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Sampatakakis SN, Mourtzi N, Hatzimanolis A, Koutsis G, Charisis S, Gkelmpesi I, Mamalaki E, Ntanasi E, Ramirez A, Yannakoulia M, Kosmidis MH, Dardiotis E, Hadjigeorgiou G, Sakka P, Scarmeas N. Genetic Prοpensity for Different Aspects of Dementia Pathology and Cognitive Decline in a Community Elderly Population. Int J Mol Sci 2025; 26:910. [PMID: 39940679 PMCID: PMC11817854 DOI: 10.3390/ijms26030910] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2024] [Revised: 01/15/2025] [Accepted: 01/18/2025] [Indexed: 02/16/2025] Open
Abstract
In the present study, we investigated the association of genetic predisposition with specific dimensions of dementia pathophysiology for global and domain-specific cognitive decline in older adults. The sample was drawn from the Hellenic Longitudinal Investigation of Aging and Diet (HELIAD) study, comprising 512 cognitively normal individuals over 64 years of age, with a mean follow-up of 2.9 years. Cognitive function was evaluated through a neuropsychological test battery, while genetic predisposition was assessed based on two distinct Polygenic Risk Scores (PRS) for amyloid-beta 42 (Aβ42) and white matter hyperintensities (WMH). The association of each PRS with the cognitive decline rate was examined using generalized estimating equation models. In the whole sample, higher PRSs Aβ42 (β = -0.042) and WMH (β =-0.029) were associated with a higher rate of global cognitive decline per year, an association which remained significant in age, sex, and education subgroups. Moreover, higher PRSs Aβ42 and WMH were related to significant memory decline only in females, older, and highly educated participants. Thus, while the association of both PRSs with global cognitive decline over time was independent of age, sex, or education, the relationship of the specific PRSs with the memory decline rate appeared to vary depending on these factors.
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Affiliation(s)
- Stefanos N. Sampatakakis
- 1st Department of Neurology, Aiginition Hospital, Athens Medical School, National and Kapodistrian University, 11528 Athens, Greece; (S.N.S.); (N.M.); (I.G.); (E.M.); (E.N.)
| | - Niki Mourtzi
- 1st Department of Neurology, Aiginition Hospital, Athens Medical School, National and Kapodistrian University, 11528 Athens, Greece; (S.N.S.); (N.M.); (I.G.); (E.M.); (E.N.)
| | - Alex Hatzimanolis
- Department of Psychiatry, Aiginition Hospital, Athens Medical School, National and Kapodistrian University, 11528 Athens, Greece;
| | - Georgios Koutsis
- Neurogenetics Unit, 1st Department of Neurology, Aiginition Hospital, Athens Medical School, National and Kapodistrian University, 11528 Athens, Greece;
| | - Sokratis Charisis
- Department of Neurology, UT Health San Antonio, San Antonio, TX 78229, USA;
| | - Iliana Gkelmpesi
- 1st Department of Neurology, Aiginition Hospital, Athens Medical School, National and Kapodistrian University, 11528 Athens, Greece; (S.N.S.); (N.M.); (I.G.); (E.M.); (E.N.)
| | - Eirini Mamalaki
- 1st Department of Neurology, Aiginition Hospital, Athens Medical School, National and Kapodistrian University, 11528 Athens, Greece; (S.N.S.); (N.M.); (I.G.); (E.M.); (E.N.)
| | - Eva Ntanasi
- 1st Department of Neurology, Aiginition Hospital, Athens Medical School, National and Kapodistrian University, 11528 Athens, Greece; (S.N.S.); (N.M.); (I.G.); (E.M.); (E.N.)
