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von Berg J, McArdle PF, Häppölä P, Haessler J, Kooperberg C, Lemmens R, Pezzini A, Thijs V, Pulit SL, Kittner SJ, Mitchell BD, de Ridder J, van der Laan SW. Evidence of survival bias in the association between APOE-Є4 and age at ischemic stroke onset. Front Genet 2024; 15:1392061. [PMID: 39286457 PMCID: PMC11403718 DOI: 10.3389/fgene.2024.1392061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Accepted: 06/18/2024] [Indexed: 09/19/2024] Open
Abstract
Introduction Large genome-wide association studies (GWASs) using case-control study designs have now identified tens of loci associated with ischemic stroke (IS). As a complement to these studies, we performed GWAS in a case-only design to identify loci influencing the age at onset (AAO) of ischemic stroke. Methods Analyses were conducted in a discovery cohort of 10,857 ischemic stroke cases using a linear regression framework. We meta-analyzed all SNPs with p-value <1 x 10-5 in a sexcombined or sex-stratified analysis using summary data from two additional replication cohorts. Results In the women-only meta-analysis, we detected significant evidence for the association of AAO with rs429358, an exonic variant in apolipoprotein E (APOE) that encodes for the APOE-Є4 allele. Each copy of the rs429358:T>C allele was associated with a 1.29-year earlier stroke AAO (meta p-value = 2.48 x 10-11). This APOE variant has previously been associated with increased mortality and ischemic stroke AAO. We hypothesized that the association with AAO may reflect a survival bias attributable to an age-related decrease in mortality among APOE-Є4 carriers and have no association to stroke AAO per se. A simulation study showed that a variant associated with overall mortality might indeed be detected with an AAO analysis. A variant with a 2-fold increase in mortality risk would lead to an observed effect of AAO that is comparable to what we found. Discussion In conclusion, we detected a robust association of the APOE locus with stroke AAO and provided simulations to suggest that this association may be unrelated to ischemic stroke per se but related to a general survival bias.
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Affiliation(s)
- Joanna von Berg
- Center for Molecular Medicine, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
- Oncode Institute, Utrecht, Netherlands
| | - Patrick F. McArdle
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Paavo Häppölä
- Institute for Molecular Medicine Finland FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
| | | | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, United States
| | - Robin Lemmens
- University Hospitals Leuven, Department of Neurology, Leuven, Belgium
- KU Leuven–University of Leuven, Department of Neurosciences, Experimental Neurology, Leuven, Belgium
| | - Alessandro Pezzini
- Department of Medicine and Surgery, University of Parma, Parma, Italy
- Stroke Care Program, Department of Emergency, Parma University Hospital, Parma, Italy
| | - Vincent Thijs
- Stroke Theme, The Florey, Heidelberg, VIC, Australia
- Department of Medicine, University of Melbourne, Melbourne, VIC, Australia
- Department of Neurology, Austin Health, Heidelberg, VIC, Australia
| | - Sara L. Pulit
- Center for Molecular Medicine, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Steven J. Kittner
- Geriatric Research and Education Clinical Center, VA Maryland Healthcare System, Baltimore, MD, United States
- Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Braxton D. Mitchell
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
- Geriatric Research and Education Clinical Center, VA Maryland Healthcare System, Baltimore, MD, United States
| | - Jeroen de Ridder
- Center for Molecular Medicine, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
- Oncode Institute, Utrecht, Netherlands
| | - Sander W. van der Laan
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
- Center of Population Health and Genomics, University of Virginia, Charlottesville, VA, United States
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2
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Oh S, Kim S, Lee JE, Park BY, Hye Won J, Park H. Multimodal analysis of disease onset in Alzheimer's disease using Connectome, Molecular, and genetics data. Neuroimage Clin 2024; 43:103660. [PMID: 39197213 PMCID: PMC11393605 DOI: 10.1016/j.nicl.2024.103660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2024] [Revised: 08/23/2024] [Accepted: 08/23/2024] [Indexed: 09/01/2024]
Abstract
Alzheimer's disease (AD) and its related age at onset (AAO) are highly heterogeneous, due to the inherent complexity of the disease. They are affected by multiple factors, such as neuroimaging and genetic predisposition. Multimodal integration of various data types is necessary; however, it has been nontrivial due to the high dimensionality of each modality. We aimed to identify multimodal biomarkers of AAO in AD using an extended version of sparse canonical correlation analysis, in which we integrated two imaging modalities, functional magnetic resonance imaging (fMRI) and positron emission tomography (PET), and genetic data in the form of single-nucleotide polymorphisms (SNPs) obtained from the Alzheimer's disease neuroimaging initiative database. These three modalities cover low-to-high-level complementary information and offer multiscale insights into the AAO. We identified multivariate markers of AAO in AD using fMRI, PET, and SNP. Furthermore, the markers identified were largely consistent with those reported in the existing literature. In particular, our serial mediation analysis suggests that genetic variants influence the AAO in AD by indirectly affecting brain connectivity by mediation of amyloid-beta protein accumulation, supporting a plausible path in existing research. Our approach provides comprehensive biomarkers related to AAO in AD and offers novel multimodal insights into AD.
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Affiliation(s)
- Sewook Oh
- Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, Republic of Korea
| | - Sunghun Kim
- Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, Republic of Korea; Department of Artificial Intelligence, Sungkyunkwan University, Suwon, Republic of Korea; Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea
| | - Jong-Eun Lee
- Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, Republic of Korea; Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea
| | - Bo-Yong Park
- Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea; Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea
| | - Ji Hye Won
- Department of Computer Engineering, Pukyong National University, Busan, Republic of Korea
| | - Hyunjin Park
- Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, Republic of Korea; Department of Artificial Intelligence, Sungkyunkwan University, Suwon, Republic of Korea; Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea.
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3
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Ferrer I. Alzheimer's Disease Neuropathological Change in Aged Non-Primate Mammals. Int J Mol Sci 2024; 25:8118. [PMID: 39125687 PMCID: PMC11311584 DOI: 10.3390/ijms25158118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2024] [Revised: 07/18/2024] [Accepted: 07/23/2024] [Indexed: 08/12/2024] Open
Abstract
Human brain aging is characterized by the production and deposition of β-amyloid (Aβ) in the form of senile plaques and cerebral amyloid angiopathy and the intracellular accumulation of hyper-phosphorylated tau (Hp-tau) to form neurofibrillary tangles (NFTs) and dystrophic neurites of senile plaques. The process progresses for years and eventually manifests as cognitive impairment and dementia in a subgroup of aged individuals. Aβ is produced and deposited first in the neocortex in most aged mammals, including humans; it is usually not accompanied by altered behavior and cognitive impairment. Hp-tau is less frequent than Aβ pathology, and NFTs are rare in most mammals. In contrast, NFTs are familiar from middle age onward in humans; NFTs first appear in the paleocortex and selected brain stem nuclei. NFTs precede for decades or years Aβ deposition and correlate with dementia in about 5% of individuals at the age of 65 and 25% at the age of 85. Based on these comparative data, (a) Aβ deposition is the most common Alzheimer's disease neuropathological change (ADNC) in the brain of aged mammals; (b) Hp-tau is less common, and NFTs are rare in most aged mammals; however, NFTs are the principal cytoskeletal pathology in aged humans; (c) NFT in aged humans starts in selected nuclei of the brain stem and paleocortical brain regions progressing to the most parts of the neocortex and other regions of the telencephalon; (d) human brain aging is unique among mammalian species due to the early appearance and dramatic progression of NFTs from middle age onward, matching with cognitive impairment and dementia in advanced cases; (e) neither mammalian nor human brain aging supports the concept of the amyloid cascade hypothesis.
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Affiliation(s)
- Isidro Ferrer
- Department of Pathology and Experimental Therapeutics, University of Barcelona, carrer Feixa Llarga sn, 08907 Hospitalet de Llobregat, Spain;
- Reial Acadèmia de Medicina de Catalunya, carrer del Carme 47, 08001 Barcelona, Spain
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4
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Mosquera-Heredia MI, Vidal OM, Morales LC, Silvera-Redondo C, Barceló E, Allegri R, Arcos-Burgos M, Vélez JI, Garavito-Galofre P. Long Non-Coding RNAs and Alzheimer's Disease: Towards Personalized Diagnosis. Int J Mol Sci 2024; 25:7641. [PMID: 39062884 PMCID: PMC11277322 DOI: 10.3390/ijms25147641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2024] [Revised: 07/06/2024] [Accepted: 07/08/2024] [Indexed: 07/28/2024] Open
Abstract
Alzheimer's disease (AD), a neurodegenerative disorder characterized by progressive cognitive decline, is the most common form of dementia. Currently, there is no single test that can diagnose AD, especially in understudied populations and developing countries. Instead, diagnosis is based on a combination of medical history, physical examination, cognitive testing, and brain imaging. Exosomes are extracellular nanovesicles, primarily composed of RNA, that participate in physiological processes related to AD pathogenesis such as cell proliferation, immune response, and neuronal and cardiovascular function. However, the identification and understanding of the potential role of long non-coding RNAs (lncRNAs) in AD diagnosis remain largely unexplored. Here, we clinically, cognitively, and genetically characterized a sample of 15 individuals diagnosed with AD (cases) and 15 controls from Barranquilla, Colombia. Advanced bioinformatics, analytics and Machine Learning (ML) techniques were used to identify lncRNAs differentially expressed between cases and controls. The expression of 28,909 lncRNAs was quantified. Of these, 18 were found to be differentially expressed and harbored in pivotal genes related to AD. Two lncRNAs, ENST00000608936 and ENST00000433747, show promise as diagnostic markers for AD, with ML models achieving > 95% sensitivity, specificity, and accuracy in both the training and testing datasets. These findings suggest that the expression profiles of lncRNAs could significantly contribute to advancing personalized AD diagnosis in this community, offering promising avenues for early detection and follow-up.
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Affiliation(s)
- Maria I. Mosquera-Heredia
- Department of Medicine, Universidad del Norte, Barranquilla 081007, Colombia; (M.I.M.-H.); (O.M.V.); (L.C.M.); (C.S.-R.)
| | - Oscar M. Vidal
- Department of Medicine, Universidad del Norte, Barranquilla 081007, Colombia; (M.I.M.-H.); (O.M.V.); (L.C.M.); (C.S.-R.)
| | - Luis C. Morales
- Department of Medicine, Universidad del Norte, Barranquilla 081007, Colombia; (M.I.M.-H.); (O.M.V.); (L.C.M.); (C.S.-R.)
| | - Carlos Silvera-Redondo
- Department of Medicine, Universidad del Norte, Barranquilla 081007, Colombia; (M.I.M.-H.); (O.M.V.); (L.C.M.); (C.S.-R.)
| | - Ernesto Barceló
- Instituto Colombiano de Neuropedagogía, Barranquilla 080020, Colombia;
- Department of Health Sciences, Universidad de La Costa, Barranquilla 080002, Colombia
- Grupo Internacional de Investigación Neuro-Conductual (GIINCO), Universidad de La Costa, Barranquilla 080002, Colombia
| | - Ricardo Allegri
- Institute for Neurological Research FLENI, Montañeses 2325, Buenos Aires C1428AQK, Argentina;
| | - Mauricio Arcos-Burgos
- Grupo de Investigación en Psiquiatría (GIPSI), Departamento de Psiquiatría, Instituto de Investigaciones Médicas, Facultad de Medicina, Universidad de Antioquia, Medellin 050010, Colombia;
| | - Jorge I. Vélez
- Department of Industrial Engineering, Universidad del Norte, Barranquilla 081007, Colombia
| | - Pilar Garavito-Galofre
- Department of Medicine, Universidad del Norte, Barranquilla 081007, Colombia; (M.I.M.-H.); (O.M.V.); (L.C.M.); (C.S.-R.)
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5
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Fessel J. Personalized, Precision Medicine to Cure Alzheimer's Dementia: Approach #1. Int J Mol Sci 2024; 25:3909. [PMID: 38612719 PMCID: PMC11012190 DOI: 10.3390/ijms25073909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2024] [Revised: 03/22/2024] [Accepted: 03/26/2024] [Indexed: 04/14/2024] Open
Abstract
The goal of the treatment for Alzheimer's dementia (AD) is the cure of dementia. A literature review revealed 18 major elements causing AD and 29 separate medications that address them. For any individual with AD, one is unlikely to discern which major causal elements produced dementia. Thus, for personalized, precision medicine, all causal elements must be treated so that each individual patient will have her or his causal elements addressed. Twenty-nine drugs cannot concomitantly be administered, so triple combinations of drugs taken from that list are suggested, and each triple combination can be administered sequentially, in any order. Ten combinations given over 13 weeks require 2.5 years, or if given over 26 weeks, they require 5.0 years. Such sequential treatment addresses all 18 elements and should cure dementia. In addition, any comorbid risk factors for AD whose first presence or worsening was within ±1 year of when AD first appeared should receive appropriate, standard treatment together with the sequential combinations. The article outlines a randomized clinical trial that is necessary to assess the safety and efficacy of the proposed treatments; it includes a triple-drug Rx for equipoise. Clinical trials should have durations of both 2.5 and 5.0 years unless the data safety monitoring board (DSMB) determines earlier success or futility since it is uncertain whether three or six months of treatment will be curative in humans, although studies in animals suggest that the briefer duration of treatment might be effective and restore defective neural tracts.
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Affiliation(s)
- Jeffrey Fessel
- Clinical Medicine, Department of Medicine, University of California, 2069 Filbert Street, San Francisco, CA 94123, USA
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6
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Martinelli F, Heinken A, Henning AK, Ulmer MA, Hensen T, González A, Arnold M, Asthana S, Budde K, Engelman CD, Estaki M, Grabe HJ, Heston MB, Johnson S, Kastenmüller G, Martino C, McDonald D, Rey FE, Kilimann I, Peters O, Wang X, Spruth EJ, Schneider A, Fliessbach K, Wiltfang J, Hansen N, Glanz W, Buerger K, Janowitz D, Laske C, Munk MH, Spottke A, Roy N, Nauck M, Teipel S, Knight R, Kaddurah-Daouk RF, Bendlin BB, Hertel J, Thiele I. Whole-body metabolic modelling reveals microbiome and genomic interactions on reduced urine formate levels in Alzheimer's disease. Sci Rep 2024; 14:6095. [PMID: 38480804 PMCID: PMC10937638 DOI: 10.1038/s41598-024-55960-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Accepted: 02/29/2024] [Indexed: 03/17/2024] Open
Abstract
In this study, we aimed to understand the potential role of the gut microbiome in the development of Alzheimer's disease (AD). We took a multi-faceted approach to investigate this relationship. Urine metabolomics were examined in individuals with AD and controls, revealing decreased formate and fumarate concentrations in AD. Additionally, we utilised whole-genome sequencing (WGS) data obtained from a separate group of individuals with AD and controls. This information allowed us to create and investigate host-microbiome personalised whole-body metabolic models. Notably, AD individuals displayed diminished formate microbial secretion in these models. Additionally, we identified specific reactions responsible for the production of formate in the host, and interestingly, these reactions were linked to genes that have correlations with AD. This study suggests formate as a possible early AD marker and highlights genetic and microbiome contributions to its production. The reduced formate secretion and its genetic associations point to a complex connection between gut microbiota and AD. This holistic understanding might pave the way for novel diagnostic and therapeutic avenues in AD management.
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Affiliation(s)
- Filippo Martinelli
- School of Medicine, University of Galway, Galway, Ireland
- The Ryan Institute, University of Galway, Galway, Ireland
| | - Almut Heinken
- School of Medicine, University of Galway, Galway, Ireland
- The Ryan Institute, University of Galway, Galway, Ireland
- Inserm UMRS 1256 NGERE, University of Lorraine, Nancy, France
| | - Ann-Kristin Henning
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Maria A Ulmer
- Institute of Computational Biology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Tim Hensen
- School of Medicine, University of Galway, Galway, Ireland
- The Ryan Institute, University of Galway, Galway, Ireland
| | - Antonio González
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Matthias Arnold
- Institute of Computational Biology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Department of Psychiatry and Behavioural Sciences, Duke University, Durham, NC, USA
| | - Sanjay Asthana
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, Madison, USA
| | - Kathrin Budde
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Corinne D Engelman
- Department of Population Health Sciences, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Mehrbod Estaki
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Hans-Jörgen Grabe
- German Center of Neurodegenerative Diseases (DZNE), Rostock/Greifswald, Germany
| | - Margo B Heston
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, Madison, USA
| | - Sterling Johnson
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, Madison, USA
| | - Gabi Kastenmüller
- Institute of Computational Biology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Cameron Martino
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Daniel McDonald
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Federico E Rey
- Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, USA
| | - Ingo Kilimann
- German Center of Neurodegenerative Diseases (DZNE), Rostock, Germany
- Department of Psychosomatic Medicine, University Medicine Rostock, Rostock, Germany
| | - Olive Peters
- German Center of Neurodegenerative Diseases (DZNE), Berlin, Germany
- Department of Psychiatry, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Xiao Wang
- Department of Psychiatry, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Eike Jakob Spruth
- German Center of Neurodegenerative Diseases (DZNE), Berlin, Germany
- Department of Psychiatry and Psychotherapy, Charité, Berlin, Germany
| | - Anja Schneider
- German Center of Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurology, University of Bonn, Bonn, Germany
| | - Klaus Fliessbach
- German Center of Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurology, University of Bonn, Bonn, Germany
| | - Jens Wiltfang
- German Center of Neurodegenerative Diseases (DZNE), Goettingen, Germany
- Department of Psychiatry and Psychotherapy, University of Goettingen, Goettingen, Germany
- Neurosciences and Signaling Group, Department of Medical Sciences, Institute of Biomedicine (iBiMED), University of Aveiro, Aveiro, Portugal
| | - Niels Hansen
- Department of Psychiatry and Psychotherapy, University of Goettingen, Goettingen, Germany
| | - Wenzel Glanz
- German Center of Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Katharina Buerger
- German Center of Neurodegenerative Diseases (DZNE), Munich, Germany
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Daniel Janowitz
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Christoph Laske
- German Center of Neurodegenerative Diseases (DZNE), Tübingen, Germany
- Section for Dementia Research, Hertie Institute for Clinical Brain Research, Tübingen, Germany
- Section for Dementia Research, Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Matthias H Munk
- German Center of Neurodegenerative Diseases (DZNE), Tübingen, Germany
- Section for Dementia Research, Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Annika Spottke
- German Center of Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurology, University of Bonn, Bonn, Germany
| | - Nina Roy
- German Center of Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Matthias Nauck
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, University Medicine, Greifswald, Germany
| | - Stefan Teipel
- German Center of Neurodegenerative Diseases (DZNE), Rostock, Germany
- Department of Psychosomatic Medicine, University Medicine Rostock, Rostock, Germany
| | - Rob Knight
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
- Center for Microbiome Innovation, University of California San Diego, La Jolla, CA, USA
- Shu Chien-Gene Lay Department of Engineering, University of California San Diego, La Jolla, CA, USA
- Halıcıoğlu Data Science Institute, University of California San Diego, La Jolla, CA, USA
| | | | - Barbara B Bendlin
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, Madison, USA
| | - Johannes Hertel
- School of Medicine, University of Galway, Galway, Ireland.
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, University Medicine, Greifswald, Germany.
| | - Ines Thiele
- School of Medicine, University of Galway, Galway, Ireland.
- The Ryan Institute, University of Galway, Galway, Ireland.
- School of Microbiology, University of Galway, Galway, Ireland.
- APC Microbiome Ireland, Cork, Ireland.
