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      Gga3 deletion and a GGA3 rare variant associated with late onset Alzheimer’s disease trigger BACE1 accumulation in axonal swellings

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          Abstract

          Axonal dystrophy, indicative of perturbed axonal transport, occurs early during Alzheimer’s disease (AD) pathogenesis. Little is known about the mechanisms underlying this initial sign of the pathology. This study proves that Golgi-localized γ-ear-containing ARF binding protein 3 (GGA3) loss of function, due to Gga3 genetic deletion or a GGA3 rare variant that cosegregates with late-onset AD, disrupts the axonal trafficking of the β-site APP-cleaving enzyme 1 (BACE1) resulting in its accumulation in axonal swellings in cultured neurons and in vivo. We show that BACE pharmacological inhibition ameliorates BACE1 axonal trafficking and diminishes axonal dystrophies in Gga3 null neurons in vitro and in vivo. These data indicate that axonal accumulation of BACE1 engendered by GGA3 loss of function results in local toxicity leading to axonopathy. Gga3 deletion exacerbates axonal dystrophies in a mouse model of AD before β-amyloid (Aβ) deposition. Our study strongly supports a role for GGA3 in AD pathogenesis, where GGA3 loss of function triggers BACE1 axonal accumulation independently of extracellular Aβ, and initiates a cascade of events leading to the axonal damage distinctive of the early stage of AD.

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          Is Open Access

          A global reference for human genetic variation

          The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.
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            A guided tour into subcellular colocalization analysis in light microscopy.

            It is generally accepted that the functional compartmentalization of eukaryotic cells is reflected by the differential occurrence of proteins in their compartments. The location and physiological function of a protein are closely related; local information of a protein is thus crucial to understanding its role in biological processes. The visualization of proteins residing on intracellular structures by fluorescence microscopy has become a routine approach in cell biology and is increasingly used to assess their colocalization with well-characterized markers. However, image-analysis methods for colocalization studies are a field of contention and enigma. We have therefore undertaken to review the most currently used colocalization analysis methods, introducing the basic optical concepts important for image acquisition and subsequent analysis. We provide a summary of practical tips for image acquisition and treatment that should precede proper colocalization analysis. Furthermore, we discuss the application and feasibility of colocalization tools for various biological colocalization situations and discuss their respective strengths and weaknesses. We have created a novel toolbox for subcellular colocalization analysis under ImageJ, named JACoP, that integrates current global statistic methods and a novel object-based approach.
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              Genome-wide meta-analysis identifies new loci and functional pathways influencing Alzheimer’s disease risk

              Alzheimer's disease (AD) is highly heritable and recent studies have identified over 20 disease-associated genomic loci. Yet these only explain a small proportion of the genetic variance, indicating that undiscovered loci remain. Here, we performed a large genome-wide association study of clinically diagnosed AD and AD-by-proxy (71,880 cases, 383,378 controls). AD-by-proxy, based on parental diagnoses, showed strong genetic correlation with AD (rg = 0.81). Meta-analysis identified 29 risk loci, implicating 215 potential causative genes. Associated genes are strongly expressed in immune-related tissues and cell types (spleen, liver, and microglia). Gene-set analyses indicate biological mechanisms involved in lipid-related processes and degradation of amyloid precursor proteins. We show strong genetic correlations with multiple health-related outcomes, and Mendelian randomization results suggest a protective effect of cognitive ability on AD risk. These results are a step forward in identifying the genetic factors that contribute to AD risk and add novel insights into the neurobiology of AD.
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                Author and article information

                Contributors
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                Journal
                Science Translational Medicine
                Sci. Transl. Med.
                American Association for the Advancement of Science (AAAS)
                1946-6234
                1946-6242
                November 18 2020
                November 18 2020
                November 18 2020
                November 18 2020
                : 12
                : 570
                : eaba1871
                Affiliations
                [1 ]Department of Neuroscience, Tufts University School of Medicine, Boston, MA 02111, USA.
                [2 ]Genetics and Aging Research Unit, MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA 02129, USA.
                [3 ]Department of Neuroscience, Merck & Co. Inc., Boston, MA 02115, USA.
                Article
                10.1126/scitranslmed.aba1871
                33208500
                ca8ac85b-e3ba-4645-9efe-5decb33b235e
                © 2020

                https://www.sciencemag.org/about/science-licenses-journal-article-reuse

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