DGLinker: flexible knowledge-graph prediction of disease-gene associations

As a result of the advent of high-throughput technologies, there has been rapid progress in our understanding of the genetics underlying biological processes. However, despite such advances, the genetic landscape of human diseases has only marginally been disclosed. Exploiting the present availability of large amounts of biological and phenotypic data, we can use our current understanding of disease genetics to train machine learning models to predict novel genetic factors associated with the disease. To this end, we developed DGLinker, a webserver for the prediction of novel candidate genes for human diseases given a set of known disease genes. DGLinker has a user-friendly interface that allows non-expert users to exploit biomedical information from a wide range of biological and phenotypic databases, and/or to upload their own data, to generate a knowledge-graph and use machine learning to predict new disease-associated genes. The webserver includes tools to explore and interpret the results and generates publication-ready figures. DGLinker is available at https://dglinker.rosalind.kcl.ac.uk. The webserver is free and open to all users without the need for registration

Protocol for a double-blind randomised placebo-controlled trial of lithium carbonate in patients with amyotrophic lateral sclerosis (LiCALS) [Eudract number: 2008-006891-31].

BACKGROUND: Amyotrophic lateral sclerosis is a rapidly progressive neurodegenerative disorder characterised by loss of motor neurons leading to severe weakness and death from respiratory failure within 3-5 years. Riluzole prolongs survival in ALS. A published report has suggested a dramatic effect of lithium carbonate on survival. 44 patients were studied, with 16 randomly selected to take LiCO3 and riluzole and 28 allocated to take riluzole alone. In the group treated with lithium, no patients had died (i.e., 100% survival) at the end of the study (15 months from entry), compared to 71% surviving in the riluzole-only group. Although the trial can be criticised on several grounds, there is a substantial rationale from other laboratory studies that lithium is worth investigating therapeutically in amyotrophic lateral sclerosis. METHODS/DESIGN: LiCALS is a multi-centre double-blind randomised parallel group controlled trial of the efficacy, safety, and tolerability of lithium carbonate (LiCO3) at doses to achieve stable 'therapeutic' plasma levels (0.4-0.8 mmol/L), plus standard treatment, versus matched placebo plus standard treatment, in patients with amyotrophic lateral sclerosis. The study will be based in the UK, in partnership with the MND Association and DeNDRoN (the Dementias and Neurodegnerative Diseases Clinical Research Network). 220 patients will be recruited. All patients will be on the standard treatment for ALS of riluzole 100 mg daily. The primary outcome measure will be death from any cause at 18 months defined from the date of randomisation. Secondary outcome measures will be changes in three functional rating scales, the ALS Functional Rating Scale-Revised, The EuroQOL (EQ-5D), and the Hospital Anxiety and Depression Scale.Eligible patients will have El Escorial Possible, Laboratory-supported Probable, Probable or Definite amyotrophic lateral sclerosis with disease duration between 6 months and 36 months (inclusive), vital capacity ≥ 60% of predicted within 1 month prior to randomisation and age at least18 years. DISCUSSION: Patient recruitment began in June 2009 and the last patient is expected to complete the trial protocol in November 2011. TRIAL REGISTRATION: Current controlled trials ISRCTN83178718

Genotyping DNA pools on microarrays: Tackling the QTL problem of large samples and large numbers of SNPs

BACKGROUND: Quantitative trait locus (QTL) theory predicts that genetic influence on complex traits involves multiple genes of small effect size. To detect QTL associations of small effect size, large samples and systematic screens of thousands of DNA markers are required. An efficient solution is to genotype case and control DNA pools using SNP microarrays. We demonstrate that this is practical using DNA pools of 100 individuals. RESULTS: Using standard microarray protocols for the Affymetrix GeneChip(® )Mapping 10 K Array Xba 131, we show that relative allele signal (RAS) values provide a quantitative index of allele frequencies in pooled DNA that correlate 0.986 with allele frequencies for 104 SNPs that were genotyped individually for 100 individuals. The sensitivity of the assay was demonstrated empirically in a spiking experiment in which 15% and 20% of one individual's DNA was added to a DNA pool. CONCLUSION: We conclude that this approach, which we call SNP-MaP (SNP microarrays and pooling), is rapid, cost effective and promises to be a valuable initial screening method in the hunt for QTLs

