scholarly journals The Role of APOE and TREM2 in Alzheimer′s Disease—Current Understanding and Perspectives

2018 ◽  
Vol 20 (1) ◽  
pp. 81 ◽  
Author(s):  
Cody Wolfe ◽  
Nicholas Fitz ◽  
Kyong Nam ◽  
Iliya Lefterov ◽  
Radosveta Koldamova
Keyword(s):  
Genetic Risk ◽  
Late Onset ◽  
Association Studies ◽  
Cholesterol Homeostasis ◽  
Genome Wide Association Studies ◽  
Immune Functions ◽  
Binding Assays ◽  
Lipid Trafficking ◽  
Genome Wide ◽  
The Brain

Alzheimer’s disease (AD) is the leading cause of dementia worldwide. The extracellular deposits of Amyloid beta (Aβ) in the brain—called amyloid plaques, and neurofibrillary tangles—intracellular tau aggregates, are morphological hallmarks of the disease. The risk for AD is a complicated interplay between aging, genetic risk factors, and environmental influences. One of the Apolipoprotein E (APOE) alleles—APOEε4, is the major genetic risk factor for late-onset AD (LOAD). APOE is the primary cholesterol carrier in the brain, and plays an essential role in lipid trafficking, cholesterol homeostasis, and synaptic stability. Recent genome-wide association studies (GWAS) have identified other candidate LOAD risk loci, as well. One of those is the triggering receptor expressed on myeloid cells 2 (TREM2), which, in the brain, is expressed primarily by microglia. While the function of TREM2 is not fully understood, it promotes microglia survival, proliferation, and phagocytosis, making it important for cell viability and normal immune functions in the brain. Emerging evidence from protein binding assays suggests that APOE binds to TREM2 and APOE-containing lipoproteins in the brain as well as periphery, and are putative ligands for TREM2, thus raising the possibility of an APOE-TREM2 interaction modulating different aspects of AD pathology, potentially in an isoform-specific manner. This review is focusing on the interplay between APOE isoforms and TREM2 in association with AD pathology.

scholarly journals Alzheimer's disease-associated P460L mutation in ephrin receptor type A1 (EphA1) leads to dysregulated Rho-GTPase signaling

2021 ◽  
Author(s):  
Yoon Kim ◽  
Gorka Lasso ◽  
Hardik Patel ◽  
Badri Vardarajan ◽  
Ismael Santa-Maria ◽  
...  
Keyword(s):  
Rho Gtpase ◽  
Late Onset ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
The Brain ◽  
Receptor Tyrosine Kinase Family

Recently, late onset AD (LOAD) genome-wide association studies identified EphA1, a member of receptor tyrosine kinase family (RTK) as a disease associated loci. In the follow-up study where 3 independent LOAD cohorts were performed, a P460L coding mutation in EphA1 loci showed a significant association with LOAD. However, the role of EphA1 and P460L mutant EphA1 in AD is not fully understood. We have characterized this mutation biophysically and biochemically. Our structural in silico model and in vitro biochemical analysis demonstrate that EphA1-P460L mutation makes the receptor constitutively active suggesting a gain-of-toxic function leading to chronic EphA1 signaling in the brain. Moreover, we report that the EphA1 P460L variant triggers Rho-GTPase signaling dysregulation that could potentially contribute to spine morphology abnormalities and synaptic dysfunction observed in AD pathology.

scholarly journals Association analysis of juvenile idiopathic arthritis genetic susceptibility factors in Estonian patients

2021 ◽  
Author(s):  
Tiit Nikopensius ◽  
Priit Niibo ◽  
Toomas Haller ◽  
Triin Jagomägi ◽  
Ülle Voog-Oras ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Juvenile Idiopathic Arthritis ◽  
Autoimmune Diseases ◽  
Genetic Risk ◽  
Association Studies ◽  
Control Sample ◽  
Case Control ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

