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Dressman D, Tasaki S, Yu L, Schneider J, Bennett DA, Elyaman W, Vardarajan B. Polygenic risk associated with Alzheimer's disease and other traits influences genes involved in T cell signaling and activation. Front Immunol 2024; 15:1337831. [PMID: 38590520 PMCID: PMC10999606 DOI: 10.3389/fimmu.2024.1337831] [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: 11/13/2023] [Accepted: 02/22/2024] [Indexed: 04/10/2024] Open
Abstract
Introduction T cells, known for their ability to respond to an enormous variety of pathogens and other insults, are increasingly recognized as important mediators of pathology in neurodegeneration and other diseases. T cell gene expression phenotypes can be regulated by disease-associated genetic variants. Many complex diseases are better represented by polygenic risk than by individual variants. Methods We first compute a polygenic risk score (PRS) for Alzheimer's disease (AD) using genomic sequencing data from a cohort of Alzheimer's disease (AD) patients and age-matched controls, and validate the AD PRS against clinical metrics in our cohort. We then calculate the PRS for several autoimmune disease, neurological disorder, and immune function traits, and correlate these PRSs with T cell gene expression data from our cohort. We compare PRS-associated genes across traits and four T cell subtypes. Results Several genes and biological pathways associated with the PRS for these traits relate to key T cell functions. The PRS-associated gene signature generally correlates positively for traits within a particular category (autoimmune disease, neurological disease, immune function) with the exception of stroke. The trait-associated gene expression signature for autoimmune disease traits was polarized towards CD4+ T cell subtypes. Discussion Our findings show that polygenic risk for complex disease and immune function traits can have varying effects on T cell gene expression trends. Several PRS-associated genes are potential candidates for therapeutic modulation in T cells, and could be tested in in vitro applications using cells from patients bearing high or low polygenic risk for AD or other conditions.
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Affiliation(s)
- Dallin Dressman
- Department of Neurology, Columbia University, New York, NY, United States
- The Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University, New York, NY, United States
| | - Shinya Tasaki
- Rush University Medical Center, Rush Alzheimer’s Disease Center, Chicago, IL, United States
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, United States
| | - Lei Yu
- Rush University Medical Center, Rush Alzheimer’s Disease Center, Chicago, IL, United States
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, United States
| | - Julie Schneider
- Rush University Medical Center, Rush Alzheimer’s Disease Center, Chicago, IL, United States
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, United States
- Department of Pathology, Rush University Medical Center, Chicago, IL, United States
| | - David A. Bennett
- Rush University Medical Center, Rush Alzheimer’s Disease Center, Chicago, IL, United States
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, United States
| | - Wassim Elyaman
- Department of Neurology, Columbia University, New York, NY, United States
- The Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University, New York, NY, United States
| | - Badri Vardarajan
- Department of Neurology, Columbia University, New York, NY, United States
- The Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University, New York, NY, United States
- College of Physicians and Surgeons, Columbia University, The New York Presbyterian Hospital, The Gertrude H. Sergievsky Center, New York, NY, United States
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Kikuchi M, Miyashita A, Hara N, Kasuga K, Saito Y, Murayama S, Kakita A, Akatsu H, Ozaki K, Niida S, Kuwano R, Iwatsubo T, Nakaya A, Ikeuchi T. Polygenic effects on the risk of Alzheimer's disease in the Japanese population. Alzheimers Res Ther 2024; 16:45. [PMID: 38414085 PMCID: PMC10898021 DOI: 10.1186/s13195-024-01414-x] [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: 08/10/2023] [Accepted: 02/11/2024] [Indexed: 02/29/2024]
Abstract
BACKGROUND Polygenic effects have been proposed to account for some disease phenotypes; these effects are calculated as a polygenic risk score (PRS). This score is correlated with Alzheimer's disease (AD)-related phenotypes, such as biomarker abnormalities and brain atrophy, and is associated with conversion from mild cognitive impairment (MCI) to AD. However, the AD PRS has been examined mainly in Europeans, and owing to differences in genetic structure and lifestyle, it is unclear whether the same relationships between the PRS and AD-related phenotypes exist in non-European populations. In this study, we calculated and evaluated the AD PRS in Japanese individuals using genome-wide association study (GWAS) statistics from Europeans. METHODS In this study, we calculated the AD PRS in 504 Japanese participants (145 cognitively unimpaired (CU) participants, 220 participants with late mild cognitive impairment (MCI), and 139 patients with mild AD dementia) enrolled in the Japanese Alzheimer's Disease Neuroimaging Initiative (J-ADNI) project. In order to evaluate the clinical value of this score, we (1) determined the polygenic effects on AD in the J-ADNI and validated it using two independent cohorts (a Japanese neuropathology (NP) cohort (n = 565) and the North American ADNI (NA-ADNI) cohort (n = 617)), (2) examined the AD-related phenotypes associated with the PRS, and (3) tested whether the PRS helps predict the conversion of MCI to AD. RESULTS The PRS using 131 SNPs had an effect independent of APOE. The PRS differentiated between CU participants and AD patients with an area under the curve (AUC) of 0.755 when combined with the APOE variants. Similar AUC was obtained when PRS calculated by the NP and NA-ADNI cohorts was applied. In MCI patients, the PRS was associated with cerebrospinal fluid phosphorylated-tau levels (β estimate = 0.235, p value = 0.026). MCI with a high PRS showed a significantly increased conversion to AD in APOE ε4 noncarriers with a hazard rate of 2.22. In addition, we also developed a PRS model adjusted for LD and observed similar results. CONCLUSIONS We showed that the AD PRS is useful in the Japanese population, whose genetic structure is different from that of the European population. These findings suggest that the polygenicity of AD is partially common across ethnic differences.
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Affiliation(s)
- Masataka Kikuchi
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Science, The University of Tokyo, 6-2-3 Kashiwanoha, Kashiwa, Chiba, 277-0882, Japan.
- Department of Medical Informatics, Graduate School of Medicine, Osaka University, Osaka, Japan.
| | - Akinori Miyashita
- Department of Molecular Genetics, Brain Research Institute, Niigata University, 1-757 Asahimachi, Niigata, 951-8585, Japan
| | - Norikazu Hara
- Department of Molecular Genetics, Brain Research Institute, Niigata University, 1-757 Asahimachi, Niigata, 951-8585, Japan
| | - Kensaku Kasuga
- Department of Molecular Genetics, Brain Research Institute, Niigata University, 1-757 Asahimachi, Niigata, 951-8585, Japan
| | - Yuko Saito
- Brain Bank for Aging Research (Department of Neuropathology), Tokyo Metropolitan Institute of Geriatrics and Gerontology, Tokyo, Japan
| | - Shigeo Murayama
- Brain Bank for Aging Research (Department of Neuropathology), Tokyo Metropolitan Institute of Geriatrics and Gerontology, Tokyo, Japan
- Brain Bank for Neurodevelopmental, Neurological and Psychiatric Disorders, United Graduate School of Child Development, Osaka University, Osaka, Japan
| | - Akiyoshi Kakita
- Department of Pathology, Brain Research Institute, Niigata University, Niigata, Japan
| | - Hiroyasu Akatsu
- Department of General Medicine & General Internal Medicine, Nagoya City University Graduate School of Medicine, Nagoya, Japan
| | - Kouichi Ozaki
- Medical Genome Center, National Center for Geriatrics and Gerontology, Research Institute, Aichi, Japan
- RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Shumpei Niida
- Core Facility Administration, National Center for Geriatrics and Gerontology, Research Institute, Aichi, Japan
| | - Ryozo Kuwano
- Social Welfare Corporation Asahigawaso, Asahigawaso Research Institute, Okayama, Japan
| | - Takeshi Iwatsubo
- Department of Neuropathology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Akihiro Nakaya
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Science, The University of Tokyo, 6-2-3 Kashiwanoha, Kashiwa, Chiba, 277-0882, Japan
| | - Takeshi Ikeuchi
- Department of Molecular Genetics, Brain Research Institute, Niigata University, 1-757 Asahimachi, Niigata, 951-8585, Japan.
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Veitch DP, Weiner MW, Miller M, Aisen PS, Ashford MA, Beckett LA, Green RC, Harvey D, Jack CR, Jagust W, Landau SM, Morris JC, Nho KT, Nosheny R, Okonkwo O, Perrin RJ, Petersen RC, Rivera Mindt M, Saykin A, Shaw LM, Toga AW, Tosun D. The Alzheimer's Disease Neuroimaging Initiative in the era of Alzheimer's disease treatment: A review of ADNI studies from 2021 to 2022. Alzheimers Dement 2024; 20:652-694. [PMID: 37698424 PMCID: PMC10841343 DOI: 10.1002/alz.13449] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 07/27/2023] [Accepted: 08/01/2023] [Indexed: 09/13/2023]
Abstract
The Alzheimer's Disease Neuroimaging Initiative (ADNI) aims to improve Alzheimer's disease (AD) clinical trials. Since 2006, ADNI has shared clinical, neuroimaging, and cognitive data, and biofluid samples. We used conventional search methods to identify 1459 publications from 2021 to 2022 using ADNI data/samples and reviewed 291 impactful studies. This review details how ADNI studies improved disease progression understanding and clinical trial efficiency. Advances in subject selection, detection of treatment effects, harmonization, and modeling improved clinical trials and plasma biomarkers like phosphorylated tau showed promise for clinical use. Biomarkers of amyloid beta, tau, neurodegeneration, inflammation, and others were prognostic with individualized prediction algorithms available online. Studies supported the amyloid cascade, emphasized the importance of neuroinflammation, and detailed widespread heterogeneity in disease, linked to genetic and vascular risk, co-pathologies, sex, and resilience. Biological subtypes were consistently observed. Generalizability of ADNI results is limited by lack of cohort diversity, an issue ADNI-4 aims to address by enrolling a diverse cohort.