| | - Alfredo Ramirez
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Medical Faculty, University of Cologne, 50923 Cologne, Germany;
- Department of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, 53127 Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE Bonn), 53127 Bonn, Germany
- Department of Psychiatry, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, San Antonio, TX 78229, USA
- Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, 50923 Cologne, Germany
| | - Mary Yannakoulia
- Department of Nutrition and Dietetics, Harokopio University, 17676 Athens, Greece;
| | - Mary H. Kosmidis
- Laboratory of Neuropsychology and Behavioral Neuroscience, School of Psychology, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece;
| | - Efthimios Dardiotis
- Department of Neurology, University Hospital of Larissa, Faculty of Medicine, School of Health Sciences, University of Thessaly, 41334 Larissa, Greece;
| | | | - Paraskevi Sakka
- Athens Association of Alzheimer’s Disease and Related Disorders, 11636 Marousi, Greece;
| | - Nikolaos Scarmeas
- 1st Department of Neurology, Aiginition Hospital, Athens Medical School, National and Kapodistrian University, 11528 Athens, Greece; (S.N.S.); (N.M.); (I.G.); (E.M.); (E.N.)
- Department of Neurology, The Gertrude H. Sergievsky Center, Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, Columbia University, New York, NY 10027, USA
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Roe JM, Vidal-Piñeiro D, Sørensen Ø, Grydeland H, Leonardsen EH, Iakunchykova O, Pan M, Mowinckel A, Strømstad M, Nawijn L, Milaneschi Y, Andersson M, Pudas S, Bråthen ACS, Kransberg J, Falch ES, Øverbye K, Kievit RA, Ebmeier KP, Lindenberger U, Ghisletta P, Demnitz N, Boraxbekk CJ, Drevon CA, Penninx B, Bertram L, Nyberg L, Walhovd KB, Fjell AM, Wang Y. Brain change trajectories in healthy adults correlate with Alzheimer's related genetic variation and memory decline across life. Nat Commun 2024; 15:10651. [PMID: 39690174 DOI: 10.1038/s41467-024-53548-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 10/16/2024] [Indexed: 12/19/2024] Open
Abstract
Throughout adulthood and ageing our brains undergo structural loss in an average pattern resembling faster atrophy in Alzheimer's disease (AD). Using a longitudinal adult lifespan sample (aged 30-89; 2-7 timepoints) and four polygenic scores for AD, we show that change in AD-sensitive brain features correlates with genetic AD-risk and memory decline in healthy adults. We first show genetic risk links with more brain loss than expected for age in early Braak regions, and find this extends beyond APOE genotype. Next, we run machine learning on AD-control data from the Alzheimer's Disease Neuroimaging Initiative using brain change trajectories conditioned on age, to identify AD-sensitive features and model their change in healthy adults. Genetic AD-risk linked with multivariate change across many AD-sensitive features, and we show most individuals over age ~50 are on an accelerated trajectory of brain loss in AD-sensitive regions. Finally, high genetic risk adults with elevated brain change showed more memory decline through adulthood, compared to high genetic risk adults with less brain change. Our findings suggest quantitative AD risk factors are detectable in healthy individuals, via a shared pattern of ageing- and AD-related neurodegeneration that occurs along a continuum and tracks memory decline through adulthood.
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Affiliation(s)
- James M Roe
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Oslo, Norway.
