Genome-wide genotyping in amyotrophic lateral sclerosis and neurologically normal controls: first stage analysis and public release of data

Genomic and transcriptomic advances in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder and the most common motor neuron disease. ALS shows substantial clinical and molecular heterogeneity. In vitro and in vivo models coupled with multiomic techniques have provided important contributions to unraveling the pathomechanisms underlying ALS. To date, despite promising results and accumulating knowledge, an effective treatment is still lacking. Here, we provide an overview of the literature on the use of genomics, epigenomics, transcriptomics and microRNAs to deeply investigate the molecular mechanisms developing and sustaining ALS. We report the most relevant genes implicated in ALS pathogenesis, discussing the use of different high-throughput sequencing techniques and the role of epigenomic modifications. Furthermore, we present transcriptomic studies discussing the most recent advances, from microarrays to bulk and single-cell RNA sequencing. Finally, we discuss the use of microRNAs as potential biomarkers and promising tools for molecular intervention. The integration of data from multiple omic approaches may provide new insights into pathogenic pathways in ALS by shedding light on diagnostic and prognostic biomarkers, helping to stratify patients into clinically relevant subgroups, revealing novel therapeutic targets and supporting the development of new effective therapies.

Rare variant association on unrelated individuals in case-control studies using aggregation tests: existing methods and current limitations

Over the past years, progress made in next-generation sequencing technologies and bioinformatics have sparked a surge in association studies. Especially, genome-wide association studies (GWASs) have demonstrated their effectiveness in identifying disease associations with common genetic variants. Yet, rare variants can contribute to additional disease risk or trait heterogeneity. Because GWASs are underpowered for detecting association with such variants, numerous statistical methods have been recently proposed. Aggregation tests collapse multiple rare variants within a genetic region (e.g. gene, gene set, genomic loci) to test for association. An increasing number of studies using such methods successfully identified trait-associated rare variants and led to a better understanding of the underlying disease mechanism. In this review, we compare existing aggregation tests, their statistical features and scope of application, splitting them into the five classical classes: burden, adaptive burden, variance-component, omnibus and other. Finally, we describe some limitations of current aggregation tests, highlighting potential direction for further investigations.

Amyotrophic lateral sclerosis: translating genetic discoveries into therapies

Recent advances in sequencing technologies and collaborative efforts have led to substantial progress in identifying the genetic causes of amyotrophic lateral sclerosis (ALS). This momentum has, in turn, fostered the development of putative molecular therapies. In this Review, we outline the current genetic knowledge, emphasizing recent discoveries and emerging concepts such as the implication of distinct types of mutation, variability in mutated genes in diverse genetic ancestries and gene-environment interactions. We also propose a high-level model to synthesize the interdependent effects of genetics, environmental and lifestyle factors, and ageing into a unified theory of ALS. Furthermore, we summarize the current status of therapies developed on the basis of genetic knowledge established for ALS over the past 30 years, and we discuss how developing treatments for ALS will advance our understanding of targeting other neurological diseases.

Genome-Wide Gene-Set Analysis Approaches in Amyotrophic Lateral Sclerosis

The rapid increase in the number of genetic variants identified to be associated with Amyotrophic Lateral Sclerosis (ALS) through genome-wide association studies (GWAS) has created an emerging need to understand the functional pathways that are implicated in the pathology of ALS. Gene-set analysis (GSA) is a powerful method that can provide insight into the associated biological pathways, determining the joint effect of multiple genetic markers. The main contribution of this review is the collection of ALS GSA studies that employ GWAS or individual-based genotype data, investigating their methodology and results related to ALS-associated molecular pathways. Furthermore, the limitations in standard single-gene analyses are summarized, highlighting the power of gene-set analysis, and a brief overview of the statistical properties of gene-set analysis and related concepts is provided. The main aims of this review are to investigate the reproducibility of the collected studies and identify their strengths and limitations, in order to enhance the experimental design and therefore the quality of the results of future studies, deepening our understanding of this devastating disease.

Selecting Genetic Variants and Interactions Associated with Amyotrophic Lateral Sclerosis: A Group LASSO Approach

Amyotrophic lateral sclerosis (ALS) is a multi-system neurodegenerative disease that affects both upper and lower motor neurons, resulting from a combination of genetic, environmental, and lifestyle factors. Usually, the association between single-nucleotide polymorphisms (SNPs) and this disease is tested individually, which leads to the testing of multiple hypotheses. In addition, this classical approach does not support the detection of interaction-dependent SNPs. We applied a two-step procedure to select SNPs and pairwise interactions associated with ALS. SNP data from 276 ALS patients and 268 controls were analyzed by a two-step group LASSO in 2000 iterations. In the first step, we fitted a group LASSO model to a bootstrap sample and a random subset of predictors (25%) from the original data set aiming to screen for important SNPs and, in the second step, we fitted a hierarchical group LASSO model to evaluate pairwise interactions. An in silico analysis was performed on a set of variables, which were prioritized according to their bootstrap selection frequency. We identified seven SNPs (rs16984239, rs10459680, rs1436918, rs1037666, rs4552942, rs10773543, and rs2241493) and two pairwise interactions (rs16984239:rs2118657 and rs16984239:rs3172469) potentially involved in nervous system conservation and function. These results may contribute to the understanding of ALS pathogenesis, its diagnosis, and therapeutic strategy improvement.

The Big Picture of Neurodegeneration: A Meta Study to Extract the Essential Evidence on Neurodegenerative Diseases in a Network-Based Approach

The common features of all neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, Amyotrophic Lateral Sclerosis (ALS), and Huntington's disease, are the accumulation of aggregated and misfolded proteins and the progressive loss of neurons, leading to cognitive decline and locomotive dysfunction. Still, they differ in their ultimate manifestation, the affected brain region, and the kind of proteinopathy. In the last decades, a vast number of processes have been described as associated with neurodegenerative diseases, making it increasingly harder to keep an overview of the big picture forming from all those data. In this meta-study, we analyzed genomic, transcriptomic, proteomic, and epigenomic data of the aforementioned diseases using the data of 234 studies in a network-based approach to study significant general coherences but also specific processes in individual diseases or omics levels. In the analysis part, we focus on only some of the emerging findings, but trust that the meta-study provided here will be a valuable resource for various other researchers focusing on specific processes or genes contributing to the development of neurodegeneration.