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Affiliation(s)
- Dallas P. Veitch
- Department of Veterans Affairs Medical CenterNorthern California Institute for Research and Education (NCIRE)San FranciscoCaliforniaUSA
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA
| | - Michael W. Weiner
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA
- Department of Radiology and Biomedical ImagingUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of MedicineUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of Psychiatry and Behavioral SciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Melanie Miller
- Department of Veterans Affairs Medical CenterNorthern California Institute for Research and Education (NCIRE)San FranciscoCaliforniaUSA
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA
| | - Paul S. Aisen
- Alzheimer's Therapeutic Research InstituteUniversity of Southern CaliforniaSan DiegoCaliforniaUSA
| | - Miriam A. Ashford
- Department of Veterans Affairs Medical CenterNorthern California Institute for Research and Education (NCIRE)San FranciscoCaliforniaUSA
| | - Laurel A. Beckett
- Division of BiostatisticsDepartment of Public Health SciencesUniversity of CaliforniaDavisCaliforniaUSA
| | - Robert C. Green
- Division of GeneticsDepartment of MedicineBrigham and Women's HospitalBroad Institute Ariadne Labs and Harvard Medical SchoolBostonMassachusettsUSA
| | - Danielle Harvey
- Division of BiostatisticsDepartment of Public Health SciencesUniversity of CaliforniaDavisCaliforniaUSA
| | | | - William Jagust
- Helen Wills Neuroscience InstituteUniversity of California BerkeleyBerkeleyCaliforniaUSA
| | - Susan M. Landau
- Helen Wills Neuroscience InstituteUniversity of California BerkeleyBerkeleyCaliforniaUSA
| | - John C. Morris
- Knight Alzheimer's Disease Research CenterWashington University School of MedicineSaint LouisMissouriUSA
- Department of NeurologyWashington University School of MedicineSaint LouisMissouriUSA
- Department of Pathology and ImmunologyWashington University School of MedicineSaint LouisMissouriUSA
| | - Kwangsik T. Nho
- Department of Radiology and Imaging Sciences and the Indiana Alzheimer's Disease Research CenterIndiana University School of MedicineIndianapolisIndianaUSA
- Center for Computational Biology and BioinformaticsIndiana University School of MedicineIndianapolisIndianaUSA
| | - Rachel Nosheny
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA
- Department of Psychiatry and Behavioral SciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Ozioma Okonkwo
- Wisconsin Alzheimer's Disease Research Center and Department of MedicineUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Richard J. Perrin
- Knight Alzheimer's Disease Research CenterWashington University School of MedicineSaint LouisMissouriUSA
- Department of NeurologyWashington University School of MedicineSaint LouisMissouriUSA
- Department of Pathology and ImmunologyWashington University School of MedicineSaint LouisMissouriUSA
| | | | - Monica Rivera Mindt
- Department of PsychologyLatin American and Latino Studies InstituteAfrican and African American StudiesFordham UniversityNew YorkNew YorkUSA
- Department of NeurologyIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Andrew Saykin
- Department of Radiology and Imaging Sciences and the Indiana Alzheimer's Disease Research CenterIndiana University School of MedicineIndianapolisIndianaUSA
- Department of Medical and Molecular GeneticsIndiana University School of MedicineIndianapolisIndianaUSA
| | - Leslie M. Shaw
- Department of Pathology and Laboratory Medicine and the PENN Alzheimer's Disease Research CenterCenter for Neurodegenerative ResearchPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Arthur W. Toga
- Laboratory of Neuro ImagingInstitute of Neuroimaging and InformaticsKeck School of Medicine of University of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Duygu Tosun
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA
- Department of Radiology and Biomedical ImagingUniversity of CaliforniaSan FranciscoCaliforniaUSA
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Logue MW, Dasgupta S, Farrer LA. Genetics of Alzheimer's Disease in the African American Population. J Clin Med 2023; 12:5189. [PMID: 37629231 PMCID: PMC10455208 DOI: 10.3390/jcm12165189] [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: 06/26/2023] [Revised: 08/02/2023] [Accepted: 08/06/2023] [Indexed: 08/27/2023] Open
Abstract
Black/African American (AA) individuals have a higher risk of Alzheimer's disease (AD) than White non-Hispanic persons of European ancestry (EUR) for reasons that may include economic disparities, cardiovascular health, quality of education, and biases in the methods used to diagnose AD. AD is also heritable, and some of the differences in risk may be due to genetics. Many AD-associated variants have been identified by candidate gene studies, genome-wide association studies (GWAS), and genome-sequencing studies. However, most of these studies have been performed using EUR cohorts. In this paper, we review the genetics of AD and AD-related traits in AA individuals. Importantly, studies of genetic risk factors in AA cohorts can elucidate the molecular mechanisms underlying AD risk in AA and other populations. In fact, such studies are essential to enable reliable precision medicine approaches in persons with considerable African ancestry. Furthermore, genetic studies of AA cohorts allow exploration of the ways the impact of genes can vary by ancestry, culture, and economic and environmental disparities. They have yielded important gains in our knowledge of AD genetics, and increasing AA individual representation within genetic studies should remain a priority for inclusive genetic study design.
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Affiliation(s)
- Mark W. Logue
- National Center for PTSD, Behavioral Sciences Division, VA Boston Healthcare System, Boston, MA 02130, USA;
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA;
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Shoumita Dasgupta
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA;
- Department of Medical Sciences and Education, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
| | - Lindsay A. Farrer
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA;
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
- Department of Ophthalmology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA 02118, USA
- Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
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Shi L, Xu J, Green R, Wretlind A, Homann J, Buckley NJ, Tijms BM, Vos SJB, Lill CM, Kate MT, Engelborghs S, Sleegers K, Frisoni GB, Wallin A, Lleó A, Popp J, Martinez-Lage P, Streffer J, Barkhof F, Zetterberg H, Visser PJ, Lovestone S, Bertram L, Nevado-Holgado AJ, Proitsi P, Legido-Quigley C. Multiomics profiling of human plasma and cerebrospinal fluid reveals ATN-derived networks and highlights causal links in Alzheimer's disease. Alzheimers Dement 2023; 19:3350-3364. [PMID: 36790009 DOI: 10.1002/alz.12961] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 12/07/2022] [Accepted: 12/20/2022] [Indexed: 02/16/2023]
Abstract
INTRODUCTION This study employed an integrative system and causal inference approach to explore molecular signatures in blood and CSF, the amyloid/tau/neurodegeneration [AT(N)] framework, mild cognitive impairment (MCI) conversion to Alzheimer's disease (AD), and genetic risk for AD. METHODS Using the European Medical Information Framework (EMIF)-AD cohort, we measured 696 proteins in cerebrospinal fluid (n = 371), 4001 proteins in plasma (n = 972), 611 metabolites in plasma (n = 696), and genotyped whole-blood (7,778,465 autosomal single nucleotide epolymorphisms, n = 936). We investigated associations: molecular modules to AT(N), module hubs with AD Polygenic Risk scores and APOE4 genotypes, molecular hubs to MCI conversion and probed for causality with AD using Mendelian randomization (MR). RESULTS AT(N) framework associated with protein and lipid hubs. In plasma, Proprotein Convertase Subtilisin/Kexin Type 7 showed evidence for causal associations with AD. AD was causally associated with Reticulocalbin 2 and sphingomyelins, an association driven by the APOE isoform. DISCUSSION This study reveals multi-omics networks associated with AT(N) and causal AD molecular candidates.
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Affiliation(s)
- Liu Shi
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Jin Xu
- Institute of Pharmaceutical Science, King's College London, London, UK
| | - Rebecca Green
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
- UK National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre, South London and Maudsley Trust, London, UK
- MRC Unit for Lifelong Health & Ageing at UCL, University College London, London, UK
| | | | - Jan Homann
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
| | - Noel J Buckley
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Betty M Tijms
- Alzheimer Center, VU University Medical Center, Amsterdam, the Netherlands
| | - Stephanie J B Vos
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands
| | - Christina M Lill
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
- Institute of Epidemiology and Social Medicine, University of Muenster, Muenster, Germany
- Ageing Epidemiology Research Unit (AGE), School of Public Health, Imperial College London, London, UK
| | - Mara Ten Kate
- Alzheimer Center, VU University Medical Center, Amsterdam, the Netherlands
| | - Sebastiaan Engelborghs
- Reference Center for Biological Markers of Dementia (BIODEM), Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
- Department of Neurology, UZ Brussel and Center for Neurociences (C4N), Vrije Universiteit Brussel, Brussels, Belgium
| | - Kristel Sleegers
- Complex Genetics Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
- Institute Born-Bunge, Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Giovanni B Frisoni
- University of Geneva, Geneva, Switzerland
- IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Anders Wallin
- Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Gothenburg, Sweden
| | - Alberto Lleó
- Neurology Department, Centro de Investigación en Red en enfermedades neurodegenerativas (CIBERNED), Hospital Sant Pau, Barcelona, Spain
| | - Julius Popp
- University Hospital of Lausanne, Lausanne, Switzerland
- Department of Geriatric Psychiatry, University Hospital of Psychiatry and University of Zürich, Zürich, Switzerland
| | | | - Johannes Streffer
- AC Immune SA, formerly Janssen R&D, LLC. Beerse, Belgium at the time of study conduct, Lausanne, Switzerland
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherland
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, UK
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- UK Dementia Research Institute at UCL, London, UK
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | - Pieter Jelle Visser
- Alzheimer Center, VU University Medical Center, Amsterdam, the Netherlands
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands
| | - Simon Lovestone
- Department of Psychiatry, University of Oxford, Oxford, UK
- Janssen Medical (UK), High Wycombe, UK
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
- Department of Psychology, University of Oslo, Oslo, Norway
| | | | - Petroula Proitsi
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Cristina Legido-Quigley
- Institute of Pharmaceutical Science, King's College London, London, UK
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
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Stocker H, Trares K, Beyer L, Perna L, Rujescu D, Holleczek B, Beyreuther K, Gerwert K, Schöttker B, Brenner H. Alzheimer's polygenic risk scores, APOE, Alzheimer's disease risk, and dementia-related blood biomarker levels in a population-based cohort study followed over 17 years. Alzheimers Res Ther 2023; 15:129. [PMID: 37516890 PMCID: PMC10386275 DOI: 10.1186/s13195-023-01277-8] [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: 02/10/2023] [Accepted: 07/21/2023] [Indexed: 07/31/2023]
Abstract
BACKGROUND In order to utilize polygenic risk scores (PRSs) for Alzheimer's disease (AD) in a meaningful way, influential factors (i.e. training set) and prediction across groups such as APOE e4 (APOE4) genotype as well as associations to dementia-related biomarkers should be explored. Therefore, we examined the association of APOE4 and various PRSs, based on training sets that utilized differing AD definitions, with incident AD and all-cause dementia (ACD) within 17 years, and with levels of phosphorylated tau181 (P-tau181), neurofilament light (NfL), and glial fibrillary acidic protein (GFAP) in blood. Secondarily, effect modification by APOE4 status and sex was examined. METHODS In this prospective, population-based cohort study and nested case-control study, 9,940 participants in Germany were enrolled between 2000 and 2002 by their general practitioners and followed for up to 17 years. Participants were included in this study if dementia status and genetic data were available. A subsample of participants additionally had measurements of P-tau181, NfL, and GFAP obtained from blood samples. Cox and logistic regression analyses were used to assess the association of genetic risk (APOE genotype and PRSnoAPOE) with incident ACD/AD and log-transformed blood levels of P-tau181, NfL, and GFAP. RESULTS Five thousand seven hundred sixty-five participants (54% female, aged 50-75years at baseline) were included in this study, of whom 464 received an all-cause dementia diagnosis within 17 years. The PRSs were not more predictive of dementia than APOE4. An APOE4 specific relationship was apparent with PRSs only exhibiting associations to dementia among APOE4 carriers. In the nested case-control study including biomarkers (n = 712), APOE4 status and polygenic risk were significantly associated to levels of GFAP in blood. CONCLUSIONS The use of PRSs may be beneficial for increased precision in risk estimates among APOE4 carriers. While APOE4 may play a crucial etiological role in initial disease processes such as Aβ deposition, the PRS may be an indicator of further disease drivers as well as astrocyte activation. Further research is necessary to confirm these findings, especially the association to GFAP.