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7
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Zhang J, Pandey M, Awe A, Lue N, Kittock C, Fikse E, Degner K, Staples J, Mokhasi N, Chen W, Yang Y, Adikaram P, Jacob N, Greenfest-Allen E, Thomas R, Bomeny L, Zhang Y, Petros TJ, Wang X, Li Y, Simonds WF. The association of GNB5 with Alzheimer disease revealed by genomic analysis restricted to variants impacting gene function. Am J Hum Genet 2024; 111:473-486. [PMID: 38354736 PMCID: PMC10940018 DOI: 10.1016/j.ajhg.2024.01.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Revised: 01/09/2024] [Accepted: 01/10/2024] [Indexed: 02/16/2024] Open
Abstract
Disease-associated variants identified from genome-wide association studies (GWASs) frequently map to non-coding areas of the genome such as introns and intergenic regions. An exclusive reliance on gene-agnostic methods of genomic investigation could limit the identification of relevant genes associated with polygenic diseases such as Alzheimer disease (AD). To overcome such potential restriction, we developed a gene-constrained analytical method that considers only moderate- and high-risk variants that affect gene coding sequences. We report here the application of this approach to publicly available datasets containing 181,388 individuals without and with AD and the resulting identification of 660 genes potentially linked to the higher AD prevalence among Africans/African Americans. By integration with transcriptome analysis of 23 brain regions from 2,728 AD case-control samples, we concentrated on nine genes that potentially enhance the risk of AD: AACS, GNB5, GNS, HIPK3, MED13, SHC2, SLC22A5, VPS35, and ZNF398. GNB5, the fifth member of the heterotrimeric G protein beta family encoding Gβ5, is primarily expressed in neurons and is essential for normal neuronal development in mouse brain. Homozygous or compound heterozygous loss of function of GNB5 in humans has previously been associated with a syndrome of developmental delay, cognitive impairment, and cardiac arrhythmia. In validation experiments, we confirmed that Gnb5 heterozygosity enhanced the formation of both amyloid plaques and neurofibrillary tangles in the brains of AD model mice. These results suggest that gene-constrained analysis can complement the power of GWASs in the identification of AD-associated genes and may be more broadly applicable to other polygenic diseases.
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Affiliation(s)
- Jianhua Zhang
- Metabolic Diseases Branch, Bldg. 10/Rm 8C-101, National Institutes of Health, Bethesda, MD 20892, USA.
| | - Mritunjay Pandey
- Metabolic Diseases Branch, Bldg. 10/Rm 8C-101, National Institutes of Health, Bethesda, MD 20892, USA
| | - Adam Awe
- Metabolic Diseases Branch, Bldg. 10/Rm 8C-101, National Institutes of Health, Bethesda, MD 20892, USA
| | - Nicole Lue
- Metabolic Diseases Branch, Bldg. 10/Rm 8C-101, National Institutes of Health, Bethesda, MD 20892, USA
| | - Claire Kittock
- Metabolic Diseases Branch, Bldg. 10/Rm 8C-101, National Institutes of Health, Bethesda, MD 20892, USA
| | - Emma Fikse
- Metabolic Diseases Branch, Bldg. 10/Rm 8C-101, National Institutes of Health, Bethesda, MD 20892, USA
| | - Katherine Degner
- Metabolic Diseases Branch, Bldg. 10/Rm 8C-101, National Institutes of Health, Bethesda, MD 20892, USA
| | - Jenna Staples
- Metabolic Diseases Branch, Bldg. 10/Rm 8C-101, National Institutes of Health, Bethesda, MD 20892, USA
| | - Neha Mokhasi
- Metabolic Diseases Branch, Bldg. 10/Rm 8C-101, National Institutes of Health, Bethesda, MD 20892, USA
| | - Weiping Chen
- Genomic Core, National Institute of Diabetes and Digestive and Kidney Diseases, Bldg. 8/Rm 1A11, National Institutes of Health, Bethesda, MD 20892, USA
| | - Yanqin Yang
- Laboratory of Transplantation Genomics, National Heart Lung and Blood Institute, Bldg. 10/Rm 7S261, National Institutes of Health, Bethesda, MD 20892, USA
| | - Poorni Adikaram
- Metabolic Diseases Branch, Bldg. 10/Rm 8C-101, National Institutes of Health, Bethesda, MD 20892, USA
| | - Nirmal Jacob
- Metabolic Diseases Branch, Bldg. 10/Rm 8C-101, National Institutes of Health, Bethesda, MD 20892, USA
| | - Emily Greenfest-Allen
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Rachel Thomas
- Metabolic Diseases Branch, Bldg. 10/Rm 8C-101, National Institutes of Health, Bethesda, MD 20892, USA
| | - Laura Bomeny
- Metabolic Diseases Branch, Bldg. 10/Rm 8C-101, National Institutes of Health, Bethesda, MD 20892, USA
| | - Yajun Zhang
- Unit on Cellular and Molecular Neurodevelopment, Bldg. 35/Rm 3B 1002, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD 20892, USA
| | - Timothy J Petros
- Unit on Cellular and Molecular Neurodevelopment, Bldg. 35/Rm 3B 1002, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD 20892, USA
| | - Xiaowen Wang
- Partek Incorporated, 12747 Olive Boulevard, St. Louis, MO 63141, USA
| | - Yulong Li
- Metabolic Diseases Branch, Bldg. 10/Rm 8C-101, National Institutes of Health, Bethesda, MD 20892, USA
| | - William F Simonds
- Metabolic Diseases Branch, Bldg. 10/Rm 8C-101, National Institutes of Health, Bethesda, MD 20892, USA.
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8
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Huang X, Yuan S, Ling Y, Cheng H, Tan S, Xu A, Lyu J. Evaluating the effect of kidney function on brain volumes and dementia risk in the UK Biobank. Arch Gerontol Geriatr 2024; 116:105157. [PMID: 37634304 DOI: 10.1016/j.archger.2023.105157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 08/06/2023] [Accepted: 08/10/2023] [Indexed: 08/29/2023]
Abstract
OBJECTIVE To investigate the association between kidney function with the risk of dementia and brain volumes. METHODS A total of 452,996 UK Biobank participants with calculated glomerular filtration rate (eGFR) and albumin-to-creatinine ratio (ACR) were included. We utilized Cox proportional hazards regression models and restricted cubic spline analyses to examine the relationships between kidney function and the risk of all-cause dementia (ACD), Alzheimer's disease (AD), and vascular dementia (VD). Additionally, we explored the correlations between kidney function and brain magnetic resonance indicators among 40,380 participants. RESULTS During a median follow-up of 12 years, 5,258 incident ACD cases were identified. The deterioration of kidney function was associated with an increased risk of ACD. When compared to eGFR ≥ 90 ml/min/1.73 m², the highest risk increase was evident for eGFRcre < 30 ml/min/1.73 m² (adjusted HR = 2.372, 95% CI: 1.444-3.897, P < 0.001), with eGFRcys showing greater significance (adjusted HR = 3.045, 95% CI: 2.212-4.191, P < 0.001), especially in relation to AD. Compared to the ACR level in the range of 3-30 mg/mmol, the category of > 30 mg/mmol was associated with an increased risk of ACD (adjusted HR = 1.720, 95% CI: 1.350-2.190, P < 0.001). Moreover, the decline in kidney function was associated with the total brain volume atrophy and reduction in certain subcortical areas. CONCLUSIONS Our study indicates that diminished kidney function, as evidenced by a drop in eGFR and aggravated proteinuria, elevates dementia risk. Associated brain structural changes further underpin this connection from a neuro-pathophysiological perspective.
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Affiliation(s)
- Xiaxuan Huang
- Department of Neurology, The First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Shiqi Yuan
- Department of Neurology, The First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Yitong Ling
- Department of Neurology, The First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Hongtao Cheng
- School of Nursing, Jinan University, Guangzhou 510630, China
| | - Shanyuan Tan
- Department of Neurology, The First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Anding Xu
- Department of Neurology, The First Affiliated Hospital of Jinan University, Guangzhou 510630, China
| | - Jun Lyu
- Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou 510630, China; Guangdong Provincial Key Laboratory of Traditional Chinese Medicine Informatization, Guangzhou 510630, China.
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9
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von Berg J, McArdle PF, Häppölä P, Haessler J, Kooperberg C, Lemmens R, Pezzini A, Thijs V, Pulit SL, Kittner SJ, Mitchell BD, de Ridder J, van der Laan SW. Evidence of survival bias in the association between APOE-ϵ4 and age of ischemic stroke onset. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.01.23294385. [PMID: 38076909 PMCID: PMC10705635 DOI: 10.1101/2023.12.01.23294385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
Large genome-wide association studies (GWAS) employing case-control study designs have now identified tens of loci associated with ischemic stroke (IS). As a complement to these studies, we performed GWAS in a case-only design to identify loci influencing age at onset (AAO) of ischemic stroke. Analyses were conducted in a Discovery cohort of 10,857 ischemic stroke cases using a linear regression framework. We meta-analyzed all SNPs with p-value < 1×10-5 in a sex-combined or sex-stratified analysis using summary data from two additional replication cohorts. In the women-only meta-analysis, we detected significant evidence for association of AAO with rs429358, an exonic variant in APOE that encodes for the APOE-ϵ4 allele. Each copy of the rs429358:T>C allele was associated with a 1.29 years earlier stroke AOO (meta p-value = 2.48×10-11). This APOE variant has previously been associated with increased mortality and ischemic stroke AAO. We hypothesized that the association with AAO may reflect a survival bias attributable to an age-related decline in mortality among APOE-ϵ4 carriers and have no association to stroke AAO per se. Using a simulation study, we found that a variant associated with overall mortality might indeed be detected with an AAO analysis. A variant with a two-fold increase on mortality risk would lead to an observed effect of AAO that is comparable to what we found. In conclusion, we detected a robust association of the APOE locus with stroke AAO and provided simulations to suggest that this association may be unrelated to ischemic stroke per se but related to a general survival bias.
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Affiliation(s)
- Joanna von Berg
- Center for Molecular Medicine, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Oncode Institute, Utrecht, The Netherlands
| | - Patrick F. McArdle
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Paavo Häppölä
- Institute for Molecular Medicine Finland FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
| | | | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seatle, WA, USA
| | - Robin Lemmens
- University Hospitals Leuven, Department of Neurology, Leuven, Belgium
- KU Leuven - University of Leuven, Department of Neurosciences, Experimental Neurology, Leuven, Belgium
| | - Alessandro Pezzini
- Department of Medicine and Surgery, University of Parma, Parma, Italy
- Stroke Care Program, Department of Emergency, Parma University Hospital, Parma, Italy
- Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Vincent Thijs
- Stroke Theme, The Florey, Heidelberg, Victoria, Australia
- Department of Medicine, University of Melbourne, Victoria, Australia
- Department of Neurology, Austin Health, Heidelberg, Victoria, Australia
| | | | - Sara L. Pulit
- Center for Molecular Medicine, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Steven J. Kittner
- Geriatric Research and Education Clinical Center, VA Maryland Health Care System, Baltimore, MD, USA
- Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Braxton D. Mitchell
- Division of Endocrinology, Diabetes and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
- Geriatric Research and Education Clinical Center, VA Maryland Health Care System, Baltimore, MD, USA
| | - Jeroen de Ridder
- Center for Molecular Medicine, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
- Oncode Institute, Utrecht, The Netherlands
| | - Sander W. van der Laan
- Central Diagnostics Laboratory, Division Laboratories, Pharmacy, and Biomedical Genetics, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
- Center of Population Health and Genomics, University of Virginia, Charlottesville, VA, USA
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10
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Bai H, Naj AC, Benchek P, Dumitrescu L, Hohman T, Hamilton-Nelson K, Kallianpur AR, Griswold AJ, Vardarajan B, Martin ER, Beecham GW, Below JE, Schellenberg G, Mayeux R, Farrer L, Pericak-Vance MA, Haines JL, Bush WS. A haptoglobin (HP) structural variant alters the effect of APOE alleles on Alzheimer's disease. Alzheimers Dement 2023; 19:4886-4895. [PMID: 37051669 DOI: 10.1002/alz.13050] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Revised: 01/19/2023] [Accepted: 01/20/2023] [Indexed: 04/14/2023]
Abstract
BACKGROUND Haptoglobin (HP) is an antioxidant of apolipoprotein E (APOE), and previous reports have shown HP binds with APOE and amyloid beta (Aβ) to aid its clearance. A common structural variant of the HP gene distinguishes it into two alleles: HP1 and HP2. METHODS HP genotypes were imputed in 29 cohorts from the Alzheimer's Disease Genetics Consortium (N = 20,512). Associations between the HP polymorphism and Alzheimer's disease (AD) risk and age of onset through APOE interactions were investigated using regression models. RESULTS The HP polymorphism significantly impacts AD risk in European-descent individuals (and in meta-analysis with African-descent individuals) by modifying both the protective effect of APOE ε2 and the detrimental effect of APOE ε4. The effect is particularly significant among APOE ε4 carriers. DISCUSSION The effect modification of APOE by HP suggests adjustment and/or stratification by HP genotype is warranted when APOE risk is considered. Our findings also provided directions for further investigations on potential mechanisms behind this association.
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Affiliation(s)
- Haimeng Bai
- Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, Ohio, USA
- Systems Biology and Bioinformatics, Department of Nutrition, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
| | - Adam C Naj
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Penelope Benchek
- Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, Ohio, USA
- Department of Population & Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
| | - Logan Dumitrescu
- Vanderbilt Memory & Alzheimer's Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Timothy Hohman
- Vanderbilt Memory & Alzheimer's Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Kara Hamilton-Nelson
- John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida, USA
| | - Asha R Kallianpur
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, Ohio, USA
- Department of Molecular Medicine, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
| | - Anthony J Griswold
- John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida, USA
| | - Badri Vardarajan
- Department of Neurology, The Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York, USA
| | - Eden R Martin
- John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida, USA
| | - Gary W Beecham
- John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida, USA
| | - Jennifer E Below
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Gerard Schellenberg
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Richard Mayeux
- Department of Neurology, The Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York, USA
| | - Lindsay Farrer
- Departments of Medicine (Biomedical Genetics), Neurology, Ophthalmology, Biostatistics, and Epidemiology, Boston University Schools of Medicine and Public Health, Boston, Massachusetts, USA
| | | | - Jonathan L Haines
- Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, Ohio, USA
- Department of Population & Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
| | - William S Bush
- Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, Ohio, USA
- Department of Population & Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
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11
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Wang F, Wang H, Yuan Y, Han B, Qiu S, Hu Y, Zang T. Integration of multiple-omics data to reveal the shared genetic architecture of educational attainment, intelligence, cognitive performance, and Alzheimer's disease. Front Genet 2023; 14:1243879. [PMID: 37900179 PMCID: PMC10601659 DOI: 10.3389/fgene.2023.1243879] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Accepted: 09/01/2023] [Indexed: 10/31/2023] Open
Abstract
Growing evidence suggests the effect of educational attainment (EA) on Alzheimer's disease (AD), but less is known about the shared genetic architecture between them. Here, leveraging genome-wide association studies (GWAS) for AD (N = 21,982/41,944), EA (N = 1,131,881), cognitive performance (N = 257,828), and intelligence (N = 78,308), we investigated their causal association with the linkage disequilibrium score (LDSC) and Mendelian randomization and their shared loci with the conjunctional false discovery rate (conjFDR), transcriptome-wide association studies (TWAS), and colocalization. We observed significant genetic correlations of EA (rg = -0.22, p = 5.07E-05), cognitive performance (rg = -0.27, p = 2.44E-05), and intelligence (rg = -0.30, p = 3.00E-04) with AD, and a causal relationship between EA and AD (OR = 0.74, 95% CI: 0.58-0.94, p = 0.013). We identified 13 shared loci at conjFDR <0.01, of which five were novel, and prioritized three causal genes. These findings inform early prevention strategies for AD.
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Affiliation(s)
- Fuxu Wang
- Center for Bioinformatics, Faculty of Computing, Harbin Institute of Technology, Harbin, Heilongjiang, China
| | - Haoyan Wang
- Center for Bioinformatics, Faculty of Computing, Harbin Institute of Technology, Harbin, Heilongjiang, China
| | - Ye Yuan
- Beidahuang Industry Group General Hospital, Harbin, China
| | - Bing Han
- Aier Eye Hospital, Harbin, China
| | - Shizheng Qiu
- Center for Bioinformatics, Faculty of Computing, Harbin Institute of Technology, Harbin, Heilongjiang, China
| | - Yang Hu
- Center for Bioinformatics, Faculty of Computing, Harbin Institute of Technology, Harbin, Heilongjiang, China
| | - Tianyi Zang
- Center for Bioinformatics, Faculty of Computing, Harbin Institute of Technology, Harbin, Heilongjiang, China
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12
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Haller S, Jäger HR, Vernooij MW, Barkhof F. Neuroimaging in Dementia: More than Typical Alzheimer Disease. Radiology 2023; 308:e230173. [PMID: 37724973 DOI: 10.1148/radiol.230173] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/21/2023]
Abstract
Alzheimer disease (AD) is the most common cause of dementia. The prevailing theory of the underlying pathology assumes amyloid accumulation followed by tau protein aggregation and neurodegeneration. However, the current antiamyloid and antitau treatments show only variable clinical efficacy. Three relevant points are important for the radiologic assessment of dementia. First, besides various dementing disorders (including AD, frontotemporal dementia, and dementia with Lewy bodies), clinical variants and imaging subtypes of AD include both typical and atypical AD. Second, atypical AD has overlapping radiologic and clinical findings with other disorders. Third, the diagnostic process should consider mixed pathologies in neurodegeneration, especially concurrent cerebrovascular disease, which is frequent in older age. Neuronal loss is often present at, or even before, the onset of cognitive decline. Thus, for effective emerging treatments, early diagnosis before the onset of clinical symptoms is essential to slow down or stop subsequent neuronal loss, requiring molecular imaging or plasma biomarkers. Neuroimaging, particularly MRI, provides multiple imaging parameters for neurodegenerative and cerebrovascular disease. With emerging treatments for AD, it is increasingly important to recognize AD variants and other disorders that mimic AD. Describing the individual composition of neurodegenerative and cerebrovascular disease markers while considering overlapping and mixed diseases is necessary to better understand AD and develop efficient individualized therapies.
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Affiliation(s)
- Sven Haller
- From the Centre d'Imagerie Médicale de Cornavin, Place de Cornavin 18, 1201 Geneva, Switzerland (S.H.); Department of Surgical Sciences, Radiology, Uppsala University, Uppsala, Sweden (S.H.); Faculty of Medicine of the University of Geneva, Geneva, Switzerland (S.H.); Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China (S.H.); Tanta University, Faculty of Medicine, Tanta, Egypt (S.H.); Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, Queen Square Institute of Neurology (H.R.J., F.B.), and Centre for Medical Image Computing, Institute of Healthcare Engineering (F.B.), University College London, London, England; Lysholm Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, London, England (H.R.J.); Departments of Epidemiology and Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands (M.W.V.); and Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centre, Amsterdam, the Netherlands (F.B.)
| | - Hans Rolf Jäger
- From the Centre d'Imagerie Médicale de Cornavin, Place de Cornavin 18, 1201 Geneva, Switzerland (S.H.); Department of Surgical Sciences, Radiology, Uppsala University, Uppsala, Sweden (S.H.); Faculty of Medicine of the University of Geneva, Geneva, Switzerland (S.H.); Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China (S.H.); Tanta University, Faculty of Medicine, Tanta, Egypt (S.H.); Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, Queen Square Institute of Neurology (H.R.J., F.B.), and Centre for Medical Image Computing, Institute of Healthcare Engineering (F.B.), University College London, London, England; Lysholm Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, London, England (H.R.J.); Departments of Epidemiology and Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands (M.W.V.); and Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centre, Amsterdam, the Netherlands (F.B.)
| | - Meike W Vernooij
- From the Centre d'Imagerie Médicale de Cornavin, Place de Cornavin 18, 1201 Geneva, Switzerland (S.H.); Department of Surgical Sciences, Radiology, Uppsala University, Uppsala, Sweden (S.H.); Faculty of Medicine of the University of Geneva, Geneva, Switzerland (S.H.); Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China (S.H.); Tanta University, Faculty of Medicine, Tanta, Egypt (S.H.); Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, Queen Square Institute of Neurology (H.R.J., F.B.), and Centre for Medical Image Computing, Institute of Healthcare Engineering (F.B.), University College London, London, England; Lysholm Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, London, England (H.R.J.); Departments of Epidemiology and Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands (M.W.V.); and Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centre, Amsterdam, the Netherlands (F.B.)
| | - Frederik Barkhof
- From the Centre d'Imagerie Médicale de Cornavin, Place de Cornavin 18, 1201 Geneva, Switzerland (S.H.); Department of Surgical Sciences, Radiology, Uppsala University, Uppsala, Sweden (S.H.); Faculty of Medicine of the University of Geneva, Geneva, Switzerland (S.H.); Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China (S.H.); Tanta University, Faculty of Medicine, Tanta, Egypt (S.H.); Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, Queen Square Institute of Neurology (H.R.J., F.B.), and Centre for Medical Image Computing, Institute of Healthcare Engineering (F.B.), University College London, London, England; Lysholm Department of Neuroradiology, The National Hospital for Neurology and Neurosurgery, London, England (H.R.J.); Departments of Epidemiology and Radiology & Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands (M.W.V.); and Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centre, Amsterdam, the Netherlands (F.B.)
