Advances in the Genetics and Epigenetics of Neurodegenerative Diseases

2013 ◽  
Vol 1 (1) ◽  
Author(s):  
Fabio Coppedè
Keyword(s):  
Neurodegenerative Diseases ◽  
Trinucleotide Repeat ◽  
Association Studies ◽  
Genetic Association Studies ◽  
Motor Impairments ◽  
Monogenic Disorder ◽  
Causative Gene ◽  
Complex Disorders ◽  
Genome Wide ◽  
Lateral Sclerosis

AbstractAlzheimer’s disease (AD), Parkinson’s disease (PD), amyotrophic lateral sclerosis (ALS) and Huntington’s disease (HD) represent four of the major neurodegenerative diseases. AD, PD and ALS are complex disorders including both Mendelian and sporadic forms. Studies on families with these diseases led to the identification of several genes and pathways responsible for the familial forms. Those studies have been paralleled by hundreds of genetic association studies, including genome-wide screenings, in order to identify genes likely contributing to the sporadic forms. HD is a monogenic disorder caused by a trinucleotide repeat expansion in the causative gene. Increasing evidence points to an epigenetic contribution to neurodegeneration, suggesting that DNA methylation, histone tail modifications and RNA mediated mechanisms might contribute to the onset and progression of all the above diseases. In addition, epigenetic drugs are promising for the restoration of memory and motor impairments in animal models of the diseases. The aim of this review article is to provide an updated overview of the genetics and epigenetics of these major neurodegenerative disorders.

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 Investigating Casual Associations among Gut Microbiota, Metabolites and Neurodegenerative Diseases: A Mendelian Randomization Study

2021 ◽  
Author(s):  
Jin-Tai Yu ◽  
Jing Ning ◽  
Shu-Yi Huang ◽  
Shi-Dong Chen ◽  
Yu-Xiang Yang ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Neurodegenerative Diseases ◽  
Protective Factor ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Causal Relationships ◽  
Genome Wide ◽  
Underlying Mechanisms ◽  
Lateral Sclerosis

Abstract Background Recent studies had explored that the gut microbiota was associated with neurodegenerative diseases (including Alzheimer’s disease (AD), Parkinson’s disease (PD) and amyotrophic lateral sclerosis (ALS)) through the gut-brain axis, among which metabolic pathways played an important role. However, the underlying causality remained unclear. Our study aimed to evaluate potential causal relationships between gut microbiota, metabolites and neurodegenerative diseases through Mendelian randomization (MR) approach. Methods We selected genetic variants associated with gut microbiota traits (N = 18340) and gut microbiota-derived metabolites (N = 7824) from genome-wide association studies (GWASs). Summary statistics of neurodegenerative diseases were obtained from IGAP (AD: 17008 cases; 37154 controls), IPDGC (PD: 37 688 cases; 141779 controls) and IALSC (ALS: 20806 cases; 59804 controls) respectively. Results A total of 19 gut microbiota traits were found to be causally associated with risk of neurodegenerative diseases, including 1 phylum, 2 classes, 2 orders, 2 families and 12 genera. We found genetically predicted greater abundance of Ruminococcus, at genus level (OR:1.245, 95%CI:1.103,1.405; P = 0.0004) was significantly related to higher risk of ALS. We also found suggestive association between 12 gut microbiome-dependent metabolites and neurodegenerative diseases. For serotonin pathway, our results revealed serotonin as protective factor of PD, and kynurenine as risk factor of ALS. Besides, reduction of glutamine was found causally associated with occurrence of AD. Conclusions Our study firstly applied a two-sample MR approach to detect causal relationships among gut microbiota, gut metabolites and the risk of AD, PD and ALS, and we revealed several causal relationships. These findings may provide new targets for treatment of these neurodegenerative diseases, and may offer valuable insights for further researches on the underlying mechanisms.

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 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 Evaluation of genome-wide power of genetic association studies based on empirical data from the HapMap project

2007 ◽  
Vol 16 (20) ◽  
pp. 2494-2505 ◽  
Author(s):  
Yasuhito Nannya ◽  
Kenjiro Taura ◽  
Mineo Kurokawa ◽  
Shigeru Chiba ◽  
Seishi Ogawa
Keyword(s):  
Genetic Association ◽  
Empirical Data ◽  
Association Studies ◽  
Genetic Association Studies ◽  
Hapmap Project ◽  
Genome Wide

scholarly journals Anthocyanins and Their Metabolites as Therapeutic Agents for Neurodegenerative Disease

Antioxidants ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 333 ◽  
Author(s):  
Aimee N. Winter ◽  
Paula C. Bickford
Keyword(s):  
Neurodegenerative Diseases ◽  
Nitrosative Stress ◽  
Therapeutic Potential ◽  
Stress Protein ◽  
Motor Impairments ◽  
Oxidative And Nitrosative Stress ◽  
Beneficial Effects ◽  
Neuronal Populations ◽  
Neurodegenerative Process ◽  
Lateral Sclerosis