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Affiliation(s)
- Hannah Stocker
- Network Aging Research, Heidelberg University, Heidelberg, Germany.
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany.
| | - Kira Trares
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany
| | - Léon Beyer
- Center for Protein Diagnostics (ProDi), Ruhr-University Bochum, Bochum, Germany
- Department of Biophysics, Ruhr-University Bochum, Bochum, Germany
| | - Laura Perna
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Munich, Germany
| | - Dan Rujescu
- Department of Psychiatry, Medical University of Vienna, Vienna, Austria
| | | | | | - Klaus Gerwert
- Center for Protein Diagnostics (ProDi), Ruhr-University Bochum, Bochum, Germany
- Department of Biophysics, Ruhr-University Bochum, Bochum, Germany
| | - Ben Schöttker
- Network Aging Research, Heidelberg University, Heidelberg, Germany
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany
| | - Hermann Brenner
- Network Aging Research, Heidelberg University, Heidelberg, Germany
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany
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Juul Rasmussen I, Frikke-Schmidt R. Modifiable cardiovascular risk factors and genetics for targeted prevention of dementia. Eur Heart J 2023; 44:2526-2543. [PMID: 37224508 PMCID: PMC10481783 DOI: 10.1093/eurheartj/ehad293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 02/22/2023] [Accepted: 05/04/2023] [Indexed: 05/26/2023] Open
Abstract
Dementia is a major global challenge for health and social care in the 21st century. A third of individuals >65 years of age die with dementia, and worldwide incidence numbers are projected to be higher than 150 million by 2050. Dementia is, however, not an inevitable consequence of old age; 40% of dementia may theoretically be preventable. Alzheimer's disease (AD) accounts for approximately two-thirds of dementia cases and the major pathological hallmark of AD is accumulation of amyloid-β. Nevertheless, the exact pathological mechanisms of AD remain unknown. Cardiovascular disease and dementia share several risk factors and dementia often coexists with cerebrovascular disease. In a public health perspective, prevention is crucial, and it is suggested that a 10% reduction in prevalence of cardiovascular risk factors could prevent more than nine million dementia cases worldwide by 2050. Yet this assumes causality between cardiovascular risk factors and dementia and adherence to the interventions over decades for a large number of individuals. Using genome-wide association studies, the entire genome can be scanned for disease/trait associated loci in a hypothesis-free manner, and the compiled genetic information is not only useful for pinpointing novel pathogenic pathways but also for risk assessments. This enables identification of individuals at high risk, who likely will benefit the most from a targeted intervention. Further optimization of the risk stratification can be done by adding cardiovascular risk factors. Additional studies are, however, highly needed to elucidate dementia pathogenesis and potential shared causal risk factors between cardiovascular disease and dementia.
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Affiliation(s)
- Ida Juul Rasmussen
- Department of Clinical Biochemistry, Rigshospitalet, Copenhagen University Hospital, Blegdamsvej 9, DK-2100 Copenhagen, Denmark
| | - Ruth Frikke-Schmidt
- Department of Clinical Biochemistry, Rigshospitalet, Copenhagen University Hospital, Blegdamsvej 9, DK-2100 Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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8
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Leffa DT, Ferrari-Souza JP, Bellaver B, Tissot C, Ferreira PCL, Brum WS, Caye A, Lord J, Proitsi P, Martins-Silva T, Tovo-Rodrigues L, Tudorascu DL, Villemagne VL, Cohen AD, Lopez OL, Klunk WE, Karikari TK, Rosa-Neto P, Zimmer ER, Molina BSG, Rohde LA, Pascoal TA. Genetic risk for attention-deficit/hyperactivity disorder predicts cognitive decline and development of Alzheimer's disease pathophysiology in cognitively unimpaired older adults. Mol Psychiatry 2023; 28:1248-1255. [PMID: 36476732 DOI: 10.1038/s41380-022-01867-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 10/07/2022] [Accepted: 11/01/2022] [Indexed: 12/12/2022]
Abstract
Attention-deficit/hyperactivity disorder (ADHD) persists in older age and is postulated as a risk factor for cognitive impairment and Alzheimer's Disease (AD). However, these findings rely primarily on electronic health records and can present biased estimates of disease prevalence. An obstacle to investigating age-related cognitive decline in ADHD is the absence of large-scale studies following patients with ADHD into older age. Alternatively, this study aimed to determine whether genetic liability for ADHD, as measured by a well-validated ADHD polygenic risk score (ADHD-PRS), is associated with cognitive decline and the development of AD pathophysiology in cognitively unimpaired (CU) older adults. We calculated a weighted ADHD-PRS in 212 CU individuals without a clinical diagnosis of ADHD (55-90 years). These individuals had baseline amyloid-β (Aβ) positron emission tomography, longitudinal cerebrospinal fluid (CSF) phosphorylated tau at threonine 181 (p-tau181), magnetic resonance imaging, and cognitive assessments for up to 6 years. Linear mixed-effects models were used to test the association of ADHD-PRS with cognition and AD biomarkers. Higher ADHD-PRS was associated with greater cognitive decline over 6 years. The combined effect between high ADHD-PRS and brain Aβ deposition on cognitive deterioration was more significant than each individually. Additionally, higher ADHD-PRS was associated with increased CSF p-tau181 levels and frontoparietal atrophy in CU Aβ-positive individuals. Our results suggest that genetic liability for ADHD is associated with cognitive deterioration and the development of AD pathophysiology. Findings were mostly observed in Aβ-positive individuals, suggesting that the genetic liability for ADHD increases susceptibility to the harmful effects of Aβ pathology.
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Affiliation(s)
- Douglas T Leffa
- ADHD Outpatient Program & Development Psychiatry Program, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - João Pedro Ferrari-Souza
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Bruna Bellaver
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Cécile Tissot
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Translational Neuroimaging Laboratory, McGill University, Montreal, Quebec, Canada
| | | | - Wagner S Brum
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Arthur Caye
- ADHD Outpatient Program & Development Psychiatry Program, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil
- Center for Innovation in Mental Health (CISM)/National Institute for Developmental Psychiatry (INPD), São Paulo, Brazil
| | - Jodie Lord
- Institute of Psychology, Psychiatry & Neuroscience, King's College London, London, UK
| | - Petroula Proitsi
- Institute of Psychology, Psychiatry & Neuroscience, King's College London, London, UK
| | - Thais Martins-Silva
- Human Development and Violence Research Centre (DOVE), Post-Graduate Program in Epidemiology, Universidade Federal de Pelotas, Pelotas, Rio Grande do Sul, Brazil
| | - Luciana Tovo-Rodrigues
- Postgraduate Program in Epidemiology, Universidade Federal de Pelotas, Pelotas, Rio Grande do Sul, Brazil
| | - Dana L Tudorascu
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Ann D Cohen
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Oscar L Lopez
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - William E Klunk
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Thomas K Karikari
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, McGill University, Montreal, Quebec, Canada
| | - Eduardo R Zimmer
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
- Department of Pharmacology, Graduate Program in Biological Sciences: Pharmacology and Therapeutics, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Brooke S G Molina
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Luis Augusto Rohde
- ADHD Outpatient Program & Development Psychiatry Program, Hospital de Clínicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil.
- Center for Innovation in Mental Health (CISM)/National Institute for Developmental Psychiatry (INPD), São Paulo, Brazil.
- UniEduk, Indaiatuba, São Paulo, Brazil.
| | - Tharick A Pascoal
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA.