Abstract Background Juvenile idiopathic arthritis (JIA) is the most common chronic rheumatic condition of childhood. Genetic association studies have revealed several JIA susceptibility loci with the strongest effect size observed in the human leukocyte antigen (HLA) region. Genome-wide association studies have augmented the number of JIA-associated loci, particularly for non-HLA genes. The aim of this study was to identify new associations at non-HLA loci predisposing to the risk of JIA development in Estonian patients. Methods We performed genome-wide association analyses in an entire JIA case–control sample (All-JIA) and in a case–control sample for oligoarticular JIA, the most prevalent JIA subtype. The entire cohort was genotyped using the Illumina HumanOmniExpress BeadChip arrays. After imputation, 16,583,468 variants were analyzed in 263 cases and 6956 controls. Results We demonstrated nominal evidence of association for 12 novel non-HLA loci not previously implicated in JIA predisposition. We replicated known JIA associations in CLEC16A and VCTN1 regions in the oligoarticular JIA sample. The strongest associations in the All-JIA analysis were identified at PRKG1 (P = 2,54 × 10−6), LTBP1 (P = 9,45 × 10−6), and ELMO1 (P = 1,05 × 10−5). In the oligoarticular JIA analysis, the strongest associations were identified at NFIA (P = 5,05 × 10−6), LTBP1 (P = 9,95 × 10−6), MX1 (P = 1,65 × 10−5), and CD200R1 (P = 2,59 × 10−5). Conclusion This study increases the number of known JIA risk loci and provides additional evidence for the existence of overlapping genetic risk loci between JIA and other autoimmune diseases, particularly rheumatoid arthritis. The reported loci are involved in molecular pathways of immunological relevance and likely represent genomic regions that confer susceptibility to JIA in Estonian patients. Key Points• Juvenile idiopathic arthritis (JIA) is the most common childhood rheumatic disease with heterogeneous presentation and genetic predisposition.• Present genome-wide association study for Estonian JIA patients is first of its kind in Northern and Northeastern Europe.• The results of the present study increase the knowledge about JIA risk loci replicating some previously described associations, so adding weight to their relevance and describing novel loci.• The study provides additional evidence for the existence of overlapping genetic risk loci between JIA and other autoimmune diseases, particularly rheumatoid arthritis.

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 Age-related late-onset disease heritability patterns and implications for genome-wide association studies

2018 ◽  
Author(s):  
Roman Teo Oliynyk
Keyword(s):  
Old Age ◽  
Cumulative Incidence ◽  
Late Onset ◽  
Association Studies ◽  
Genome Wide Association ◽  
Risk Scores ◽  
Cerebral Stroke ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Genome Wide

AbstractBackgroundGenome-wide association studies and other computational biology techniques are gradually discovering the causal gene variants that contribute to late-onset human diseases. After more than a decade of genome-wide association study efforts, these can account for only a fraction of the heritability implied by familial studies, the so-called “missing heritability” problem.MethodsComputer simulations of polygenic late-onset diseases in an aging population have quantified the risk allele frequency decrease at older ages caused by individuals with higher polygenic risk scores becoming ill proportionately earlier. This effect is most prominent for diseases characterized by high cumulative incidence and high heritability, examples of which include Alzheimer’s disease, coronary artery disease, cerebral stroke, and type 2 diabetes.ResultsThe incidence rate for late-onset diseases grows exponentially for decades after early onset ages, guaranteeing that the cohorts used for genome-wide association studies overrepresent older individuals with lower polygenic risk scores, whose disease cases are disproportionately due to environmental causes such as old age itself. This mechanism explains the decline in clinical predictive power with age and the lower discovery power of familial studies of heritability and genome-wide association studies. It also explains the relatively constant-with-age heritability found for late-onset diseases of lower prevalence, exemplified by cancers.ConclusionsFor late-onset polygenic diseases showing high cumulative incidence together with high initial heritability, rather than using relatively old age-matched cohorts, study cohorts combining the youngest possible cases with the oldest possible controls may significantly improve the discovery power of genome-wide association studies.

scholarly journals Critical Analysis of Genome-Wide Association Studies: Triple Negative Breast Cancer Quae Exempli Causa

2020 ◽  
Vol 21 (16) ◽  
pp. 5835
Author(s):  
Maria-Ancuta Jurj ◽  
Mihail Buse ◽  
Alina-Andreea Zimta ◽  
Angelo Paradiso ◽  
Schuyler S. Korban ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Genetic Risk ◽  
Triple Negative ◽  
Cancer Susceptibility ◽  
Association Studies ◽  
Breast Cancer Susceptibility ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Genome Wide