Causal Inference of Genetic Variants and Genes in Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a fatal progressive multisystem disorder with limited therapeutic options. Although genome-wide association studies (GWASs) have revealed multiple ALS susceptibility loci, the exact identities of causal variants, genes, cell types, tissues, and their functional roles in the development of ALS remain largely unknown. Here, we reported a comprehensive post-GWAS analysis of the recent large ALS GWAS (n = 80,610), including functional mapping and annotation (FUMA), transcriptome-wide association study (TWAS), colocalization (COLOC), and summary data-based Mendelian randomization analyses (SMR) in extensive multi-omics datasets. Gene property analysis highlighted inhibitory neuron 6, oligodendrocytes, and GABAergic neurons (Gad1/Gad2) as functional cell types of ALS and confirmed cerebellum and cerebellar hemisphere as functional tissues of ALS. Functional annotation detected the presence of multiple deleterious variants at three loci (9p21.2, 12q13.3, and 12q14.2) and highlighted a list of SNPs that are potentially functional. TWAS, COLOC, and SMR identified 43 genes at 24 loci, including 23 novel genes and 10 novel loci, showing significant evidence of causality. Integrating multiple lines of evidence, we further proposed that rs2453555 at 9p21.2 and rs229243 at 14q12 functionally contribute to the development of ALS by regulating the expression of C9orf72 in pituitary and SCFD1 in skeletal muscle, respectively. Together, these results advance our understanding of the biological etiology of ALS, feed into new therapies, and provide a guide for subsequent functional experiments.

Long non-coding RNA-associated competing endogenous RNA axes in the olfactory epithelium in schizophrenia: a bioinformatics analysis

The etiology of schizophrenia (SCZ), as a serious mental illness, is unknown. The significance of genetics in SCZ pathophysiology is yet unknown, and newly identified mechanisms involved in the regulation of gene transcription may be helpful in determining how these changes affect SCZ development and progression. In the current work, we used a bioinformatics approach to describe the role of long non-coding RNA (lncRNA)-associated competing endogenous RNAs (ceRNAs) in the olfactory epithelium (OE) samples in order to better understand the molecular regulatory processes implicated in SCZ disorders in living individuals. The Gene Expression Omnibus database was used to obtain the OE microarray dataset (GSE73129) from SCZ sufferers and control subjects, which contained information about both lncRNAs and mRNAs. The limma package of R software was used to identify the differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs). RNA interaction pairs were discovered using the Human MicroRNA Disease Database, DIANA-LncBase, and miRTarBase databases. In this study, the Pearson correlation coefficient was utilized to find positive correlations between DEmRNAs and DElncRNAs in the ceRNA network. Eventually, lncRNA-associated ceRNA axes were developed based on co-expression relations and DElncRNA-miRNA-DEmRNA interactions. This work found six potential DElncRNA-miRNA-DEmRNA loops in SCZ pathogenesis, including, SNTG2-AS1/hsa-miR-7-5p/SLC7A5, FLG-AS1/hsa-miR-34a-5p/FOSL1, LINC00960/hsa-miR-34a-5p/FOSL1, AQP4-AS1/hsa-miR-335-5p/FMN2, SOX2-OT/hsa-miR-24-3p/NOS3, and CASC2/hsa-miR-24-3p/NOS3. According to the findings, ceRNAs in OE might be promising research targets for studying SCZ molecular mechanisms. This could be a great opportunity to examine different aspects of neurodevelopment that may have been hampered early in SCZ patients.

Trans-ethnic genome-wide association study of severe COVID-19

COVID-19 has caused numerous infections with diverse clinical symptoms. To identify human genetic variants contributing to the clinical development of COVID-19, we genotyped 1457 (598/859 with severe/mild symptoms) and sequenced 1141 (severe/mild: 474/667) patients of Chinese ancestry. We further incorporated 1401 genotyped and 948 sequenced ancestry-matched population controls, and tested genome-wide association on 1072 severe cases versus 3875 mild or population controls, followed by trans-ethnic meta-analysis with summary statistics of 3199 hospitalized cases and 897,488 population controls from the COVID-19 Host Genetics Initiative. We identified three significant signals outside the well-established 3p21.31 locus: an intronic variant in FOXP4-AS1 (rs1853837, odds ratio OR = 1.28, P = 2.51 × 10-10, allele frequencies in Chinese/European AF = 0.345/0.105), a frameshift insertion in ABO (rs8176719, OR = 1.19, P = 8.98 × 10-9, AF = 0.422/0.395) and a Chinese-specific intronic variant in MEF2B (rs74490654, OR = 8.73, P = 1.22 × 10-8, AF = 0.004/0). These findings highlight an important role of the adaptive immunity and the ABO blood-group system in protection from developing severe COVID-19.

Novel EDGE encoding method enhances ability to identify genetic interactions

Assumptions are made about the genetic model of single nucleotide polymorphisms (SNPs) when choosing a traditional genetic encoding: additive, dominant, and recessive. Furthermore, SNPs across the genome are unlikely to demonstrate identical genetic models. However, running SNP-SNP interaction analyses with every combination of encodings raises the multiple testing burden. Here, we present a novel and flexible encoding for genetic interactions, the elastic data-driven genetic encoding (EDGE), in which SNPs are assigned a heterozygous value based on the genetic model they demonstrate in a dataset prior to interaction testing. We assessed the power of EDGE to detect genetic interactions using 29 combinations of simulated genetic models and found it outperformed the traditional encoding methods across 10%, 30%, and 50% minor allele frequencies (MAFs). Further, EDGE maintained a low false-positive rate, while additive and dominant encodings demonstrated inflation. We evaluated EDGE and the traditional encodings with genetic data from the Electronic Medical Records and Genomics (eMERGE) Network for five phenotypes: age-related macular degeneration (AMD), age-related cataract, glaucoma, type 2 diabetes (T2D), and resistant hypertension. A multi-encoding genome-wide association study (GWAS) for each phenotype was performed using the traditional encodings, and the top results of the multi-encoding GWAS were considered for SNP-SNP interaction using the traditional encodings and EDGE. EDGE identified a novel SNP-SNP interaction for age-related cataract that no other method identified: rs7787286 (MAF: 0.041; intergenic region of chromosome 7)–rs4695885 (MAF: 0.34; intergenic region of chromosome 4) with a Bonferroni LRT p of 0.018. A SNP-SNP interaction was found in data from the UK Biobank within 25 kb of these SNPs using the recessive encoding: rs60374751 (MAF: 0.030) and rs6843594 (MAF: 0.34) (Bonferroni LRT p: 0.026). We recommend using EDGE to flexibly detect interactions between SNPs exhibiting diverse action.