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13
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Cochran JN, Acosta-Uribe J, Esposito BT, Madrigal L, Aguillón D, Giraldo MM, Taylor JW, Bradley J, Fulton-Howard B, Andrews SJ, Acosta-Baena N, Alzate D, Garcia GP, Piedrahita F, Lopez HE, Anderson AG, Rodriguez-Nunez I, Roberts K, Dominantly Inherited Alzheimer Network, Absher D, Myers RM, Beecham GW, Reitz C, Rizzardi LF, Fernandez MV, Goate AM, Cruchaga C, Renton AE, Lopera F, Kosik KS. Genetic associations with age at dementia onset in the PSEN1 E280A Colombian kindred. Alzheimers Dement 2023; 19:3835-3847. [PMID: 36951251 PMCID: PMC10514237 DOI: 10.1002/alz.13021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 02/03/2023] [Accepted: 02/07/2023] [Indexed: 03/24/2023]
Abstract
INTRODUCTION Genetic associations with Alzheimer's disease (AD) age at onset (AAO) could reveal genetic variants with therapeutic applications. We present a large Colombian kindred with autosomal dominant AD (ADAD) as a unique opportunity to discover AAO genetic associations. METHODS A genetic association study was conducted to examine ADAD AAO in 340 individuals with the PSEN1 E280A mutation via TOPMed array imputation. Replication was assessed in two ADAD cohorts, one sporadic early-onset AD study and four late-onset AD studies. RESULTS 13 variants had p<1×10-7 or p<1×10-5 with replication including three independent loci with candidate associations with clusterin including near CLU. Other suggestive associations were identified in or near HS3ST1, HSPG2, ACE, LRP1B, TSPAN10, and TSPAN14. DISCUSSION Variants with suggestive associations with AAO were associated with biological processes including clusterin, heparin sulfate, and amyloid processing. The detection of these effects in the presence of a strong mutation for ADAD reinforces their potentially impactful role.
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Affiliation(s)
| | - Juliana Acosta-Uribe
- Neuroscience Research Institute, University of California, Santa Barbara, California, and Department of Molecular Cellular and Developmental Biology University of California, Santa Barbara, California, USA
- Grupo de Neurociencias de Antioquia. School of Medicine. Universidad de Antioquia, Medellín, Antioquia, Colombia
| | - Bianca T Esposito
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Lucia Madrigal
- Grupo de Neurociencias de Antioquia. School of Medicine. Universidad de Antioquia, Medellín, Antioquia, Colombia
| | - David Aguillón
- Grupo de Neurociencias de Antioquia. School of Medicine. Universidad de Antioquia, Medellín, Antioquia, Colombia
| | - Margarita M Giraldo
- Grupo de Neurociencias de Antioquia. School of Medicine. Universidad de Antioquia, Medellín, Antioquia, Colombia
| | - Jared W Taylor
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, USA
| | - Joseph Bradley
- Washington University School of Medicine, St. Louis, Missouri, USA
| | - Brian Fulton-Howard
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Shea J Andrews
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Natalia Acosta-Baena
- Grupo de Neurociencias de Antioquia. School of Medicine. Universidad de Antioquia, Medellín, Antioquia, Colombia
| | - Diana Alzate
- Grupo de Neurociencias de Antioquia. School of Medicine. Universidad de Antioquia, Medellín, Antioquia, Colombia
| | - Gloria P Garcia
- Grupo de Neurociencias de Antioquia. School of Medicine. Universidad de Antioquia, Medellín, Antioquia, Colombia
| | - Francisco Piedrahita
- Grupo de Neurociencias de Antioquia. School of Medicine. Universidad de Antioquia, Medellín, Antioquia, Colombia
| | - Hugo E Lopez
- Grupo de Neurociencias de Antioquia. School of Medicine. Universidad de Antioquia, Medellín, Antioquia, Colombia
| | | | | | - Kevin Roberts
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, USA
| | | | - Devin Absher
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, USA
| | - Richard M Myers
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, USA
| | - Gary W Beecham
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida, USA
| | - Christiane Reitz
- Department of Epidemiology, Sergievsky Center, Taub Institute for Research on the Aging Brain, Columbia University, New York, New York, USA
| | | | | | - Alison M Goate
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Carlos Cruchaga
- Washington University School of Medicine, St. Louis, Missouri, USA
| | - Alan E Renton
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Francisco Lopera
- Grupo de Neurociencias de Antioquia. School of Medicine. Universidad de Antioquia, Medellín, Antioquia, Colombia
| | - Kenneth S Kosik
- Neuroscience Research Institute, University of California, Santa Barbara, California, and Department of Molecular Cellular and Developmental Biology University of California, Santa Barbara, California, USA
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14
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Calafatti M, Cocozza G, Limatola C, Garofalo S. Microglial crosstalk with astrocytes and immune cells in amyotrophic lateral sclerosis. Front Immunol 2023; 14:1223096. [PMID: 37564648 PMCID: PMC10410456 DOI: 10.3389/fimmu.2023.1223096] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 07/03/2023] [Indexed: 08/12/2023] Open
Abstract
In recent years, biomedical research efforts aimed to unravel the mechanisms involved in motor neuron death that occurs in amyotrophic lateral sclerosis (ALS). While the main causes of disease progression were first sought in the motor neurons, more recent studies highlight the gliocentric theory demonstrating the pivotal role of microglia and astrocyte, but also of infiltrating immune cells, in the pathological processes that take place in the central nervous system microenvironment. From this point of view, microglia-astrocytes-lymphocytes crosstalk is fundamental to shape the microenvironment toward a pro-inflammatory one, enhancing neuronal damage. In this review, we dissect the current state-of-the-art knowledge of the microglial dialogue with other cell populations as one of the principal hallmarks of ALS progression. Particularly, we deeply investigate the microglia crosstalk with astrocytes and immune cells reporting in vitro and in vivo studies related to ALS mouse models and human patients. At last, we highlight the current experimental therapeutic approaches that aim to modulate microglial phenotype to revert the microenvironment, thus counteracting ALS progression.
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Affiliation(s)
- Matteo Calafatti
- Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy
| | - Germana Cocozza
- Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy
| | - Cristina Limatola
- Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Neuromed, Pozzilli, Italy
- Department of Physiology and Pharmacology, Sapienza University, Laboratory Affiliated to Istituto Pasteur, Rome, Italy
| | - Stefano Garofalo
- Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy
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15
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Horimoto AR, Boyken LA, Blue EE, Grinde KE, Nafikov RA, Sohi HK, Nato AQ, Bis JC, Brusco LI, Morelli L, Ramirez A, Dalmasso MC, Temple S, Satizabal C, Browning SR, Seshadri S, Wijsman EM, Thornton TA. Admixture mapping implicates 13q33.3 as ancestry-of-origin locus for Alzheimer disease in Hispanic and Latino populations. HGG ADVANCES 2023; 4:100207. [PMID: 37333771 PMCID: PMC10276158 DOI: 10.1016/j.xhgg.2023.100207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Accepted: 05/16/2023] [Indexed: 06/20/2023] Open
Abstract
Alzheimer disease (AD) is the most common form of senile dementia, with high incidence late in life in many populations including Caribbean Hispanic (CH) populations. Such admixed populations, descended from more than one ancestral population, can present challenges for genetic studies, including limited sample sizes and unique analytical constraints. Therefore, CH populations and other admixed populations have not been well represented in studies of AD, and much of the genetic variation contributing to AD risk in these populations remains unknown. Here, we conduct genome-wide analysis of AD in multiplex CH families from the Alzheimer Disease Sequencing Project (ADSP). We developed, validated, and applied an implementation of a logistic mixed model for admixture mapping with binary traits that leverages genetic ancestry to identify ancestry-of-origin loci contributing to AD. We identified three loci on chromosome 13q33.3 associated with reduced risk of AD, where associations were driven by Native American (NAM) ancestry. This AD admixture mapping signal spans the FAM155A, ABHD13, TNFSF13B, LIG4, and MYO16 genes and was supported by evidence for association in an independent sample from the Alzheimer's Genetics in Argentina-Alzheimer Argentina consortium (AGA-ALZAR) study with considerable NAM ancestry. We also provide evidence of NAM haplotypes and key variants within 13q33.3 that segregate with AD in the ADSP whole-genome sequencing data. Interestingly, the widely used genome-wide association study approach failed to identify associations in this region. Our findings underscore the potential of leveraging genetic ancestry diversity in recently admixed populations to improve genetic mapping, in this case for AD-relevant loci.
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Affiliation(s)
| | - Lisa A. Boyken
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Elizabeth E. Blue
- Division of Medical Genetics/Department of Medicine, University of Washington, Seattle, WA 98195, USA
- Brotman Baty Institute for Precision Medicine, Seattle, WA 98195, USA
| | - Kelsey E. Grinde
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
- Department of Mathematics, Statistics and Computer Science, Macalester College, Saint Paul, MN 55105, USA
| | - Rafael A. Nafikov
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
- Division of Medical Genetics/Department of Medicine, University of Washington, Seattle, WA 98195, USA
| | - Harkirat K. Sohi
- Division of Medical Genetics/Department of Medicine, University of Washington, Seattle, WA 98195, USA
- Biomedical and Health Informatics Program, University of Washington, Seattle, WA 98195, USA
| | - Alejandro Q. Nato
- Division of Medical Genetics/Department of Medicine, University of Washington, Seattle, WA 98195, USA
- Department of Biomedical Sciences, Joan C. Edwards School of Medicine, Marshall University, Huntington, WV 25755, USA
| | - Joshua C. Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 98101, USA
| | - Luis I. Brusco
- CENECON - Center of Behavioural Neurology and Neuropsychiatry, School of Medicine, University of Buenos Aires, C1121A6B Buenos Aires, Argentina
| | - Laura Morelli
- Laboratory of Brain Aging and Neurodegeneration-Fundación Instituto Leloir-IIBBA- National Scientific and Technical Research Council (CONICET), C1405BWE Ciudad Autónoma de Buenos Aires, Argentina
| | - Alfredo Ramirez
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, University of Cologne, Medical Faculty, 50937 Cologne, Germany
- Department of Neurodegeneration and Gerontopsychiatry, University of Bonn, 53127 Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
- Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD) University of Cologne, 50674 Cologne, Germany
- Department of Psychiatry, UT Health San Antonio, San Antonio, TX 78229, USA
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, TX 78229, USA
| | - Maria Carolina Dalmasso
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, University of Cologne, Medical Faculty, 50937 Cologne, Germany
- Neurosciences and Complex Systems Unit (EnyS), CONICET, Hospital El Cruce, National University A. Jauretche (UNAJ), B1888AAE Florencio Varela, Argentina
| | - Seth Temple
- Department of Statistics, University of Washington, Seattle, WA 98195, USA
| | - Claudia Satizabal
- Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, TX 78229, USA
- Department of Population Health Sciences, University of Texas, San Antonio, TX 78229, USA
- Department of Neurology, University of Texas, San Antonio, TX 78229, USA
| | - Sharon R. Browning
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Sudha Seshadri
- Department of Neurology, University of Texas, San Antonio, TX 78229, USA
| | - Ellen M. Wijsman
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
- Division of Medical Genetics/Department of Medicine, University of Washington, Seattle, WA 98195, USA
| | - Timothy A. Thornton
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
- Department of Statistics, University of Washington, Seattle, WA 98195, USA
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16
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Li YJ, Nuytemans K, La JO, Jiang R, Slifer SH, Sun S, Naj A, Gao XR, Martin ER. Identification of novel genes for age-at-onset of Alzheimer's disease by combining quantitative and survival trait analyses. Alzheimers Dement 2023; 19:3148-3157. [PMID: 36738287 DOI: 10.1002/alz.12927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 12/06/2022] [Accepted: 12/19/2022] [Indexed: 02/05/2023]
Abstract
INTRODUCTION Our understanding of the genetic predisposition for age-at-onset (AAO) of Alzheimer's disease (AD) is limited. Here, we sought to identify genes modifying AAO and examined whether any have sex-specific effects. METHODS Genome-wide association analysis were performed on imputed genetic data of 9219 AD cases and 10,345 controls from 20 cohorts of the Alzheimer's Disease Genetics Consortium. AAO was modeled from cases directly and as a survival outcome. RESULTS We identified 11 genome-wide significant loci (P < 5 × 10-8 ), including six known AD-risk genes and five novel loci, UMAD1, LUZP2, ARFGEF2, DSCAM, and 4q25, affecting AAO of AD. Additionally, 39 suggestive loci showed strong association. Twelve loci showed sex-specific effects on AAO including CD300LG and MLX/TUBG2 for females and MIR4445 for males. DISCUSSION Genes that influence AAO of AD are excellent therapeutic targets for delaying onset of AD. Several loci identified include genes with promising functional implications for AD.
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Affiliation(s)
- Yi-Ju Li
- Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, North Carolina, USA
- Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, North Carolina, USA
| | - Karen Nuytemans
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, Florida, USA
- John T. MacDonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, Florida, USA
| | - Jong Ok La
- Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, North Carolina, USA
| | - Rong Jiang
- Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, North Carolina, USA
- Department of Psychiatry and Behavior Science, Duke University School of Medicine, Durham, North Carolina, USA
| | - Susan H Slifer
- John T. MacDonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, Florida, USA
| | - Shuming Sun
- Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, North Carolina, USA
| | - Adam Naj
- Department of Biostatistics, Epidemiology, and Informatics, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Xiaoyi Raymond Gao
- Department of Ophthalmology and Visual Sciences, Division of Human Genetics, The Ohio State University, Columbus, Ohio, USA
- Department of Biomedical Informatics, The Ohio State University, Columbus, Ohio, USA
| | - Eden R Martin
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, Florida, USA
- John T. MacDonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, Florida, USA
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17
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Holloway KN, Douglas JC, Rafferty TM, Majewska AK, Kane CJM, Drew PD. Ethanol-induced cerebellar transcriptomic changes in a postnatal model of fetal alcohol spectrum disorders: Focus on disease onset. Front Neurosci 2023; 17:1154637. [PMID: 37008214 PMCID: PMC10062483 DOI: 10.3389/fnins.2023.1154637] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 02/27/2023] [Indexed: 03/18/2023] Open
Abstract
Fetal alcohol spectrum disorders (FASD) are a group of neurodevelopmental disorders caused by ethanol exposure in utero, which can result in neurocognitive and behavioral impairments, growth defects, and craniofacial anomalies. FASD affects up to 1-5% of school-aged children in the United States, and there is currently no cure. The underlying mechanisms involved in ethanol teratogenesis remain elusive and need greater understanding to develop and implement effective therapies. Using a third trimester human equivalent postnatal mouse model of FASD, we evaluate the transcriptomic changes induced by ethanol exposure in the cerebellum on P5 and P6, after only 1 or 2 days of ethanol exposure, with the goal of shedding light on the transcriptomic changes induced early during the onset and development of FASD. We have highlighted key pathways and cellular functions altered by ethanol exposure, which include pathways related to immune function and cytokine signaling as well as the cell cycle. Additionally, we found that ethanol exposure resulted in an increase in transcripts associated with a neurodegenerative microglia phenotype, and acute- and pan-injury reactive astrocyte phenotypes. Mixed effects on oligodendrocyte lineage cell associated transcripts and cell cycle associated transcripts were observed. These studies help to elucidate the underlying mechanisms that may be involved with the onset of FASD and provide further insights that may aid in identifying novel targets for interventions and therapeutics.
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Affiliation(s)
- Kalee N. Holloway
- Department of Neurobiology and Developmental Sciences, University of Arkansas for Medical Sciences, Little Rock, AR, United States
| | - James C. Douglas
- Department of Neurobiology and Developmental Sciences, University of Arkansas for Medical Sciences, Little Rock, AR, United States
| | - Tonya M. Rafferty
- Department of Neurobiology and Developmental Sciences, University of Arkansas for Medical Sciences, Little Rock, AR, United States
| | - Ania K. Majewska
- Department of Neuroscience, University of Rochester Medical Center, Rochester, NY, United States
| | - Cynthia J. M. Kane
- Department of Neurobiology and Developmental Sciences, University of Arkansas for Medical Sciences, Little Rock, AR, United States
| | - Paul D. Drew
- Department of Neurobiology and Developmental Sciences, University of Arkansas for Medical Sciences, Little Rock, AR, United States
- Department of Neurology, University of Arkansas for Medical Sciences, Little Rock, AR, United States
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18
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I F. The unique neuropathological vulnerability of the human brain to aging. Ageing Res Rev 2023; 87:101916. [PMID: 36990284 DOI: 10.1016/j.arr.2023.101916] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 03/19/2023] [Accepted: 03/21/2023] [Indexed: 03/30/2023]
Abstract
Alzheimer's disease (AD)-related neurofibrillary tangles (NFT), argyrophilic grain disease (AGD), aging-related tau astrogliopathy (ARTAG), limbic predominant TDP-43 proteinopathy (LATE), and amygdala-predominant Lewy body disease (LBD) are proteinopathies that, together with hippocampal sclerosis, progressively appear in the elderly affecting from 50% to 99% of individuals aged 80 years, depending on the disease. These disorders usually converge on the same subject and associate with additive cognitive impairment. Abnormal Tau, TDP-43, and α-synuclein pathologies progress following a pattern consistent with an active cell-to-cell transmission and abnormal protein processing in the host cell. However, cell vulnerability and transmission pathways are specific for each disorder, albeit abnormal proteins may co-localize in particular neurons. All these alterations are unique or highly prevalent in humans. They all affect, at first, the archicortex and paleocortex to extend at later stages to the neocortex and other regions of the telencephalon. These observations show that the phylogenetically oldest areas of the human cerebral cortex and amygdala are not designed to cope with the lifespan of actual humans. New strategies aimed at reducing the functional overload of the human telencephalon, including optimization of dream repair mechanisms and implementation of artificial circuit devices to surrogate specific brain functions, appear promising.
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Affiliation(s)
- Ferrer I
- Department of Pathology and Experimental Therapeutics, University of Barcelona, Barcelona, Spain; Emeritus Researcher of the Bellvitge Institute of Biomedical Research (IDIBELL), Barcelona, Spain; Biomedical Research Network of Neurodegenerative Diseases (CIBERNED), Barcelona, Spain; Institute of Neurosciences, University of Barcelona, Barcelona, Spain; Hospitalet de Llobregat, Barcelona, Spain.
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19
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Holloway KN, Pinson MR, Douglas JC, Rafferty TM, Kane CJM, Miranda RC, Drew PD. Cerebellar Transcriptomic Analysis in a Chronic plus Binge Mouse Model of Alcohol Use Disorder Demonstrates Ethanol-Induced Neuroinflammation and Altered Glial Gene Expression. Cells 2023; 12:745. [PMID: 36899881 PMCID: PMC10000476 DOI: 10.3390/cells12050745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 02/21/2023] [Accepted: 02/24/2023] [Indexed: 03/02/2023] Open
Abstract
Alcohol use disorder (AUD) is one of the most common preventable mental health disorders and can result in pathology within the CNS, including the cerebellum. Cerebellar alcohol exposure during adulthood has been associated with disruptions in proper cerebellar function. However, the mechanisms regulating ethanol-induced cerebellar neuropathology are not well understood. High-throughput next generation sequencing was performed to compare control versus ethanol-treated adult C57BL/6J mice in a chronic plus binge model of AUD. Mice were euthanized, cerebella were microdissected, and RNA was isolated and submitted for RNA-sequencing. Down-stream transcriptomic analyses revealed significant changes in gene expression and global biological pathways in control versus ethanol-treated mice that included pathogen-influenced signaling pathways and cellular immune response pathways. Microglial-associated genes showed a decrease in homeostasis-associated transcripts and an increase in transcripts associated with chronic neurodegenerative diseases, while astrocyte-associated genes showed an increase in transcripts associated with acute injury. Oligodendrocyte lineage cell genes showed a decrease in transcripts associated with both immature progenitors as well as myelinating oligodendrocytes. These data provide new insight into the mechanisms by which ethanol induces cerebellar neuropathology and alterations to the immune response in AUD.
