TDP-43 Is Not a Common Cause of Sporadic Amyotrophic Lateral Sclerosis

Background: TAR DNA binding protein, encoded by TARDBP, was shown to be a central component of ubiquitin-positive, tau-negative inclusions in frontotemporal lobar degeneration (FTLD-U) and amyotrophic lateral sclerosis (ALS). Recently, mutations in TARDBP have been linked to familial and sporadic ALS.Methodology/Principal Findings: To further examine the frequency of mutations in TARDBP in sporadic ALS, 279 ALS cases and 806 neurologically normal control individuals of European descent were screened for sequence variants, copy number variants, genetic and haplotype association with disease. An additional 173 African samples from the Human Gene Diversity Panel were sequenced as this population had the highest likelihood of finding changes. No mutations were found in the ALS cases. Several genetic variants were identified in controls, which were considered as non-pathogenic changes. Furthermore, pathogenic structural variants were not observed in the cases and there was no genetic or haplotype association with disease status across the TARDBP locus.Conclusions: Our data indicate that genetic variation in TARDBP is not a common cause of sporadic ALS in North American

Generating samples for association studies based on HapMap data

<p>Abstract</p> <p>Background</p> <p>With the completion of the HapMap project, a variety of computational algorithms and tools have been proposed for haplotype inference, tag SNP selection and genome-wide association studies. Simulated data are commonly used in evaluating these new developed approaches. In addition to simulations based on population models, empirical data generated by perturbing real data, has also been used because it may inherit specific properties from real data. However, there is no tool that is publicly available to generate large scale simulated variation data by taking into account knowledge from the HapMap project.</p> <p>Results</p> <p>A computer program (<it>gs</it>) was developed to quickly generate a large number of samples based on real data that are useful for a variety of purposes, including evaluating methods for haplotype inference, tag SNP selection and association studies. Two approaches have been implemented to generate dense SNP haplotype/genotype data that share similar local <it>linkage disequilibrium </it>(LD) patterns as those in human populations. The first approach takes haplotype pairs from samples as inputs, and the second approach takes patterns of haplotype block structures as inputs. Both quantitative and qualitative traits have been incorporated in the program. Phenotypes are generated based on a disease model, or based on the effect of a quantitative trait nucleotide, both of which can be specified by users. In addition to single-locus disease models, two-locus disease models have also been implemented that can incorporate any degree of epistasis. Users are allowed to specify all nine parameters in a 3 × 3 penetrance table. For several commonly used two-locus disease models, the program can automatically calculate penetrances based on the population prevalence and marginal effects of a disease that users can conveniently specify.</p> <p>Conclusion</p> <p>The program <it>gs </it>can effectively generate large scale genetic and phenotypic variation data that can be used for evaluating new developed approaches. It is freely available from the authors' web site at <url>http://www.eecs.case.edu/~jxl175/gs.html</url>.</p

New application of intelligent agents in sporadic amyotrophic lateral sclerosis identifies unexpected specific genetic background

<p>Abstract</p> <p>Background</p> <p>Few genetic factors predisposing to the sporadic form of amyotrophic lateral sclerosis (ALS) have been identified, but the pathology itself seems to be a true multifactorial disease in which complex interactions between environmental and genetic susceptibility factors take place. The purpose of this study was to approach genetic data with an innovative statistical method such as artificial neural networks to identify a possible genetic background predisposing to the disease. A DNA multiarray panel was applied to genotype more than 60 polymorphisms within 35 genes selected from pathways of lipid and homocysteine metabolism, regulation of blood pressure, coagulation, inflammation, cellular adhesion and matrix integrity, in 54 sporadic ALS patients and 208 controls. Advanced intelligent systems based on novel coupling of artificial neural networks and evolutionary algorithms have been applied. The results obtained have been compared with those derived from the use of standard neural networks and classical statistical analysis</p> <p>Results</p> <p>Advanced intelligent systems based on novel coupling of artificial neural networks and evolutionary algorithms have been applied. The results obtained have been compared with those derived from the use of standard neural networks and classical statistical analysis. An unexpected discovery of a strong genetic background in sporadic ALS using a DNA multiarray panel and analytical processing of the data with advanced artificial neural networks was found. The predictive accuracy obtained with Linear Discriminant Analysis and Standard Artificial Neural Networks ranged from 70% to 79% (average 75.31%) and from 69.1 to 86.2% (average 76.6%) respectively. The corresponding value obtained with Advanced Intelligent Systems reached an average of 96.0% (range 94.4 to 97.6%). This latter approach allowed the identification of seven genetic variants essential to differentiate cases from controls: apolipoprotein E arg158cys; hepatic lipase -480 C/T; endothelial nitric oxide synthase 690 C/T and glu298asp; vitamin K-dependent coagulation factor seven arg353glu, glycoprotein Ia/IIa 873 G/A and E-selectin ser128arg.</p> <p>Conclusion</p> <p>This study provides an alternative and reliable method to approach complex diseases. Indeed, the application of a novel artificial intelligence-based method offers a new insight into genetic markers of sporadic ALS pointing out the existence of a strong genetic background.</p