Although traditional genetic encodings are widely implemented in genetics research, including in genome-wide association studies (GWAS) and epistasis, each method makes assumptions that may not reflect the underlying etiology. Here, we introduce a novel encoding method that estimates and assigns an individualized data-driven encoding for each single nucleotide polymorphism (SNP): the elastic data-driven genetic encoding (EDGE). With simulations, we demonstrate that this novel method is more accurate and robust than traditional encoding methods in estimating heterozygous genotype values, reducing the type I error, and detecting SNP-SNP interactions. We further applied the traditional encodings and EDGE to biomedical data from the Electronic Medical Records and Genomics (eMERGE) Network for five phenotypes, and EDGE identified a novel interaction for age-related cataract not detected by traditional methods, which replicated in data from the UK Biobank. EDGE provides an alternative approach to understanding and modeling diverse SNP models and is recommended for studying complex genetics in common human phenotypes.

Common Factors in Neurodegeneration: A Meta-Study Revealing Shared Patterns on a Multi-Omics Scale

Neurodegenerative diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), and amyotrophic lateral sclerosis (ALS) are heterogeneous, progressive diseases with frequently overlapping symptoms characterized by a loss of neurons. Studies have suggested relations between neurodegenerative diseases for many years (e.g., regarding the aggregation of toxic proteins or triggering endogenous cell death pathways). We gathered publicly available genomic, transcriptomic, and proteomic data from 177 studies and more than one million patients to detect shared genetic patterns between the neurodegenerative diseases on three analyzed omics-layers. The results show a remarkably high number of shared differentially expressed genes between the transcriptomic and proteomic levels for all conditions, while showing a significant relation between genomic and proteomic data between AD and PD and AD and ALS. We identified a set of 139 genes being differentially expressed in several transcriptomic experiments of all four diseases. These 139 genes showed overrepresented gene ontology (GO) Terms involved in the development of neurodegeneration, such as response to heat and hypoxia, positive regulation of cytokines and angiogenesis, and RNA catabolic process. Furthermore, the four analyzed neurodegenerative diseases (NDDs) were clustered by their mean direction of regulation throughout all transcriptomic studies for this set of 139 genes, with the closest relation regarding this common gene set seen between AD and HD. GO-Term and pathway analysis of the proteomic overlap led to biological processes (BPs), related to protein folding and humoral immune response. Taken together, we could confirm the existence of many relations between Alzheimer's disease, Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis on transcriptomic and proteomic levels by analyzing the pathways and GO-Terms arising in these intersections. The significance of the connection and the striking relation of the results to processes leading to neurodegeneration between the transcriptomic and proteomic data for all four analyzed neurodegenerative diseases showed that exploring many studies simultaneously, including multiple omics-layers of different neurodegenerative diseases simultaneously, holds new relevant insights that do not emerge from analyzing these data separately. Furthermore, the results shed light on processes like the humoral immune response that have previously been described only for certain diseases. Our data therefore suggest human patients with neurodegenerative diseases should be addressed as complex biological systems by integrating multiple underlying data sources.

What Can Machine Learning Approaches in Genomics Tell Us about the Molecular Basis of Amyotrophic Lateral Sclerosis?

Amyotrophic Lateral Sclerosis (ALS) is the most common late-onset motor neuron disorder, but our current knowledge of the molecular mechanisms and pathways underlying this disease remain elusive. This review (1) systematically identifies machine learning studies aimed at the understanding of the genetic architecture of ALS, (2) outlines the main challenges faced and compares the different approaches that have been used to confront them, and (3) compares the experimental designs and results produced by those approaches and describes their reproducibility in terms of biological results and the performances of the machine learning models. The majority of the collected studies incorporated prior knowledge of ALS into their feature selection approaches, and trained their machine learning models using genomic data combined with other types of mined knowledge including functional associations, protein-protein interactions, disease/tissue-specific information, epigenetic data, and known ALS phenotype-genotype associations. The importance of incorporating gene-gene interactions and cis-regulatory elements into the experimental design of future ALS machine learning studies is highlighted. Lastly, it is suggested that future advances in the genomic and machine learning fields will bring about a better understanding of ALS genetic architecture, and enable improved personalized approaches to this and other devastating and complex diseases.

Multiple-Tissue Integrative Transcriptome-Wide Association Studies Discovered New Genes Associated With Amyotrophic Lateral Sclerosis

Genome-wide association studies (GWAS) have identified multiple causal genes associated with amyotrophic lateral sclerosis (ALS); however, the genetic architecture of ALS remains completely unknown and a large number of causal genes have yet been discovered. To full such gap in part, we implemented an integrative analysis of transcriptome-wide association study (TWAS) for ALS to prioritize causal genes with summary statistics from 80,610 European individuals and employed 13 GTEx brain tissues as reference transcriptome panels. The summary-level TWAS analysis with single brain tissue was first undertaken and then a flexible p-value combination strategy, called summary data-based Cauchy Aggregation TWAS (SCAT), was proposed to pool association signals from single-tissue TWAS analysis while protecting against highly positive correlation among tests. Extensive simulations demonstrated SCAT can produce well-calibrated p-value for the control of type I error and was often much more powerful to identify association signals across various scenarios compared with single-tissue TWAS analysis. Using SCAT, we replicated three ALS-associated genes (i.e., ATXN3, SCFD1, and C9orf72) identified in previous GWASs and discovered additional five genes (i.e., SLC9A8, FAM66D, TRIP11, JUP, and RP11-529H20.6) which were not reported before. Furthermore, we discovered the five associations were largely driven by genes themselves and thus might be new genes which were likely related to the risk of ALS. However, further investigations are warranted to verify these results and untangle the pathophysiological function of the genes in developing ALS.

Genetics of Amyotrophic Lateral Sclerosis

Purpose of Review

Amyotrophic lateral sclerosis and frontotemporal dementia (ALS-FTD) spectrum disorder is a rare fatal disease with strong genetic influences. The implementation of short-read sequencing methodologies in increasingly large patient cohorts has rapidly expanded our knowledge of the complex genetic architecture of the disease. We aim to convey the broad history of ALS gene discovery as context for a focused review of 11 ALS gene associations reported over the last 5 years. We also summarize the current level of genetic evidence for all previously reported genes.

Recent Findings

The history of ALS gene discovery has occurred in at least four identifiable phases, each powered by different technologies and scale of investigation. The most recent epoch, benefitting from population-scale genome data, large international consortia, and low-cost sequencing, has yielded 11 new gene associations. We summarize the current level of genetic evidence supporting these ALS genes, highlighting any genotype-phenotype or genotype-pathology correlations, and discussing preliminary understanding of molecular pathogenesis. This era has also raised uncertainty around prior ALS-associated genes and clarified the role of others.