Predicting the future of ALS: the impact of demographic change and potential new treatments on the prevalence of ALS in the United Kingdom, 2020-2116

OBJECTIVE To model the effects of demographic change under various scenarios of possible future treatment developments in ALS. METHODS Patients diagnosed with ALS at the King's College Hospital Motor Nerve Clinic between 2004 and 2017, and living within the London boroughs of Lambeth, Southwark, and Lewisham (LSL), were included as incident cases. We also ascertained incident cases from the Canterbury region over the same period. Future incidence of ALS was estimated by applying the calculated age- and sex-specific incidence rates to the UK population projections from 2020 to 2116. The number of prevalent cases for each future year was estimated based on an established method. Assuming constant incidence, we modelled four possible future prevalence scenarios by altering the median disease duration for varying subsets of the population, to represent the impact of new treatments. RESULTS The total number of people newly diagnosed with ALS per year in the UK is projected to rise from a baseline of 1415 UK cases in 2010 to 1701 in 2020 and 2635 in 2116. Overall prevalence of ALS was predicted to increase from 8.58 per 100,000 persons in 2020 to 9.67 per 100,000 persons in 2116. Halting disease progression in patients with C9orf72 mutations would yield the greatest impact of the modelled treatment scenarios, increasing prevalence in the year 2066 from a baseline of 9.50 per 100,000 persons to 15.68 per 100,000 persons. CONCLUSIONS Future developments in treatment would combine with the effects of demographic change to result in more people living longer with ALS

Infection of the Central Nervous System, Sepsis and Amyotrophic Lateral Sclerosis

Severe infections may lead to chronic inflammation in the central nervous system (CNS) which may in turn play a role in the etiopathogenesis of amyotrophic lateral sclerosis (ALS). The relentless progression and invasive supportive treatments of ALS may on the other hand induce severe infections among ALS patients.The present study included 4,004 ALS patients identified from the Swedish Patient Register during 1991-2007 and 20,020 age and sex matched general population controls. Conditional logistic regression was used to estimate the odds ratios (ORs) of ALS given a previous hospitalization for CNS infection or sepsis. Cox models were used to estimate the hazard ratios (HRs) of hospitalization for CNS infection or sepsis after ALS diagnosis. Overall, previous CNS infection (OR: 1.3, 95% confidence interval [CI]: 0.8, 2.4) or sepsis (OR: 1.2, 95% CI: 0.9, 1.6) was not associated with ALS risk. However, compared to ALS free individuals, ALS cases were more likely to be hospitalized for sepsis after diagnosis (HR: 2.6, 95% CI: 1.9, 3.5). We did not observe a higher risk of CNS infection after ALS diagnosis.Our results suggest that acute and severe infections unlikely contribute to the development of ALS; however, ALS patients are at a higher risk of sepsis after diagnosis, compared to ALS free individuals

The Heritability of Amyotrophic Lateral Sclerosis in a Clinically Ascertained United States Research Registry

The genetic basis of amyotrophic lateral sclerosis (ALS) is not entirely clear. While there are families with rare highly penetrant mutations in Cu/Zn superoxide dismutase 1 and several other genes that cause apparent Mendelian inheritance of the disease, most ALS occurs in families without another affected individual. However, twin studies suggest that all ALS has a substantial genetic basis. Herein, we estimate the genetic contribution to ALS in a clinically ascertained case series from the United States.We used the database of the Emory ALS Center to ascertain individuals with ALS along with their family histories to determine the concordance among parents and offspring for the disease. We found that concordance for all parent-offspring pairs was low (<2%). With this concordance we found that ALS heritability, or the proportion of the disease explained by genetic factors, is between 40 and 45% for all likely estimates of ALS lifetime prevalence.We found the lifetime risk of ALS is 1.1% in first-degree relatives of those with ALS. Environmental and genetic factors appear nearly equally important for the development of ALS