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9
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Green RE, Lord J, Scelsi MA, Xu J, Wong A, Naomi-James S, Handy A, Gilchrist L, Williams DM, Parker TD, Lane CA, Malone IB, Cash DM, Sudre CH, Coath W, Thomas DL, Keuss S, Dobson R, Legido-Quigley C, Fox NC, Schott JM, Richards M, Proitsi P. Investigating associations between blood metabolites, later life brain imaging measures, and genetic risk for Alzheimer's disease. Alzheimers Res Ther 2023; 15:38. [PMID: 36814324 PMCID: PMC9945600 DOI: 10.1186/s13195-023-01184-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 02/08/2023] [Indexed: 02/24/2023]
Abstract
BACKGROUND Identifying blood-based signatures of brain health and preclinical pathology may offer insights into early disease mechanisms and highlight avenues for intervention. Here, we systematically profiled associations between blood metabolites and whole-brain volume, hippocampal volume, and amyloid-β status among participants of Insight 46-the neuroscience sub-study of the National Survey of Health and Development (NSHD). We additionally explored whether key metabolites were associated with polygenic risk for Alzheimer's disease (AD). METHODS Following quality control, levels of 1019 metabolites-detected with liquid chromatography-mass spectrometry-were available for 1740 participants at age 60-64. Metabolite data were subsequently clustered into modules of co-expressed metabolites using weighted coexpression network analysis. Accompanying MRI and amyloid-PET imaging data were present for 437 participants (age 69-71). Regression analyses tested relationships between metabolite measures-modules and hub metabolites-and imaging outcomes. Hub metabolites were defined as metabolites that were highly connected within significant (pFDR < 0.05) modules or were identified as a hub in a previous analysis on cognitive function in the same cohort. Regression models included adjustments for age, sex, APOE genotype, lipid medication use, childhood cognitive ability, and social factors. Finally, associations were tested between AD polygenic risk scores (PRS), including and excluding the APOE region, and metabolites and modules that significantly associated (pFDR < 0.05) with an imaging outcome (N = 1638). RESULTS In the fully adjusted model, three lipid modules were associated with a brain volume measure (pFDR < 0.05): one enriched in sphingolipids (hippocampal volume: ß = 0.14, 95% CI = [0.055,0.23]), one in several fatty acid pathways (whole-brain volume: ß = - 0.072, 95%CI = [- 0.12, - 0.026]), and another in diacylglycerols and phosphatidylethanolamines (whole-brain volume: ß = - 0.066, 95% CI = [- 0.11, - 0.020]). Twenty-two hub metabolites were associated (pFDR < 0.05) with an imaging outcome (whole-brain volume: 22; hippocampal volume: 4). Some nominal associations were reported for amyloid-β, and with an AD PRS in our genetic analysis, but none survived multiple testing correction. CONCLUSIONS Our findings highlight key metabolites, with functions in membrane integrity and cell signalling, that associated with structural brain measures in later life. Future research should focus on replicating this work and interrogating causality.
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Affiliation(s)
- Rebecca E Green
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AB, UK.,UK National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre, South London and Maudsley Trust, London, UK
| | - Jodie Lord
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AB, UK
| | - Marzia A Scelsi
- Department of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing (CMIC), University College London (UCL), London, UK
| | - Jin Xu
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AB, UK.,Institute of Pharmaceutical Science, King's College London, London, UK
| | - Andrew Wong
- MRC Unit for Lifelong Health & Ageing at UCL, University College London, Floor 5, MRC LHA at UCL, 1 - 19 Torrington Place, London, WC1E 7HB, UK
| | - Sarah Naomi-James
- MRC Unit for Lifelong Health & Ageing at UCL, University College London, Floor 5, MRC LHA at UCL, 1 - 19 Torrington Place, London, WC1E 7HB, UK.,Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK
| | - Alex Handy
- University College London, Institute of Health Informatics, London, UK
| | - Lachlan Gilchrist
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AB, UK
| | - Dylan M Williams
- MRC Unit for Lifelong Health & Ageing at UCL, University College London, Floor 5, MRC LHA at UCL, 1 - 19 Torrington Place, London, WC1E 7HB, UK.,Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Thomas D Parker
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK.,Department of Brain Sciences, Imperial College London, London, W12 0NN, UK.,UK DRI Centre for Care Research and Technology, Imperial College London, London, W12 0BZ, UK
| | - Christopher A Lane
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK
| | - Ian B Malone
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK
| | - David M Cash
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK.,UK Dementia Research Institute at University College London, London, UK
| | - Carole H Sudre
- Department of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing (CMIC), University College London (UCL), London, UK.,MRC Unit for Lifelong Health & Ageing at UCL, University College London, Floor 5, MRC LHA at UCL, 1 - 19 Torrington Place, London, WC1E 7HB, UK.,Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK.,School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - William Coath
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK
| | - David L Thomas
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK.,Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Sarah Keuss
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK
| | - Richard Dobson
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AB, UK.,UK National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre, South London and Maudsley Trust, London, UK.,University College London, Institute of Health Informatics, London, UK.,Health Data Research UK London, University College London, London, UK.,NIHR Biomedical Research Centre at University College London Hospitals NHS Foundation Trust, London, UK
| | - Cristina Legido-Quigley
- Institute of Pharmaceutical Science, King's College London, London, UK.,Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - Nick C Fox
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK.,UK Dementia Research Institute at University College London, London, UK
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK.
| | - Marcus Richards
- MRC Unit for Lifelong Health & Ageing at UCL, University College London, Floor 5, MRC LHA at UCL, 1 - 19 Torrington Place, London, WC1E 7HB, UK.
| | - Petroula Proitsi
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AB, UK.
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10
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Stevenson-Hoare J, Heslegrave A, Leonenko G, Fathalla D, Bellou E, Luckcuck L, Marshall R, Sims R, Morgan BP, Hardy J, de Strooper B, Williams J, Zetterberg H, Escott-Price V. Plasma biomarkers and genetics in the diagnosis and prediction of Alzheimer's disease. Brain 2023; 146:690-699. [PMID: 35383826 PMCID: PMC9924904 DOI: 10.1093/brain/awac128] [Citation(s) in RCA: 40] [Impact Index Per Article: 40.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 02/14/2022] [Accepted: 03/13/2022] [Indexed: 11/12/2022] Open
Abstract
Plasma biomarkers for Alzheimer's disease-related pathologies have undergone rapid developments during the past few years, and there are now well-validated blood tests for amyloid and tau pathology, as well as neurodegeneration and astrocytic activation. To define Alzheimer's disease with biomarkers rather than clinical assessment, we assessed prediction of research-diagnosed disease status using these biomarkers and tested genetic variants associated with the biomarkers that may reflect more accurately the risk of biochemically defined Alzheimer's disease instead of the risk of dementia. In a cohort of Alzheimer's disease cases [n = 1439, mean age 68 years (standard deviation = 8.2)] and screened controls [n = 508, mean age 82 years (standard deviation = 6.8)], we measured plasma concentrations of the 40 and 42 amino acid-long amyloid-β (Aβ) fragments (Aβ40 and Aβ42, respectively), tau phosphorylated at amino acid 181 (P-tau181), neurofilament light (NfL) and glial fibrillary acidic protein (GFAP) using state-of-the-art Single molecule array (Simoa) technology. We tested the relationships between the biomarkers and Alzheimer's disease genetic risk, age at onset and disease duration. We also conducted a genome-wide association study for association of disease risk genes with these biomarkers. The prediction accuracy of Alzheimer's disease clinical diagnosis by the combination of all biomarkers, APOE and polygenic risk score reached area under receiver operating characteristic curve (AUC) = 0.81, with the most significant contributors being ε4, Aβ40 or Aβ42, GFAP and NfL. All biomarkers were significantly associated with age in cases and controls (P < 4.3 × 10-5). Concentrations of the Aβ-related biomarkers in plasma were significantly lower in cases compared with controls, whereas other biomarker levels were significantly higher in cases. In the case-control genome-wide analyses, APOE-ε4 was associated with all biomarkers (P = 0.011-4.78 × 10-8), except NfL. No novel genome-wide significant single nucleotide polymorphisms were found in the case-control design; however, in a case-only analysis, we found two independent genome-wide significant associations between the Aβ42/Aβ40 ratio and WWOX and COPG2 genes. Disease prediction modelling by the combination of all biomarkers indicates that the variance attributed to P-tau181 is mostly captured by APOE-ε4, whereas Aβ40, Aβ42, GFAP and NfL biomarkers explain additional variation over and above APOE. We identified novel plausible genome wide-significant genes associated with Aβ42/Aβ40 ratio in a sample which is 50 times smaller than current genome-wide association studies in Alzheimer's disease.
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Affiliation(s)
| | - Amanda Heslegrave
- Dementia Research Institute, University College London, London, UK
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
| | - Ganna Leonenko
- Dementia Research Institute, Cardiff University, Cardiff, UK
| | - Dina Fathalla
- Dementia Research Institute, Cardiff University, Cardiff, UK
| | - Eftychia Bellou
- Dementia Research Institute, Cardiff University, Cardiff, UK
| | - Lauren Luckcuck
- Dementia Research Institute, Cardiff University, Cardiff, UK
| | - Rachel Marshall
- Division of Neuroscience and Mental Health, Cardiff University, Cardiff, UK
| | - Rebecca Sims
- Division of Neuroscience and Mental Health, Cardiff University, Cardiff, UK
| | | | - John Hardy
- Dementia Research Institute, University College London, London, UK
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
| | - Bart de Strooper
- Dementia Research Institute, University College London, London, UK
- VIB Center for Brain and Disease Research, 3000 Leuven, Belgium
- KU Leuven, Leuven Brain Institute, 3000 Leuven, Belgium
| | - Julie Williams
- Dementia Research Institute, Cardiff University, Cardiff, UK
| | - Henrik Zetterberg
- Dementia Research Institute, University College London, London, UK
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Valentina Escott-Price
- Dementia Research Institute, Cardiff University, Cardiff, UK
- Division of Neuroscience and Mental Health, Cardiff University, Cardiff, UK
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11
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Wang S, Ke S, Liu S, Wang E, Pan T. APOE ε4 status and plasma p-tau181 interact to influence cognitive performance among non-demented older adults. Neurosci Lett 2023; 796:137052. [PMID: 36608927 DOI: 10.1016/j.neulet.2023.137052] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 12/25/2022] [Accepted: 01/02/2023] [Indexed: 01/05/2023]
Abstract
OBJECTIVE In this study, we aimed to investigate the relationships among plasma p-tau181, APOE ε4, and cognitive performance in non-demented elderly individuals. METHODS We used individuals (n = 630) with cognitive normal (CN, n = 182) and mild cognitive impairment (MCI, n = 448). Multiple linear regression models were performed to test the effects of APOE ε4 × plasma p-tau181 interaction on MMSE, CDR-SOB, ADAS-cog13, and RAVLT immediate recall. All models adjusted for age, sex, and education. RESULTS In total, our study comprised 630 samples including 364 APOE ε4 non-carriers and 266 APOE ε4 carriers. In APOE ε4 carriers, plasma p-tau181 was significantly associated with MMSE (B = -0.04, p = 0.003), ADAS-Cog13 (B [unstandardized coefficient] = 0.21, p < 0.001), CDR-SB (B = 0.02, p = 0.003) and RAVLT immediate recall ((B = -0.17, p = 0.035). After correcting for Aβ status and diagnosis, the interaction between APOE ε4 and plasma p-tau181 was significant or marginally significant associations for RAVLT immediate recall (p = 0.076), MMSE (p = 0.011), CDR (p = 0.008), and ADAS-Cog13 (p < 0.001). CONCLUSIONS Our findings suggested that plasma p-tau181 levels predicted cognitive performance among non-demented older adults, but only in the APOE ε4 carriers.