Summary

Our understanding of the genetic underpinning of ALS has expanded rapidly over the last 25 years and has led directly to the clinical application of molecularly driven therapies. Ongoing sequencing efforts in ALS will identify new causative and risk factor genes while clarifying the status of genes reported in prior eras of research.

A logical relationship for schizophrenia, bipolar, and major depressive disorder. Part 1: Evidence from chromosome 1 high density association screen

Familial clustering of schizophrenia (SCZ), bipolar disorder (BPD), and major depressive disorder (MDD) was investigated systematically (Aukes et al., Genetics in Medicine, 2012, 14, 338-341) and any two or even three of these disorders could coexist in some families. Furthermore, evidence from symptomatology and psychopharmacology also imply the existence of intrinsic connections between these three major psychiatric disorders. A total of 71,445 SNPs on chromosome 1 were genotyped on 119 SCZ, 253 BPD (type-I), 177 MDD cases and 1000 controls and further validated in 986 SCZ patients in the population of Shandong province of China. Outstanding psychosis genes are systematically revealed( ATP1A4, ELTD1, FAM5C, HHAT, KIF26B, LMX1A, NEGR1, NFIA, NR5A2, NTNG1, PAPPA2, PDE4B, PEX14, RYR2, SYT6, TGFBR3, TTLL7, and USH2A). Unexpectedly, flanking genes for up to 97.09% of the associated SNPs were also replicated in an enlarged cohort of 986 SCZ patients. From the perspective of etiological rather than clinical psychiatry, bipolar, and major depressive disorder could be subtypes of schizophrenia. Meanwhile, the varied clinical feature and prognosis might be the result of interaction of genetics and epigenetics, for example, irreversible or reversible shut down, and over or insufficient expression of certain genes, which may gives other aspects of these severe mental disorders.

Circulating RNAs as Potential Biomarkers in Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a complex multi-system neurodegenerative disorder with currently limited diagnostic and no therapeutic options. Despite the intense efforts no clinically applicable biomarkers for ALS are yet established. Most current research is thus focused, in particular, in identifying potential non-invasive circulating biomarkers for more rapid and accurate diagnosis and monitoring of the disease. In this review, we have focused on messenger RNA (mRNA), non-coding RNAs (lncRNAs), micro RNAs (miRNAs) and circular RNA (circRNAs) as potential biomarkers for ALS in peripheral blood serum, plasma and cells. The most promising miRNAs include miR-206, miR-133b, miR-27a, mi-338-3p, miR-183, miR-451, let-7 and miR-125b. To test clinical potential of this miRNA panel, a useful approach may be to perform such analysis on larger multi-center scale using similar experimental design. However, other types of RNAs (lncRNAs, circRNAs and mRNAs) that, together with miRNAs, represent RNA networks, have not been yet extensively studied in blood samples of patients with ALS. Additional research has to be done in order to find robust circulating biomarkers and therapeutic targets that will distinguish key RNA interactions in specific ALS-types to facilitate diagnosis, predict progression and design therapy.

Omics in Neurodegenerative Disease: Hope or Hype?

The past 15 years have seen a boom in the use and integration of 'omic' approaches (limited here to genomic, transcriptomic, and epigenomic techniques) to study neurodegenerative disease in an unprecedented way. We first highlight advances in and the limitations of using such approaches in the neurodegenerative disease literature, with a focus on Alzheimer's disease (AD), Parkinson's disease (PD), frontotemporal lobar degeneration (FTLD), and amyotrophic lateral sclerosis (ALS). We next discuss how these studies can advance human health in the form of generating leads for downstream mechanistic investigation or yielding polygenic risk scores (PRSs) for prognostication. However, we argue that these approaches constitute a new form of molecular description, analogous to clinical or pathological description, that alone does not hold the key to solving these complex diseases.

Circular RNAs as Potential Blood Biomarkers in Amyotrophic Lateral Sclerosis

Circular RNAs (circRNAs) are emerging as a novel, yet powerful player in many human diseases. They are involved in several cellular processes and are becoming a noteworthy type of biomarkers. Among other functions, circRNAs can serve as RNA sponges or as scaffolds for RNA-binding proteins. Here, we investigated a microarray expression profile of circRNAs in leukocyte samples from ALS patients and age- and sex-matched healthy controls to identify differentially expressed circRNAs. We selected 10 of them for a qPCR validation of expression on a larger set of samples, identification of their associations with clinical parameters, and evaluation of their diagnostic potential. In total, expression of 7/10 circRNAs was significant in a larger cohort of ALS patients, compared with age- and sex-matched healthy controls. Three of them (hsa_circ_0023919, hsa_circ_0063411, and hsa_circ_0088036) showed the same regulation as in microarray results. These three circRNAs also had AUC > 0.95, and sensitivity and specificity for the optimal threshold point > 90%, showing their potential for using them as diagnostic biomarkers.

Integrated molecular landscape of amyotrophic lateral sclerosis provides insights into disease etiology

Amyotrophic lateral sclerosis (ALS) is a severe, progressive and ultimately fatal motor neuron disease caused by a combination of genetic and environmental factors, but its underlying mechanisms are largely unknown. To gain insight into the etiology of ALS, we here conducted genetic network and literature analyses of the top-ranked findings from six genome-wide association studies of sporadic ALS (involving 3589 cases and 8577 controls) as well as genes implicated in ALS etiology through other evidence, including familial ALS candidate gene association studies. We integrated these findings into a molecular landscape of ALS that allowed the identification of three main processes that interact with each other and are crucial to maintain axonal functionality, especially of the long axons of motor neurons, i.e. (1) Rho-GTPase signaling; (2) signaling involving the three regulatory molecules estradiol, folate, and methionine; and (3) ribonucleoprotein granule functioning and axonal transport. Interestingly, estradiol signaling is functionally involved in all three cascades and as such an important mediator of the molecular ALS landscape. Furthermore, epidemiological findings together with an analysis of possible gender effects in our own cohort of sporadic ALS patients indicated that estradiol may be a protective factor, especially for bulbar-onset ALS. Taken together, our molecular landscape of ALS suggests that abnormalities within three interconnected molecular processes involved in the functioning and maintenance of motor neuron axons are important in the etiology of ALS. Moreover, estradiol appears to be an important modulator of the ALS landscape, providing important clues for the development of novel disease-modifying treatments.