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Affiliation(s)
- Kalee N. Holloway
- Department of Neurobiology and Developmental Sciences, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA; (K.N.H.); (J.C.D.); (T.M.R.); (C.J.M.K.)
| | - Marisa R. Pinson
- Department of Neuroscience and Experimental Therapeutics, Texas A&M University School of Medicine, Bryan, TX 77807, USA; (M.R.P.); (R.C.M.)
| | - James C. Douglas
- Department of Neurobiology and Developmental Sciences, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA; (K.N.H.); (J.C.D.); (T.M.R.); (C.J.M.K.)
| | - Tonya M. Rafferty
- Department of Neurobiology and Developmental Sciences, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA; (K.N.H.); (J.C.D.); (T.M.R.); (C.J.M.K.)
| | - Cynthia J. M. Kane
- Department of Neurobiology and Developmental Sciences, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA; (K.N.H.); (J.C.D.); (T.M.R.); (C.J.M.K.)
| | - Rajesh C. Miranda
- Department of Neuroscience and Experimental Therapeutics, Texas A&M University School of Medicine, Bryan, TX 77807, USA; (M.R.P.); (R.C.M.)
| | - Paul D. Drew
- Department of Neurobiology and Developmental Sciences, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA; (K.N.H.); (J.C.D.); (T.M.R.); (C.J.M.K.)
- Department of Neurology, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA
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20
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Fan K, Francis L, Aslam MM, Bedison MA, Lawrence E, Acharya V, Snitz BE, Ganguli M, DeKosky ST, Lopez OL, Feingold E, Kamboh MI. Investigation of the independent role of a rare APOE variant (L28P; APOE*4Pittsburgh) in late-onset Alzheimer disease. Neurobiol Aging 2023; 122:107-111. [PMID: 36528961 PMCID: PMC9839598 DOI: 10.1016/j.neurobiolaging.2022.11.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Accepted: 11/05/2022] [Indexed: 11/19/2022]
Abstract
A rare missense APOE variant (L28P; APOE*4Pittsburgh), which is present only in populations with European ancestry, has been reported to be a risk factor for late-onset Alzheimer's disease (LOAD). However, due to the complete linkage disequilibrium of L28P with APOE*4 (C112R), its independent genetic association is uncertain. The original association study implicating L28P with LOAD risk was carried out in a relatively small sample size. In the current study, we have re-evaluated this association in a large case-control sample of 15,762 White U.S. subjects and investigated its independent effect in APOE 3/4 subjects, as L28P has been observed only in the heterozygous state of APOE*4 carriers and 3/4 is the most common genotype containing the APOE*4 allele. The heterozygous carrier frequency of L28P, all with APOE*4, was about 3-fold higher in AD cases than in cognitively intact controls (0.845% vs. 0.277%). The age- and sex-adjusted meta-analysis odds ratio (OR) was 2.87 (95% CI: 1.34 - 6.13; = 0.0066). Among APOE 3/4 subjects, age- and sex-adjusted meta-analysis OR was 1.53 (95% CI: 0.70 - 3.36; p = 0.28), indicating its effect was independent of APOE*4. The lack of statistical significance appears mainly due to the low power of 4138 subjects with the 3/4 genotype (12% power at α= 0.05) compared to the required sample of 139,088 subjects with the 3/4 genotype to detect an OR of 1.5 at α= 0.05 and 80% power. Our data suggesting that L28P has an independent genetic effect on AD risk is reinforced by earlier experimental findings showing that this mutation leads to significant structural and conformational changes in the ApoE4 molecule and can induce functional defects associated with neuronal Aβ42 accumulation and oxidative stress. Additional functional studies in cell-based systems and animal models will help to delineate its functional significance in the etiology of AD.
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Affiliation(s)
- KangHsien Fan
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Lily Francis
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - M Muaaz Aslam
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Margret A Bedison
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Elizabeth Lawrence
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Vibha Acharya
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Beth E Snitz
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Mary Ganguli
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Department of Epidemiology, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Steven T DeKosky
- McKnight Brain Institute and Department of Neurology, College of Medicine, University of Florida, FL, USA
| | - Oscar L Lopez
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Eleanor Feingold
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - M Ilyas Kamboh
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA; Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Department of Epidemiology, School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.
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21
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Cerulli Irelli E, Cocchi E, Ramantani G, Riva A, Caraballo RH, Morano A, Giuliano L, Yilmaz T, Panagiotakaki E, Operto FF, Giraldez BG, Balestrini S, Silvennoinen K, Casciato S, Comajuan M, Fortunato F, Giallonardo AT, Gamirova R, Coppola A, Di Gennaro G, Labate A, Sofia V, Kluger GJ, Gambardella A, Kasteleijn-Nolst Trenite D, Baykan B, Sisodiya SM, Arzimanoglou A, Striano P, Di Bonaventura C. The spectrum of epilepsy with eyelid myoclonia: delineation of disease subtypes from a large multicenter study. Epilepsia 2022; 64:196-207. [PMID: 36307934 DOI: 10.1111/epi.17450] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 10/26/2022] [Accepted: 10/26/2022] [Indexed: 02/18/2024]
Abstract
OBJECTIVE Epilepsy with eyelid myoclonia (EEM) has been associated with marked clinical heterogeneity. Early epilepsy onset has been recently linked to lower chances of achieving sustained remission and to a less favorable neuropsychiatric outcome. However, much work is still needed to better delineate this epilepsy syndrome. METHODS In this multicenter retrospective cohort study, we included 267 EEM patients from 9 countries. Data about electroclinical and demographic features, intellectual functioning, migraine with or without aura, family history of epilepsy and epilepsy syndromes in relatives were collected in each patient. The impact of age at epilepsy onset (AEO) on EEM clinical features was investigated, along with the distinctive clinical characteristics of patients showing sporadic myoclonia over body regions other than eyelids (body-MYO). RESULTS Kernel density estimation revealed a trimodal distribution of AEO and Fisher-Jenks optimization disclosed three EEM subgroups: early-onset (EO-EEM), intermediate-onset (IO-EEM) and late-onset subgroup (LO-EEM). EO-EEM was associated with the highest rate of intellectual disability, antiseizure medication refractoriness and psychiatric comorbidities and with the lowest rate of family history of epilepsy. LO-EEM was associated with the highest proportion of body-MYO and generalized tonic-clonic seizures (GTCS), whereas IO-EEM had the lowest observed rate of additional findings. A family history of EEM was significantly more frequent in IO-EEM and LO-EEM compared with EO-EEM. In the subset of patients with body-MYO (58/267), we observed a significantly higher rate of migraine and GTCS but no relevant differences in other electroclinical features and seizure outcome. SIGNIFICANCE Based on AEO, we identified consistent EEM subtypes characterized by distinct electroclinical and familial features. Our observations shed new light on the spectrum of clinical features of this generalized epilepsy syndrome and may help clinicians towards a more accurate classification and prognostic profiling of EEM patients.
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Affiliation(s)
| | - Enrico Cocchi
- Department of Precision Medicine and Genomics, Department of Medicine, Columbia University, New York
| | - Georgia Ramantani
- Department of Neuropediatrics, University Children's Hospital Zurich, Zurich, Switzerland
| | - Antonella Riva
- Department of Neurosciences Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
| | - Roberto H Caraballo
- Department of Neurology, Hospital de Pediatría "Prof. Dr. Juan P Garrahan", Buenos Aires, Argentina
| | - Alessandra Morano
- Department of Human Neurosciences, Sapienza, University of Rome, Rome, Italy
| | - Loretta Giuliano
- Department of Medical and Surgical Sciences and Advanced Technologies "G.F. Ingrassia", Section of Neurosciences, University of Catania, Catania, Italy
| | - Tülay Yilmaz
- Departments of Neurology and Clinical Neurophysiology, Istanbul University, Istanbul Faculty of Medicine, Istanbul, Turkey
| | - Eleni Panagiotakaki
- Department of Paediatric Clinical Epileptology, Sleep Disorders and Functional Neurology, University Hospitals of Lyon (HCL), Member of the ERN EpiCARE, Lyon, France
| | - Francesca F Operto
- Child and Adolescent Neuropsychiatry Unit, Department of Medicine, Surgery and Dentistry, University of Salerno, Salerno, Italy
| | - Beatriz Gonzalez Giraldez
- Epilepsy Unit, Neurology Service, Hospital Universitario and IIS Fundación Jiménez Díaz and CIBERER, Madrid, Spain
| | - Simona Balestrini
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London, UK and Chalfont Centre for Epilepsy, Bucks, UK; Neuroscience Department, Meyer Children's Hospital-University of Florence, Member of the ERN EpiCARE, Florence, Italy
| | - Katri Silvennoinen
- Department of Clinical and Experimental Epilepsy, Partner of the ERN EpiCARE, UCL Queen Square Institute of Neurology, London, UK and Chalfont Centre for Epilepsy, Bucks, UK
| | | | - Marion Comajuan
- Department of Paediatric Clinical Epileptology, Sleep Disorders and Functional Neurology, University Hospitals of Lyon (HCL), Member of the ERN EpiCARE, Lyon, France
| | | | - Anna T Giallonardo
- Department of Human Neurosciences, Sapienza, University of Rome, Rome, Italy
| | | | - Antonietta Coppola
- Department of Neuroscience, Reproductive and Odontostomatological Sciences, Federico II University, Naples, Italy
| | | | - Angelo Labate
- Neurophysiopatology and Movement Disorders Clinic, University of Messina, Italy
| | - Vito Sofia
- Department of Medical and Surgical Sciences and Advanced Technologies "G.F. Ingrassia", Section of Neurosciences, University of Catania, Catania, Italy
| | - Gerhard J Kluger
- Clinic for Neuropediatrics and Neurorehabilitation, Epilepsy Center for Children and Adolescents, Schoen Clinic Vogtareuth, Vogtareuth, Germany; PMU, Salzburg, Salzburg, Austria
| | | | - Dorothee Kasteleijn-Nolst Trenite
- Department of Neurosurgery and Epilepsy, University Medical Center, Member of the ERN EpiCARE, Utrecht University, Utrecht, The Netherlands; Nesmos Department, Faculty of Medicine and Psychology, Sapienza University, Rome, Italy
| | - Betul Baykan
- Departments of Neurology and Clinical Neurophysiology, Istanbul University, Istanbul Faculty of Medicine, Istanbul, Turkey
| | - Sanjay M Sisodiya
- Department of Clinical and Experimental Epilepsy, Partner of the ERN EpiCARE, UCL Queen Square Institute of Neurology, London, UK and Chalfont Centre for Epilepsy, Bucks, UK
| | - Alexis Arzimanoglou
- Department of Paediatric Clinical Epileptology, Sleep Disorders and Functional Neurology, University Hospitals of Lyon (HCL), Member of the ERN EpiCARE, Lyon, France
| | - Pasquale Striano
- Pediatric Neurology and Muscular Diseases Unit, IRCCS Istituto "Giannina Gaslini", Member of the ERN EpiCARE, Genoa, Italy; Department of Neurosciences Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
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22
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Limone A, Veneruso I, D'Argenio V, Sarnataro D. Endosomal trafficking and related genetic underpinnings as a hub in Alzheimer's disease. J Cell Physiol 2022; 237:3803-3815. [PMID: 35994714 DOI: 10.1002/jcp.30864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 07/13/2022] [Accepted: 08/08/2022] [Indexed: 01/07/2023]
Abstract
Genetic studies support the amyloid cascade as the leading hypothesis for the pathogenesis of Alzheimer's disease (AD). Although significant efforts have been made in untangling the amyloid and other pathological events in AD, ongoing interventions for AD have not been revealed efficacious for slowing down disease progression. Recent advances in the field of genetics have shed light on the etiology of AD, identifying numerous risk genes associated with late-onset AD, including genes related to intracellular endosomal trafficking. Some of the bases for the development of AD may be explained by the recently emerging AD genetic "hubs," which include the processing pathway of amyloid precursor protein and the endocytic pathway. The endosomal genetic hub may represent a common pathway through which many pathological effects can be mediated and novel, alternative biological targets could be identified for therapeutic interventions. The aim of this review is to focus on the genetic and biological aspects of the endosomal compartments related to AD progression. We report recent studies which describe how changes in endosomal genetics impact on functional events, such as the amyloidogenic and non-amyloidogenic processing, degradative pathways, and the importance of receptors related to endocytic trafficking, including the 37/67 kDa laminin-1 receptor ribosomal protein SA, and their implications for neurodegenerative diseases.
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Affiliation(s)
- Adriana Limone
- Department of Molecular Medicine and Medical Biotechnology, Federico II University, Napoli, Italy
| | - Iolanda Veneruso
- Department of Molecular Medicine and Medical Biotechnology, Federico II University, Napoli, Italy.,CEINGE-Biotecnologie Avanzate, Napoli, Italy
| | - Valeria D'Argenio
- CEINGE-Biotecnologie Avanzate, Napoli, Italy.,Department of Human Sciences and Quality of Life Promotion, San Raffaele Open University, Roma, Italy
| | - Daniela Sarnataro
- Department of Molecular Medicine and Medical Biotechnology, Federico II University, Napoli, Italy
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23
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Saiyasit N, Butlig EAR, Chaney SD, Traylor MK, Hawley NA, Randall RB, Bobinger HV, Frizell CA, Trimm F, Crook ED, Lin M, Hill BD, Keller JL, Nelson AR. Neurovascular Dysfunction in Diverse Communities With Health Disparities-Contributions to Dementia and Alzheimer's Disease. Front Neurosci 2022; 16:915405. [PMID: 35844216 PMCID: PMC9279126 DOI: 10.3389/fnins.2022.915405] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2022] [Accepted: 05/31/2022] [Indexed: 12/13/2022] Open
Abstract
Alzheimer's disease and related dementias (ADRD) are an expanding worldwide crisis. In the absence of scientific breakthroughs, the global prevalence of ADRD will continue to increase as more people are living longer. Racial or ethnic minority groups have an increased risk and incidence of ADRD and have often been neglected by the scientific research community. There is mounting evidence that vascular insults in the brain can initiate a series of biological events leading to neurodegeneration, cognitive impairment, and ADRD. We are a group of researchers interested in developing and expanding ADRD research, with an emphasis on vascular contributions to dementia, to serve our local diverse community. Toward this goal, the primary objective of this review was to investigate and better understand health disparities in Alabama and the contributions of the social determinants of health to those disparities, particularly in the context of vascular dysfunction in ADRD. Here, we explain the neurovascular dysfunction associated with Alzheimer's disease (AD) as well as the intrinsic and extrinsic risk factors contributing to dysfunction of the neurovascular unit (NVU). Next, we ascertain ethnoregional health disparities of individuals living in Alabama, as well as relevant vascular risk factors linked to AD. We also discuss current pharmaceutical and non-pharmaceutical treatment options for neurovascular dysfunction, mild cognitive impairment (MCI) and AD, including relevant studies and ongoing clinical trials. Overall, individuals in Alabama are adversely affected by social and structural determinants of health leading to health disparities, driven by rurality, ethnic minority status, and lower socioeconomic status (SES). In general, these communities have limited access to healthcare and healthy food and other amenities resulting in decreased opportunities for early diagnosis of and pharmaceutical treatments for ADRD. Although this review is focused on the current state of health disparities of ADRD patients in Alabama, future studies must include diversity of race, ethnicity, and region to best be able to treat all individuals affected by ADRD.
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Affiliation(s)
- Napatsorn Saiyasit
- Department of Physiology and Cell Biology, College of Medicine, University of South Alabama, Mobile, AL, United States
| | - Evan-Angelo R. Butlig
- Department of Neurology, Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, Intellectual and Developmental Disabilities Research Center, University of California, Los Angeles, Los Angeles, CA, United States
| | - Samantha D. Chaney
- Department of Physiology and Cell Biology, College of Medicine, University of South Alabama, Mobile, AL, United States
| | - Miranda K. Traylor
- Department of Health, Kinesiology, and Sport, University of South Alabama, Mobile, AL, United States
| | - Nanako A. Hawley
- Department of Psychology, University of South Alabama, Mobile, AL, United States
| | - Ryleigh B. Randall
- Department of Physiology and Cell Biology, College of Medicine, University of South Alabama, Mobile, AL, United States
| | - Hanna V. Bobinger
- Department of Physiology and Cell Biology, College of Medicine, University of South Alabama, Mobile, AL, United States
| | - Carl A. Frizell
- Department of Physician Assistant Studies, University of South Alabama, Mobile, AL, United States
| | - Franklin Trimm
- College of Medicine, University of South Alabama, Mobile, AL, United States
| | - Errol D. Crook
- Department of Internal Medicine, College of Medicine, University of South Alabama, Mobile, AL, United States
| | - Mike Lin
- Department of Physiology and Cell Biology, College of Medicine, University of South Alabama, Mobile, AL, United States
| | - Benjamin D. Hill
- Department of Psychology, University of South Alabama, Mobile, AL, United States
| | - Joshua L. Keller
- Department of Health, Kinesiology, and Sport, University of South Alabama, Mobile, AL, United States
| | - Amy R. Nelson
- Department of Physiology and Cell Biology, College of Medicine, University of South Alabama, Mobile, AL, United States
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24
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Song C, Shi J, Zhang P, Zhang Y, Xu J, Zhao L, Zhang R, Wang H, Chen H. Immunotherapy for Alzheimer's disease: targeting β-amyloid and beyond. Transl Neurodegener 2022; 11:18. [PMID: 35300725 PMCID: PMC8932191 DOI: 10.1186/s40035-022-00292-3] [Citation(s) in RCA: 77] [Impact Index Per Article: 38.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 02/25/2022] [Indexed: 12/16/2022] Open
Abstract
Alzheimer's disease (AD) is the most common neurodegenerative disease in the elderly worldwide. However, the complexity of AD pathogenesis leads to discrepancies in the understanding of this disease, and may be the main reason for the failure of AD drug development. Fortunately, many ongoing preclinical and clinical studies will continually open up avenues to unravel disease mechanisms and guide strategies for AD diagnosis and drug development. For example, immunotherapeutic strategies targeting amyloid-β (Aβ) and tau proteins were once deemed almost certainly effective in clinical treatment due to the excellent preclinical results. However, the repeated failures of clinical trials on vaccines and humanized anti-Aβ and anti-tau monoclonal antibodies have resulted in doubts on this strategy. Recently, a new anti-Aβ monoclonal antibody (Aducanumab) has been approved by the US Food and Drug Administration, which brings us back to the realization that immunotherapy strategies targeting Aβ may be still promising. Meanwhile, immunotherapies based on other targets such as tau, microglia and gut-brain axis are also under development. Further research is still needed to clarify the forms and epitopes of targeted proteins to improve the accuracy and effectiveness of immunotherapeutic drugs. In this review, we focus on the immunotherapies based on Aβ, tau and microglia and their mechanisms of action in AD. In addition, we present up-to-date advances and future perspectives on immunotherapeutic strategies for AD.
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Affiliation(s)
- Chenghuan Song
- Department of Pharmacology and Chemical Biology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Shanghai Universities Collaborative Innovation Center for Translational Medicine, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Jiyun Shi
- Department of Pharmacology and Chemical Biology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Shanghai Universities Collaborative Innovation Center for Translational Medicine, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Pingao Zhang
- Department of Pharmacology and Chemical Biology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Shanghai Universities Collaborative Innovation Center for Translational Medicine, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Yongfang Zhang
- Department of Pharmacology and Chemical Biology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Shanghai Universities Collaborative Innovation Center for Translational Medicine, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Jianrong Xu
- Department of Pharmacology and Chemical Biology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Academy of Integrative Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, China
| | - Lanxue Zhao
- Department of Pharmacology and Chemical Biology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Shanghai Universities Collaborative Innovation Center for Translational Medicine, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Rui Zhang
- Department of Pharmacology and Chemical Biology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Shanghai Universities Collaborative Innovation Center for Translational Medicine, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Hao Wang
- Department of Pharmacology and Chemical Biology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- Shanghai Universities Collaborative Innovation Center for Translational Medicine, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- Academy of Integrative Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, China.
| | - Hongzhuan Chen
- Department of Pharmacology and Chemical Biology, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- Shanghai Universities Collaborative Innovation Center for Translational Medicine, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
- Department of Clinical Pharmacy, Institute of Interdisciplinary Integrative Medicine Research, Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, China.
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25
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Chen Y, Chen T, Hou R. Locus coeruleus in the pathogenesis of Alzheimer's disease: A systematic review. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2022; 8:e12257. [PMID: 35282658 PMCID: PMC8900465 DOI: 10.1002/trc2.12257] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Revised: 12/19/2021] [Accepted: 12/21/2021] [Indexed: 01/22/2023]
Abstract
The locus coeruleus (LC) is a nucleus in the brain stem producing noradrenaline. While cognitive decline in Alzheimer's disease (AD) has primarily been related to cholinergic depletion, evidence indicates extensive LC degeneration as its earliest pathological marker. The current study aimed to systematically evaluate current evidence investigating the role of the LC in the pathogenesis of AD. A systematic search of the literature was performed on electronic databases including PubMed and Web of Science. Twelve animal, human post mortem, and human imaging studies were included in this review. Screening, data extraction, and quality assessment were undertaken following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for preferred reporting of systematic reviews. Significant associations were identified between LC changes and cognitive decline. Significant reductions in fiber density, neuronal number, and LC volume were seen to correlate with other pathological degenerative markers. Current evidence indicates an important role of the LC in pathogenesis of AD and suggests its potential in both diagnosis and treatment of AD. This systematic review advances our understanding of the role of the LC in AD by synthesizing available evidence, identifying research gaps, highlighting methodological challenges, and making recommendations for future work.
