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      Dissecting the clinical heterogeneity of early-onset Alzheimer’s disease

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          Abstract

          Early-onset Alzheimer’s disease (EOAD) is a rare but particularly devastating form of AD. Though notable for its high degree of clinical heterogeneity, EOAD is defined by the same neuropathological hallmarks underlying the more common, late-onset form of AD. In this review, we describe the various clinical syndromes associated with EOAD, including the typical amnestic phenotype as well as atypical variants affecting visuospatial, language, executive, behavioral, and motor functions. We go on to highlight advances in fluid biomarker research and describe how molecular, structural, and functional neuroimaging can be used not only to improve EOAD diagnostic acumen but also enhance our understanding of fundamental pathobiological changes occurring years (and even decades) before the onset of symptoms. In addition, we discuss genetic variation underlying EOAD, including pathogenic variants responsible for the well-known mendelian forms of EOAD as well as variants that may increase risk for the much more common forms of EOAD that are either considered to be sporadic or lack a clear autosomal-dominant inheritance pattern. Intriguingly, specific pathogenic variants in PRNP and MAPT—genes which are more commonly associated with other neurodegenerative diseases—may provide unexpectedly important insights into the formation of AD tau pathology. Genetic analysis of the atypical clinical syndromes associated with EOAD will continue to be challenging given their rarity, but integration of fluid biomarker data, multimodal imaging, and various ‘omics techniques and their application to the study of large, multicenter cohorts will enable future discoveries of fundamental mechanisms underlying the development of EOAD and its varied clinical presentations.

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          The diagnosis of dementia due to Alzheimer's disease: Recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease

          The National Institute on Aging and the Alzheimer's Association charged a workgroup with the task of revising the 1984 criteria for Alzheimer's disease (AD) dementia. The workgroup sought to ensure that the revised criteria would be flexible enough to be used by both general healthcare providers without access to neuropsychological testing, advanced imaging, and cerebrospinal fluid measures, and specialized investigators involved in research or in clinical trial studies who would have these tools available. We present criteria for all-cause dementia and for AD dementia. We retained the general framework of probable AD dementia from the 1984 criteria. On the basis of the past 27 years of experience, we made several changes in the clinical criteria for the diagnosis. We also retained the term possible AD dementia, but redefined it in a manner more focused than before. Biomarker evidence was also integrated into the diagnostic formulations for probable and possible AD dementia for use in research settings. The core clinical criteria for AD dementia will continue to be the cornerstone of the diagnosis in clinical practice, but biomarker evidence is expected to enhance the pathophysiological specificity of the diagnosis of AD dementia. Much work lies ahead for validating the biomarker diagnosis of AD dementia. Copyright © 2011. Published by Elsevier Inc.
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            The STRING database in 2021: customizable protein–protein networks, and functional characterization of user-uploaded gene/measurement sets

            Abstract Cellular life depends on a complex web of functional associations between biomolecules. Among these associations, protein–protein interactions are particularly important due to their versatility, specificity and adaptability. The STRING database aims to integrate all known and predicted associations between proteins, including both physical interactions as well as functional associations. To achieve this, STRING collects and scores evidence from a number of sources: (i) automated text mining of the scientific literature, (ii) databases of interaction experiments and annotated complexes/pathways, (iii) computational interaction predictions from co-expression and from conserved genomic context and (iv) systematic transfers of interaction evidence from one organism to another. STRING aims for wide coverage; the upcoming version 11.5 of the resource will contain more than 14 000 organisms. In this update paper, we describe changes to the text-mining system, a new scoring-mode for physical interactions, as well as extensive user interface features for customizing, extending and sharing protein networks. In addition, we describe how to query STRING with genome-wide, experimental data, including the automated detection of enriched functionalities and potential biases in the user's query data. The STRING resource is available online, at https://string-db.org/.
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              Clinical diagnosis of Alzheimer's disease: Report of the NINCDS-ADRDA Work Group* under the auspices of Department of Health and Human Services Task Force on Alzheimer's Disease

              Neurology, 34(7), 939-939
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                Author and article information

                Contributors
                jennifer.yokoyama@ucsf.edu
                Journal
                Mol Psychiatry
                Mol Psychiatry
                Molecular Psychiatry
                Nature Publishing Group UK (London )
                1359-4184
                1476-5578
                7 April 2022
                7 April 2022
                2022
                : 27
                : 6
                : 2674-2688
                Affiliations
                [1 ]GRID grid.266102.1, ISNI 0000 0001 2297 6811, Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, , University of California, San Francisco, ; San Francisco, CA 94158 USA
                [2 ]GRID grid.266102.1, ISNI 0000 0001 2297 6811, Department of Radiology and Biomedical Imaging, , University of California, San Francisco, ; San Francisco, CA 94158 USA
                Author information
                http://orcid.org/0000-0003-2581-8100
                http://orcid.org/0000-0001-7274-2634
                Article
                1531
                10.1038/s41380-022-01531-9
                9156414
                35393555
                dc6ca329-f227-44b9-b4f2-17f0d8435c97
                © The Author(s) 2022

                Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 11 November 2021
                : 7 March 2022
                : 16 March 2022
                Funding
                Funded by: FundRef https://doi.org/10.13039/100000049, U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging);
                Award ID: AG062588
                Award ID: AG057234
                Award ID: AG062422
                Award ID: AG065501
                Award Recipient :
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging)
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging)
                Funded by: FundRef https://doi.org/10.13039/100000065, U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke (NINDS);
                Award ID: NS123985
                Award Recipient :
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute on Aging (U.S. National Institute on Aging)
                Categories
                Expert Review
                Custom metadata
                © The Author(s), under exclusive licence to Springer Nature Limited 2022

                Molecular medicine
                diseases,genetics,neuroscience
                Molecular medicine
                diseases, genetics, neuroscience

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