| | - Didac Vidal-Piñeiro
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Oslo, Norway
| | - Øystein Sørensen
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Oslo, Norway
| | - Håkon Grydeland
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Oslo, Norway
| | - Esten H Leonardsen
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Oslo, Norway
- Norwegian Centre for Mental Disorders Research (NORMENT), Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Olena Iakunchykova
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Oslo, Norway
| | - Mengyu Pan
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Oslo, Norway
- Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
| | - Athanasia Mowinckel
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Oslo, Norway
| | - Marie Strømstad
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Oslo, Norway
| | - Laura Nawijn
- Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Psychiatry and Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Yuri Milaneschi
- Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Psychiatry and Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Micael Andersson
- Department of Medical and Translational Biology, Umeå University, Umeå, Sweden
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå, Sweden
| | - Sara Pudas
- Department of Medical and Translational Biology, Umeå University, Umeå, Sweden
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå, Sweden
| | - Anne Cecilie Sjøli Bråthen
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Oslo, Norway
| | - Jonas Kransberg
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Oslo, Norway
| | - Emilie Sogn Falch
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Oslo, Norway
| | - Knut Øverbye
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Oslo, Norway
| | - Rogier A Kievit
- Cognitive Neuroscience Department, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Klaus P Ebmeier
- Department of Psychiatry and Wellcome Centre for Integrative Neuroimaging, University of Oxford, Warneford Hospital, Oxford, United Kingdom
| | - Ulman Lindenberger
- Center for Lifespan Psychology, Max Planck Institute for Human Development, Berlin, Germany
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, Berlin, Germany
| | - Paolo Ghisletta
- Faculty of Psychology and Educational Sciences, University of Geneva, Geneva, Switzerland
| | - Naiara Demnitz
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark
| | - Carl-Johan Boraxbekk
- Institute for Clinical Medicine, Faculty of Medical and Health Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Radiation Sciences, Diagnostic Radiology, and Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå, Sweden
- Institute of Sports Medicine Copenhagen (ISMC) and Department of Neurology, Copenhagen University Hospital Bispebjerg, Copenhagen, Denmark
| | - Christian A Drevon
- Department of Nutrition, Institute of Basic Medical Science, Faculty of Medicine, University of Oslo, Oslo, Norway
- Vitas Ltd, Oslo Science Park, Oslo, Norway
| | - Brenda Penninx
- Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Psychiatry and Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Lübeck, Germany
| | - Lars Nyberg
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Oslo, Norway
- Department of Medical and Translational Biology, Umeå University, Umeå, Sweden
- Umeå Center for Functional Brain Imaging (UFBI), Umeå University, Umeå, Sweden
- Department of Diagnostics and Intervention, Umeå University, Umeå, Sweden
- Department of Health, Education and Technology, Luleå University of Technology, Luleå, Sweden
| | - Kristine B Walhovd
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Oslo, Norway
- Computational Radiology and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Anders M Fjell
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Oslo, Norway
- Computational Radiology and Artificial Intelligence, Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Yunpeng Wang
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of Psychology, University of Oslo, Oslo, Norway
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Shin SH, Walker SL, Ji H, Lee HY. Performance Under Fire: Older Adult Cognitive Risks and Protections Under Heat Strain. THE GERONTOLOGIST 2024; 64:gnae116. [PMID: 39166357 PMCID: PMC11467403 DOI: 10.1093/geront/gnae116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2024] [Indexed: 08/22/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Although extreme heat events disproportionately affect older adults and the importance of cognition is known, research examining older adult cognition under heat stress is limited. This study examines the relationship between risk/protective factors and heat strain on older adult cognition, employing a social-ecological model. RESEARCH DESIGN AND METHODS Retrieved from the 1996-2016 waves of the Health and Retirement Study, our study used older adults aged 50 and older and their spouses residing in the United States. Individual-fixed effects models estimated changes in cognition as measured by fluid and crystallized intelligence scores in response to extreme heat days. This study further estimated interactions of extreme heat with protective/risk factors for cognition (i.e., education, physical activity, social engagement, and genetic risk for Alzheimer's disease). RESULTS Our results demonstrated that extreme heat days were associated with fluid but not crystallized intelligence scores. Educational attainment, mild physical activity, and social contacts with children moderated this relationship. Furthermore, Alzheimer's disease polygenic scores moderated the correlation between extreme heat days and crystallized intelligence scores. DISCUSSION AND IMPLICATIONS An increasing frequency of extreme heat events and an aging population globally highlight the need for policies and interventions building resiliency in older adults. Actions promoting the protective modifiable behaviors to older adult cognition identified by our study can lead to healthier individuals and communities.