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Affiliation(s)
- Yuqing Chen
- School of Clinical MedicineAddenbrooke's HospitalUniversity of CambridgeCambridgeUK
| | - Teng Chen
- Department of NeurosurgeryQilu Hospital of Shandong UniversityJinanShandongChina
| | - Ruihua Hou
- Clinical and Experimental SciencesFaculty of MedicineUniversity of SouthamptonSouthamptonUK
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26
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Abstract
Alzheimer's disease (AD) is a complex and multifactorial neurodegenerative disease. Due to its long clinical course and lack of an effective treatment, AD has become a major public health problem in the USA and worldwide. Due to variation in age-at-onset, AD is classified into early-onset (< 60 years) and late-onset (≥ 60 years) forms with early-onset accounting for only 5-10% of all cases. With the exception of a small number of early-onset cases that are afflicted because of high penetrant single gene mutations in APP, PSEN1, and PSEN2 genes, AD is genetically heterogeneous, especially the late-onset form having a polygenic or oligogenic risk inheritance. Since the identification of APOE as the most significant risk factor for late-onset AD in 1993, the path to the discovery of additional AD risk genes had been arduous until 2009 when the use of large genome-wide association studies opened up the discovery gateways that led the identification of ~ 95 additional risk loci from 2009 to early 2022. This article reviews the history of AD genetics followed by the potential molecular pathways and recent application of functional genomics methods to identify the causal AD gene(s) among the many genes that reside within a single locus. The ultimate goal of integrating genomics and functional genomics is to discover novel pathways underlying the AD pathobiology in order to identify drug targets for the therapeutic treatment of this heterogeneous disorder.
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Affiliation(s)
- M Ilyas Kamboh
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.
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27
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Duara R, Barker W. Heterogeneity in Alzheimer's Disease Diagnosis and Progression Rates: Implications for Therapeutic Trials. Neurotherapeutics 2022; 19:8-25. [PMID: 35084721 PMCID: PMC9130395 DOI: 10.1007/s13311-022-01185-z] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/05/2022] [Indexed: 01/03/2023] Open
Abstract
The clinical presentation and the pathological processes underlying Alzheimer's disease (AD) can be very heterogeneous in severity, location, and composition including the amount and distribution of AB deposition and spread of neurofibrillary tangles in different brain regions resulting in atypical clinical patterns and the existence of distinct AD variants. Heterogeneity in AD may be related to demographic factors (such as age, sex, educational and socioeconomic level) and genetic factors, which influence underlying pathology, the cognitive and behavioral phenotype, rate of progression, the occurrence of neuropsychiatric features, and the presence of comorbidities (e.g., vascular disease, neuroinflammation). Heterogeneity is also manifest in the individual resilience to the development of neuropathology (brain reserve) and the ability to compensate for its cognitive and functional impact (cognitive and functional reserve). The variability in specific cognitive profiles and types of functional impairment may be associated with different progression rates, and standard measures assessing progression may not be equivalent for individual cognitive and functional profiles. Other factors, which may govern the presence, rate, and type of progression of AD, include the individuals' general medical health, the presence of specific systemic conditions, and lifestyle factors, including physical exercise, cognitive and social stimulation, amount of leisure activities, environmental stressors, such as toxins and pollution, and the effects of medications used to treat medical and behavioral conditions. These factors that affect progression are important to consider while designing a clinical trial to ensure, as far as possible, well-balanced treatment and control groups.
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Affiliation(s)
- Ranjan Duara
- Wien Center for Alzheimer's Disease and Memory Disorders, Mount Sinai Medical Center, Miami Beach, FL, USA
- Departments of Neurology, University of Florida College of Medicine, Gainesville, FL, USA
- Herbert Wertheim College of Medicine, Florida International University, Miami, FL, USA
| | - Warren Barker
- Wien Center for Alzheimer's Disease and Memory Disorders, Mount Sinai Medical Center, Miami Beach, FL, USA.
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28
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Bacalini MG, Palombo F, Garagnani P, Giuliani C, Fiorini C, Caporali L, Stanzani Maserati M, Capellari S, Romagnoli M, De Fanti S, Benussi L, Binetti G, Ghidoni R, Galimberti D, Scarpini E, Arcaro M, Bonanni E, Siciliano G, Maestri M, Guarnieri B, Martucci M, Monti D, Carelli V, Franceschi C, La Morgia C, Santoro A. Association of rs3027178 polymorphism in the circadian clock gene PER1 with susceptibility to Alzheimer's disease and longevity in an Italian population. GeroScience 2021; 44:881-896. [PMID: 34921659 PMCID: PMC9135916 DOI: 10.1007/s11357-021-00477-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 10/15/2021] [Indexed: 12/11/2022] Open
Abstract
Many physiological processes in the human body follow a 24-h circadian rhythm controlled by the circadian clock system. Light, sensed by retina, is the predominant “zeitgeber” able to synchronize the circadian rhythms to the light-dark cycles. Circadian rhythm dysfunction and sleep disorders have been associated with aging and neurodegenerative diseases including mild cognitive impairment (MCI) and Alzheimer’s disease (AD). In the present study, we aimed at investigating the genetic variability of clock genes in AD patients compared to healthy controls from Italy. We also included a group of Italian centenarians, considered as super-controls in association studies given their extreme phenotype of successful aging. We analyzed the exon sequences of eighty-four genes related to circadian rhythms, and the most significant variants identified in this first discovery phase were further assessed in a larger independent cohort of AD patients by matrix assisted laser desorption/ionization-time of flight mass spectrometry. The results identified a significant association between the rs3027178 polymorphism in the PER1 circadian gene with AD, the G allele being protective for AD. Interestingly, rs3027178 showed similar genotypic frequencies among AD patients and centenarians. These results collectively underline the relevance of circadian dysfunction in the predisposition to AD and contribute to the discussion on the role of the relationship between the genetics of age-related diseases and of longevity.
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Affiliation(s)
- Maria Giulia Bacalini
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Laboratorio Brain Aging, Bologna, Italy
| | - Flavia Palombo
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Programma di Neurogenetica, Bologna, Italy
| | - Paolo Garagnani
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy.,Applied Biomedical Research Center (CRBA), S. Orsola-Malpighi Polyclinic, Bologna, Italy.,CNR Institute of Molecular Genetics "Luigi Luca Cavalli-Sforza", Unit of Bologna, Bologna, Italy.,Department of Laboratory Medicine, Clinical Chemistry, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden.,Alma Mater Research Institute on Global Challenges and Climate Change (Alma Climate), University of Bologna, Bologna, Italy
| | - Cristina Giuliani
- Alma Mater Research Institute on Global Challenges and Climate Change (Alma Climate), University of Bologna, Bologna, Italy.,Laboratory of Molecular Anthropology and Centre for Genome Biology, Department of Biological, Geological and Environmental Sciences, University of Bologna, Bologna, Italy
| | - Claudio Fiorini
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Programma di Neurogenetica, Bologna, Italy
| | - Leonardo Caporali
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Programma di Neurogenetica, Bologna, Italy
| | | | - Sabina Capellari
- IRCCS Istituto delle Scienze Neurologiche di Bologna, UOC Clinica Neurologica, Bologna, Italy.,Department of Biomedical and Neuromotor Sciences (DIBINEM), University of Bologna, Bologna, Italy
| | - Martina Romagnoli
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Programma di Neurogenetica, Bologna, Italy
| | - Sara De Fanti
- Alma Mater Research Institute on Global Challenges and Climate Change (Alma Climate), University of Bologna, Bologna, Italy.,Laboratory of Molecular Anthropology and Centre for Genome Biology, Department of Biological, Geological and Environmental Sciences, University of Bologna, Bologna, Italy
| | - Luisa Benussi
- IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Giuliano Binetti
- IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Roberta Ghidoni
- IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Daniela Galimberti
- Fondazione IRCCS Ca' Granda, Ospedale Policlinico, Milan, Italy.,Dino Ferrari Center, University of Milan, Milan, Italy
| | - Elio Scarpini
- Fondazione IRCCS Ca' Granda, Ospedale Policlinico, Milan, Italy.,Dino Ferrari Center, University of Milan, Milan, Italy
| | - Marina Arcaro
- Fondazione IRCCS Ca' Granda, Ospedale Policlinico, Milan, Italy
| | - Enrica Bonanni
- Neurology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Gabriele Siciliano
- Neurology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Michelangelo Maestri
- Neurology Unit, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Biancamaria Guarnieri
- Center of Sleep Medicine, Villa Serena Hospital and Villaserena Foundation for the Research, Città S. Angelo, Pescara, Italy
| | | | - Morena Martucci
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy
| | - Daniela Monti
- Department of Experimental and Clinical Biomedical Sciences "Mario Serio", University of Florence, Florence, Italy
| | - Valerio Carelli
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Programma di Neurogenetica, Bologna, Italy.,Department of Biomedical and Neuromotor Sciences (DIBINEM), University of Bologna, Bologna, Italy
| | - Claudio Franceschi
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy.,Department of Applied Mathematics, Institute of Information Technology, Mathematics and Mechanics (ITMM), Lobachevsky State University of Nizhny Novgorod-National Research University (UNN), Nizhny Novgorod, Russia
| | - Chiara La Morgia
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Programma di Neurogenetica, Bologna, Italy.,IRCCS Istituto delle Scienze Neurologiche di Bologna, UOC Clinica Neurologica, Bologna, Italy
| | - Aurelia Santoro
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, Bologna, Italy. .,Alma Mater Research Institute on Global Challenges and Climate Change (Alma Climate), University of Bologna, Bologna, Italy.
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29
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Kalman JL, Olde Loohuis LM, Vreeker A, McQuillin A, Stahl EA, Ruderfer D, Grigoroiu-Serbanescu M, Panagiotaropoulou G, Ripke S, Bigdeli TB, Stein F, Meller T, Meinert S, Pelin H, Streit F, Papiol S, Adams MJ, Adolfsson R, Adorjan K, Agartz I, Aminoff SR, Anderson-Schmidt H, Andreassen OA, Ardau R, Aubry JM, Balaban C, Bass N, Baune BT, Bellivier F, Benabarre A, Bengesser S, Berrettini WH, Boks MP, Bromet EJ, Brosch K, Budde M, Byerley W, Cervantes P, Chillotti C, Cichon S, Clark SR, Comes AL, Corvin A, Coryell W, Craddock N, Craig DW, Croarkin PE, Cruceanu C, Czerski PM, Dalkner N, Dannlowski U, Degenhardt F, Del Zompo M, DePaulo JR, Djurovic S, Edenberg HJ, Eissa MA, Elvsåshagen T, Etain B, Fanous AH, Fellendorf F, Fiorentino A, Forstner AJ, Frye MA, Fullerton JM, Gade K, Garnham J, Gershon E, Gill M, Goes FS, Gordon-Smith K, Grof P, Guzman-Parra J, Hahn T, Hasler R, Heilbronner M, Heilbronner U, Jamain S, Jimenez E, Jones I, Jones L, Jonsson L, Kahn RS, Kelsoe JR, Kennedy JL, Kircher T, Kirov G, Kittel-Schneider S, Klöhn-Saghatolislam F, Knowles JA, Kranz TM, Lagerberg TV, Landen M, Lawson WB, Leboyer M, Li QS, Maj M, Malaspina D, Manchia M, Mayoral F, McElroy SL, McInnis MG, McIntosh AM, Medeiros H, Melle I, Milanova V, Mitchell PB, Monteleone P, Monteleone AM, Nöthen MM, Novak T, Nurnberger JI, O'Brien N, O'Connell KS, O'Donovan C, O'Donovan MC, Opel N, Ortiz A, Owen MJ, Pålsson E, Pato C, Pato MT, Pawlak J, Pfarr JK, Pisanu C, Potash JB, Rapaport MH, Reich-Erkelenz D, Reif A, Reininghaus E, Repple J, Richard-Lepouriel H, Rietschel M, Ringwald K, Roberts G, Rouleau G, Schaupp S, Scheftner WA, Schmitt S, Schofield PR, Schubert KO, Schulte EC, Schweizer B, Senner F, Severino G, Sharp S, Slaney C, Smeland OB, Sobell JL, Squassina A, Stopkova P, Strauss J, Tortorella A, Turecki G, Twarowska-Hauser J, Veldic M, Vieta E, Vincent JB, Xu W, Zai CC, Zandi PP, Di Florio A, Smoller JW, Biernacka JM, McMahon FJ, Alda M, Müller-Myhsok B, Koutsouleris N, Falkai P, Freimer NB, Andlauer TF, Schulze TG, Ophoff RA. Characterisation of age and polarity at onset in bipolar disorder. Br J Psychiatry 2021; 219:659-669. [PMID: 35048876 PMCID: PMC8636611 DOI: 10.1192/bjp.2021.102] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Revised: 05/26/2021] [Accepted: 07/01/2021] [Indexed: 01/12/2023]
Abstract
BACKGROUND Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools. AIMS To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics. METHOD Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts. RESULTS Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = -0.34 years, s.e. = 0.08), major depression (β = -0.34 years, s.e. = 0.08), schizophrenia (β = -0.39 years, s.e. = 0.08), and educational attainment (β = -0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO. CONCLUSIONS AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.
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Affiliation(s)
- Janos L. Kalman
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Germany; Department of Psychiatry and Psychotherapy, University Hospital Munich, Germany; and International Max Planck Research School for Translational Psychiatry, Germany
| | - Loes M. Olde Loohuis
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, USA
| | - Annabel Vreeker
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Centre–Sophia Children’s Hospital, the Netherlands
| | | | - Eli A. Stahl
- Division of Psychiatric Genomics, Mount Sinai School of Medicine, USA
| | - Douglas Ruderfer
- Division of Genetic Medicine, Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, USA; Department of Biomedical Informatics, Vanderbilt University Medical Center, USA; and Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, USA
| | | | | | - Stephan Ripke
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, USA; and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, USA
| | - Tim B. Bigdeli
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, USA; and VA NY Harbor Healthcare System, USA
| | - Frederike Stein
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany
| | - Tina Meller
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany; and Center for Mind, Brain and Behavior (CMBB), Germany
| | - Susanne Meinert
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Germany; and Institute for Translational Neuroscience, University of Münster, Germany
| | - Helena Pelin
- International Max Planck Research School for Translational Psychiatry, Germany; and Max Planck Institute of Psychiatry, Germany
| | - Fabian Streit
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Germany
| | - Sergi Papiol
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Germany; Department of Psychiatry and Psychotherapy, University Hospital Munich, Germany; and Centro de Investigación Biomedica en Red de Salud Mental (CIBERSAM), Spain
| | | | - Rolf Adolfsson
- Department of Clinical Sciences, Medical Faculty, Umeå University, Sweden
| | - Kristina Adorjan
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Germany; and Department of Psychiatry and Psychotherapy, University Hospital Munich, Germany
| | - Ingrid Agartz
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet, Sweden; Department of Psychiatric Research, Diakonhjemmet Hospital, Norway; and NORMENT Centre, Division of Mental Health and Addiction, Institute of Clinical Medicine, University of Oslo, Norway
| | - Sofie R. Aminoff
- Division of Mental Health and Addiction, Oslo University Hospital, Norway; and NORMENT Centre, Inst of Clinical Medicine, University of Oslo, Norway
| | - Heike Anderson-Schmidt
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Germany
| | - Ole A. Andreassen
- NORMENT Centre, Inst of Clinical Medicine, University of Oslo, Norway; and Division of Mental Health and Addiction, Oslo University Hosptial, Norway
| | - Raffaella Ardau
- Unit of Clinical Pharmacology, University Hospital Agency of Cagliari, Italy
| | - Jean-Michel Aubry
- Faculty of medicine, University of Geneva, Switzerland; and Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Germany
| | - Ceylan Balaban
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Germany
| | - Nicholas Bass
- Division of Psychiatry, University College London, UK
| | - Bernhard T. Baune
- Department of Psychiatry, University of Münster, Germany; Department of Psychiatry, Melbourne Medical School, The University of Melbourne, Australia; The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Australia; and Discipline of Psychiatry, Adelaide Medical School, The University of Adelaide, Australia
| | - Frank Bellivier
- Universite de Paris, France; INSERM UMRS 1144, France; and DMU Neurosciences, GHU Lariboisière Fernand Widal, Departement de Psychiatrie, APHP, France
| | - Antoni Benabarre
- Hospital Clinic, University of Barcelona, IDIBAPS, CIBERSAM, Spain
| | - Susanne Bengesser
- Department of Psychiatry and Psychotherapeutic Medicine, Medical University Graz, Austria
| | | | - Marco P. Boks
- Psychiatry, UMC Utrecht Brain Center, the Netherlands
| | | | - Katharina Brosch
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany
| | - Monika Budde
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Germany
| | | | | | - Catina Chillotti
- Unit of Clinical Pharmacology, University Hospital Agency of Cagliari, Italy
| | - Sven Cichon
- Department of Biomedicine, University of Basel, Switzerland; Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Germany; Institute of Medical Genetics and Pathology, University Hospital Basel, Switzerland; and Institute of Neuroscience and Medicine (INM-1), Research Centre Julich, Germany
| | - Scott R. Clark
- Discipline of Psychiatry, University of Adelaide, Australia; and Bazil Hetzel Institute, Australia
| | - Ashley L. Comes
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Germany; Department of Psychiatry and Psychotherapy, University Hospital Munich, Germany; and International Max Planck Research School for Translational Psychiatry, Germany
| | - Aiden Corvin
- Department of Psychiatry & Trinity Translational Medicine Institute, Trinity College Dublin, Ireland
| | | | - Nick Craddock
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, UK
| | | | | | - Cristiana Cruceanu
- Department of Translational Research, Max Planck Institute of Psychiatry, Germany
| | - Piotr M. Czerski
- Department of Psychiatric Genetics, Poznan University of Medical Sciences, Poland
| | - Nina Dalkner
- Department of Psychiatry and Psychotherapeutic Medicine, Medical University Graz, Austria
| | - Udo Dannlowski
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Germany
| | - Franziska Degenhardt
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Germany; and Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Essen, University of Duisburg-Essen, Germany
| | - Maria Del Zompo
- Department of Biomedical Science, Section of Neuroscience & Clinical Pharmacology, University of Cagliari, Italy; and Unit of Clinical Pharmacology, University Hospital Agency of Cagliari, Italy
| | - J. Raymond DePaulo
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, USA
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital Ullevål, Norway; and NORMENT, Department of Clinical Science, University of Bergen, Norway
| | - Howard J. Edenberg
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, USA
| | | | - Torbjørn Elvsåshagen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Norway
| | - Bruno Etain
- Universite de Paris, France; INSERM UMRS 1144, France; and DMU Neurosciences, GHU Lariboisière Fernand Widal, Departement de Psychiatrie, APHP, France
| | - Ayman H. Fanous
- Department of Psychiatry and Behavioral Sciences, SUNY Downstate Health Sciences University, USA; and VA NY Harbor Healthcare System, USA
| | - Frederike Fellendorf
- Department of Psychiatry and Psychotherapeutic Medicine, Medical University Graz, Austria
| | | | - Andreas J. Forstner
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Germany; and Centre for Human Genetics, University of Marburg, Germany
| | - Mark A. Frye
- Department of Psychiatry and Psychology, Mayo Clinic, USA
| | - Janice M. Fullerton
- Neuroscience Research Australia, Australia; and School of Medical Sciences, University of New South Wales, Australia
| | - Katrin Gade
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Germany
