the mutation. Genome-wide association testing was performed first using all samples, and then restricting the analysis to samples not carrying the mutation. rs3849942 and rs903603 were strongly associated with ALS when all samples were included (rs3849942, p = [3 × 2] × 10(-6), rank 7/442,057; rs903603, p = [7 × 6] × 10(-8), rank 2/442,057). Removal of the mutation-carrying cases resulted in loss of association for rs3849942 (p = [2 × 6] × 10(-3), rank 1225/442,068), but had little effect on rs903603 (p = [1 × 9] × 10(-5), rank 8/442,068). Those with a risk allele of rs903603 had an excess of apparent homozygosity for wild type repeat alleles, consistent with polymerase chain reaction failure of 1 allele because of massive repeat expansion. These results indicate residual association at the C9orf72 locus suggesting a second disease-causing repeat mutation.

Credibility analysis of putative disease-causing genes using bioinformatics

Background

Genetic studies are challenging in many complex diseases, particularly those with limited diagnostic certainty, low prevalence or of old age. The result is that genes may be reported as disease-causing with varying levels of evidence, and in some cases, the data may be so limited as to be indistinguishable from chance findings. When there are large numbers of such genes, an objective method for ranking the evidence is useful. Using the neurodegenerative and complex disease amyotrophic lateral sclerosis (ALS) as a model, and the disease-specific database ALSoD, the objective is to develop a method using publicly available data to generate a credibility score for putative disease-causing genes.

Methods

Genes with at least one publication suggesting involvement in adult onset familial ALS were collated following an exhaustive literature search. SQL was used to generate a score by extracting information from the publications and combined with a pathogenicity analysis using bioinformatics tools. The resulting score allowed us to rank genes in order of credibility. To validate the method, we compared the objective ranking with a rank generated by ALS genetics experts. Spearman's Rho was used to compare rankings generated by the different methods.

Results

The automated method ranked ALS genes in the following order: SOD1, TARDBP, FUS, ANG, SPG11, NEFH, OPTN, ALS2, SETX, FIG4, VAPB, DCTN1, TAF15, VCP, DAO. This compared very well to the ranking of ALS genetics experts, with Spearman's Rho of 0.69 (P = 0.009).

Conclusion

We have presented an automated method for scoring the level of evidence for a gene being disease-causing. In developing the method we have used the model disease ALS, but it could equally be applied to any disease in which there is genotypic uncertainty.

ALSoD: A user-friendly online bioinformatics tool for amyotrophic lateral sclerosis genetics

Amyotrophic lateral sclerosis (ALS) is the commonest adult onset motor neuron disease, with a peak age of onset in the seventh decade. With advances in genetic technology, there is an enormous increase in the volume of genetic data produced, and a corresponding need for storage, analysis, and interpretation, particularly as our understanding of the relationships between genotype and phenotype mature. Here, we present a system to enable this in the form of the ALS Online Database (ALSoD at http://alsod.iop.kcl.ac.uk), a freely available database that has been transformed from a single gene storage facility recording mutations in the SOD1 gene to a multigene ALS bioinformatics repository and analytical instrument combining genotype, phenotype, and geographical information with associated analysis tools. These include a comparison tool to evaluate genes side by side or jointly with user configurable features, a pathogenicity prediction tool using a combination of computational approaches to distinguish variants with nonfunctional characteristics from disease-associated mutations with more dangerous consequences, and a credibility tool to enable ALS researchers to objectively assess the evidence for gene causation in ALS. Furthermore, integration of external tools, systems for feedback, annotation by users, and two-way links to collaborators hosting complementary databases further enhance the functionality of ALSoD.

Keeping up with genetic discoveries in amyotrophic lateral sclerosis: the ALSoD and ALSGene databases

Amyotrophic lateral sclerosis (ALS) is a genetically heterogeneous disorder that shows a characteristic dichotomy of familial forms typically displaying Mendelian inheritance patterns, and sporadic ALS showing no or less obvious familial aggregation. While the former is caused by rare, highly penetrant, and pathogenic mutations, risk for sporadic ALS is probably the result of the combined effects of common polymorphisms with minor to moderate effect sizes. Owing to recent advances in high-throughput genotyping and sequencing technologies, genetic research in both fields is evolving at a rapidly increasing pace making it more and more difficult to follow and evaluate the most significant progress in the field. To alleviate this problem, our groups have created dedicated and freely available online databases, ALSoD ( http://alsod.iop.kcl.ac.uk/ ) and ALSGene ( http://www.alsgene.org ), which provide systematic and in-depth qualitative and quantitative overviews of genetic research in both familial and sporadic ALS. This review briefly introduces the background and main features of both databases and provides an overview of the currently most compelling genetic findings in ALS derived from analyses using these resources.

Chromosome 9p21 in sporadic amyotrophic lateral sclerosis in the UK and seven other countries: a genome-wide association study

Background

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease of motor neurons that results in progressive weakness and death from respiratory failure, commonly within about 3 years. Previous studies have shown association of a locus on chromosome 9p with ALS and linkage with ALS–frontotemporal dementia. We aimed to test whether this genomic region is also associated with ALS in an independent set of UK samples, and to identify risk factors associated with ALS in a further genome-wide association study that combined data from the independent analysis with those from other countries.

Methods

We collected samples from patients with sporadic ALS from 20 UK hospitals and obtained UK control samples from the control groups of the Depression Case Control study, the Bipolar Affective Case Control Study, and the British 1958 birth cohort DNA collection. Genotyping of DNA in this independent analysis was done with Illumina HumanHap550 BeadChips. We then undertook a joint genome-wide analysis that combined data from the independent set with published data from the UK, USA, Netherlands, Ireland, Italy, France, Sweden, and Belgium. The threshold for significance was p=0·05 in the independent analysis, because we were interested in replicating a small number of previously reported associations, whereas the Bonferroni-corrected threshold for significance in the joint analysis was p=2·20×10⁻⁷

Findings

After quality control, samples were available from 599 patients and 4144 control individuals in the independent set. In this analysis, two single nucleotide polymorphisms in a locus on chromosome 9p21.2 were associated with ALS: rs3849942 (p=2·22×10⁻⁶; odds ratio [OR] 1·39, 95% CI 1·21–1·59) and rs2814707 (p=3·32×10⁻⁶; 1·38, 1·20–1·58). In the joint analysis, which included samples from 4312 patients with ALS and 8425 control individuals, rs3849942 (p=4·64×10⁻¹⁰; OR 1·22, 95% CI 1·15–1·30) and rs2814707 (p=4·72×10⁻¹⁰; 1·22, 1·15–1·30) were associated with ALS.

Interpretation

We have found strong evidence of a genetic association of two single nucleotide polymorphisms on chromosome 9 with sporadic ALS, in line with findings from previous independent GWAS of ALS and linkage studies of ALS–frontotemporal dementia. Our findings together with these earlier findings suggest that genetic variation at this locus on chromosome 9 causes sporadic ALS and familial ALS–frontotemporal dementia. Resequencing studies and then functional analysis should be done to identify the defective gene.

Funding

ALS Therapy Alliance, the Angel Fund, the Medical Research Council, the Motor Neurone Disease Association of Great Britain and Northern Ireland, the Wellcome Trust, and the National Institute for Health Research Dementias and Neurodegenerative Diseases Research Network (DeNDRoN).