scholarly journals Searching Far and Genome-Wide: The Relevance of Association Studies in Amyotrophic Lateral Sclerosis

2021 ◽  
Vol 14 ◽  
Author(s):  
Kelly A. Rich ◽  
Jennifer Roggenbuck ◽  
Stephen J. Kolb
Keyword(s):  
Amyotrophic Lateral Sclerosis ◽  
Complex Disease ◽  
Association Studies ◽  
Genetic Association Studies ◽  
Disease Status ◽  
Therapeutic Interventions ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Disease Associated Genes ◽  
Lateral Sclerosis

Genome-wide association studies (GWAS) and rare variant association studies (RVAS) are applied across many areas of complex disease to analyze variation in whole genomes of thousands of unrelated patients. These approaches are able to identify variants and/or biological pathways which are associated with disease status and, in contrast to traditional linkage studies or candidate gene approaches, do so without requiring multigenerational affected families, prior hypotheses, or known genes of interest. However, the novel associations identified by these methods typically have lower effect sizes than those found in classical family studies. In the motor neuron disease amyotrophic lateral sclerosis (ALS), GWAS, and RVAS have been used to identify multiple disease-associated genes but have not yet resulted in novel therapeutic interventions. There is significant urgency within the ALS community to identify additional genetic markers of disease to uncover novel biological mechanisms, stratify genetic subgroups of disease, and drive drug development. Given the widespread and increasing application of genetic association studies of complex disease, it is important to recognize the strengths and limitations of these approaches. Here, we review ALS gene discovery via GWAS and RVAS.

scholarly journals Genome-wide Identification of the Genetic Basis of Amyotrophic Lateral Sclerosis

2020 ◽  
Author(s):  
Sai Zhang ◽  
Johnathan Cooper-Knock ◽  
Annika K. Weimer ◽  
Minyi Shi ◽  
Tobias Moll ◽  
...  
Keyword(s):  
Amyotrophic Lateral Sclerosis ◽  
Motor Neurons ◽  
Complex Traits ◽  
Complex Disease ◽  
Association Studies ◽  
Genetic Association Studies ◽  
Network Analyses ◽  
Genome Wide ◽  
Human Neurons ◽  
Lateral Sclerosis

ABSTRACTAmyotrophic lateral sclerosis (ALS) is an archetypal complex disease centered on progressive death of motor neurons. Despite heritability estimates of 52%, GWAS studies have discovered only seven genome-wide significant hits, which are relevant to <10% of ALS patients. To increase the power of gene discovery, we integrated motor neuron functional genomics with ALS genetics in a hierarchical Bayesian model called RefMap. Comprehensive transcriptomic and epigenetic profiling of iPSC-derived motor neurons enabled RefMap to systematically fine-map genes and pathways associated with ALS. As a significant extension of the known genetic architecture of ALS, we identified a group of 690 candidate ALS genes, which is enriched with previously discovered risk genes. Extensive conservation, transcriptome and network analyses demonstrated the functional significance of these candidate genes in motor neurons and disease progression. In particular, we observed a genetic convergence on the distal axon, which supports the prevailing view of ALS as a distal axonopathy. Of the new ALS genes we discovered, we further characterized KANK1 that is enriched with coding and noncoding, common and rare ALS-associated genetic variation. Modelling patient mutations in human neurons reduced KANK1 expression and produced neurotoxicity with disruption of the distal axon. RefMap can be applied broadly to increase the discovery power in genetic association studies of human complex traits and diseases.

scholarly journals Evidence for GRN as part of a neuroinflammatory mechanism connecting common neurodegenerative diseases

2020 ◽  
Author(s):  
Mike A. Nalls ◽  
Cornelis Blauwendraat ◽  
Lana Sargent ◽  
Dan Vitale ◽  
Hampton Leonard ◽  
...  
Keyword(s):  
Amyotrophic Lateral Sclerosis ◽  
Neurodegenerative Diseases ◽  
Genetic Risk ◽  
Association Studies ◽  
Molecular Data ◽  
Genome Wide Association Studies ◽  
Data Types ◽  
Genome Wide ◽  
Trait Locus ◽  
Lateral Sclerosis