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Affiliation(s)
- Shanshan Wang
- Department of Neurology, Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, China
| | - Shaofa Ke
- Department of Neurology, Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, China
| | - Suzhi Liu
- Department of Neurology, Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, China
| | - En Wang
- Department of Neurology, Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, China
| | - Tengwei Pan
- Department of Neurology, Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, China.
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12
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Genetically predicted telomere length and Alzheimer’s disease endophenotypes: a Mendelian randomization study. Alzheimers Res Ther 2022; 14:167. [PMID: 36345036 PMCID: PMC9641781 DOI: 10.1186/s13195-022-01101-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Accepted: 10/16/2022] [Indexed: 11/09/2022]
Abstract
Telomere length (TL) is associated with biological aging, consequently influencing the risk of age-related diseases such as Alzheimer’s disease (AD). We aimed to evaluate the potential causal role of TL in AD endophenotypes (i.e., cognitive performance, N = 2233; brain age and AD-related signatures, N = 1134; and cerebrospinal fluid biomarkers (CSF) of AD and neurodegeneration, N = 304) through a Mendelian randomization (MR) analysis. Our analysis was conducted in the context of the ALFA (ALzheimer and FAmilies) study, a population of cognitively healthy individuals at risk of AD. A total of 20 single nucleotide polymorphisms associated with TL were used to determine the effect of TL on AD endophenotypes. Analyses were adjusted by age, sex, and years of education. Stratified analyses by APOE-ɛ4 status and polygenic risk score of AD were conducted. MR analysis revealed significant associations between genetically predicted longer TL and lower levels of CSF Aβ and higher levels of CSF NfL only in APOE-ɛ4 non-carriers. Moreover, inheriting longer TL was associated with greater cortical thickness in age and AD-related brain signatures and lower levels of CSF p-tau among individuals at a high genetic predisposition to AD. Further observational analyses are warranted to better understand these associations.
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13
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Tippett LJ, Cawston EE, Morgan CA, Melzer TR, Brickell KL, Ilse C, Cheung G, Kirk IJ, Roberts RP, Govender J, Griner L, Le Heron C, Buchanan S, Port W, Dudley M, Anderson TJ, Williams JM, Cutfield NJ, Dalrymple-Alford JC, Wood P. Dementia Prevention Research Clinic: a longitudinal study investigating factors influencing the development of Alzheimer’s disease in Aotearoa, New Zealand. J R Soc N Z 2022. [DOI: 10.1080/03036758.2022.2098780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2022]
Affiliation(s)
- Lynette J. Tippett
- NZ-Dementia Prevention Research Clinic, New Zealand
- School of Psychology, University of Auckland, Auckland, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Erin E. Cawston
- NZ-Dementia Prevention Research Clinic, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Department of Pharmacology, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Catherine A. Morgan
- NZ-Dementia Prevention Research Clinic, New Zealand
- School of Psychology, University of Auckland, Auckland, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Tracy R. Melzer
- NZ-Dementia Prevention Research Clinic, New Zealand
- New Zealand Brain Research Institute, Christchurch, New Zealand
- Department of Medicine, University of Otago, Christchurch, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Kiri L. Brickell
- NZ-Dementia Prevention Research Clinic, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- School of Medicine, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Christina Ilse
- NZ-Dementia Prevention Research Clinic, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Gary Cheung
- NZ-Dementia Prevention Research Clinic, New Zealand
- Department of Psychological Medicine, School of Medicine, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Ian J. Kirk
- NZ-Dementia Prevention Research Clinic, New Zealand
- School of Psychology, University of Auckland, Auckland, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Reece P. Roberts
- NZ-Dementia Prevention Research Clinic, New Zealand
- School of Psychology, University of Auckland, Auckland, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Jane Govender
- NZ-Dementia Prevention Research Clinic, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Leon Griner
- NZ-Dementia Prevention Research Clinic, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Department of Pharmacology, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Campbell Le Heron
- NZ-Dementia Prevention Research Clinic, New Zealand
- New Zealand Brain Research Institute, Christchurch, New Zealand
- Department of Medicine, University of Otago, Christchurch, New Zealand
- Dept of Neurology, Canterbury District Health Board, Christchurch, New Zealand
| | - Sarah Buchanan
- NZ-Dementia Prevention Research Clinic, New Zealand
- Department of Neurology, Southern District Health Board, Dunedin, New Zealand
- Department of Medicine, University of Otago, Dunedin, New Zealand
| | - Waiora Port
- NZ-Dementia Prevention Research Clinic, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Makarena Dudley
- NZ-Dementia Prevention Research Clinic, New Zealand
- School of Psychology, University of Auckland, Auckland, New Zealand
- Centre for Brain Research, University of Auckland, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Tim J. Anderson
- NZ-Dementia Prevention Research Clinic, New Zealand
- New Zealand Brain Research Institute, Christchurch, New Zealand
- Department of Medicine, University of Otago, Christchurch, New Zealand
- Dept of Neurology, Canterbury District Health Board, Christchurch, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Joanna M. Williams
- NZ-Dementia Prevention Research Clinic, New Zealand
- Brain Health Research Centre, University of Otago, Dunedin, New Zealand
- Department of Anatomy, University of Otago, Dunedin, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Nicholas J. Cutfield
- NZ-Dementia Prevention Research Clinic, New Zealand
- Department of Neurology, Southern District Health Board, Dunedin, New Zealand
- Department of Medicine, University of Otago, Dunedin, New Zealand
- Brain Health Research Centre, University of Otago, Dunedin, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - John C. Dalrymple-Alford
- NZ-Dementia Prevention Research Clinic, New Zealand
- New Zealand Brain Research Institute, Christchurch, New Zealand
- School of Psychology, Speech and Hearing, University of Canterbury, Christchurch, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
| | - Phil Wood
- NZ-Dementia Prevention Research Clinic, New Zealand
- School of Medicine, University of Auckland, Auckland, New Zealand
- Ministry of Health, Wellington, New Zealand
- Department of Older Adults and Home Health, Waitemata District Health Board, Auckland, New Zealand
- Brain Research New Zealand, Rangahau Roro Aotearoa, Dunedin, New Zealand
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14
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Hawksworth J, Fernández E, Gevaert K. A new generation of AD biomarkers: 2019 to 2021. Ageing Res Rev 2022; 79:101654. [PMID: 35636691 DOI: 10.1016/j.arr.2022.101654] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 05/17/2022] [Accepted: 05/25/2022] [Indexed: 12/14/2022]
Abstract
Alzheimer's disease (AD) is the most common form of dementia and cases are rising worldwide. The effort to fight this disease is hampered by a lack of disease-modifying treatments and the absence of an early, accurate diagnostic tool. Neuropathology begins years or decades before symptoms occur and, upon onset of symptoms, diagnosis can take a year or more. Such delays postpone treatment and make research into the early stages of the disease difficult. Ideally, clinicians require a minimally invasive test that can detect AD in its early stages, before cognitive symptoms occur. Advances in proteomic technologies have facilitated the study of promising biomarkers of AD. Over the last two years (2019-2021) studies have identified and validated many species which can be measured in cerebrospinal fluid (CSF), plasma, or in both fluids, and which have a high predictive value for AD. We herein discuss proteins which have been highlighted as promising biomarkers of AD in the last two years, and consider implications for future research within the research framework of the amyloid (A), tau (T), neurodegeneration (N) scoring system. We review recently identified species of amyloid and tau which may improve diagnosis when used in combination with current measures such as amyloid-beta-42 (Aβ42), total tau (t-tau) and phosphorylated tau (p-tau). In addition, several proteins have been identified as likely proxies for neurodegeneration, including neurofilament light (NfL), synaptosomal-associated protein 25 (SNAP-25) and neurogranin (NRGN). Finally, proteins originating from diverse processes such as neuroinflammation, lipid transport and mitochondrial dysfunction could aid in both AD diagnosis and patient stratification.
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15
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Blood phospho-tau in Alzheimer disease: analysis, interpretation, and clinical utility. Nat Rev Neurol 2022; 18:400-418. [PMID: 35585226 DOI: 10.1038/s41582-022-00665-2] [Citation(s) in RCA: 95] [Impact Index Per Article: 47.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/21/2022] [Indexed: 12/11/2022]
Abstract
Well-authenticated biomarkers can provide critical insights into the biological basis of Alzheimer disease (AD) to enable timely and accurate diagnosis, estimate future burden and support therapeutic trials. Current cerebrospinal fluid and molecular neuroimaging biomarkers fulfil these criteria but lack the scalability and simplicity necessary for widespread application. Blood biomarkers of adequate effectiveness have the potential to act as first-line diagnostic and prognostic tools, and offer the possibility of extensive population screening and use that is not limited to specialized centres. Accelerated progress in our understanding of the biochemistry of brain-derived tau protein and advances in ultrasensitive technologies have enabled the development of AD-specific phosphorylated tau (p-tau) biomarkers in blood. In this Review we discuss how new information on the molecular processing of brain p-tau and secretion of specific fragments into biofluids is informing blood biomarker development, enabling the evaluation of preanalytical factors that affect quantification, and informing harmonized protocols for blood handling. We also review the performance of blood p-tau biomarkers in the context of AD and discuss their potential contexts of use for clinical and research purposes. Finally, we highlight outstanding ethical, clinical and analytical challenges, and outline the steps that need to be taken to standardize inter-laboratory and inter-assay measurements.