Neurodegenerative diseases, including Alzheimer’s disease, Parkinson’s disease, and amyotrophic lateral sclerosis (ALS), are characterized by the death of neurons within specific regions of the brain or spinal cord. While the etiology of many neurodegenerative diseases remains elusive, several factors are thought to contribute to the neurodegenerative process, such as oxidative and nitrosative stress, excitotoxicity, endoplasmic reticulum stress, protein aggregation, and neuroinflammation. These processes culminate in the death of vulnerable neuronal populations, which manifests symptomatically as cognitive and/or motor impairments. Until recently, most treatments for these disorders have targeted single aspects of disease pathology; however, this strategy has proved largely ineffective, and focus has now turned towards therapeutics which target multiple aspects underlying neurodegeneration. Anthocyanins are unique flavonoid compounds that have been shown to modulate several of the factors contributing to neuronal death, and interest in their use as therapeutics for neurodegeneration has grown in recent years. Additionally, due to observations that the bioavailability of anthocyanins is low relative to that of their metabolites, it has been proposed that anthocyanin metabolites may play a significant part in mediating the beneficial effects of an anthocyanin-rich diet. Thus, in this review, we will explore the evidence evaluating the neuroprotective and therapeutic potential of anthocyanins and their common metabolites for treating neurodegenerative diseases.

scholarly journals Molecular Variants in Human Trace Amine-Associated Receptors and Their Implications in Mental and Metabolic Disorders

2019 ◽  
Vol 40 (2) ◽  
pp. 239-255 ◽  
Author(s):  
Grazia Rutigliano ◽  
Riccardo Zucchi
Keyword(s):  
Genetic Variants ◽  
Affective Disorders ◽  
Metabolic Disorders ◽  
Association Studies ◽  
Single Gene ◽  
Genome Wide Association Studies ◽  
Complex Disorders ◽  
Linkage Analyses ◽  
Genome Wide ◽  
Trace Amine

Abstract We provide a comprehensive review of the available evidence on the pathophysiological implications of genetic variants in the human trace amine-associated receptor (TAAR) superfamily. Genes coding for trace amine-associated receptors (taars) represent a multigene family of G-protein-coupled receptors, clustered to a small genomic region of 108 kb located in chromosome 6q23, which has been consistently identified by linkage analyses as a susceptibility locus for schizophrenia and affective disorders. Most TAARs are expressed in brain areas involved in emotions, reward and cognition. TAARs are activated by endogenous trace amines and thyronamines, and evidence for a modulatory action on other monaminergic systems has been reported. Therefore, linkage analyses were followed by fine mapping association studies in schizophrenia and affective disorders. However, none of these reports has received sufficient universal replication, so their status remains uncertain. Single nucleotide polymorphisms in taars have emerged as susceptibility loci from genome-wide association studies investigating migraine and brain development, but none of the detected variants reached the threshold for genome-wide significance. In the last decade, technological advances enabled single-gene or whole-exome sequencing, thus allowing the detection of rare genetic variants, which may have a greater impact on the risk of complex disorders. Using these approaches, several taars (especially taar1) variants have been detected in patients with mental and metabolic disorders, and in some cases, defective receptor function has been demonstrated in vitro. Finally, with the use of transcriptomic and peptidomic techniques, dysregulations of TAARs (especially TAAR6) have been identified in brain disorders characterized by cognitive impairment.

scholarly journals Concordance of genetic risk across migraine subgroups: Impact on current and future genetic association studies

Cephalalgia ◽  
2014 ◽  
Vol 35 (6) ◽  
pp. 489-499 ◽  
Author(s):  
Dale R Nyholt ◽  
Verneri Anttila ◽  
Bendik S Winsvold ◽  
Tobias Kurth ◽  
Hreinn Stefansson ◽  
...  
Keyword(s):  
Genetic Risk ◽  
Association Studies ◽  
Meta Analysis ◽  
Genetic Association Studies ◽  
Population Based ◽  
Significant Heterogeneity ◽  
Single Nucleotide ◽  
Disease Spectrum ◽  
Genome Wide ◽  
Genetic Overlap

Background There has been intensive debate whether migraine with aura (MA) and migraine without aura (MO) should be considered distinct subtypes or part of the same disease spectrum. There is also discussion to what extent migraine cases collected in specialised headache clinics differ from cases from population cohorts, and how female cases differ from male cases with respect to their migraine. To assess the genetic overlap between these migraine subgroups, we examined genome-wide association (GWA) results from analysis of 23,285 migraine cases and 95,425 population-matched controls. Methods Detailed heterogeneity analysis of single-nucleotide polymorphism (SNP) effects (odds ratios) between migraine subgroups was performed for the 12 independent SNP loci significantly associated ( p < 5 × 10−8; thus surpassing the threshold for genome-wide significance) with migraine susceptibility. Overall genetic overlap was assessed using SNP effect concordance analysis (SECA) at over 23,000 independent SNPs. Results Significant heterogeneity of SNP effects ( phet < 1.4 × 10−3) was observed between the MA and MO subgroups (for SNP rs9349379), and between the clinic- and population-based subgroups (for SNPs rs10915437, rs6790925 and rs6478241). However, for all 12 SNPs the risk-increasing allele was the same, and SECA found the majority of genome-wide SNP effects to be in the same direction across the subgroups. Conclusions Any differences in common genetic risk across these subgroups are outweighed by the similarities. Meta-analysis of additional migraine GWA datasets, regardless of their major subgroup composition, will identify new susceptibility loci for migraine.

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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