SUMMARYBackgroundPrevious research using genome wide association studies (GWAS) has identified variants that may contribute to lifetime risk of multiple neurodegenerative diseases. However, whether there are common mechanisms that link neurodegenerative diseases is uncertain. Here, we focus on one gene, GRN, encoding progranulin, and the potential mechanistic interplay between genetic risk, gene expression in the brain and inflammation across multiple common neurodegenerative diseases.MethodsWe utilized GWAS, expression quantitative trait locus (eQTL) mapping and Bayesian colocalization analyses to evaluate potential causal and mechanistic inferences. We integrate various molecular data types from public resources to infer disease connectivity and shared mechanisms using a data driven process.FindingseQTL analyses combined with GWAS identified significant functional associations between increasing genetic risk in the GRN region and decreased expression of the gene in Parkinson’s, Alzheimer’s and amyotrophic lateral sclerosis. Additionally, colocalization analyses show a connection between blood based inflammatory biomarkers relating to platelets and GRN expression in the frontal cortex.InterpretationGRN expression mediates neuroinflammation function related to general neurodegeneration. This analysis suggests shared mechanisms for Parkinson’s, Alzheimer’s and amyotrophic lateral sclerosis.FundingNational Institute on Aging, National Institute of Neurological Disorders and Stroke, and the Michael J. Fox Foundation.

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

2020 ◽  
Vol 11 ◽  
Author(s):  
Lishun Xiao ◽  
Zhongshang Yuan ◽  
Siyi Jin ◽  
Ting Wang ◽  
Shuiping Huang ◽  
...  
Keyword(s):  
Amyotrophic Lateral Sclerosis ◽  
Type I Error ◽  
Association Studies ◽  
Type I ◽  
Genome Wide Association Studies ◽  
Combination Strategy ◽  
New Genes ◽  
Genome Wide ◽  
Causal Genes ◽  
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.

scholarly journals Evidence for GRN connecting multiple neurodegenerative diseases

2021 ◽  
Author(s):  
Mike A Nalls ◽  
Cornelis Blauwendraat ◽  
Lana Sargent ◽  
Dan Vitale ◽  
Hampton Leonard ◽  
...  
Keyword(s):  
Quantitative Trait Locus ◽  
Amyotrophic Lateral Sclerosis ◽  
Neurodegenerative Diseases ◽  
Genetic Risk ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Trait Locus ◽  
Lateral Sclerosis

Abstract Previous research using genome wide association studies has identified variants that may contribute to lifetime risk of multiple neurodegenerative diseases. However, whether there are common mechanisms that link neurodegenerative diseases is uncertain. Here, we focus on one gene, GRN, encoding progranulin, and the potential mechanistic interplay between genetic risk, gene expression in the brain and inflammation across multiple common neurodegenerative diseases. We utilized genome wide association studies, expression quantitative trait locus mapping and Bayesian colocalization analyses to evaluate potential causal and mechanistic inferences. We integrate various molecular data types from public resources to infer disease connectivity and shared mechanisms using a data driven process. Expression quantitative trait locus analyses combined with genome wide association studies identified significant functional associations between increasing genetic risk in the GRN region and decreased expression of the gene in Parkinson’s, Alzheimer’s and amyotrophic lateral sclerosis. Additionally, colocalization analyses show a connection between blood based inflammatory biomarkers relating to platelets and GRN expression in the frontal cortex. GRN expression mediates neuroinflammation function related to multiple neurodegenerative diseases. This analysis suggests shared mechanisms for Parkinson’s, Alzheimer’s and amyotrophic lateral sclerosis.

scholarly journals Genome-wide genetic links between amyotrophic lateral sclerosis and autoimmune diseases

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Chun Yu Li ◽  
Tian Mi Yang ◽  
Ru Wei Ou ◽  
Qian Qian Wei ◽  
Hui Fang Shang
Keyword(s):  
Amyotrophic Lateral Sclerosis ◽  
Autoimmune Diseases ◽  
Genetic Correlation ◽  
Functional Enrichment ◽  
Genome Wide Association Studies ◽  
Risk Genes ◽  
Genome Wide ◽  
Shared Risk ◽  
Lateral Sclerosis ◽  
Shared Genetic