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16
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Ramanan VK, Heckman MG, Lesnick TG, Przybelski SA, Cahn EJ, Kosel ML, Murray ME, Mielke MM, Botha H, Graff-Radford J, Jones DT, Lowe VJ, Machulda MM, Jack CR, Knopman DS, Petersen RC, Ross OA, Vemuri P. Tau polygenic risk scoring: a cost-effective aid for prognostic counseling in Alzheimer's disease. Acta Neuropathol 2022; 143:571-583. [PMID: 35412102 PMCID: PMC9109940 DOI: 10.1007/s00401-022-02419-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 04/07/2022] [Accepted: 04/07/2022] [Indexed: 11/28/2022]
Abstract
Tau deposition is one of two hallmark features of biologically defined Alzheimer's disease (AD) and is more closely related to cognitive decline than amyloidosis. Further, not all amyloid-positive individuals develop tauopathy, resulting in wide heterogeneity in clinical outcomes across the population with AD. We hypothesized that a polygenic risk score (PRS) based on tau PET (tau PRS) would capture the aggregate inherited susceptibility/resistance architecture influencing tau accumulation, beyond solely the measurement of amyloid-β burden. Leveraging rich multimodal data from a population-based sample of older adults, we found that this novel tau PRS was a strong surrogate of tau PET deposition and captured a significant proportion of the variance in tau PET levels as compared with amyloid PET burden, APOE (apolipoprotein E) ε4 (the most common risk allele for AD), and a non-APOE PRS of clinical case-control AD risk variants. In independent validation samples, the tau PRS was associated with cerebrospinal fluid phosphorylated tau levels in one cohort and with postmortem Braak neurofibrillary tangle stage in another. We also observed an association of the tau PRS with longitudinal cognitive trajectories, including a statistical interaction of the tau PRS with amyloid burden on cognitive decline. Although additional study is warranted, these findings demonstrate the potential utility of a tau PRS for capturing the collective genetic background influencing tau deposition in the general population. In the future, a tau PRS could be leveraged for cost-effective screening and risk stratification to guide trial enrollment and clinical interventions in AD.
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Affiliation(s)
- Vijay K Ramanan
- Department of Neurology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA.
| | - Michael G Heckman
- Department of Quantitative Health Sciences, Mayo Clinic-Florida, Jacksonville, FL, 32224, USA
| | - Timothy G Lesnick
- Department of Quantitative Health Sciences, Mayo Clinic-Minnesota, Rochester, MN, 55905, USA
| | - Scott A Przybelski
- Department of Quantitative Health Sciences, Mayo Clinic-Minnesota, Rochester, MN, 55905, USA
| | - Elliot J Cahn
- Department of Quantitative Health Sciences, Mayo Clinic-Minnesota, Rochester, MN, 55905, USA
| | - Matthew L Kosel
- Department of Quantitative Health Sciences, Mayo Clinic-Minnesota, Rochester, MN, 55905, USA
| | - Melissa E Murray
- Department of Neuroscience, Mayo Clinic-Florida, Jacksonville, FL, 32224, USA
| | - Michelle M Mielke
- Department of Neurology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
- Department of Quantitative Health Sciences, Mayo Clinic-Minnesota, Rochester, MN, 55905, USA
| | - Hugo Botha
- Department of Neurology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
| | - Jonathan Graff-Radford
- Department of Neurology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
| | - David T Jones
- Department of Neurology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
- Department of Radiology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
| | - Val J Lowe
- Department of Radiology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
| | - Mary M Machulda
- Department of Psychiatry and Psychology, Mayo Clinic-Minnesota, Rochester, MN, 55905, USA
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
| | - David S Knopman
- Department of Neurology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
| | - Ronald C Petersen
- Department of Neurology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA
- Department of Quantitative Health Sciences, Mayo Clinic-Minnesota, Rochester, MN, 55905, USA
| | - Owen A Ross
- Department of Neuroscience, Mayo Clinic-Florida, Jacksonville, FL, 32224, USA
- Department of Clinical Genomics, Mayo Clinic-Florida, Jacksonville, FL, 32224, USA
| | - Prashanthi Vemuri
- Department of Neuroscience, Mayo Clinic-Florida, Jacksonville, FL, 32224, USA.
- Department of Radiology, Mayo Clinic-Minnesota, 200 First Street SW, Rochester, MN, 55905, USA.
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17
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Li Q, Lv X, Jin F, Liao K, Gao L, Xu J. Associations of Polygenic Risk Score for Late-Onset Alzheimer's Disease With Biomarkers. Front Aging Neurosci 2022; 14:849443. [PMID: 35493930 PMCID: PMC9047857 DOI: 10.3389/fnagi.2022.849443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 03/14/2022] [Indexed: 11/25/2022] Open
Abstract
Late-onset Alzheimer's disease (LOAD) is a common irreversible neurodegenerative disease with heterogeneous genetic characteristics. Identifying the biological biomarkers with the potential to predict the conversion from normal controls to LOAD is clinically important for early interventions of LOAD and clinical treatment. The polygenic risk score for LOAD (AD-PRS) has been reported the potential possibility for reliably identifying individuals with risk of developing LOAD recently. To investigate the external phenotype changes resulting from LOAD and the underlying etiology, we summarize the comprehensive associations of AD-PRS with multiple biomarkers, including neuroimaging, cerebrospinal fluid and plasma biomarkers, cardiovascular risk factors, cognitive behavior, and mental health. This systematic review helps improve the understanding of the biomarkers with potential predictive value for LOAD and further optimizing the prediction and accurate treatment of LOAD.
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Affiliation(s)
- Qiaojun Li
- School of Information Engineering, Tianjin University of Commerce, Tianjin, China
- *Correspondence: Qiaojun Li
| | - Xingping Lv
- School of Sciences, Tianjin University of Commerce, Tianjin, China
| | - Fei Jin
- Department of Molecular Imaging, Qingdao Central Hospital, Qingdao University, Qingdao, China
| | - Kun Liao
- School of Sciences, Tianjin University of Commerce, Tianjin, China
| | - Liyuan Gao
- School of Sciences, Tianjin University of Commerce, Tianjin, China
| | - Jiayuan Xu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
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18
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Upadhya S, Liu H, Luo S, Lutz MW, Chiba-Falek O. Polygenic Risk Score Effectively Predicts Depression Onset in Alzheimer’s Disease Based on Major Depressive Disorder Risk Variants. Front Neurosci 2022; 16:827447. [PMID: 35350557 PMCID: PMC8957806 DOI: 10.3389/fnins.2022.827447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Accepted: 01/31/2022] [Indexed: 12/02/2022] Open
Abstract
Introduction Depression is a common, though heterogenous, comorbidity in late-onset Alzheimer’s Disease (LOAD) patients. In addition, individuals with depression are at greater risk to develop LOAD. In previous work, we demonstrated shared genetic etiology between depression and LOAD. Collectively, these previous studies suggested interactions between depression and LOAD. However, the underpinning genetic heterogeneity of depression co-occurrence with LOAD, and the various genetic etiologies predisposing depression in LOAD, are largely unknown. Methods Major Depressive Disorder (MDD) genome-wide association study (GWAS) summary statistics were used to create polygenic risk scores (PRS). The Religious Orders Society and Rush Memory and Aging Project (ROSMAP, n = 1,708) and National Alzheimer’s Coordinating Center (NACC, n = 10,256) datasets served as discovery and validation cohorts, respectively, to assess the PRS performance in predicting depression onset in LOAD patients. Results The PRS showed marginal results in standalone models for predicting depression onset in both ROSMAP (AUC = 0.540) and NACC (AUC = 0.527). Full models, with baseline age, sex, education, and APOEε4 allele count, showed improved prediction of depression onset (ROSMAP AUC: 0.606, NACC AUC: 0.581). In time-to-event analysis, standalone PRS models showed significant effects in ROSMAP (P = 0.0051), but not in NACC cohort. Full models showed significant performance in predicting depression in LOAD for both datasets (P < 0.001 for all). Conclusion This study provided new insights into the genetic factors contributing to depression onset in LOAD and advanced our knowledge of the genetics underlying the heterogeneity of depression in LOAD. The developed PRS accurately predicted LOAD patients with depressive symptoms, thus, has clinical implications including, diagnosis of LOAD patients at high-risk to develop depression for early anti-depressant treatment.
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Affiliation(s)
- Suraj Upadhya
- Division of Translational Brain Sciences, Department of Neurology, Duke University Medical Center, Durham, NC, United States
| | - Hongliang Liu
- Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC, United States
- Department of Population Health Sciences, Duke University School of Medicine, Durham, NC, United States
| | - Sheng Luo
- Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC, United States
| | - Michael W. Lutz
- Division of Translational Brain Sciences, Department of Neurology, Duke University Medical Center, Durham, NC, United States
| | - Ornit Chiba-Falek
- Division of Translational Brain Sciences, Department of Neurology, Duke University Medical Center, Durham, NC, United States
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC, United States
- *Correspondence: Ornit Chiba-Falek,
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19
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Ramanan VK, Heckman MG, Przybelski SA, Lesnick TG, Lowe VJ, Graff-Radford J, Mielke MM, Jack CR, Knopman DS, Petersen RC, Ross OA, Vemuri P. Polygenic Scores of Alzheimer's Disease Risk Genes Add Only Modestly to APOE in Explaining Variation in Amyloid PET Burden. J Alzheimers Dis 2022; 88:1615-1625. [PMID: 35811524 PMCID: PMC9534315 DOI: 10.3233/jad-220164] [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] [Indexed: 11/15/2022]
Abstract
BACKGROUND Brain accumulation of amyloid-β is a hallmark event in Alzheimer's disease (AD) whose underlying mechanisms are incompletely understood. Case-control genome-wide association studies have implicated numerous genetic variants in risk of clinically diagnosed AD dementia. OBJECTIVE To test for associations between case-control AD risk variants and amyloid PET burden in older adults, and to assess whether a polygenic measure encompassing these factors would account for a large proportion of the unexplained variance in amyloid PET levels in the wider population. METHODS We analyzed data from the Mayo Clinic Study of Aging (MCSA) and the Alzheimer's Disease Neuroimaging Initiative (ADNI). Global cortical amyloid PET burden was the primary outcome. The 38 gene variants from Wightman et al. (2021) were analyzed as predictors, with PRSice-2 used to assess the collective phenotypic variance explained. RESULTS Known AD risk variants in APOE, PICALM, CR1, and CLU were associated with amyloid PET levels. In aggregate, the AD risk variants were strongly associated with amyloid PET levels in the MCSA (p = 1.51×10-50) and ADNI (p = 3.21×10-64). However, in both cohorts the non-APOE variants uniquely contributed only modestly (MCSA = 2.1%, ADNI = 4.4%) to explaining variation in amyloid PET levels. CONCLUSION Additional case-control AD risk variants added only modestly to APOE in accounting for individual variation in amyloid PET burden, results which were consistent across independent cohorts with distinct recruitment strategies and subject characteristics. Our findings suggest that advancing precision medicine for dementia may require integration of strategies complementing case-control approaches, including biomarker-specific genetic associations, gene-by-environment interactions, and markers of disease progression and heterogeneity.