TDP-43 Is Not a Common Cause of Sporadic Amyotrophic Lateral Sclerosis

Background: TAR DNA binding protein, encoded by TARDBP, was shown to be a central component of ubiquitin-positive, tau-negative inclusions in frontotemporal lobar degeneration (FTLD-U) and amyotrophic lateral sclerosis (ALS). Recently, mutations in TARDBP have been linked to familial and sporadic ALS. Methodology/Principal Findings: To further examine the frequency of mutations in TARDBP in sporadic ALS, 279 ALS cases and 806 neurologically normal control individuals of European descent were screened for sequence variants, copy number variants, genetic and haplotype association with disease. An additional 173 African samples from the Human Gene Diversity Panel were sequenced as this population had the highest likelihood of finding changes. No mutations were found in the ALS cases. Several genetic variants were identified in controls, which were considered as non-pathogenic changes. Furthermore, pathogenic structural variants were not observed in the cases and there was no genetic or haplotype association with disease status across the TARDBP locus

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

Genome-wide association reveals three SNPs associated with sporadic amyotrophic lateral sclerosis through a two-locus analysis

<p>Abstract</p> <p>Background</p> <p>Amyotrophic lateral sclerosis (ALS) is a fatal, degenerative neuromuscular disease characterized by a progressive loss of voluntary motor activity. About 95% of ALS patients are in "sporadic form"-meaning their disease is not associated with a family history of the disease. To date, the genetic factors of the sporadic form of ALS are poorly understood.</p> <p>Methods</p> <p>We proposed a two-stage approach based on seventeen biological plausible models to search for two-locus combinations that have significant joint effects to the disease in a genome-wide association study (GWAS). We used a two-stage strategy to reduce the computational burden associated with performing an exhaustive two-locus search across the genome. In the first stage, all SNPs were screened using a single-marker test. In the second stage, all pairs made from the 1000 SNPs with the lowest p-values from the first stage were evaluated under each of the 17 two-locus models.</p> <p>Results</p> <p>we performed the two-stage approach on a GWAS data set of sporadic ALS from the SNP Database at the NINDS Human Genetics Resource Center DNA and Cell Line Repository <url>http://ccr.coriell.org/ninds/</url>. Our two-locus analysis showed that two two-locus combinations--rs4363506 (SNP1) and rs3733242 (SNP2), and rs4363506 and rs16984239 (SNP3) -- were significantly associated with sporadic ALS. After adjusting for multiple tests and multiple models, the combination of SNP1 and SNP2 had a p-value of 0.032 under the Dom∩Dom epistatic model; SNP1 and SNP3 had a p-value of 0.042 under the Dom × Dom multiplicative model.</p> <p>Conclusion</p> <p>The proposed two-stage analytical method can be used to search for joint effects of genes in GWAS. The two-stage strategy decreased the computational time and the multiple testing burdens associated with GWAS. We have also observed that the loci identified by our two-stage strategy can not be detected by single-locus tests.</p