Abstract Background Epidemiological and clinical studies have suggested comorbidity between amyotrophic lateral sclerosis (ALS) and autoimmune disorders. However, little is known about their shared genetic architecture. Methods To examine the relation between ALS and 10 autoimmune diseases, including asthma, celiac disease (CeD), Crohn’s disease (CD), inflammatory bowel disease (IBD), multiple sclerosis (MS), psoriasis, rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), type 1 diabetes (T1D), and ulcerative colitis (UC), and identify shared risk loci, we first estimated the genetic correlation using summary statistics from genome-wide association studies, and then analyzed the genetic enrichment leveraging the conditional false discovery rate statistical method. Results We identified a significant positive genetic correlation between ALS and CeD, MS, RA, and SLE, as well as a significant negative genetic correlation between ALS and IBD, UC, and CD. Robust genetic enrichment was observed between ALS and CeD and MS, and moderate enrichment was found between ALS and UC and T1D. Thirteen shared genetic loci were identified, among which five were suggestively significant in another ALS GWAS, namely rs3828599 (GPX3), rs3849943 (C9orf72), rs7154847 (G2E3), rs6571361 (SCFD1), and rs9903355 (GGNBP2). By integrating cis-expression quantitative trait loci analyses in Braineac and GTEx, we further identified GGNBP2, ATXN3, and SLC9A8 as novel ALS risk genes. Functional enrichment analysis indicated that the shared risk genes were involved in four pathways including membrane trafficking, vesicle-mediated transport, ER to Golgi anterograde transport, and transport to the Golgi and subsequent modification. Conclusions Our findings demonstrate a specific genetic correlation between ALS and autoimmune diseases and identify shared risk loci, including three novel ALS risk genes. These results provide a better understanding for the pleiotropy of ALS and have implications for future therapeutic trials.

scholarly journals Leukocyte telomere length and amyotrophic lateral sclerosis: a Mendelian randomization study

2021 ◽  
Author(s):  
Kailin Xia ◽  
Linjing Zhang ◽  
Gan Zhang ◽  
Yajun Wang ◽  
Tao Huang ◽  
...  
Keyword(s):  
Amyotrophic Lateral Sclerosis ◽  
Telomere Length ◽  
Causal Relationship ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Sensitivity Analyses ◽  
Genome Wide Association Studies ◽  
Leukocyte Telomere Length ◽  
Weighted Median ◽  
Lateral Sclerosis

Abstract Background Observational studies have suggested that telomere length is associated with amyotrophic lateral sclerosis (ALS). However, it remains unclear whether this association is causal. We employed a two-sample Mendelian randomization (MR) approach to explore the causal relationship between leukocyte telomere length (LTL) and ALS based on the most cited and most recent and largest LTL genome-wide association studies (GWASs) that measured LTL with the Southern blot method (n = 9190) and ALS GWAS summary data (n = 80,610). We adopted the inverse variance weighted (IVW) method to examine the effect of LTL on ALS and used the weighted median method, simple median method, MR Egger method and MR PRESSO method to perform sensitivity analyses. Results We found that genetically determined longer LTL was inversely associated with the risk of ALS (OR = 0.846, 95% CI: 0.744–0.962, P = 0.011), which was mainly driven by rs940209 in the OBFC1 gene, suggesting a potential effect of OBFC1 on ALS. In sensitivity analyses, that was confirmed in MR Egger method (OR = 0.647,95% CI = 0.447–0.936, P = 0.050), and a similar trend was shown with the weighted median method (OR = 0.893, P = 0.201) and simple median method (OR = 0.935 P = 0.535). The MR Egger analyses did not suggest directional pleiotropy, showing an intercept of 0.025 (P = 0.168). Neither the influence of instrumental outliers nor heterogeneity was found. Conclusions Our results suggest that genetically predicted longer LTL has a causal relationship with a lower risk of ALS and underscore the importance of protecting against telomere loss in ALS.