Common polymorphisms of chemokine (C-X3-C motif) receptor 1 gene modify amyotrophic lateral sclerosis outcome: A population-based study

INTRODUCTION

In the brain, the chemokine (C-X3-C motif) receptor 1 (1CX3CR1) gene is expressed only by microglia, where it acts as a key mediator of the neuron-microglia interactions. We assessed whether the 2 common polymorphisms of the CX3CR1 gene (V249I and T280M) modify amyotrophic lateral sclerosis (ALS) phenotype.

METHODS

The study included 755 ALS patients diagnosed in Piemonte between 2007 and 2012 and 369 age-matched and sex-matched controls, all genotyped with the same chips.

RESULTS

Neither of the variants was associated with an increased risk of ALS. Patients with the V249I V/V genotype had a 6-month-shorter survival than those with I/I or V/I genotypes (dominant model, P = 0.018). The T280M genotype showed a significant difference among the 3 genotypes (additive model, P = 0.036). Cox multivariable analysis confirmed these findings.

DISCUSSION

We found that common variants of the CX3CR1 gene influence ALS survival. Our data provide further evidence for the role of neuroinflammation in ALS. Muscle Nerve 57: 212-216, 2018.

Copy Number Variations in Amyotrophic Lateral Sclerosis: Piecing the Mosaic Tiles Together through a Systems Biology Approach

Amyotrophic lateral sclerosis (ALS) is a devastating and still untreatable motor neuron disease. Despite the molecular mechanisms underlying ALS pathogenesis that are still far from being understood, several studies have suggested the importance of a genetic contribution in both familial and sporadic forms of the disease. In addition to single-nucleotide polymorphisms (SNPs), which account for only a limited number of ALS cases, a consistent number of common and rare copy number variations (CNVs) have been associated to ALS. Most of the CNV-based association studies use a traditional candidate-gene approach that is inadequate for uncovering the genetic architectures of complex traits like ALS. The emergent paradigm of “systems biology” may offer a new perspective to better interpret the wide spectrum of CNVs in ALS, enabling the characterization of the complex network of gene products underlying ALS pathogenesis. In this review, we will explore the landscape of CNVs in ALS, putting specific emphasis on the functional impact of common CNV regions and genes consistently associated with increased risk of developing disease. In addition, we will discuss the potential contribution of multiple rare CNVs in ALS pathogenesis, focusing our attention on the complex mechanisms by which these proteins might impact, individually or in combination, the genetic susceptibility of ALS. The comprehensive detection and functional characterization of common and rare candidate risk CNVs in ALS susceptibility may bring new pieces into the intricate mosaic of ALS pathogenesis, providing interesting and important implications for a more precise molecular biomarker-assisted diagnosis and more effective and personalized treatments.

Screening for novel hexanucleotide repeat expansions at ALS- and FTD-associated loci

OBJECTIVE

To determine whether GGGGCC (G4C2) repeat expansions at loci other than C9orf72 serve as common causes of amyotrophic lateral sclerosis (ALS).

METHODS

We assessed G4C2 repeat number in 28 genes near known ALS and frontotemporal dementia (FTD) loci by repeat-primed PCR coupled with fluorescent fragment analysis in 199 patients with ALS (17 familial, 182 sporadic) and 136 healthy controls. We also obtained blood from patients with ALS4 for evaluation of repeats surrounding the SETX gene locus. C9orf72 expansions were evaluated in parallel.

RESULTS

Expansions of G4C2 repeats in C9orf72 explained 8.8% of sporadic and 47% of familial ALS cases analyzed. Repeat variance was observed at one other locus, RGS14, but no large expansions were observed, and repeat sizes were not different between cases and controls. No G4C2 repeat expansions were identified at other ALS or FTD risk loci or in ALS4 cases.

CONCLUSIONS

G4C2 expansions near known ALS and FTD loci other than C9orf72 are not a common cause of ALS.

Enrichment of SNPs in Functional Categories Reveals Genes Affecting Complex Traits

Genome-wide association studies (GWAS) have indicated potential to identify heritability of common complex phenotypes, but traditional approaches have limited ability to detect hiding signals because single SNP has weak effect size accounting for only a small fraction of overall phenotypic variations. To improve the power of GWAS, methods have been developed to identify truly associated genes by jointly testing effects of all SNPs. However, equally considering all SNPs within a gene might dilute strong signals of SNPs in real functional categories. Here, we observed a consistent pattern on enrichment of significant SNPs in eight functional categories across six phenotypes, with the highest enrichment in coding and both UTR regions while the lowest enrichment in the intron. Based on the pattern of SNP enrichment in functional categories, we developed a new approach for detecting gene associations on traits (DGAT) by selecting the most significant functional category and then using SNPs within it to assess gene associations. The method was found to be robust in type I error rate on simulated data, and to have mostly higher power in detecting associated genes for three different diseases than other methods. Further analysis indicated ability of the DGAT to detect novel genes. The DGAT is available by http://sparks-lab.org/server/DGAT.

Single-nucleotide Polymorphism rs2275294 in ZNF512B is not Associated with Susceptibility to Amyotrophic Lateral Sclerosis in a Large Chinese Cohort

Background:

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease that primarily affects motor neurons and has no effective treatment. Recently, Iida et al. identified a single-nucleotide polymorphism (SNP) rs2275294 in the ZNF512B gene that is significantly associated with susceptibility to ALS in the Japanese population. Here, we performed a case–control study examining the possible association of rs2275294 with risk of sporadic ALS (SALS) in a large Chinese cohort.

Methods:

To assess this association, we performed a replication study in 953 SALS patients and 1039 age- and gender-matched healthy control subjects, who were recruited from Peking University Third Hospital and the First Affiliated Hospital of Anhui Medical University from January 2004 to December 2013 throughout China. We genotyped the rs2275294 SNP using polymerase chain reaction and direct sequencing.

Results:

The allele frequency of rs2275294 in ZNF512B was different between Japanese and Chinese. The association in Chinese between ALS patients and controls did not reach statistical significance (P = 0.54; odds ratio = 0.94; 95% confidence interval = 0.76–1.15).

Conclusions:

The SNP rs2275294 in ZNF512B is not considered to be associated with ALS susceptibility in the Chinese population. Our study highlights genetic heterogeneity in ALS susceptibility in different population. Given our negative results, further replication study involving larger and more homogeneous samples in different ethnicities should be performed in the future.