Daf-2 Signaling Modifies Mutant SOD1 Toxicity in C. elegans

The DAF-2 Insulin/IGF-1 signaling (IIS) pathway is a strong modifier of Caenorhabditis elegans longevity and healthspan. As aging is the greatest risk factor for developing neurodegenerative diseases such as Amyotrophic Lateral Sclerosis (ALS), we were interested in determining if DAF-2 signaling modifies disease pathology in mutant superoxide dismutase 1 (SOD1) expressing C. elegans. Worms with pan-neuronal G85R SOD1 expression demonstrate significantly impaired locomotion as compared to WT SOD1 expressing controls and they develop insoluble SOD1 aggregates. Reductions in DAF-2 signaling, either through a hypomorphic allele or neuronally targeted RNAi, decreases the abundance of aggregated SOD1 and results in improved locomotion in a DAF-16 dependant manner. These results suggest that manipulation of the DAF-2 Insulin/IGF-1 signaling pathway may have therapeutic potential for the treatment of ALS

Disease-Related Changes in the Cerebrospinal Fluid Metabolome in Amyotrophic Lateral Sclerosis Detected by GC/TOFMS

The changes in the cerebrospinal fluid (CSF) metabolome associated with the fatal neurodegenerative disease amyotrophic lateral sclerosis (ALS) are poorly understood and earlier smaller studies have shown conflicting results. The metabolomic methodology is suitable for screening large cohorts of samples. Global metabolomics can be used for detecting changes of metabolite concentrations in samples of fluids such as CSF.Using gas chromatography coupled to mass spectrometry (GC/TOFMS) and multivariate statistical modeling, we simultaneously studied the metabolome signature of ∼120 small metabolites in the CSF of patients with ALS, stratified according to hereditary disposition and clinical subtypes of ALS in relation to controls.The study is the first to report data validated over two sub-sets of ALS vs. control patients for a large set of metabolites analyzed by GC/TOFMS. We find that patients with sporadic amyotrophic lateral sclerosis (SALS) have a heterogeneous metabolite signature in the cerebrospinal fluid, in some patients being almost identical to controls. However, familial amyotrophic lateral sclerosis (FALS) without superoxide dismutase-1 gene (SOD1) mutation is less heterogeneous than SALS. The metabolome of the cerebrospinal fluid of 17 ALS patients with a SOD1 gene mutation was found to form a separate homogeneous group. Analysis of metabolites revealed that glutamate and glutamine were reduced, in particular in patients with a familial predisposition. There are significant differences in the metabolite profile and composition among patients with FALS, SALS and patients carrying a mutation in the SOD1 gene suggesting that the neurodegenerative process in different subtypes of ALS may be partially dissimilar.Patients with a genetic predisposition to amyotrophic lateral sclerosis have a more distinct and homogeneous signature than patients with a sporadic disease

A High-Density Genome-Wide Association Screen of Sporadic ALS in US Veterans

Following reports of an increased incidence of amyotrophic lateral sclerosis (ALS) in U.S. veterans, we have conducted a high-density genome-wide association study (GWAS) of ALS outcome and survival time in a sample of U.S. veterans. We tested ∼1.3 million single nucleotide polymorphisms (SNPs) for association with ALS outcome in 442 incident Caucasian veteran cases diagnosed with definite or probable ALS and 348 Caucasian veteran controls. To increase power, we also included genotypes from 5909 publicly-available non-veteran controls in the analysis. In the survival analysis, we tested for association between SNPs and post-diagnosis survival time in 639 Caucasian veteran cases with definite or probable ALS. After this discovery phase, we performed follow-up genotyping of 299 SNPs in an independent replication sample of Caucasian veterans and non-veterans (ALS outcome: 183 cases and 961 controls; survival: 118 cases). Although no SNPs reached genome-wide significance in the discovery phase for either phenotype, three SNPs were statistically significant in the replication analysis of ALS outcome: rs6080539 (177 kb from PCSK2), rs7000234 (4 kb from ZNF704), and rs3113494 (13 kb from LOC100506746). Two SNPs located in genes that were implicated by previous GWA studies of ALS were marginally significant in the pooled analysis of discovery and replication samples: rs17174381 in DPP6 (p = 4.4×10−4) and rs6985069 near ELP3 (p = 4.8×10−4). Our results underscore the difficulty of identifying and convincingly replicating genetic associations with a rare and genetically heterogeneous disorder such as ALS, and suggest that common SNPs are unlikely to account for a substantial proportion of patients affected by this devastating disorder