| | | | - Elliot Gershon
- Department of Psychiatry and Behavioral Neuroscience, University of Chicago, USA; and Department of Human Genetics, University of Chicago, USA
| | - Michael Gill
- Department of Psychiatry & Trinity Translational Medicine Institute, Trinity College Dublin, Ireland
| | - Fernando S. Goes
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, USA
| | | | - Paul Grof
- Mood Disorders Centre of Ottawa, Canada; and Department of Psychiatry, University of Toronto, Canada
| | - Jose Guzman-Parra
- Mental Health Department, University Regional Hospital, Biomedicine Institute (IBIMA), Spain
| | - Tim Hahn
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Germany
| | - Roland Hasler
- Cell Biology, SUNY Downstate Medical Center College of Medicine, USA; and Institute for Genomic Health, SUNY Downstate Medical Center College of Medicine, USA
| | - Maria Heilbronner
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Germany
| | - Urs Heilbronner
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Germany
| | - Stephane Jamain
- Universite Paris Est Creteil, France; and INSERM U 955, Neuropsychiatrie Translationnelle, France
| | - Esther Jimenez
- Hospital Clinic, University of Barcelona, IDIBAPS, CIBERSAM, Spain
| | - Ian Jones
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, UK
| | - Lisa Jones
- Psychological Medicine, University of Worcester, UK
| | - Lina Jonsson
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Sweden
| | - Rene S. Kahn
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, USA
| | - John R. Kelsoe
- Department of Psychiatry, University of California San Diego, USA
| | - James L. Kennedy
- Department of Psychiatry, University of Toronto, Canada; The Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Canada; and Institute of Medical Science, University of Toronto, Canada
| | - Tilo Kircher
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany
| | - George Kirov
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, UK
| | - Sarah Kittel-Schneider
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Germany; and Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital Wurzburg, Germany
| | | | - James A. Knowles
- Cell Biology, SUNY Downstate Medical Center College of Medicine, USA; and Institute for Genomic Health, SUNY Downstate Medical Center College of Medicine, USA
| | - Thorsten M. Kranz
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Germany
| | - Trine Vik Lagerberg
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hosptial, Norway
| | - Mikael Landen
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Sweden; and Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Sweden
| | - William B. Lawson
- Department of Psychiatry and Behavioral Sciences, Howard University Hospital, USA
| | - Marion Leboyer
- Universite Paris Est Creteil, France; and INSERM U 955, Neuropsychiatrie Translationnelle, France
| | | | - Mario Maj
- Department of Psychiatry, University of Campania ‘Luigi Vanvitelli’, Italy
| | - Dolores Malaspina
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, USA; and Department of Genetics & Genomics, Icahn School of Medicine at Mount Sinai, USA
| | - Mirko Manchia
- Unit of Psychiatry, Department of Medical Sciences and Public Health, University of Cagliari, Italy and Department of Pharmacology, Dalhousie University, Canada
| | - Fermin Mayoral
- Mental Health Department, University Regional Hospital, Biomedicine Institute (IBIMA), Spain
| | | | | | | | - Helena Medeiros
- Institute for Genomic Health, SUNY Downstate Medical Center College of Medicine, USA
| | - Ingrid Melle
- NORMENT Centre, Division of Mental Health and Addiction, Institute of Clinical Medicine and Diakonhjemmet Hospital, University of Oslo, Norway; and Division of Mental Health and Addiction, Oslo University Hospital, Norway
| | - Vihra Milanova
- Psychiatric Clinic, Alexander University Hospital, Bulgaria
| | | | - Palmiero Monteleone
- Department of Medicine, Surgery and Dentistry ‘Scuola Medica Salernitana’, University of Salerno, Italy
| | | | - Markus M. Nöthen
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Germany
| | - Tomas Novak
- National Institute of Mental Health, Czech Republic
| | | | - Niamh O'Brien
- Division of Psychiatry, University College London, UK
| | - Kevin S. O'Connell
- Division of Mental Health and Addiction, Oslo University Hospital, Norway; and NORMENT Centre, Inst of Clinical Medicine, University of Oslo, Norway
| | | | - Michael C. O'Donovan
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, UK
| | - Nils Opel
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Germany
| | - Abigail Ortiz
- Department of Psychiatry, University of Toronto, Toronto, Canada; and Centre for Addiction and Mental Health, Toronto, Canada
| | - Michael J. Owen
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, UK
| | - Erik Pålsson
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Sweden
| | - Carlos Pato
- Institute for Genomic Health, SUNY Downstate Medical Center College of Medicine, USA
| | - Michele T. Pato
- Institute for Genomic Health, SUNY Downstate Medical Center College of Medicine, USA
| | - Joanna Pawlak
- Department of Psychiatric Genetics, Poznan University of Medical Sciences, Poland
| | | | - Claudia Pisanu
- Department of Biomedical Science, Section of Neuroscience & Clinical Pharmacology, University of Cagliari, Italy
| | - James B. Potash
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, USA
| | - Mark H Rapaport
- Department of Psychiatry and Behavioral Sciences, Emory University, USA
| | - Daniela Reich-Erkelenz
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Germany
| | - Andreas Reif
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Germany
| | - Eva Reininghaus
- Department of Psychiatry and Psychotherapeutic Medicine, Medical University Graz, Austria
| | - Jonathan Repple
- Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Germany
| | | | - Marcella Rietschel
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Germany
| | - Kai Ringwald
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany
| | - Gloria Roberts
- School of Psychiatry, University of New South Wales, Australia
| | - Guy Rouleau
- Montreal Neurological Institute, Canada and Department of Neurology, McGill University, Canada
| | - Sabrina Schaupp
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Germany
| | | | - Simon Schmitt
- Department of Psychiatry and Psychotherapy, Philipps-University Marburg, Germany
| | - Peter R. Schofield
- Neuroscience Research Australia, Australia; and School of Medical Sciences, University of New South Wales, Australia
| | - K. Oliver Schubert
- Discipline of Psychiatry, University of Adelaide, Australia; and Northern Adelaide Mental Health Service, SA Health, Australia
| | - Eva C. Schulte
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Germany; and Department of Psychiatry and Psychotherapy, University Hospital Munich, Germany
| | - Barbara Schweizer
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, USA
| | - Fanny Senner
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Germany; and Department of Psychiatry and Psychotherapy, University Hospital Munich, Germany
| | - Giovanni Severino
- Department of Biomedical Science, Section of Neuroscience & Clinical Pharmacology, University of Cagliari, Italy
| | - Sally Sharp
- Division of Psychiatry, University College London, UK
| | | | - Olav B. Smeland
- Division of Mental Health and Addiction, Oslo University Hospital, Norway; and NORMENT Centre, Inst of Clinical Medicine, University of Oslo, Norway
| | - Janet L. Sobell
- Psychiatry and the Behavioral Sciences, University of Southern California, USA
| | - Alessio Squassina
- Department of Psychiatry, Dalhousie University, Canada; and Department of Biomedical Science, Section of Neuroscience & Clinical Pharmacology, University of Cagliari, Italy
| | | | - John Strauss
- Department of Psychiatry, University of Toronto, Canada; The Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Canada; and Institute of Medical Science, University of Toronto, Canada
| | | | - Gustavo Turecki
- Department of Psychiatry, McGill University, Canada; and Douglas Institute, McGill University, Canada
| | | | - Marin Veldic
- Department of Psychiatry and Psychology, Mayo Clinic, USA
| | - Eduard Vieta
- Hospital Clinic, University of Barcelona, IDIBAPS, CIBERSAM, Spain
| | - John B. Vincent
- Department of Psychiatry, University of Toronto, Canada; The Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Canada; and Institute of Medical Science, University of Toronto, Canada
| | - Wei Xu
- Dalla Lana School of Public Health, Biostatistics Division, University of Toronto, Canada
| | - Clement C. Zai
- Department of Psychiatry, University of Toronto, Canada; The Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Canada; Institute of Medical Science, University of Toronto, Canada; Laboratory Medicine and Pathobiology, University of Toronto, Canada; and Harvard T.H. Chan School of Public Health, USA
| | - Peter P. Zandi
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, USA
| | - Arianna Di Florio
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, UK
| | - Jordan W. Smoller
- Psychiatric and Neurodevelopmental Genetics Unit, Department of Psychiatry and Center for Genomic Medicine, Massachusetts General Hospital, USA; and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, USA
| | - Joanna M. Biernacka
- Department of Psychiatry and Psychology, Mayo Clinic, USA; and Department of Health Sciences Research, Mayo Clinic, USA
| | - Francis J. McMahon
- Human Genetics Branch, Intramural Research Program, National Institute of Mental Health, USA
| | - Martin Alda
- National Institute of Mental Health, Czech Republic; and Department of Psychiatry, Dalhousie University, Canada
| | | | - Nikolaos Koutsouleris
- Department of Psychiatry and Psychotherapy, University Hospital Munich, Germany; Max Planck Institute of Psychiatry, Germany; and Institute of Psychiatry, Psychology and Neuroscience, Kings College London, UK
| | - Peter Falkai
- Department of Psychiatry and Psychotherapy, University Hospital Munich, Germany
| | - Nelson B. Freimer
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, USA; and Human Genetics, University of California Los Angeles, USA
| | - Till F.M. Andlauer
- Department of Neurology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Germany
| | - Thomas G. Schulze
- Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital, LMU Munich, Germany; Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Germany; Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Germany; Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, USA; and Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, USA
| | - Roel A. Ophoff
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, USA; Human Genetics, University of California Los Angeles, USA; and Psychiatry, Erasmus University Medical Center, the Netherlands
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Zhan L, Li J, Jew B, Sul JH. Rare variants in the endocytic pathway are associated with Alzheimer's disease, its related phenotypes, and functional consequences. PLoS Genet 2021; 17:e1009772. [PMID: 34516545 PMCID: PMC8460036 DOI: 10.1371/journal.pgen.1009772] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2021] [Revised: 09/23/2021] [Accepted: 08/10/2021] [Indexed: 11/19/2022] Open
Abstract
Late-onset Alzheimer's disease (LOAD) is the most common type of dementia causing irreversible brain damage to the elderly and presents a major public health challenge. Clinical research and genome-wide association studies have suggested a potential contribution of the endocytic pathway to AD, with an emphasis on common loci. However, the contribution of rare variants in this pathway to AD has not been thoroughly investigated. In this study, we focused on the effect of rare variants on AD by first applying a rare-variant gene-set burden analysis using genes in the endocytic pathway on over 3,000 individuals with European ancestry from three large whole-genome sequencing (WGS) studies. We identified significant associations of rare-variant burden within the endocytic pathway with AD, which were successfully replicated in independent datasets. We further demonstrated that this endocytic rare-variant enrichment is associated with neurofibrillary tangles (NFTs) and age-related phenotypes, increasing the risk of obtaining severer brain damage, earlier age-at-onset, and earlier age-of-death. Next, by aggregating rare variants within each gene, we sought to identify single endocytic genes associated with AD and NFTs. Careful examination using NFTs revealed one significantly associated gene, ANKRD13D. To identify functional associations, we integrated bulk RNA-Seq data from over 600 brain tissues and found two endocytic expression genes (eGenes), HLA-A and SLC26A7, that displayed significant influences on their gene expressions. Differential expressions between AD patients and controls of these three identified genes were further examined by incorporating scRNA-Seq data from 48 post-mortem brain samples and demonstrated distinct expression patterns across cell types. Taken together, our results demonstrated strong rare-variant effect in the endocytic pathway on AD risk and progression and functional effect of gene expression alteration in both bulk and single-cell resolution, which may bring more insight and serve as valuable resources for future AD genetic studies, clinical research, and therapeutic targeting.
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Affiliation(s)
- Lingyu Zhan
- Molecular Biology Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Jiajin Li
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Brandon Jew
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Jae Hoon Sul
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, California, United States of America
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31
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Beebe-Wang N, Okeson A, Althoff T, Lee SI. Efficient and Explainable Risk Assessments for Imminent Dementia in an Aging Cohort Study. IEEE J Biomed Health Inform 2021; 25:2409-2420. [PMID: 33596178 DOI: 10.1109/jbhi.2021.3059563] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
As the aging US population grows, scalable approaches are needed to identify individuals at risk for dementia. Common prediction tools have limited predictive value, involve expensive neuroimaging, or require extensive and repeated cognitive testing. None of these approaches scale to the sizable aging population who do not receive routine clinical assessments. Our study seeks a tractable and widely administrable set of metrics that can accurately predict imminent (i.e., within three years) dementia onset. To this end, we develop and apply a machine learning (ML) model to an aging cohort study with an extensive set of longitudinal clinical variables to highlight at-risk individuals with better accuracy than standard rudimentary approaches. Next, we reduce the burden needed to achieve accurate risk assessments for those deemed at risk by (1) predicting when consecutive clinical visits may be unnecessary, and (2) selecting a subset of highly predictive cognitive tests. Finally, we demonstrate that our method successfully provides individualized prediction explanations that retain non-linear feature effects present in the data. Our final model, which uses only four cognitive tests (less than 20 minutes to administer) collected in a single visit, affords predictive performance comparable to a standard 100-minute neuropsychological battery and personalized risk explanations. Our approach shows the potential for an efficient tool for screening and explaining dementia risk in the general aging population.
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32
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Cervantes-Henriquez ML, Acosta-López JE, Ahmad M, Sánchez-Rojas M, Jiménez-Figueroa G, Pineda-Alhucema W, Martinez-Banfi ML, Noguera-Machacón LM, Mejía-Segura E, De La Hoz M, Arcos-Holzinger M, Pineda DA, Puentes-Rozo PJ, Arcos-Burgos M, Vélez JI. ADGRL3, FGF1 and DRD4: Linkage and Association with Working Memory and Perceptual Organization Candidate Endophenotypes in ADHD. Brain Sci 2021; 11:854. [PMID: 34206913 PMCID: PMC8301925 DOI: 10.3390/brainsci11070854] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 06/14/2021] [Accepted: 06/21/2021] [Indexed: 12/12/2022] Open
Abstract
Attention deficit hyperactivity disorder (ADHD) is a highly heritable neurobehavioral disorder that affects children worldwide, with detrimental long-term consequences in affected individuals. ADHD-affected patients display visual-motor and visuospatial abilities and skills that depart from those exhibited by non-affected individuals and struggle with perceptual organization, which might partially explain impulsive responses. Endophenotypes (quantifiable or dimensional constructs that are closely related to the root cause of the disease) might provide a more powerful and objective framework for dissecting the underlying neurobiology of ADHD than that of categories offered by the syndromic classification. In here, we explore the potential presence of the linkage and association of single-nucleotide polymorphisms (SNPs), harbored in genes implicated in the etiology of ADHD (ADGRL3, DRD4, and FGF1), with cognitive endophenotypes related to working memory and perceptual organization in 113 nuclear families. These families were ascertained from a geographical area of the Caribbean coast, in the north of Colombia, where the community is characterized by its ethnic diversity and differential gene pool. We found a significant association and linkage of markers ADGRL3-rs1565902, DRD4-rs916457 and FGF1-rs2282794 to neuropsychological tasks outlining working memory and perceptual organization such as performance in the digits forward and backward, arithmetic, similarities, the completion of figures and the assembly of objects. Our results provide strong support to understand ADHD as a combination of working memory and perceptual organization deficits and highlight the importance of the genetic background shaping the neurobiology, clinical complexity, and physiopathology of ADHD. Further, this study supplements new information regarding an ethnically diverse community with a vast African American contribution, where ADHD studies are scarce.
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Affiliation(s)
- Martha L. Cervantes-Henriquez
- Facultad de Ciencias Jurídicas y Sociales, Universidad Simón Bolívar, Barranquilla 080005, Colombia; (J.E.A.-L.); (M.A.); (M.S.-R.); (G.J.-F.); (W.P.-A.); (M.L.M.-B.); (L.M.N.-M.); (E.M.-S.); (M.D.L.H.)
- Universidad del Norte, Barranquilla 081007, Colombia
| | - Johan E. Acosta-López
- Facultad de Ciencias Jurídicas y Sociales, Universidad Simón Bolívar, Barranquilla 080005, Colombia; (J.E.A.-L.); (M.A.); (M.S.-R.); (G.J.-F.); (W.P.-A.); (M.L.M.-B.); (L.M.N.-M.); (E.M.-S.); (M.D.L.H.)
| | - Mostapha Ahmad
- Facultad de Ciencias Jurídicas y Sociales, Universidad Simón Bolívar, Barranquilla 080005, Colombia; (J.E.A.-L.); (M.A.); (M.S.-R.); (G.J.-F.); (W.P.-A.); (M.L.M.-B.); (L.M.N.-M.); (E.M.-S.); (M.D.L.H.)
| | - Manuel Sánchez-Rojas
- Facultad de Ciencias Jurídicas y Sociales, Universidad Simón Bolívar, Barranquilla 080005, Colombia; (J.E.A.-L.); (M.A.); (M.S.-R.); (G.J.-F.); (W.P.-A.); (M.L.M.-B.); (L.M.N.-M.); (E.M.-S.); (M.D.L.H.)
| | - Giomar Jiménez-Figueroa
- Facultad de Ciencias Jurídicas y Sociales, Universidad Simón Bolívar, Barranquilla 080005, Colombia; (J.E.A.-L.); (M.A.); (M.S.-R.); (G.J.-F.); (W.P.-A.); (M.L.M.-B.); (L.M.N.-M.); (E.M.-S.); (M.D.L.H.)
| | - Wilmar Pineda-Alhucema
- Facultad de Ciencias Jurídicas y Sociales, Universidad Simón Bolívar, Barranquilla 080005, Colombia; (J.E.A.-L.); (M.A.); (M.S.-R.); (G.J.-F.); (W.P.-A.); (M.L.M.-B.); (L.M.N.-M.); (E.M.-S.); (M.D.L.H.)
| | - Martha L. Martinez-Banfi
- Facultad de Ciencias Jurídicas y Sociales, Universidad Simón Bolívar, Barranquilla 080005, Colombia; (J.E.A.-L.); (M.A.); (M.S.-R.); (G.J.-F.); (W.P.-A.); (M.L.M.-B.); (L.M.N.-M.); (E.M.-S.); (M.D.L.H.)
| | - Luz M. Noguera-Machacón
- Facultad de Ciencias Jurídicas y Sociales, Universidad Simón Bolívar, Barranquilla 080005, Colombia; (J.E.A.-L.); (M.A.); (M.S.-R.); (G.J.-F.); (W.P.-A.); (M.L.M.-B.); (L.M.N.-M.); (E.M.-S.); (M.D.L.H.)
| | - Elsy Mejía-Segura
- Facultad de Ciencias Jurídicas y Sociales, Universidad Simón Bolívar, Barranquilla 080005, Colombia; (J.E.A.-L.); (M.A.); (M.S.-R.); (G.J.-F.); (W.P.-A.); (M.L.M.-B.); (L.M.N.-M.); (E.M.-S.); (M.D.L.H.)
| | - Moisés De La Hoz
- Facultad de Ciencias Jurídicas y Sociales, Universidad Simón Bolívar, Barranquilla 080005, Colombia; (J.E.A.-L.); (M.A.); (M.S.-R.); (G.J.-F.); (W.P.-A.); (M.L.M.-B.); (L.M.N.-M.); (E.M.-S.); (M.D.L.H.)
| | - Mauricio Arcos-Holzinger
- Grupo de Investigación en Psiquiatría (GIPSI), Departamento de Psiquiatría, Instituto de Investigaciones Mxdicas, Facultad de Medicina, Universidad de Antioquia, Medellin 050010, Colombia; (M.A.-H.); (M.A.-B.)
| | - David A. Pineda
- Grupo de Neuropsicología y Conducta, Universidad de San Buenaventura, Medellín 050010, Colombia;
| | - Pedro J. Puentes-Rozo
- Grupo de Neurociencias del Caribe, Universidad del Atlántico, Barranquilla 081001, Colombia;
| | - Mauricio Arcos-Burgos
- Grupo de Investigación en Psiquiatría (GIPSI), Departamento de Psiquiatría, Instituto de Investigaciones Mxdicas, Facultad de Medicina, Universidad de Antioquia, Medellin 050010, Colombia; (M.A.-H.); (M.A.-B.)