A genome-wide association study on amyotrophic lateral sclerosis in the Taiwanese Han population

Identification of mutations in patients with amyotrophic lateral sclerosis (ALS) in a genome-wide association study can reveal possible biomarkers of such a rapidly progressive and fatal neurodegenerative disease. It was observed that significant single nucleotide polymorphisms vary when the tested population changes from one ethnic group to another. To identify new loci associated with ALS susceptibility in the Taiwanese Han population, we performed a genome-wide association study on 94 patients with sporadic ALS and 376 matched controls. We uncovered two new susceptibility loci at 13q14.3 (rs2785946) and 11q25 (rs11224052). In addition, we analyzed the functions of all the associated genes among 54 significant single nucleotide polymorphisms using Gene Ontology annotations, and the results showed several statistically significant neural- and muscle-related Gene Ontology terms and the associated diseases.

Replication analysis of genetic variants on 17q11.2 and 9p21.2 with sporadic amyotrophic lateral sclerosis and Parkinson's disease in a Chinese population

We performed a replication study of the 2 genetic variants, rs34517613 on 17q11.2 and rs3849942 on 9p21.2 in patients with sporadic amyotrophic lateral sclerosis (ALS) and Parkinson's disease in a Chinese population. These 2 variants are identified to be associated with increased risk of ALS in European-descended populations by genome-wide association studies. Both rs34517613 and rs3849942 showed no evidence of association in Chinese. These loci are not risk factors for sporadic ALS and Parkinson's disease in the western Han Chinese population.

Drosophila Shep and C. elegans SUP-26 are RNA-binding proteins that play diverse roles in nervous system development

The Caenorhabditis elegans gene sup-26 encodes a well-conserved RNA-recognition motif-containing RNA-binding protein (RBP) that functions in dendrite morphogenesis of the PVD sensory neuron. The Drosophila ortholog of sup-26, alan shepard (shep), is expressed throughout the nervous system and has been shown to regulate neuronal remodeling during metamorphosis. Here, we extend these studies to show that sup-26 and shep are required for the development of diverse cell types within the nematode and fly nervous systems during embryonic and larval stages. We ascribe roles for sup-26 in regulating dendrite number and the expression of genes involved in mechanosensation within the nematode peripheral nervous system. We also find that in Drosophila, shep regulates dendrite length and branch order of nociceptive neurons, regulates the organization of neuronal clusters of the peripheral nervous system and the organization of axons within the ventral nerve cord. Taken together, our results suggest that shep/sup-26 orthologs play diverse roles in neural development across animal species. Moreover, we discuss potential roles for shep/sup-26 orthologs in the human nervous system.

A common functional allele of the Nogo receptor gene, reticulon 4 receptor (RTN4R), is associated with sporadic amyotrophic lateral sclerosis in a French population

Amyotrophic lateral sclerosis is sporadic (SALS) in 90% of cases and has complex environmental and genetic influences. Nogo protein inhibits neurite outgrowth and is overexpressed in muscle in ALS. Our aims were to study the reticulon 4 receptor gene RTN4R which encodes Nogo 1 receptor (NgR1) in SALS, to test if the variants were associated with variable expression of the gene and whether NgR1 protein expression was modified in a transgenic mouse model of ALS. We genotyped three single nucleotide polymorphisms (SNPs; rs701421, rs701427, and rs1567871) of the RTN4R gene in 364 SALS French patients and 430 controls. We examined expression of RTN4R mRNA by quantitative PCR in control post mortem human brain tissue. We determined the expression of NgR1 protein in spinal motor neurons from a SOD1 G86R ALS mouse model. We observed significant associations between SALS and RTN4R alleles. Messenger RNA expression from RTN4R in human cortical brain tissue correlated significantly with the genotypes of rs701427. NgR1 protein expression was reduced in Nogo A positive motor neurons from diseased transgenic animals. In conclusion, these observations suggest that a functional RTN4R gene variant is associated with SALS. This variant may act in concert with other genetic variants or environmental influences.

Genetic causes of amyotrophic lateral sclerosis: new genetic analysis methodologies entailing new opportunities and challenges

The genetic architecture of amyotrophic lateral sclerosis (ALS) is being increasingly understood. In this far-reaching review, we examine what is currently known about ALS genetics and how these genes were initially identified. We also discuss the various types of mutations that might underlie this fatal neurodegenerative condition and outline some of the strategies that might be useful in untangling them. These include expansions of short repeat sequences, common and low-frequency genetic variations, de novo mutations, epigenetic changes, somatic mutations, epistasis, oligogenic and polygenic hypotheses. This article is part of a Special Issue entitled ALS complex pathogenesis.

Challenges in the Understanding and Treatment of Amyotrophic Lateral Sclerosis/Motor Neuron Disease

With the acceleration in our understanding of ALS and the related motor neuron disease has come even greater challenges in reconciling all of the proposed pathogenic mechanisms and how this will translate into impactful treatments. Fundamental issues such as diagnostic definition(s) of the disease spectrum, relevant biomarkers, the impact of multiple novel genetic mutations and the significant effect of symptomatic treatments on disease progression are all areas of active investigation. In this review, we will focus on these key issues and highlight the challenges that confront both clinicians and basic science researchers.

Stratified gene expression analysis identifies major amyotrophic lateral sclerosis genes

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease of motor neurons resulting in progressive paralysis. Gene expression studies of ALS only rarely identify the same gene pathways as gene association studies. We hypothesized that analyzing tissues by matching on degree of disease severity would identify different patterns of gene expression from a traditional case-control comparison. We analyzed gene expression changes in 4 postmortem central nervous system regions, stratified by severity of motor neuron loss. An overall comparison of cases (n = 6) and controls (n = 3) identified known ALS gene, SOX5, as showing differential expression (log2 fold change = 0.09, p = 5.5 × 10(-5)). Analyses stratified by disease severity identified expression changes in C9orf72 (p = 2.77 × 10(-3)), MATR3 (p = 3.46 × 10(-3)), and VEGFA (p = 8.21 × 10(-4)), all implicated in ALS through genetic studies, and changes in other genes in pathways involving RNA processing and immune response. These findings suggest that analysis of gene expression stratified by disease severity can identify major ALS genes and may be more efficient than traditional case-control comparison.

