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      Impaired SorLA maturation and trafficking as a new mechanism for SORL1 missense variants in Alzheimer disease

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          Abstract

          The SorLA protein, encoded by the SORL1 gene, is a major player in Alzheimer’s disease (AD) pathophysiology. Functional and genetic studies demonstrated that SorLA deficiency results in increased production of Aβ peptides, and thus a higher risk of AD. A large number of SORL1 missense variants have been identified in AD patients, but their functional consequences remain largely undefined. Here, we identified a new pathophysiological mechanism, by which rare SORL1 missense variants identified in AD patients result in altered maturation and trafficking of the SorLA protein. An initial screening, based on the overexpression of 70 SorLA variants in HEK293 cells, revealed that 15 of them (S114R, R332W, G543E, S564G, S577P, R654W, R729W, D806N, Y934C, D1535N, D1545E, P1654L, Y1816C, W1862C, P1914S) induced a maturation and trafficking-deficient phenotype. Three of these variants (R332W, S577P, and R654W) and two maturation-competent variants (S124R and N371T) were further studied in details in CRISPR/Cas9-modified hiPSCs. When expressed at endogenous levels, the R332W, S577P, and R654W SorLA variants also showed a maturation defective profile. We further demonstrated that these variants were largely retained in the endoplasmic reticulum, resulting in a reduction in the delivery of SorLA mature protein to the plasma membrane and to the endosomal system. Importantly, expression of the R332W and R654W variants in hiPSCs was associated with a clear increase of Aβ secretion, demonstrating a loss-of-function effect of these SorLA variants regarding this ultimate readout, and a direct link with AD pathophysiology. Furthermore, structural analysis of the impact of missense variants on SorLA protein suggested that impaired cellular trafficking of SorLA protein could be due to subtle variations of the protein 3D structure resulting from changes in the interatomic interactions.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s40478-021-01294-4.

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          Most cited references42

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          Fiji: an open-source platform for biological-image analysis.

          Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.
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            UCSF Chimera--a visualization system for exploratory research and analysis.

            The design, implementation, and capabilities of an extensible visualization system, UCSF Chimera, are discussed. Chimera is segmented into a core that provides basic services and visualization, and extensions that provide most higher level functionality. This architecture ensures that the extension mechanism satisfies the demands of outside developers who wish to incorporate new features. Two unusual extensions are presented: Multiscale, which adds the ability to visualize large-scale molecular assemblies such as viral coats, and Collaboratory, which allows researchers to share a Chimera session interactively despite being at separate locales. Other extensions include Multalign Viewer, for showing multiple sequence alignments and associated structures; ViewDock, for screening docked ligand orientations; Movie, for replaying molecular dynamics trajectories; and Volume Viewer, for display and analysis of volumetric data. A discussion of the usage of Chimera in real-world situations is given, along with anticipated future directions. Chimera includes full user documentation, is free to academic and nonprofit users, and is available for Microsoft Windows, Linux, Apple Mac OS X, SGI IRIX, and HP Tru64 Unix from http://www.cgl.ucsf.edu/chimera/. Copyright 2004 Wiley Periodicals, Inc.
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              The mutational constraint spectrum quantified from variation in 141,456 humans

              Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes 1 . Here we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors. Using an improved model of human mutation rates, we classify human protein-coding genes along a spectrum that represents tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve the power of gene discovery for both common and rare diseases.
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                Author and article information

                Contributors
                anne.roveletlecrux@univ-rouen.fr
                Sebastien.Feuillette@univ-rouen.fr
                laetitia.miguel@univ-rouen.fr
                catherine.schramm@inserm.fr
                spernet@etud.univ-angers.fr
                olivier.quenez@inserm.fr
                isabelle.milazzo@univ-rouen.fr
                laure.guilhaudis@univ-rouen.fr
                stephane.rousseau@inserm.fr
                gaetan.riou@inserm.fr
                inserm.u1245@univ-rouen.fr
                dominique.campion@univ-rouen.fr
                gaelnicolas@hotmail.com
                magalie.lecourtois@univ-rouen.fr
                Journal
                Acta Neuropathol Commun
                Acta Neuropathol Commun
                Acta Neuropathologica Communications
                BioMed Central (London )
                2051-5960
                18 December 2021
                18 December 2021
                2021
                : 9
                : 196
                Affiliations
                [1 ]GRID grid.41724.34, ISNI 0000 0001 2296 5231, Department of Genetics and CNR-MAJ, , Normandie Univ, UNIROUEN, Inserm U1245, CHU Rouen, FHU G4 Génomique, ; 76000 Rouen, France
                [2 ]Laboratoire COBRA (UMR 6014 & FR 3038), Normandie Université, UNIROUEN, INSA de Rouen, CNRS, Rouen, France
                [3 ]GRID grid.503198.6, Inserm U1234, Flow Cytometry Core – IRIB, ; Rouen, France
                Author information
                http://orcid.org/0000-0003-4454-3659
                http://orcid.org/0000-0001-8042-2745
                http://orcid.org/0000-0002-7791-2900
                http://orcid.org/0000-0002-1185-8809
                http://orcid.org/0000-0002-1788-2965
                http://orcid.org/0000-0002-6212-9593
                http://orcid.org/0000-0001-5679-9737
                http://orcid.org/0000-0001-9391-7800
                http://orcid.org/0000-0002-4257-1974
                Article
                1294
                10.1186/s40478-021-01294-4
                8684260
                34922638
                e1b75be4-a910-49dc-9930-6bbdbb3ee0c5
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 10 November 2021
                : 15 November 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100003750, Association France Alzheimer;
                Award ID: AAPSM2019 – grant n°1957
                Award Recipient :
                Funded by: Fondation pour la Recherche médicale
                Award ID: grant # DEQ20170336711
                Award Recipient :
                Funded by: Fondation pour la recherche médicale
                Award ID: grant #ARF201909009263
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2021

                sorla,ipsc,alzheimer’s disease,maturation defects,trafficking

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