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Jia J, Xu J, Liu J, Wang Y, Wang Y, Cao Y, Guo Q, Qu Q, Wei C, Wei W, Zhang J, Yu E. Comprehensive Management of Daily Living Activities, behavioral and Psychological Symptoms, and Cognitive Function in Patients with Alzheimer's Disease: A Chinese Consensus on the Comprehensive Management of Alzheimer's Disease. Neurosci Bull 2021; 37:1025-1038. [PMID: 34050523 PMCID: PMC8275730 DOI: 10.1007/s12264-021-00701-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Accepted: 01/06/2021] [Indexed: 01/05/2023] Open
Abstract
Alzheimer's disease (AD) is the most common cognitive disorder in the elderly. Its main clinical manifestations are cognitive decline (C), behavioral and psychological symptoms (B), and a decline in the activities of daily living (A), also known as ABC symptoms. Early identification and evaluation of ABC symptoms are helpful for establishing the accurate diagnosis, comprehensive treatment, and prognosis of AD. To guide Chinese clinical practice for optimization of the comprehensive management of AD, in 2018, The Academy of Cognitive Disorder of China gathered 22 neurologists and gerontologists in China to build a consensus on the comprehensive management of AD. Based on a review of the evidence, the consensus summarizes the pathogenesis, pathological changes, clinical manifestations, evaluation, diagnosis, drug and non-drug treatment, and patient care for AD. Focus group discussion was used to establish a flowchart of comprehensive ABC management for AD patients. The new consensus provides a feasible AD management process for clinicians.
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Affiliation(s)
- Jianjun Jia
- Department of Neurology, The Second Medical Center, People's Liberation Army General Hospital, Beijing, 100853, China.
| | - Jun Xu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100050, China
| | - Jun Liu
- Department of Neurology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, 510120, China
| | - Yongjun Wang
- Cognitive Impairment Department, Shenzhen Kangning Hospital, Shenzhen, 518118, China
| | - Yanjiang Wang
- Department of Neurology, Daping Hospital, Army Medical University, Chongqing, 400042, China
| | - Yunpeng Cao
- Department of Neurology, The First Hospital of China Medical University, Shenyang, 210112, China
| | - Qihao Guo
- Department of Gerontology, Shanghai Jiaotong University Affiliated Sixth People's Hospital, Shanghai, 200233, China
| | - Qiuming Qu
- Department of Neurology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, China
| | - Cuibai Wei
- Department of Neurology, Xuanwu Hospital Capital Medical University, Beijing, 100053, China
| | - Wenshi Wei
- Department of Neurology, Huadong Hospital Affiliated to Fudan University, Shanghai, 200040, China
| | - Junjian Zhang
- Department of Neurology, Zhongnan Hospital of Wuhan University, Wuhan, 430071, China
| | - Enyan Yu
- Department of Psychology, Chinese Academy of Sciences Cancer Hospital of the University of the Chinese Academy of Sciences, Hangzhou, 310022, China
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Vélez JI, Samper LA, Arcos-Holzinger M, Espinosa LG, Isaza-Ruget MA, Lopera F, Arcos-Burgos M. A Comprehensive Machine Learning Framework for the Exact Prediction of the Age of Onset in Familial and Sporadic Alzheimer's Disease. Diagnostics (Basel) 2021; 11:887. [PMID: 34067584 PMCID: PMC8156402 DOI: 10.3390/diagnostics11050887] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2021] [Revised: 04/28/2021] [Accepted: 04/29/2021] [Indexed: 11/16/2022] Open
Abstract
Machine learning (ML) algorithms are widely used to develop predictive frameworks. Accurate prediction of Alzheimer's disease (AD) age of onset (ADAOO) is crucial to investigate potential treatments, follow-up, and therapeutic interventions. Although genetic and non-genetic factors affecting ADAOO were elucidated by other research groups and ours, the comprehensive and sequential application of ML to provide an exact estimation of the actual ADAOO, instead of a high-confidence-interval ADAOO that may fall, remains to be explored. Here, we assessed the performance of ML algorithms for predicting ADAOO using two AD cohorts with early-onset familial AD and with late-onset sporadic AD, combining genetic and demographic variables. Performance of ML algorithms was assessed using the root mean squared error (RMSE), the R-squared (R2), and the mean absolute error (MAE) with a 10-fold cross-validation procedure. For predicting ADAOO in familial AD, boosting-based ML algorithms performed the best. In the sporadic cohort, boosting-based ML algorithms performed best in the training data set, while regularization methods best performed for unseen data. ML algorithms represent a feasible alternative to accurately predict ADAOO with little human intervention. Future studies may include predicting the speed of cognitive decline in our cohorts using ML.
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Affiliation(s)
- Jorge I. Vélez
- Department of Industrial Engineering, Universidad del Norte, Barranquilla 081007, Colombia
| | - Luiggi A. Samper
- Department of Public Health, Universidad del Norte, Barranquilla 081007, Colombia;
| | - Mauricio Arcos-Holzinger
- Grupo de Investigación en Psiquiatría (GIPSI), Departamento de Psiquiatría, Instituto de Investigaciones Médicas, Facultad de Medicina, Universidad de Antioquia, Medellín 050010, Colombia;
| | - Lady G. Espinosa
- INPAC Research Group, Fundación Universitaria Sanitas, Bogotá 111321, Colombia; (L.G.E.); (M.A.I.-R.)
| | - Mario A. Isaza-Ruget
- INPAC Research Group, Fundación Universitaria Sanitas, Bogotá 111321, Colombia; (L.G.E.); (M.A.I.-R.)
| | - Francisco Lopera
- Neuroscience Research Group, University of Antioquia, Medellín 050010, Colombia;
| | - Mauricio Arcos-Burgos
- Grupo de Investigación en Psiquiatría (GIPSI), Departamento de Psiquiatría, Instituto de Investigaciones Médicas, Facultad de Medicina, Universidad de Antioquia, Medellín 050010, Colombia;
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Polis B, Karasik D, Samson AO. Alzheimer's disease as a chronic maladaptive polyamine stress response. Aging (Albany NY) 2021; 13:10770-10795. [PMID: 33811757 PMCID: PMC8064158 DOI: 10.18632/aging.202928] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Accepted: 03/27/2021] [Indexed: 12/21/2022]
Abstract
Polyamines are nitrogen-rich polycationic ubiquitous bioactive molecules with diverse evolutionary-conserved functions. Their activity interferes with numerous genes' expression resulting in cell proliferation and signaling modulation. The intracellular levels of polyamines are precisely controlled by an evolutionary-conserved machinery. Their transient synthesis is induced by heat stress, radiation, and other traumatic stimuli in a process termed the polyamine stress response (PSR). Notably, polyamine levels decline gradually with age; and external supplementation improves lifespan in model organisms. This corresponds to cytoprotective and reactive oxygen species scavenging properties of polyamines. Paradoxically, age-associated neurodegenerative disorders are characterized by upsurge in polyamines levels, indicating polyamine pleiotropic, adaptive, and pathogenic roles. Specifically, arginase overactivation and arginine brain deprivation have been shown to play an important role in Alzheimer's disease (AD) pathogenesis. Here, we assert that a universal short-term PSR associated with acute stimuli is beneficial for survival. However, it becomes detrimental and maladaptive following chronic noxious stimuli, especially in an aging organism. Furthermore, we regard cellular senescence as an adaptive response to stress and suggest that PSR plays a central role in age-related neurodegenerative diseases' pathogenesis. Our perspective on AD proposes an inclusive reassessment of the causal relationships between the classical hallmarks and clinical manifestation. Consequently, we offer a novel treatment strategy predicated upon this view and suggest fine-tuning of arginase activity with natural inhibitors to preclude or halt the development of AD-related dementia.
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Affiliation(s)
- Baruh Polis
- Drug Discovery Laboratory, The Azrieli Faculty of Medicine, Bar-Ilan University, Safed 1311502, Israel
| | - David Karasik
- Hebrew SeniorLife, Hinda and Arthur Marcus Institute for Aging Research, Boston, MA 02131, USA
- Musculoskeletal Genetics Laboratory, The Azrieli Faculty of Medicine, Bar-Ilan University, Safed 1311502, Israel
| | - Abraham O. Samson
- Drug Discovery Laboratory, The Azrieli Faculty of Medicine, Bar-Ilan University, Safed 1311502, Israel
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Le Guen Y, Belloy ME, Napolioni V, Eger SJ, Kennedy G, Tao R, He Z, Greicius MD. A novel age-informed approach for genetic association analysis in Alzheimer's disease. Alzheimers Res Ther 2021; 13:72. [PMID: 33794991 PMCID: PMC8017764 DOI: 10.1186/s13195-021-00808-5] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Accepted: 03/11/2021] [Indexed: 01/17/2023]
Abstract
BACKGROUND Many Alzheimer's disease (AD) genetic association studies disregard age or incorrectly account for it, hampering variant discovery. METHODS Using simulated data, we compared the statistical power of several models: logistic regression on AD diagnosis adjusted and not adjusted for age; linear regression on a score integrating case-control status and age; and multivariate Cox regression on age-at-onset. We applied these models to real exome-wide data of 11,127 sequenced individuals (54% cases) and replicated suggestive associations in 21,631 genotype-imputed individuals (51% cases). RESULTS Modeling variable AD risk across age results in 5-10% statistical power gain compared to logistic regression without age adjustment, while incorrect age adjustment leads to critical power loss. Applying our novel AD-age score and/or Cox regression, we discovered and replicated novel variants associated with AD on KIF21B, USH2A, RAB10, RIN3, and TAOK2 genes. CONCLUSION Our AD-age score provides a simple means for statistical power gain and is recommended for future AD studies.
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Affiliation(s)
- Yann Le Guen
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, 94304, USA.
| | - Michael E Belloy
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, 94304, USA
| | - Valerio Napolioni
- School of Biosciences and Veterinary Medicine, University of Camerino, 62032, Camerino, Italy
| | - Sarah J Eger
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, 94304, USA
| | - Gabriel Kennedy
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, 94304, USA
| | - Ran Tao
- Department of Biostatistics and Vanderbilt Genetic Institute, Vanderbilt University, Nashville, TN, 37203, USA
| | - Zihuai He
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, 94304, USA
- Quantitative Sciences Unit, Department of Medicine, Stanford University, Stanford, CA, 94304, USA
| | - Michael D Greicius
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, 94304, USA
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Vogrinc D, Goričar K, Dolžan V. Genetic Variability in Molecular Pathways Implicated in Alzheimer's Disease: A Comprehensive Review. Front Aging Neurosci 2021; 13:646901. [PMID: 33815092 PMCID: PMC8012500 DOI: 10.3389/fnagi.2021.646901] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Accepted: 02/16/2021] [Indexed: 12/14/2022] Open
Abstract
Alzheimer's disease (AD) is a complex neurodegenerative disease, affecting a significant part of the population. The majority of AD cases occur in the elderly with a typical age of onset of the disease above 65 years. AD presents a major burden for the healthcare system and since population is rapidly aging, the burden of the disease will increase in the future. However, no effective drug treatment for a full-blown disease has been developed to date. The genetic background of AD is extensively studied; numerous genome-wide association studies (GWAS) identified significant genes associated with increased risk of AD development. This review summarizes more than 100 risk loci. Many of them may serve as biomarkers of AD progression, even in the preclinical stage of the disease. Furthermore, we used GWAS data to identify key pathways of AD pathogenesis: cellular processes, metabolic processes, biological regulation, localization, transport, regulation of cellular processes, and neurological system processes. Gene clustering into molecular pathways can provide background for identification of novel molecular targets and may support the development of tailored and personalized treatment of AD.
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Affiliation(s)
| | | | - Vita Dolžan
- Pharmacogenetics Laboratory, Institute of Biochemistry and Molecular Genetics, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
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Lee JW, Lee S. A comparative study on the unified model based multifactor dimensionality reduction methods for identifying gene-gene interactions associated with the survival phenotype. BioData Min 2021; 14:17. [PMID: 33648540 PMCID: PMC7923479 DOI: 10.1186/s13040-021-00248-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Accepted: 02/11/2021] [Indexed: 12/04/2022] Open
Abstract
Background For gene-gene interaction analysis, the multifactor dimensionality reduction (MDR) method has been widely employed to reduce multi-levels of gene-gene interactions into high- or low-risk groups using a binary attribute. For the survival phenotype, the Cox-MDR method has been proposed using a martingale residual of a Cox model since Surv-MDR was first proposed using a log-rank test statistic. Recently, the KM-MDR method was proposed using the Kaplan-Meier median survival time as a classifier. All three methods used the cross-validation procedure to identify single nucleotide polymorphism (SNP) using SNP interactions among all possible SNP pairs. Furthermore, these methods require the permutation test to verify the significance of the selected SNP pairs. However, the unified model-based multifactor dimensionality reduction method (UM-MDR) overcomes this shortcoming of MDR by unifying the significance testing with the MDR algorithm within the framework of the regression model. Neither cross-validation nor permutation testing is required to identify SNP by SNP interactions in the UM-MDR method. The UM-MDR method comprises two steps: in the first step, multi-level genotypes are classified into high- or low-risk groups, and an indicator variable for the high-risk group is defined. In the second step, the significance of the indicator variable of the high-risk group is tested in the regression model included with other adjusting covariates. The Cox-UMMDR method was recently proposed by combining Cox-MDR with UM-MDR to identify gene-gene interactions associated with the survival phenotype. In this study, we propose two simple methods either by combining KM-MDR with UM-MDR, called KM-UMMDR or by modifying Cox-UMMDR by adjusting for the covariate effect in step 1, rather than in step 2, a process called Cox2-UMMDR. The KM-UMMDR method allows the covariate effect to be adjusted for in the regression model of step 2, although KM-MDR cannot adjust for the covariate effect in the classification procedure of step 1. In contrast, Cox2-UMMDR differs from Cox-UMMDR in the sense that the martingale residuals are obtained from a Cox model by adjusting for the covariate effect in step 1 of Cox2-UMMDR whereas Cox-UMMDR adjusts for the covariate effect in the regression model in step 2. We performed simulation studies to compare the power of several methods such as KM-UMMDR, Cox-UMMDR, Cox2-UMMDR, Cox-MDR, and KM-MDR by considering the effect of covariates and the marginal effect of SNPs. We also analyzed a real example of Korean leukemia patient data for illustration and a short discussion is provided. Results In the simulation study, two different scenarios are considered: the first scenario compares the power of the cases with and without the covariate effect. The second scenario is to compare the power of cases with the main effect of SNPs versus without the main effect of SNPs. From the simulation results, Cox-UMMDR performs the best across all scenarios among KM-UMMDR, Cox2-UMMDR, Cox-MDR and KM-MDR. As expected, both Cox-UMMDR and Cox-MDR perform better than KM-UMMDR and KM-MDR when a covariate effect exists because the former adjusts for the covariate effect but the latter cannot. However, Cox2-UMMDR behaves similarly to KM-UMMDR and KM-MDR even though there is a covariate effect. This implies that the covariate effect would be more efficiently adjusted for in the regression model of the second step rather than under the classification procedure of the first step. When there is a main effect of any SNP, Cox-UMMDR, Cox2-UMMDR and KM-UMMDR perform better than Cox-MDR and KM-MDR if the main effects of SNPs are properly adjusted for in the regression model. From the simulation results of two different scenarios, Cox-UMMDR seems to be the most robust when there is either any covariate effect adjusting for or any SNP that has a main effect on the survival phenotype. In addition, the power of all methods decreased as the censoring fraction increased from 0.1 to 0.3, as heritability increased. The power of all methods seems to be greater under MAF = 0.2 than under MAF = 0.4. For illustration, both KM-UMMDR and Cox2-UMMDR were applied to identify SNP by SNP interactions with the survival phenotype to a real dataset of Korean leukemia patients. Conclusion Both KM-UMMDR and Cox2-UMMDR were easily implemented by combining KM-MDR and Cox-MDR with UM-MDR, respectively, to detect significant gene-gene interactions associated with survival time without cross-validation and permutation testing. The simulation results demonstrate the utility of KM-UMMDR, Cox2-UMMDR and Cox-UMMDR, which outperforms Cox-MDR and KM-MDR when some SNPs with only marginal effects might mask the detection of causal epistasis. In addition, Cox-UMMDR, Cox2-UMMDR and Cox-MDR performed better than KM-UMMDR and KM-MDR when there were potentially confounding covariate effects.
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Affiliation(s)
- Jung Wun Lee
- Department of Statistics, University of Connecticut, Storrs, CT, USA
| | - Seungyeoun Lee
- Department of Mathematics and Statistics, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul, 05006, South Korea.
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He L, Loika Y, Park Y, Bennett DA, Kellis M, Kulminski AM. Exome-wide age-of-onset analysis reveals exonic variants in ERN1 and SPPL2C associated with Alzheimer's disease. Transl Psychiatry 2021; 11:146. [PMID: 33637690 PMCID: PMC7910483 DOI: 10.1038/s41398-021-01263-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Revised: 01/07/2021] [Accepted: 02/03/2021] [Indexed: 01/31/2023] Open
Abstract
Despite recent discoveries in genome-wide association studies (GWAS) of genomic variants associated with Alzheimer's disease (AD), its underlying biological mechanisms are still elusive. The discovery of novel AD-associated genetic variants, particularly in coding regions and from APOE ε4 non-carriers, is critical for understanding the pathology of AD. In this study, we carried out an exome-wide association analysis of age-of-onset of AD with ~20,000 subjects and placed more emphasis on APOE ε4 non-carriers. Using Cox mixed-effects models, we find that age-of-onset shows a stronger genetic signal than AD case-control status, capturing many known variants with stronger significance, and also revealing new variants. We identified two novel variants, rs56201815, a rare synonymous variant in ERN1, and rs12373123, a common missense variant in SPPL2C in the MAPT region in APOE ε4 non-carriers. Besides, a rare missense variant rs144292455 in TACR3 showed the consistent direction of effect sizes across all studies with a suggestive significant level. In an attempt to unravel their regulatory and biological functions, we found that the minor allele of rs56201815 was associated with lower average FDG uptake across five brain regions in ADNI. Our eQTL analyses based on 6198 gene expression samples from ROSMAP and GTEx revealed that the minor allele of rs56201815 was potentially associated with elevated expression of ERN1, a key gene triggering unfolded protein response (UPR), in multiple brain regions, including the posterior cingulate cortex and nucleus accumbens. Our cell-type-specific eQTL analysis using ~80,000 single nuclei in the prefrontal cortex revealed that the protective minor allele of rs12373123 significantly increased the expression of GRN in microglia, and was associated with MAPT expression in astrocytes. These findings provide novel evidence supporting the hypothesis of the potential involvement of the UPR to ER stress in the pathological pathway of AD, and also give more insights into underlying regulatory mechanisms behind the pleiotropic effects of rs12373123 in multiple degenerative diseases including AD and Parkinson's disease.
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Affiliation(s)
- Liang He
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, USA.
| | - Yury Loika
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, USA
| | - Yongjin Park
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Manolis Kellis
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA, USA.
| | - Alexander M Kulminski
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, USA.
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40
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Affiliation(s)
- Parichita Choudhury
- Division of Behavioral Neurology, Department of Neurology, Mayo Clinic, Rochester, Minnesota
| | - Vijay K Ramanan
- Division of Behavioral Neurology, Department of Neurology, Mayo Clinic, Rochester, Minnesota
| | - Bradley F Boeve
- Division of Behavioral Neurology, Department of Neurology, Mayo Clinic, Rochester, Minnesota
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Farias FHG, Benitez BA, Cruchaga C. Quantitative endophenotypes as an alternative approach to understanding genetic risk in neurodegenerative diseases. Neurobiol Dis 2021; 151:105247. [PMID: 33429041 DOI: 10.1016/j.nbd.2020.105247] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 12/24/2020] [Accepted: 12/30/2020] [Indexed: 01/02/2023] Open
Abstract
Endophenotypes, as measurable intermediate features of human diseases, reflect underlying molecular mechanisms. The use of quantitative endophenotypes in genetic studies has improved our understanding of pathophysiological changes associated with diseases. The main advantage of the quantitative endophenotypes approach to study human diseases over a classic case-control study design is the inferred biological context that can enable the development of effective disease-modifying treatments. Here, we summarize recent progress on biomarkers for neurodegenerative diseases, including cerebrospinal fluid and blood-based, neuroimaging, neuropathological, and clinical studies. This review focuses on how endophenotypic studies have successfully linked genetic modifiers to disease risk, disease onset, or progression rate and provided biological context to genes identified in genome-wide association studies. Finally, we review critical methodological considerations for implementing this approach and future directions.
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Affiliation(s)
- Fabiana H G Farias
- Department of Psychiatry, Washington University, St. Louis, MO 63110, United States of America; NeuroGenomics and Informatics, Washington University, St. Louis, MO 63110, United States of America
| | - Bruno A Benitez
- Department of Psychiatry, Washington University, St. Louis, MO 63110, United States of America; NeuroGenomics and Informatics, Washington University, St. Louis, MO 63110, United States of America
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University, St. Louis, MO 63110, United States of America; NeuroGenomics and Informatics, Washington University, St. Louis, MO 63110, United States of America; Hope Center for Neurologic Diseases, Washington University, St. Louis, MO 63110, United States of America; The Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO, 63110, United States of America; Department of Genetics, Washington University School of Medicine, St Louis, MO, 63110, United States of America.