SNP imputation bias reduces effect size determination

Imputation is a commonly used technique that exploits linkage disequilibrium to infer missing genotypes in genetic datasets, using a well-characterized reference population. While there is agreement that the reference population has to match the ethnicity of the query dataset, it is common practice to use the same reference to impute genotypes for a wide variety of phenotypes. We hypothesized that using a reference composed of samples with a different phenotype than the query dataset would introduce imputation bias. To test this hypothesis we used GWAS datasets from Amyotrophic Lateral Sclerosis (ALS), Parkinson Disease (PD), and Crohn's Disease (CD). First, we masked and then performed imputation of 100 disease-associated markers and 100 non-associated markers from each study. Two references for imputation were used in parallel: one consisting of healthy controls and another consisting of patients with the same disease. We assessed the discordance (imprecision) and bias (inaccuracy) of imputation by comparing predicted genotypes to those assayed by SNP-chip. We also assessed the bias on the observed effect size when the predicted genotypes were used in a GWAS study. When healthy controls were used as reference for imputation, a significant bias was observed, particularly in the disease-associated markers. Using cases as reference significantly attenuated this bias. For nearly all markers, the direction of the bias favored the non-risk allele. In GWAS studies of the three diseases (with healthy reference controls from the 1000 genomes as reference), the mean OR for disease-associated markers obtained by imputation was lower than that obtained using original assayed genotypes. We found that the bias is inherent to imputation as using different methods did not alter the results. In conclusion, imputation is a powerful method to predict genotypes and estimate genetic risk for GWAS. However, a careful choice of reference population is needed to minimize biases inherent to this approach.

Genome-wide association studies in neurology

Genome-wide association studies (GWAS) are a powerful tool for understanding the genetic underpinnings of human disease. In this article, we briefly review the role and findings of GWAS in common neurological diseases, including Stroke, Alzheimer's disease, Parkinson's disease, epilepsy, multiple sclerosis, migraine, amyotrophic lateral sclerosis, frontotemporal lobar degeneration, restless legs syndrome, intracranial aneurysm, human prion diseases and moyamoya disease. We then discuss the present and future implications of these findings with regards to disease prediction, uncovering basic biology, and the development of potential therapeutic agents.

Genome-wide analysis of the heritability of amyotrophic lateral sclerosis

IMPORTANCE

Considerable advances have been made in our understanding of the genetics underlying amyotrophic lateral sclerosis (ALS). Nevertheless, for the majority of patients who receive a diagnosis of ALS, the role played by genetics is unclear. Further elucidation of the genetic architecture of this disease will help clarify the role of genetic variation in ALS populations.

OBJECTIVE

To estimate the relative importance of genetic factors in a complex disease such as ALS by accurately quantifying heritability using genome-wide data derived from genome-wide association studies.

DESIGN, SETTING, AND PARTICIPANTS

We applied the genome-wide complex trait analysis algorithm to 3 genome-wide association study data sets that were generated from ALS case-control cohorts of European ancestry to estimate the heritability of ALS. Cumulatively, these data sets contained genotype data from 1223 cases and 1591 controls that had been previously generated and are publically available on the National Center for Biotechnology Information database of genotypes and phenotypes website (http://www.ncbi.nlm.nih.gov/gap). The cohorts genotyped as part of these genome-wide association study efforts include the InCHIANTI (aging in the Chianti area) Study, the Piemonte and Valle d'Aosta Register for Amyotrophic Lateral Sclerosis, the National Institute of Neurological Disorders and Stroke Repository, and an ALS specialty clinic in Helsinki, Finland.

MAIN OUTCOMES AND MEASURES

A linear mixed model was used to account for all known single-nucleotide polymorphisms simultaneously and to quantify the phenotypic variance present in ostensibly outbred individuals. Variance measures were used to estimate heritability.

RESULTS

With our meta-analysis, which is based on genome-wide genotyping data, we estimated the overall heritability of ALS to be approximately 21.0% (95% CI, 17.1-24.9) (SE = 2.0%), indicating that additional genetic variation influencing risk of ALS loci remains to be identified. Furthermore, we identified 17 regions of the genome that display significantly high heritability estimates. Eleven of these regions represent novel candidate regions for ALS risk.

CONCLUSIONS AND RELEVANCE

We found the heritability of ALS to be significantly higher than previously reported. We also identified multiple, novel genomic regions that we hypothesize may contain causative risk variants that influence susceptibility to ALS.

A major QTL on mouse chromosome 17 resulting in lifespan variability in SOD1-G93A transgenic mouse models of amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis is a late-onset degenerative disease affecting motor neurons in the spinal cord, brainstem, and motor cortex. There is great variation in the expression of ALS symptoms even between siblings who both carry the same Cu/Zn superoxide dismutase (SOD1) mutations. One important use of transgenic mouse models of SOD1-ALS is the study of genetic influences on ALS severity. We utilized multiple inbred mouse strains containing the SOD1-G93A transgene to demonstrate a major quantitative trait locus (QTL) on mouse chromosome 17 resulting in a significant shift in lifespan. Reciprocal crosses between long- and short-lived strains identified critical regions, and we have narrowed the area for potential genetic modifier(s) to < 2Mb of the genome. Results showed that resequencing of this region resulted in 28 candidate genes with potentially functional differences between strains. In conclusion, these studies provide the first major modifier locus affecting lifespan in this model of FALS and, once identified, these candidate modifier genes may provide insight into modifiers of human disease and, most importantly, define new targets for the development of therapies.

State of play in amyotrophic lateral sclerosis genetics

Considerable progress has been made in unraveling the genetic etiology of amyotrophic lateral sclerosis (ALS), the most common form of adult-onset motor neuron disease and the third most common neurodegenerative disease overall. Here we review genes implicated in the pathogenesis of motor neuron degeneration and how this new information is changing the way we think about this fatal disorder. Specifically, we summarize current literature of the major genes underlying ALS, SOD1, TARDBP, FUS, OPTN, VCP, UBQLN2, C9ORF72 and PFN1, and evaluate the information being gleaned from genome-wide association studies. We also outline emerging themes in ALS research, such as next-generation sequencing approaches to identify de novo mutations, the genetic convergence of familial and sporadic ALS, the proposed oligogenic basis for the disease, and how each new genetic discovery is broadening the phenotype associated with the clinical entity we know as ALS.

Homozygosity analysis in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) may appear to be familial or sporadic, with recognised dominant and recessive inheritance in a proportion of cases. Sporadic ALS may be caused by rare homozygous recessive mutations. We studied patients and controls from the UK and a multinational pooled analysis of GWAS data on homozygosity in ALS to determine any potential recessive variant leading to the disease. Six-hundred and twenty ALS and 5169 controls were studied in the UK cohort. A total of 7646 homozygosity segments with length >2 Mb were identified, and 3568 rare segments remained after filtering 'common' segments. The mean total of the autosomal genome with homozygosity segments was longer in ALS than in controls (unfiltered segments, P=0.05). Two-thousand and seventeen ALS and 6918 controls were studied in the pooled analysis. There were more regions of homozygosity segments per case (P=1 × 10(-5)), a greater proportion of cases harboured homozygosity (P=2 × 10(-5)), a longer average length of segment (P=1 × 10(-5)), a longer total genome coverage (P=1 × 10(-5)), and a higher rate of these segments overlapped with RefSeq gene regions (P=1 × 10(-5)), in ALS patients than controls. Positive associations were found in three regions. The most significant was in the chromosome 21 SOD1 region, and also chromosome 1 2.9-4.8 Mb, and chromosome 5 in the 65 Mb region. There are more than twenty potential genes in these regions. These findings point to further possible rare recessive genetic causes of ALS, which are not identified as common variants in GWAS.