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Affiliation(s)
- Vijay K Ramanan
- Department of Neurology, Mayo Clinic-Minnesota, Rochester, Minnesota, 55905, USA
| | - Michael G. Heckman
- Department of Quantitative Health Sciences, Mayo Clinic-Florida, Jacksonville, Florida, 32224, USA
| | - Scott A. Przybelski
- Department of Quantitative Health Sciences, Mayo Clinic-Minnesota, Rochester, Minnesota, 55905, USA
| | - Timothy G. Lesnick
- Department of Quantitative Health Sciences, Mayo Clinic-Minnesota, Rochester, Minnesota, 55905, USA
| | - Val J. Lowe
- Department of Radiology, Mayo Clinic-Minnesota, Rochester, Minnesota, 55905, USA
| | | | - Michelle M. Mielke
- Department of Neurology, Mayo Clinic-Minnesota, Rochester, Minnesota, 55905, USA
- Department of Quantitative Health Sciences, Mayo Clinic-Minnesota, Rochester, Minnesota, 55905, USA
| | - Clifford R. Jack
- Department of Radiology, Mayo Clinic-Minnesota, Rochester, Minnesota, 55905, USA
| | - David S. Knopman
- Department of Neurology, Mayo Clinic-Minnesota, Rochester, Minnesota, 55905, USA
| | - Ronald C. Petersen
- Department of Neurology, Mayo Clinic-Minnesota, Rochester, Minnesota, 55905, USA
- Department of Quantitative Health Sciences, Mayo Clinic-Minnesota, Rochester, Minnesota, 55905, USA
| | - Owen A. Ross
- Department of Neuroscience, Mayo Clinic-Florida, Jacksonville, Florida, 32224, USA
- Department of Clinical Genomics, Mayo Clinic-Florida, Jacksonville, Florida, 32224, USA
| | - Prashanthi Vemuri
- Department of Radiology, Mayo Clinic-Minnesota, Rochester, Minnesota, 55905, USA
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20
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Li Y, Laws SM, Miles LA, Wiley JS, Huang X, Masters CL, Gu BJ. Genomics of Alzheimer's disease implicates the innate and adaptive immune systems. Cell Mol Life Sci 2021; 78:7397-7426. [PMID: 34708251 PMCID: PMC11073066 DOI: 10.1007/s00018-021-03986-5] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 09/14/2021] [Accepted: 10/16/2021] [Indexed: 02/08/2023]
Abstract
Alzheimer's disease (AD) is a chronic neurodegenerative disease characterised by cognitive impairment, behavioural alteration, and functional decline. Over 130 AD-associated susceptibility loci have been identified by genome-wide association studies (GWAS), while whole genome sequencing (WGS) and whole exome sequencing (WES) studies have identified AD-associated rare variants. These variants are enriched in APOE, TREM2, CR1, CD33, CLU, BIN1, CD2AP, PILRA, SCIMP, PICALM, SORL1, SPI1, RIN3, and more genes. Given that aging is the single largest risk factor for late-onset AD (LOAD), the accumulation of somatic mutations in the brain and blood of AD patients have also been explored. Collectively, these genetic findings implicate the role of innate and adaptive immunity in LOAD pathogenesis and suggest that a systemic failure of cell-mediated amyloid-β (Aβ) clearance contributes to AD onset and progression. AD-associated variants are particularly enriched in myeloid-specific regulatory regions, implying that AD risk variants are likely to perturbate the expression of myeloid-specific AD-associated genes to interfere Aβ clearance. Defective phagocytosis, endocytosis, and autophagy may drive Aβ accumulation, which may be related to naturally-occurring antibodies to Aβ (Nabs-Aβ) produced by adaptive responses. Passive immunisation is providing efficiency in clearing Aβ and slowing cognitive decline, such as aducanumab, donanemab, and lecanemab (ban2401). Causation of AD by impairment of the innate immunity and treatment using the tools of adaptive immunity is emerging as a new paradigm for AD, but immunotherapy that boosts the innate immune functions of myeloid cells is highly expected to modulate disease progression at asymptomatic stage.
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Affiliation(s)
- Yihan Li
- The Florey Institute, The University of Melbourne, 30 Royal Parade, Parkville, VIC, 3052, Australia
| | - Simon M Laws
- Centre for Precision Health, Edith Cowan University, 270 Joondalup Dr, Joondalup, WA, 6027, Australia
- Collaborative Genomics and Translation Group, School of Medical and Health Sciences, Edith Cowan University, 270 Joondalup Dr, Joondalup, WA, 6027, Australia
| | - Luke A Miles
- The Florey Institute, The University of Melbourne, 30 Royal Parade, Parkville, VIC, 3052, Australia
| | - James S Wiley
- The Florey Institute, The University of Melbourne, 30 Royal Parade, Parkville, VIC, 3052, Australia
| | - Xin Huang
- The Florey Institute, The University of Melbourne, 30 Royal Parade, Parkville, VIC, 3052, Australia
| | - Colin L Masters
- The Florey Institute, The University of Melbourne, 30 Royal Parade, Parkville, VIC, 3052, Australia
| | - Ben J Gu
- The Florey Institute, The University of Melbourne, 30 Royal Parade, Parkville, VIC, 3052, Australia.
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21
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Chong JR, Ashton NJ, Karikari TK, Tanaka T, Schöll M, Zetterberg H, Blennow K, Chen CP, Lai MKP. Blood-based high sensitivity measurements of beta-amyloid and phosphorylated tau as biomarkers of Alzheimer's disease: a focused review on recent advances. J Neurol Neurosurg Psychiatry 2021; 92:1231-1241. [PMID: 34510001 DOI: 10.1136/jnnp-2021-327370] [Citation(s) in RCA: 51] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2021] [Accepted: 08/30/2021] [Indexed: 01/11/2023]
Abstract
Discovery and development of clinically useful biomarkers for Alzheimer's disease (AD) and related dementias have been the focus of recent research efforts. While cerebrospinal fluid and positron emission tomography or MRI-based neuroimaging markers have made the in vivo detection of AD pathology and its consequences possible, the high cost and invasiveness have limited their widespread use in the clinical setting. On the other hand, advances in potentially more accessible blood-based biomarkers had been impeded by lack of sensitivity in detecting changes in markers of the hallmarks of AD, including amyloid-β (Aβ) peptides and phosphorylated tau (P-tau). More recently, however, emerging technologies with superior sensitivity and specificity for measuring Aβ and P-tau have reported high concordances with AD severity. In this focused review, we describe several emerging technologies, including immunoprecipitation-mass spectrometry (IP-MS), single molecule array and Meso Scale Discovery immunoassay platforms, and appraise the current literature arising from their use to identify plaques, tangles and other AD-associated pathology. While there is potential clinical utility in adopting these technologies, we also highlight the further studies needed to establish Aβ and P-tau as blood-based biomarkers for AD, including validation with existing large sample sets, new independent cohorts from diverse backgrounds as well as population-based longitudinal studies. In conclusion, the availability of sensitive and reliable measurements of Aβ peptides and P-tau species in blood holds promise for the diagnosis, prognosis and outcome assessments in clinical trials for AD.