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42
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Gui W, Qiu C, Shao Q, Li J. Associations of Vascular Risk Factors, APOE and TOMM40 Polymorphisms With Cognitive Function in Dementia-Free Chinese Older Adults: A Community-Based Study. Front Psychiatry 2021; 12:617773. [PMID: 33790814 PMCID: PMC8005534 DOI: 10.3389/fpsyt.2021.617773] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Accepted: 02/01/2021] [Indexed: 12/14/2022] Open
Abstract
Objective: The associations of vascular risk factors (VRFs), apolipoprotein E (APOE), and translocase of outer mitochondrial membrane 40 (TOMM40) with cognitive function have been investigated mostly in western societies. In the present study, we sought to examine the associations of VRFs [i.e., current smoking, current drinking, physical inactivity, obesity, total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), diabetes, and hypertension] and variants located in APOE (ε2/3/4) and TOMM40 (rs2075650) with global cognitive function in Chinese older adults, with a focus on their potential interactions. Methods: This is a cross-sectional study that included 422 permanent residents (mean age 69.2 years, 54.3% female) living in Beijing, who were free of dementia. Data were collected through interviews, clinical examinations, and laboratory tests. The two genetic polymorphisms were genotyped, and participants were dichotomized as carriers vs. non-carriers of APOE ε4 or TOMM40 G. Global cognitive function was assessed with the Mini-Mental State Examination (MMSE). Data were analyzed with multivariable linear regression models. Results: Physical inactivity and diabetes were independently associated with a lower MMSE score (all p < 0.05). When four putative VRFs (i.e., current smoking, physical inactivity, high LDL-C, and diabetes) were aggregated, an increasing number of having these factors was associated with a decreasing MMSE score in a dose-response manner (p = 0.001). TOMM40 polymorphisms, independent of the APOE ε4 allele, interacted with aggregated VRFs to influence cognitive performance, such that having one or more of these VRFs was particularly detrimental to the cognition of TOMM40 carriers. Further analyses revealed interactions of the TOMM40 polymorphism with (i) physical inactivity and (ii) diabetes, such that having either physical inactivity or diabetes in combination with carrying a TOMM40 G allele, compared to having neither, was significantly associated with a markedly lower MMSE score (all p < 0.05). Conclusion: This study provides some evidence supporting the association of vascular risk factors with poor cognitive performance among dementia-free Chinese older adults and further revealed their interactions with the TOMM40 polymorphism. The results underscore the vulnerability of global cognitive function to VRFs, which could be reinforced by carrying the TOMM40 rs2075650 G allele. These findings have potential implications for developing tailored intervention programs to maintain cognitive function.
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Affiliation(s)
- Wenjun Gui
- CAS Key Laboratory of Mental Health, Center on Aging Psychology, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Chengxuan Qiu
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China.,Aging Research Center and Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Qi Shao
- CAS Key Laboratory of Mental Health, Center on Aging Psychology, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Juan Li
- CAS Key Laboratory of Mental Health, Center on Aging Psychology, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
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Yan Q, Nho K, Del-Aguila JL, Wang X, Risacher SL, Fan KH, Snitz BE, Aizenstein HJ, Mathis CA, Lopez OL, Demirci FY, Feingold E, Klunk WE, Saykin AJ, Cruchaga C, Kamboh MI. Genome-wide association study of brain amyloid deposition as measured by Pittsburgh Compound-B (PiB)-PET imaging. Mol Psychiatry 2021; 26:309-321. [PMID: 30361487 PMCID: PMC6219464 DOI: 10.1038/s41380-018-0246-7] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2017] [Accepted: 07/31/2018] [Indexed: 12/25/2022]
Abstract
Deposition of amyloid plaques in the brain is one of the two main pathological hallmarks of Alzheimer's disease (AD). Amyloid positron emission tomography (PET) is a neuroimaging tool that selectively detects in vivo amyloid deposition in the brain and is a reliable endophenotype for AD that complements cerebrospinal fluid biomarkers with regional information. We measured in vivo amyloid deposition in the brains of ~1000 subjects from three collaborative AD centers and ADNI using 11C-labeled Pittsburgh Compound-B (PiB)-PET imaging followed by meta-analysis of genome-wide association studies, first to our knowledge for PiB-PET, to identify novel genetic loci for this endophenotype. The APOE region showed the most significant association where several SNPs surpassed the genome-wide significant threshold, with APOE*4 being most significant (P-meta = 9.09E-30; β = 0.18). Interestingly, after conditioning on APOE*4, 14 SNPs remained significant at P < 0.05 in the APOE region that were not in linkage disequilibrium with APOE*4. Outside the APOE region, the meta-analysis revealed 15 non-APOE loci with P < 1E-05 on nine chromosomes, with two most significant SNPs on chromosomes 8 (P-meta = 4.87E-07) and 3 (P-meta = 9.69E-07). Functional analyses of these SNPs indicate their potential relevance with AD pathogenesis. Top 15 non-APOE SNPs along with APOE*4 explained 25-35% of the amyloid variance in different datasets, of which 14-17% was explained by APOE*4 alone. In conclusion, we have identified novel signals in APOE and non-APOE regions that affect amyloid deposition in the brain. Our data also highlights the presence of yet to be discovered variants that may be responsible for the unexplained genetic variance of amyloid deposition.
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Affiliation(s)
- Qi Yan
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Pediatrics, Children's Hospital of Pittsburgh of UPMC, University of Pittsburgh, Pittsburgh, PA, USA
| | - Kwangsik Nho
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Jorge L Del-Aguila
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Xingbin Wang
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Shannon L Risacher
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kang-Hsien Fan
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Beth E Snitz
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
- Alzheimer Disease Research Center, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Chester A Mathis
- Alzheimer Disease Research Center, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Oscar L Lopez
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
- Alzheimer Disease Research Center, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - F Yesim Demirci
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Eleanor Feingold
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - William E Klunk
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
- Alzheimer Disease Research Center, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Andrew J Saykin
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - M Ilyas Kamboh
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA.
- Alzheimer Disease Research Center, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.
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44
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Lambracht-Washington D, Fu M, Hynan LS, Rosenberg RN. Changes in the brain transcriptome after DNA Aβ42 trimer immunization in a 3xTg-AD mouse model. Neurobiol Dis 2021; 148:105221. [PMID: 33316368 PMCID: PMC7845550 DOI: 10.1016/j.nbd.2020.105221] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Revised: 11/23/2020] [Accepted: 12/07/2020] [Indexed: 12/23/2022] Open
Abstract
Alzheimer's disease (AD) has been associated with accumulation of amyloid beta (Aβ) peptides in brain, and immunotherapy targeting Aβ provides potential for AD prevention. We have used a DNA Aβ42 trimer construct for immunization of 3xTg-AD mice and found previously significant reduction of amyloid and tau pathology due to the immunotherapy. We show here that DNA Aβ42 immunized 3xTg-AD mice showed better performance in nest building activities and had a higher 24 months survival rate compared to the non-treated AD controls. The analysis of differently expressed genes in brains from 24 months old mice showed significant increases transcript levels between non-immunized AD mice and wild-type controls for genes involved in microglia and astrocyte function, cytokine and inflammatory signaling, apoptosis, the innate and adaptive immune response and are consistent with an inflammatory phenotype in AD. Most of these upregulated genes were downregulated in the DNA Aβ42 immunized 3xTg-AD mice due to the vaccine. Transcript numbers for the immediate early genes, Arc, Bdnf, Homer1, Egr1 and cfos, involved in neuronal and neurotransmission pathways which were much lower in the non-immunized 3xTg-AD mice, were restored to wild-type mouse brain levels in DNA Aβ42 immunized 3xTg-AD mice indicating positive effects of DNA Aβ42 immunotherapy on synapse stability and plasticity. The immune response after immunization is complex, but the multitude of changes after DNA Aβ42 immunization shows that this response moves beyond the amyloid hypothesis and into direction of disease prevention.
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Affiliation(s)
- Doris Lambracht-Washington
- Department of Neurology, UT Southwestern Medical Center Dallas, USA; Doris Lambracht Washington, UT Southwestern Medical Center Dallas, Department of Neurology , 5323 Harry Hines Blvd, Dallas, TX 75390-8813, USA.
| | - Min Fu
- Department of Neurology, UT Southwestern Medical Center Dallas, USA.
| | - Linda S Hynan
- Departments of Population and Data Sciences (Biostatistics) & Psychiatry, UT Southwestern Medical Center Dallas, USA.
| | - Roger N Rosenberg
- Department of Neurology, UT Southwestern Medical Center Dallas, USA.
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45
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Hao X, Wang A, Li C, Shao L, Li Y, Yang P. Genetic association of BIN1 and GAB2 in Alzheimer's disease: A meta-analysis and systematic review. Geriatr Gerontol Int 2020; 21:185-191. [PMID: 33331110 PMCID: PMC7898709 DOI: 10.1111/ggi.14109] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Revised: 11/06/2020] [Accepted: 11/20/2020] [Indexed: 12/21/2022]
Abstract
Aim Heredity plays an important role in the pathogenesis of Alzheimer's disease (AD) especially for single‐nucleotide polymorphism (SNPs) of susceptible genes, which is one of the significant factors in the pathogenesis of AD. The SNPs of BIN1 rs744373, BIN1 rs7561528 and GAB2 rs2373115 are associated with AD in Asian and white people. Methods We included 34 studies with a total of 38 291 patients with AD and 55 538 controls of diverse races from four main databases. We used meta‐analysis to obtain I2‐values and odds ratios of five genetic models in three SNPs. We carried out analysis of sensitivity, subgroup, publication bias and linkage disequilibrium test. Results The forest plots showed the odds ratio value of the three SNPs was >1 in white individuals, but not Asian individuals, in their genetic model. The funnel plot was symmetrical, and the D'‐value was 0.986 between rs744373 and rs7561528. Conclusions BIN1 rs744373, BIN1 rs7561528 and GAB2 rs2373115 are pathogenicity sites for AD in white people, and also rs7561528 belongs to a risk site in Asian people. The rs7561528 and rs744373 SNPs have strong linkage disequilibrium in Chinese people. In addition, apolipoprotein E ε4 status promotes them to result in the pathogenesis of AD. Geriatr Gerontol Int 2021; 21: 185–191.
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Affiliation(s)
- Xiaoyan Hao
- Department of Neurology, Ningxia Medical University, Yinchuan, China
| | - Aijun Wang
- Department of Neurology, General Hospital of Ningxia Medical University, Yinchuan, China
| | - Chong Li
- Department of Neurology, Ningxia Medical University, Yinchuan, China
| | - Lufei Shao
- Department of Neurology, General Hospital of Ningxia Medical University, Yinchuan, China
| | - Yi Li
- Department of Neurology, General Hospital of Ningxia Medical University, Yinchuan, China
| | - Ping Yang
- Department of Neurology, General Hospital of Ningxia Medical University, Yinchuan, China
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46
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Podleśny-Drabiniok A, Marcora E, Goate AM. Microglial Phagocytosis: A Disease-Associated Process Emerging from Alzheimer’s Disease Genetics. Trends Neurosci 2020; 43:965-979. [DOI: 10.1016/j.tins.2020.10.002] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Revised: 09/02/2020] [Accepted: 10/05/2020] [Indexed: 01/02/2023]
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47
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Martin ER, Gao XR, Li YJ. An exploration of genetic association tests for disease risk and age at onset. Genet Epidemiol 2020; 45:249-279. [PMID: 33075194 DOI: 10.1002/gepi.22368] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Revised: 08/26/2020] [Accepted: 09/17/2020] [Indexed: 11/07/2022]
Abstract
Risk genes influence the chance of an individual developing disease over their lifetime, although the age at onset (AAO) genes influence disease timing. These two categories are not disjoint; a gene that influences AAO might also appear to influence the risk. When an allele influences both AAO and risk, a reasonable question is whether we would have more power to detect association using a statistical test based on risk or AAO. To address this question, we compared power analytically for the Cochran-Armitage trend case-control test for risk and a linear regression case-only test for AAO. We also used simulations to compare the power of these tests with a 2-degree of freedom joint test (which combines the risk and AAO statistics) and the Cox proportional hazards survival model testing AAO (with censored data in controls). We found that when there is little heterogeneity, the case-control risk test has more power than the case-only AAO test (with equivalent sample sizes), but when the model is complex (e.g., with heterogeneity or reduced penetrance), the relationship reverses. The joint test generally outperforms the risk or AAO test alone and ultimately is our recommendation as a powerful alternative in many scenarios.
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Affiliation(s)
- Eden R Martin
- John P. Hussman Institute for Human Genetics, Miller School of Medicine, University of Miami, Miami, Florida, USA.,John T. MacDonald Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, Florida, USA
| | - Xiaoyi R Gao
- Departments of Ophthalmology and Visual Science, Department of Biomedical Informatics, Division of Human Genetics, The Ohio State University, Columbus, Ohio, USA
| | - Yi-Ju Li
- Duke Molecular Physiology Institute, School of Medicine, Duke University, Durham, North Carolina, USA.,Department of Biostatistics and Bioinformatics, School of Medicine, Duke University, Durham, North Carolina, USA
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48
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Li J, Chen F, Zhang Q, Meng X, Yao X, Risacher SL, Yan J, Saykin AJ, Liang H, Shen L. Genome-wide Network-assisted Association and Enrichment Study of Amyloid Imaging Phenotype in Alzheimer's Disease. Curr Alzheimer Res 2020; 16:1163-1174. [PMID: 31755389 DOI: 10.2174/1567205016666191121142558] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2019] [Revised: 11/19/2019] [Accepted: 11/21/2019] [Indexed: 11/22/2022]
Abstract
BACKGROUND The etiology of Alzheimer's disease remains poorly understood at the mechanistic level, and genome-wide network-based genetics have the potential to provide new insights into the disease mechanisms. OBJECTIVE The study aimed to explore the collective effects of multiple genetic association signals on an AV-45 PET measure, which is a well-known Alzheimer's disease biomarker, by employing a network assisted strategy. METHODS First, we took advantage of a dense module search algorithm to identify modules enriched by genetic association signals in a protein-protein interaction network. Next, we performed statistical evaluation to the modules identified by dense module search, including a normalization process to adjust the topological bias in the network, a replication test to ensure the modules were not found randomly , and a permutation test to evaluate unbiased associations between the modules and amyloid imaging phenotype. Finally, topological analysis, module similarity tests and functional enrichment analysis were performed for the identified modules. RESULTS We identified 24 consensus modules enriched by robust genetic signals in a genome-wide association analysis. The results not only validated several previously reported AD genes (APOE, APP, TOMM40, DDAH1, PARK2, ATP5C1, PVRL2, ELAVL1, ACTN1 and NRF1), but also nominated a few novel genes (ABL1, ABLIM2) that have not been studied in Alzheimer's disease but have shown associations with other neurodegenerative diseases. CONCLUSION The identified genes, consensus modules and enriched pathways may provide important clues to future research on the neurobiology of Alzheimer's disease and suggest potential therapeutic targets.
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Affiliation(s)
- Jin Li
- College of Automation, Harbin Engineering University, Harbin, China
| | - Feng Chen
- College of Automation, Harbin Engineering University, Harbin, China
| | - Qiushi Zhang
- College of Information Engineering, Northeast Dianli University, Jilin, China
| | - Xianglian Meng
- College of Automation, Harbin Engineering University, Harbin, China
| | - Xiaohui Yao
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Shannon L Risacher
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, PA, United States
| | - Jingwen Yan
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, PA, United States
| | - Andrew J Saykin
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, PA, United States
| | - Hong Liang
- College of Automation, Harbin Engineering University, Harbin, China
| | - Li Shen
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
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49
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Greater effect of polygenic risk score for Alzheimer's disease among younger cases who are apolipoprotein E-ε4 carriers. Neurobiol Aging 2020; 99:101.e1-101.e9. [PMID: 33164815 DOI: 10.1016/j.neurobiolaging.2020.09.014] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Revised: 09/04/2020] [Accepted: 09/10/2020] [Indexed: 12/12/2022]
Abstract
To evaluate how age and apolipoprotein E-ε4 (APOE4) status interact with APOE-independent polygenic risk score (PRSnon-APOE), we estimated PRSnon-APOE in superagers (age ≥ 90 years, N = 346), 89- controls (age 60-89, N = 2930), and Alzheimer's disease (AD) cases (N = 1760). Using superagers, we see a nearly 5 times greater odds ratio (OR) for AD comparing the top PRSnon-APOE decile to the lowest decile (OR = 4.82, p = 2.5 × 10-6), which is twice the OR as using 89- controls (OR = 2.38, p = 4.6 × 10-9). Thus PRSnon-APOE is correlated with age, which in turn is associated with APOE. Further exploring these relationships, we find that PRSnon-APOE modifies age at onset among APOE4 carriers, but not among noncarriers. More specifically, PRSnon-APOE in the top decile predicts an age at onset 5 years earlier compared with the lowest decile (70.1 vs. 75.0 years; t-test p = 2.4 × 10-5) among APOE4 carriers. This disproportionally large PRSnon-APOE among younger APOE4-positive cases is reflected in a significant statistical interaction between APOE4 status and age at onset (β = -0.02, p = 4.8 × 10-3) as a predictor of PRSnon-APOE. Thus, the known AD risk variants are particularly detrimental in young APOE4 carriers.
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50
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Zhang Q, Sidorenko J, Couvy-Duchesne B, Marioni RE, Wright MJ, Goate AM, Marcora E, Huang KL, Porter T, Laws SM, Sachdev PS, Mather KA, Armstrong NJ, Thalamuthu A, Brodaty H, Yengo L, Yang J, Wray NR, McRae AF, Visscher PM. Risk prediction of late-onset Alzheimer's disease implies an oligogenic architecture. Nat Commun 2020; 11:4799. [PMID: 32968074 PMCID: PMC7511365 DOI: 10.1038/s41467-020-18534-1] [Citation(s) in RCA: 83] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Accepted: 08/25/2020] [Indexed: 01/09/2023] Open
Abstract
Genetic association studies have identified 44 common genome-wide significant risk loci for late-onset Alzheimer's disease (LOAD). However, LOAD genetic architecture and prediction are unclear. Here we estimate the optimal P-threshold (Poptimal) of a genetic risk score (GRS) for prediction of LOAD in three independent datasets comprising 676 cases and 35,675 family history proxy cases. We show that the discriminative ability of GRS in LOAD prediction is maximised when selecting a small number of SNPs. Both simulation results and direct estimation indicate that the number of causal common SNPs for LOAD may be less than 100, suggesting LOAD is more oligogenic than polygenic. The best GRS explains approximately 75% of SNP-heritability, and individuals in the top decile of GRS have ten-fold increased odds when compared to those in the bottom decile. In addition, 14 variants are identified that contribute to both LOAD risk and age at onset of LOAD.
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Affiliation(s)
- Qian Zhang
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Julia Sidorenko
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Baptiste Couvy-Duchesne
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Margaret J Wright
- Queensland Brain Institute, The University of Queensland, St Lucia, QLD, 4072, Australia
- Centre for Advanced Imaging, The University of Queensland, St Lucia, QLD, 4072, Australia
| | - Alison M Goate
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Edoardo Marcora
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Kuan-Lin Huang
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Tenielle Porter
- Collaborative Genomics Group, Centre of Excellence for Alzheimer's Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - Simon M Laws
- Collaborative Genomics Group, Centre of Excellence for Alzheimer's Disease Research and Care, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- School of Pharmacy and Biomedical Sciences, Faculty of Health Sciences, Curtin Health Innovation Research Institute, Curtin University, Bentley, WA, Australia
| | - Perminder S Sachdev
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
- Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, NSW, Australia
| | - Karen A Mather
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
- Neuroscience Research Australia, Sydney, NSW, Australia
| | - Nicola J Armstrong
- Department of Mathematics and Statistics, Murdoch University, Perth, WA, Australia
| | - Anbupalam Thalamuthu
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
- Neuroscience Research Australia, Sydney, NSW, Australia
| | - Henry Brodaty
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, Australia
- Dementia Centre for Research Collaboration, University of New South Wales, Sydney, NSW, Australia
| | - Loic Yengo
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Jian Yang
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Naomi R Wray
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
- Queensland Brain Institute, The University of Queensland, St Lucia, QLD, 4072, Australia
| | - Allan F McRae
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Peter M Visscher
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.
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