A genome-wide association meta-analysis identifies a novel locus at 17q11.2 associated with sporadic amyotrophic lateral sclerosis

Identification of mutations at familial loci for amyotrophic lateral sclerosis (ALS) has provided novel insights into the aetiology of this rapidly progressing fatal neurodegenerative disease. However, genome-wide association studies (GWAS) of the more common (∼90%) sporadic form have been less successful with the exception of the replicated locus at 9p21.2. To identify new loci associated with disease susceptibility, we have established the largest association study in ALS to date and undertaken a GWAS meta-analytical study combining 3959 newly genotyped Italian individuals (1982 cases and 1977 controls) collected by SLAGEN (Italian Consortium for the Genetics of ALS) together with samples from Netherlands, USA, UK, Sweden, Belgium, France, Ireland and Italy collected by ALSGEN (the International Consortium on Amyotrophic Lateral Sclerosis Genetics). We analysed a total of 13 225 individuals, 6100 cases and 7125 controls for almost 7 million single-nucleotide polymorphisms (SNPs). We identified a novel locus with genome-wide significance at 17q11.2 (rs34517613 with P = 1.11 × 10(-8); OR 0.82) that was validated when combined with genotype data from a replication cohort (P = 8.62 × 10(-9); OR 0.833) of 4656 individuals. Furthermore, we confirmed the previously reported association at 9p21.2 (rs3849943 with P = 7.69 × 10(-9); OR 1.16). Finally, we estimated the contribution of common variation to heritability of sporadic ALS as ∼12% using a linear mixed model accounting for all SNPs. Our results provide an insight into the genetic structure of sporadic ALS, confirming that common variation contributes to risk and that sufficiently powered studies can identify novel susceptibility loci.

A rare motor neuron deleterious missense mutation in the DPYSL3 (CRMP4) gene is associated with ALS

The dihydropyrimidinase-like 3 (DPYSL3) or Collapsin Response Mediator Protein 4a (CRMP4a) expression is modified in neurodegeneration and is involved in several ALS-associated pathways including axonal transport, glutamate excitotoxicity, and oxidative stress. The objective of the study was to analyze CRMP4 as a risk factor for ALS. We analyzed the DPYSL3/CRMP4 gene in French ALS patients (n = 468) and matched-controls (n = 394). We subsequently examined a variant in a Swedish population (184 SALS, 186 controls), and evaluated its functional effects on axonal growth and survival in motor neuron cell culture. The rs147541241:A>G missense mutation occurred in higher frequency among French ALS patients (odds ratio = 2.99) but the association was not confirmed in the Swedish population. In vitro expression of mutated DPYSL3 in motor neurons reduced axonal growth and accelerated cell death compared with wild type protein. Thus, the association between the rs147541241 variant and ALS was limited to the French population, highlighting the geographic particularities of genetic influences (risks, contributors). The identified variant appears to shorten motor neuron survival through a detrimental effect on axonal growth and CRMP4 could act as a key unifier in transduction pathways leading to neurodegeneration through effects on early axon development.

Controversies and priorities in amyotrophic lateral sclerosis

Two decades after the discovery that 20% of familial amyotrophic lateral sclerosis (ALS) cases were linked to mutations in the superoxide dismutase-1 (SOD1) gene, a substantial proportion of the remainder of cases of familial ALS have now been traced to an expansion of the intronic hexanucleotide repeat sequence in C9orf72. This breakthrough provides an opportunity to re-evaluate longstanding concepts regarding the cause and natural history of ALS, coming soon after the pathological unification of ALS with frontotemporal dementia through a shared pathological signature of cytoplasmic inclusions of the ubiquitinated protein TDP-43. However, with profound clinical, prognostic, neuropathological, and now genetic heterogeneity, the concept of ALS as one disease appears increasingly untenable. This background calls for the development of a more sophisticated taxonomy, and an appreciation of ALS as the breakdown of a wider network rather than a discrete vulnerable population of specialised motor neurons. Identification of C9orf72 repeat expansions in patients without a family history of ALS challenges the traditional division between familial and sporadic disease. By contrast, the 90% of apparently sporadic cases and incomplete penetrance of several genes linked to familial cases suggest that at least some forms of ALS arise from the interplay of multiple genes, poorly understood developmental, environmental, and age-related factors, as well as stochastic events.

Age of onset of amyotrophic lateral sclerosis is modulated by a locus on 1p34.1

Amyotrophic lateral sclerosis (ALS) is the third most common adult-onset neurodegenerative disease. Individuals with ALS rapidly progress to paralysis and die from respiratory failure within 3 to 5 years after symptom onset. Epidemiological factors explain only a modest amount of the risk for ALS. However, there is growing evidence of a strong genetic component to both familial and sporadic ALS risk. The International Consortium on Amyotrophic Lateral Sclerosis Genetics was established to bring together existing genome-wide association cohorts and identify sporadic ALS susceptibility and age at symptom onset loci. Here, we report the results of a meta-analysis of the International Consortium on Amyotrophic Lateral Sclerosis Genetics genome-wide association samples, consisting of 4243 ALS cases and 5112 controls from 13 European ancestry cohorts from across the United States and Europe. Eight genomic regions provided evidence of association with ALS, including 9p21.2 (rs3849942, odds ratio [OR] = 1.21; p = 4.41 × 10(-7)), 17p11.2 (rs7477, OR = 1.30; p = 2.89 × 10(-7)), and 19p13 (rs12608932, OR = 1.37, p = 1.29 × 10(-7)). Six genomic regions were associated with age at onset of ALS. The strongest evidence for an age of onset locus was observed at 1p34.1, with comparable evidence at rs3011225 (R(2)(partial) = 0.0061; p = 6.59 × 10(-8)) and rs803675 (R(2)(partial) = 0.0060; p = 6.96 × 10(-8)). These associations were consistent across all 13 cohorts. For rs3011225, individuals with at least 1 copy of the minor allele had an earlier average age of onset of over 2 years. Identifying the underlying pathways influencing susceptibility to and age at onset of ALS may provide insight into the pathogenic mechanisms and motivate new pharmacologic targets for this fatal neurodegenerative disease.