scholarly journals Genetics of Atrial Fibrillation in 2020

2020 ◽  
Vol 127 (1) ◽  
pp. 21-33 ◽  
Author(s):  
Carolina Roselli ◽  
Michiel Rienstra ◽  
Patrick T. Ellinor
Keyword(s):  
Atrial Fibrillation ◽  
Complex Disease ◽  
Association Studies ◽  
Heart Rhythm ◽  
Genome Wide Association Studies ◽  
Future Directions ◽  
Genetics Research ◽  
Genome Wide ◽  
Increased Risk ◽  
Rhythm Disorder

Atrial fibrillation is a common heart rhythm disorder that leads to an increased risk for stroke and heart failure. Atrial fibrillation is a complex disease with both environmental and genetic risk factors that contribute to the arrhythmia. Over the last decade, rapid progress has been made in identifying the genetic basis for this common condition. In this review, we provide an overview of the primary types of genetic analyses performed for atrial fibrillation, including linkage studies, genome-wide association studies, and studies of rare coding variation. With these results in mind, we aim to highlighting the existing knowledge gaps and future directions for atrial fibrillation genetics research.

Microglia in Brain Development, Homeostasis, and Neurodegeneration

2019 ◽  
Vol 53 (1) ◽  
pp. 263-288 ◽  
Author(s):  
Christopher J. Bohlen ◽  
Brad A. Friedman ◽  
Borislav Dejanovic ◽  
Morgan Sheng
Keyword(s):  
Alzheimer Disease ◽  
Brain Development ◽  
Neurodegenerative Disease ◽  
Human Genetics ◽  
Association Studies ◽  
Therapeutic Interventions ◽  
Genome Wide Association Studies ◽  
Expression Studies ◽  
Genome Wide ◽  
Gene Expression Studies

Advances in human genetics have implicated a growing number of genes in neurodegenerative diseases, providing insight into pathological processes. For Alzheimer disease in particular, genome-wide association studies and gene expression studies have emphasized the pathogenic contributions from microglial cells and motivated studies of microglial function/dysfunction. Here, we summarize recent genetic evidence for microglial involvement in neurodegenerative disease with a focus on Alzheimer disease, for which the evidence is most compelling. To provide context for these genetic discoveries, we discuss how microglia influence brain development and homeostasis, how microglial characteristics change in disease, and which microglial activities likely influence the course of neurodegeneration. In all, we aim to synthesize varied aspects of microglial biology and highlight microglia as possible targets for therapeutic interventions in neurodegenerative disease.

scholarly journals Statistical challenges for genome-wide association studies of suicidality using family data

2010 ◽  
Vol 25 (5) ◽  
pp. 307-309 ◽  
Author(s):  
J. Lasky-Su ◽  
C. Lange
Keyword(s):  
Association Studies ◽  
Statistical Tests ◽  
Genetic Association Studies ◽  
Genetic Effect ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genetic Etiology ◽  
Genome Wide ◽  
Family Based ◽  
Study Designs

AbstractThe etiology of suicide is complex in nature with both environmental and genetic causes that are extremely diverse. This extensive heterogeneity weakens the relationship between genotype and phenotype and as a result, we face many challenges when studying the genetic etiology of suicide. We are now in the midst of a genetics revolution, where genotyping costs are decreasing and genotyping speed is increasing at a fast rate, allowing genetic association studies to genotype thousands to millions of SNPs that cover the entire human genome. As such, genome-wide association studies (GWAS) are now the norm. In this article we address several statistical challenges that occur when studying the genetic etiology of suicidality in the age of the genetics revolution. These challenges include: (1) the large number of statistical tests; (2) complex phenotypes that are difficult to quantify; and (3) modest genetic effect sizes. We address these statistical issues in the context of family-based study designs. Specifically, we discuss several statistical extensions of family-based association tests (FBATs) that work to alleviate these challenges. As our intention is to describe how statistical methodology may work to identify disease variants for suicidality, we avoid the mathematical details of the methodologies presented.

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