Latent cluster analysis of ALS phenotypes identifies prognostically differing groups

BACKGROUND Amyotrophic lateral sclerosis (ALS) is a degenerative disease predominantly affecting motor neurons and manifesting as several different phenotypes. Whether these phenotypes correspond to different underlying disease processes is unknown. We used latent cluster analysis to identify groupings of clinical variables in an objective and unbiased way to improve phenotyping for clinical and research purposes. METHODS Latent class cluster analysis was applied to a large database consisting of 1467 records of people with ALS, using discrete variables which can be readily determined at the first clinic appointment. The model was tested for clinical relevance by survival analysis of the phenotypic groupings using the Kaplan-Meier method. RESULTS The best model generated five distinct phenotypic classes that strongly predicted survival (p<0.0001). Eight variables were used for the latent class analysis, but a good estimate of the classification could be obtained using just two variables: site of first symptoms (bulbar or limb) and time from symptom onset to diagnosis (p<0.00001). CONCLUSION The five phenotypic classes identified using latent cluster analysis can predict prognosis. They could be used to stratify patients recruited into clinical trials and generating more homogeneous disease groups for genetic, proteomic and risk factor research

The risk to relatives of patients with sporadic amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis is a neurodegenerative disease of motor neurons with a median survival of 2 years. Most patients have no family history of amyotrophic lateral sclerosis, but current understanding of such diseases suggests there should be an increased risk to relatives. Furthermore, it is a common question to be asked by patients and relatives in clinic. We therefore set out to determine the risk of amyotrophic lateral sclerosis to first degree relatives of patients with sporadic amyotrophic lateral sclerosis attending a specialist clinic. Case records of patients with sporadic amyotrophic lateral sclerosis seen at a tertiary referral centre over a 16-year period were reviewed, and pedigree structures extracted. All individuals who had originally presented with sporadic amyotrophic lateral sclerosis, but who subsequently had an affected first degree relative, were identified. Calculations were age-adjusted using clinic population demographics. Probands (n = 1502), full siblings (n = 1622) and full offspring (n = 1545) were identified. Eight of the siblings and 18 offspring had developed amyotrophic lateral sclerosis. The unadjusted risk of amyotrophic lateral sclerosis over the observation period was 0.5% for siblings and 1.0% for offspring. Age information was available for 476 siblings and 824 offspring. For this subset, the crude incidence of amyotrophic lateral sclerosis was 0.11% per year (0.05–0.21%) in siblings and 0.11% per year (0.06–0.19%) in offspring, and the clinic age-adjusted incidence rate was 0.12% per year (0.04–0.21%) in siblings. By age 85, siblings were found to have an 8-fold increased risk of amyotrophic lateral sclerosis, in comparison to the background population. In practice, this means the risk of remaining unaffected by age 85 dropped from 99.7% to 97.6%. Relatives of people with sporadic amyotrophic lateral sclerosis have a small but definite increased risk of being affected

TRICALS: creating a highway toward a cure

A change in our current approach toward drug development is required to improve the likelihood of finding effective treatment for patients with amyotrophic lateral sclerosis (ALS). The aim of the Treatment Research Initiative to Cure ALS (TRICALS) is to extend the collective effort with industry and consolidate drug development paths. TRICALS has begun a series of meetings on how to best move the field forward collaboratively, thereby addressing five major topics in ALS clinical trials: (1) preclinical research, (2) biomarker development, (3) eligibility criteria, (4) efficacy endpoints and (5) innovative trial design. There is an appetite for ongoing discussions of these major topics in clinical trials between representatives from academia, patient advocacy groups, industry partners and funding bodies. Industry is open to fundamentally change drug development for ALS and shorten the time to effective therapy for patients by implementing promising innovations in biomarker development, trial design, and patient selection. There is however, a pressing need from all stakeholders for regulatory discussions and amendments of current guidelines to successfully adopt innovation in future clinical development lines