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Affiliation(s)
- Joyce R Chong
- Memory, Aging and Cognition Centre, National University Health Systems, Singapore.,Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Nicholas J Ashton
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden.,Psychology and Neuroscience, King's College London, Institute of Psychiatry, Maurice Wohl Institute Clinical Neuroscience Institute, London, UK.,NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia, South London and Maudsley NHS Foundation, London, UK.,Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Thomas K Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.,Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Tomotaka Tanaka
- Memory, Aging and Cognition Centre, National University Health Systems, Singapore.,Department of Neurology, National Cerebral and Cardiovascular Center, Suita, Osaka, Japan.,Clinical Imaging Research Centre, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Michael Schöll
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden.,Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.,Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.,Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden.,UK Dementia Research Institute at UCL, University College London, London, UK
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.,UK Dementia Research Institute at UCL, University College London, London, UK
| | - Christopher P Chen
- Memory, Aging and Cognition Centre, National University Health Systems, Singapore.,Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Mitchell K P Lai
- Memory, Aging and Cognition Centre, National University Health Systems, Singapore .,Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
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22
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Wang YL, Chen J, Du ZL, Weng H, Zhang Y, Li R, Jia Z, Sun M, Jiang J, Wang FZ, Xu J. Plasma p-tau181 Level Predicts Neurodegeneration and Progression to Alzheimer's Dementia: A Longitudinal Study. Front Neurol 2021; 12:695696. [PMID: 34557143 PMCID: PMC8452983 DOI: 10.3389/fneur.2021.695696] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Accepted: 07/09/2021] [Indexed: 11/30/2022] Open
Abstract
Background: Plasma-based biomarkers would be potential biomarkers for early diagnosis of Alzheimer's disease (AD) because they are more available and cost-effective than cerebrospinal fluid (CSF) or neuroimaging. Therefore, we aimed to evaluate whether phosphorylated tau181 (p-tau181) in plasma could be an accurate AD predictor. Methods: Participants from the ADNI database included 185 cognitively unimpaired subjects with negative Aβ (CU–), 66 subjects with pre-clinical AD (CU with positive Aβ), 164 subjects with mild cognitive impairment with negative Aβ (MCI–), 254 subjects with prodromal AD (MCI with positive Aβ), and 98 subjects with dementia. Multiple linear regression models, linear mixed-effects models, and local regression were used to explore cross-sectional and longitudinal associations of plasma p-tau181 with cognition, neuroimaging, or CSF biomarkers adjusted for age, sex, education, and APOE genotype. Besides, Kaplan–Meier and adjusted Cox-regression model were performed to predict the risk of progression to dementia. Receiver operating characteristic analyses were performed to evaluate the predictive value of p-tau181. Results: Plasma p-tau181 level was highest in AD dementia, followed by prodromal AD and pre-clinical AD. In pre-clinical AD, plasma p-tau181 was negatively associated with hippocampal volume (β = −0.031, p-value = 0.017). In prodromal AD, plasma p-tau181 was associated with decreased global cognition, executive function, memory, language, and visuospatial functioning (β range −0.119 to −0.273, p-value < 0.05) and correlated with hippocampal volume (β = −0.028, p-value < 0.005) and white matter hyperintensity volume (WMH) volume (β = 0.02, p-value = 0.01). In AD dementia, increased plasma p-tau181 was associated with worse memory. In the whole group, baseline plasma p-tau181 was significantly associated with longitudinal increases in multiple neuropsychological test z-scores and correlated with AD-related CSF biomarkers and hippocampal volume (p-value < 0.05). Meanwhile, CU or MCI with high plasma p-tau181 carried a higher risk of progression to dementia. The area under the curve (AUC) of the adjusted model (age, sex, education, APOE genotype, and plasma p-tau181) was 0.78; that of additionally included CSF biomarkers was 0.84. Conclusions: Plasma p-tau181 level is related to multiple AD-associated cognitive domains and AD-related CSF biomarkers at the clinical stages of AD. Moreover, plasma p-tau181 level is related to the change rates of cognitive decline and hippocampal atrophy. Thus, this study confirms the utility of plasma p-tau181 as a non-invasive biomarker for early detection and prediction of AD.
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Affiliation(s)
- Yan-Li Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jinglong Chen
- Department of Geriatric Medicine, China National Clinical Key Specialty, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Zhong-Li Du
- National Center for Clinical Laboratories, Beijing Hospital, National Center of Gerontology, Beijing, China.,Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Haoyi Weng
- Shenzhen WeGene Clinical Laboratory, Shenzhen, China.,WeGene, Shenzhen Zaozhidao Technology Co. Ltd., Shenzhen, China.,Hunan Provincial Key Lab on Bioinformatics, School of Science and Engineering, Central South University, Shenzhen, China
| | - Yuan Zhang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Runzhi Li
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Ziyan Jia
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Mengfan Sun
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jiwei Jiang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Fang-Ze Wang
- Department of Cardiology, Weifang People's Hospital, Weifang, China
| | - Jun Xu
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
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Lord J, Zettergren A, Ashton NJ, Karikari TK, Benedet AL, Simrén J, Hye A, Aarsland D, Blennow K, Zetterberg H, Proitsi P. A genome-wide association study of plasma phosphorylated tau181. Neurobiol Aging 2021; 106:304.e1-304.e3. [PMID: 34119372 DOI: 10.1016/j.neurobiolaging.2021.04.018] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Accepted: 04/21/2021] [Indexed: 11/18/2022]
Abstract
Plasma phosphorylated tau at threonine-181 (P-tau181) demonstrates promise as an accessible blood-based biomarker specific to Alzheimer's Disease (AD), with levels recently demonstrating high predictive accuracy for AD-relevant pathology. The genetic underpinnings of P-tau181 levels, however, remain elusive. This study presents the first genome-wide association study of plasma P-tau181 in a total sample of 1153 participants from 2 independent cohorts. No loci, other than those within the APOE genomic region (lead variant = rs429358, beta = 0.32, p =8.44 × 10-25) demonstrated association with P-tau181 at genome-wide significance (p < 5 × 10-08), though rs60872856 on chromosome 2 came close (beta = -0.28, p = 3.23 × 10-07, nearest gene=CYTIP). As the APOE ε4 allele is already a well-established genetic variant associated with AD, this study found no evidence of novel genetic associations relevant to plasma P-tau181, though presents rs60872856 on chromosome 2 as a candidate locus to be further evaluated in future larger size GWAS.
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Affiliation(s)
- Jodie Lord
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Anna Zettergren
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden; Department of Old Age Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London & Maudsley NHS Foundation, London, UK
| | - Thomas K Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Andrea L Benedet
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Joel Simrén
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Abdul Hye
- Department of Old Age Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London & Maudsley NHS Foundation, London, UK; Centre for Age Related Research, Stavanger University Hospital, Stavanger, Norway
| | - Dag Aarsland
- Department of Old Age Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK; Centre for Age Related Research, Stavanger University Hospital, Stavanger, Norway
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK; UK Dementia Research Institute at UCL, London, UK.
| | - Petroula Proitsi
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
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Ding X, Zhang S, Jiang L, Wang L, Li T, Lei P. Ultrasensitive assays for detection of plasma tau and phosphorylated tau 181 in Alzheimer's disease: a systematic review and meta-analysis. Transl Neurodegener 2021; 10:10. [PMID: 33712071 PMCID: PMC7953695 DOI: 10.1186/s40035-021-00234-5] [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: 12/08/2020] [Accepted: 02/24/2021] [Indexed: 02/08/2023] Open
Abstract
A lack of convenient and reliable biomarkers for diagnosis and prognosis is a common challenge for neurodegenerative diseases such as Alzheimer's disease (AD). Recent advancement in ultrasensitive protein assays has allowed the quantification of tau and phosphorylated tau proteins in peripheral plasma. Here we identified 66 eligible studies reporting quantification of plasma tau and phosphorylated tau 181 (ptau181) using four ultrasensitive methods. Meta-analysis of these studies confirmed that the AD patients had significantly higher plasma tau and ptau181 levels compared with controls, and that the plasma tau and ptau181 could predict AD with high-accuracy area under curve of the Receiver Operating Characteristic. Therefore, plasma tau and plasma ptau181 can be considered as biomarkers for AD diagnosis.
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Affiliation(s)
- Xulong Ding
- Department of Neurology and State Key Laboratory of Biotherapy/Collaborative Innovation Center for Biotherapy, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Shuting Zhang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Lijun Jiang
- Mental Health Center and West China Brain Research Center, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Lu Wang
- Department of Rehabilitation Medicine, West China Hospital, Sichuan University, Chengdu, 610041, China
| | - Tao Li
- Mental Health Center and West China Brain Research Center, West China Hospital, Sichuan University, Chengdu, 610041, China.
| | - Peng Lei
- Department of Neurology and State Key Laboratory of Biotherapy/Collaborative Innovation Center for Biotherapy, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, 610041, China.
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25
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Handy A, Lord J, Green R, Xu J, Aarsland D, Velayudhan L, Hye A, Dobson R, Proitsi P. Assessing Genetic Overlap and Causality Between Blood Plasma Proteins and Alzheimer's Disease. J Alzheimers Dis 2021; 83:1825-1839. [PMID: 34459398 PMCID: PMC8609677 DOI: 10.3233/jad-210462] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/30/2021] [Indexed: 12/21/2022]
Abstract
BACKGROUND Blood plasma proteins have been associated with Alzheimer's disease (AD), but understanding which proteins are on the causal pathway remains challenging. OBJECTIVE Investigate the genetic overlap between candidate proteins and AD using polygenic risk scores (PRS) and interrogate their causal relationship using bi-directional Mendelian randomization (MR). METHODS Following a literature review, 31 proteins were selected for PRS analysis. PRS were constructed for prioritized proteins with and without the apolipoprotein E region (APOE+/-PRS) and tested for association with AD status across three cohorts (n = 6,244). An AD PRS was also tested for association with protein levels in one cohort (n = 410). Proteins showing association with AD were taken forward for MR. RESULTS For APOE ɛ3, apolipoprotein B-100, and C-reactive protein (CRP), protein APOE+ PRS were associated with AD below Bonferroni significance (pBonf, p < 0.00017). No protein APOE- PRS or AD PRS (APOE+/-) passed pBonf. However, vitamin D-binding protein (protein PRS APOE-, p = 0.009) and insulin-like growth factor-binding protein 2 (AD APOE- PRS p = 0.025, protein APOE- PRS p = 0.045) displayed suggestive signals and were selected for MR. In bi-directional MR, none of the five proteins demonstrated a causal association (p < 0.05) in either direction. CONCLUSION Apolipoproteins and CRP PRS are associated with AD and provide a genetic signal linked to a specific, accessible risk factor. While evidence of causality was limited, this study was conducted in a moderate sample size and provides a framework for larger samples with greater statistical power.
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Affiliation(s)
- Alex Handy
- University College London, Institute of Health Informatics, London, UK
- King’s College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK
| | - Jodie Lord
- King’s College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK
| | - Rebecca Green
- King’s College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK
- NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - Jin Xu
- King’s College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK
- Institute of Pharmaceutical Science, King’s College London, UK
| | - Dag Aarsland
- King’s College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK
- Center for Age-Related Medicine, Stavanger University Hospital, Norway
| | - Latha Velayudhan
- King’s College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK
| | - Abdul Hye
- King’s College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK
| | - Richard Dobson
- University College London, Institute of Health Informatics, London, UK
- King’s College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK
- NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
- Health Data Research UK London, University College London, London, UK
- NIHR Biomedical Research Centre at University College London Hospitals NHS Foundation Trust, London, UK
| | - Petroula Proitsi
- King’s College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK
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