Genome-wide association studies (GWAS) are useful in assessing and analyzing either differences or variations in DNA sequences across the human genome to detect genetic risk factors of diseases prevalent within a target population under study. The ultimate goal of GWAS is to predict either disease risk or disease progression by identifying genetic risk factors. These risk factors will define the biological basis of disease susceptibility for the purposes of developing innovative, preventative, and therapeutic strategies. As single nucleotide polymorphisms (SNPs) are often used in GWAS, their relevance for triple negative breast cancer (TNBC) will be assessed in this review. Furthermore, as there are different levels and patterns of linkage disequilibrium (LD) present within different human subpopulations, a plausible strategy to evaluate known SNPs associated with incidence of breast cancer in ethnically different patient cohorts will be presented and discussed. Additionally, a description of GWAS for TNBC will be presented, involving various identified SNPs correlated with miRNA sites to determine their efficacies on either prognosis or progression of TNBC in patients. Although GWAS have identified multiple common breast cancer susceptibility variants that individually would result in minor risks, it is their combined effects that would likely result in major risks. Thus, one approach to quantify synergistic effects of such common variants is to utilize polygenic risk scores. Therefore, studies utilizing predictive risk scores (PRSs) based on known breast cancer susceptibility SNPs will be evaluated. Such PRSs are potentially useful in improving stratification for screening, particularly when combining family history, other risk factors, and risk prediction models. In conclusion, although interpretation of the results from GWAS remains a challenge, the use of SNPs associated with TNBC may elucidate and better contextualize these studies.

scholarly journals Polygenic Susceptibility of Aortic Aneurysms Associates to the Diameter of the Aneurysm Sac: the Aneurysm-Express Biobank Cohort

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Constance J. H. C. M. van Laarhoven ◽  
Jessica van Setten ◽  
Joost A. van Herwaarden ◽  
Gerard Pasterkamp ◽  
Dominique P. V. de Kleijn ◽  
...  
Keyword(s):  
Genetic Risk ◽  
Association Studies ◽  
Significant Risk ◽  
Aortic Aneurysms ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Risk Variants ◽  
Genome Wide ◽  
Best Fit ◽  
Genetic Risk Variants

AbstractRecent genome-wide association studies (GWAS) have discovered ten genetic risk variants for abdominal aortic aneurysms (AAA). To what extent these genetic variants contribute to the pathology of aneurysms is yet unknown. The present study aims to investigate whether genetic risk variants are associated with three clinical features: diameter of aneurysm sac, type of artery and aneurysm related-symptoms in aortic and peripheral aneurysm patients. Aneurysm tissue of 415 patients included in the Aneurysm-Express biobank was used. A best-fit polygenic risk score (PRS) based on previous GWAS effect estimates was modeled for each clinical phenotype. The best-fit PRS (including 272 variants at PT = 0.01015) showed a significant correlation with aneurysm diameter (R2 = 0.019, p = 0.001). No polygenic association was found with clinical symptoms or artery type. In addition, the ten genome-wide significant risk variants for AAA were tested individually, but no associations were observed with any of the clinical phenotypes. All models were corrected for confounders and data was normalized. In conclusion, a weighted PRS of AAA susceptibility explained 1.9% of the phenotypic variation (p = 0.001) in diameter in aneurysm patients. Given our limited sample size, future biobank collaborations need to confirm a potential causal role of susceptibility variants on aneurysmal disease initiation and progression.

Genetic Methodologies and Applications

2017 ◽  
Author(s):  
Shaun M. Purcell
Keyword(s):  
Mental Illness ◽  
Genetic Risk ◽  
Genetic Basis ◽  
Common Mental Disorders ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
The Past ◽  
Genome Wide ◽  
Experimental Approaches ◽  
Large Families

Mental illness is highly heritable, yet it has been difficult historically to identify the specific genes that comprise that risk. This difficulty resides in the fact that the genetic risk for all common mental disorders is polygenic, with perhaps hundreds of genetic variations, each of small effect, contributing to the overall risk. Despite these challenges, the field has made dramatic advances over the past decade in beginning to understand the genetic basis of mental illness. This chapter provides an overview of the experimental approaches used, beginning with epidemiology and population genetics to define the heritability of an illness, to classic studies of large families and linkage disequilibrium analysis, to genome-wide investigations including genome-wide association studies (GWAS), exome sequencing, and whole genome sequencing. Increasingly, these genetic advances are being understood within the biological context of disease pathophysiology.

scholarly journals What is Next for the Genetics of Multiple Sclerosis?

2011 ◽  
Vol 2011 ◽  
pp. 1-3 ◽  
Author(s):  
Sreeram V. Ramagopalan ◽  
David A. Dyment
Keyword(s):  
Multiple Sclerosis ◽  
Genetic Risk ◽  
Neurological Disease ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
New Genes ◽  
Histocompatibility Complex ◽  
Genome Wide ◽  
The Common

We review here our current understanding of the genetic aetiology of the common complex neurological disease multiple sclerosis (MS). The strongest genetic risk factor for MS is the major histocompatibility complex which was identified in the 1970s. In 2011, after a number of genome-wide association studies have been completed and have identified approximately 20 new genes for MS, we ask the question—what is next for the genetics of MS?

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