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Affiliation(s)
- Su Hyun Shin
- Department of Family and Consumer Studies, University of Utah, Salt Lake City, Utah, USA
| | - Susan Lee Walker
- Department of Family and Consumer Studies, University of Utah, Salt Lake City, Utah, USA
| | - Hyunjung Ji
- Department of Political Science, The University of Alabama, Tuscaloosa, Alabama, USA
| | - Hee Yun Lee
- School of Social Work, The University of Alabama, Tuscaloosa, Alabama, USA
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Soldan A, Wang J, Pettigrew C, Davatzikos C, Erus G, Hohman TJ, Dumitrescu L, Bilgel M, Resnick SM, Rivera-Rivera LA, Langhough R, Johnson SC, Benzinger T, Morris JC, Laws SM, Fripp J, Masters CL, Albert MS. Alzheimer's disease genetic risk and changes in brain atrophy and white matter hyperintensities in cognitively unimpaired adults. Brain Commun 2024; 6:fcae276. [PMID: 39229494 PMCID: PMC11369827 DOI: 10.1093/braincomms/fcae276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 06/25/2024] [Accepted: 08/12/2024] [Indexed: 09/05/2024] Open
Abstract
Reduced brain volumes and more prominent white matter hyperintensities on MRI scans are commonly observed among older adults without cognitive impairment. However, it remains unclear whether rates of change in these measures among cognitively normal adults differ as a function of genetic risk for late-onset Alzheimer's disease, including APOE-ɛ4, APOE-ɛ2 and Alzheimer's disease polygenic risk scores (AD-PRS), and whether these relationships are influenced by other variables. This longitudinal study examined the trajectories of regional brain volumes and white matter hyperintensities in relationship to APOE genotypes (N = 1541) and AD-PRS (N = 1093) in a harmonized dataset of middle-aged and older individuals with normal cognition at baseline (mean baseline age = 66 years, SD = 9.6) and an average of 5.3 years of MRI follow-up (max = 24 years). Atrophy on volumetric MRI scans was quantified in three ways: (i) a composite score of regions vulnerable to Alzheimer's disease (SPARE-AD); (ii) hippocampal volume; and (iii) a composite score of regions indexing advanced non-Alzheimer's disease-related brain aging (SPARE-BA). Global white matter hyperintensity volumes were derived from fluid attenuated inversion recovery (FLAIR) MRI. Using linear mixed effects models, there was an APOE-ɛ4 gene-dose effect on atrophy in the SPARE-AD composite and hippocampus, with greatest atrophy among ɛ4/ɛ4 carriers, followed by ɛ4 heterozygouts, and lowest among ɛ3 homozygouts and ɛ2/ɛ2 and ɛ2/ɛ3 carriers, who did not differ from one another. The negative associations of APOE-ɛ4 with atrophy were reduced among those with higher education (P < 0.04) and younger baseline ages (P < 0.03). Higher AD-PRS were also associated with greater atrophy in SPARE-AD (P = 0.035) and the hippocampus (P = 0.014), independent of APOE-ɛ4 status. APOE-ɛ2 status (ɛ2/ɛ2 and ɛ2/ɛ3 combined) was not related to baseline levels or atrophy in SPARE-AD, SPARE-BA or the hippocampus, but was related to greater increases in white matter hyperintensities (P = 0.014). Additionally, there was an APOE-ɛ4 × AD-PRS interaction in relation to white matter hyperintensities (P = 0.038), with greater increases in white matter hyperintensities among APOE-ɛ4 carriers with higher AD-PRS. APOE and AD-PRS associations with MRI measures did not differ by sex. These results suggest that APOE-ɛ4 and AD-PRS independently and additively influence longitudinal declines in brain volumes sensitive to Alzheimer's disease and synergistically increase white matter hyperintensity accumulation among cognitively normal individuals. Conversely, APOE-ɛ2 primarily influences white matter hyperintensity accumulation, not brain atrophy. Results are consistent with the view that genetic factors for Alzheimer's disease influence atrophy in a regionally specific manner, likely reflecting preclinical neurodegeneration, and that Alzheimer's disease risk genes contribute to white matter hyperintensity formation.
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Affiliation(s)
- Anja Soldan
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Jiangxia Wang
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Corinne Pettigrew
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Christos Davatzikos
- Centre for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Guray Erus
- Centre for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Timothy J Hohman
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Logan Dumitrescu
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Murat Bilgel
- Laboratory of Behavioral Neuroscience, National Institute on Aging Intramural Research Program, Baltimore, MD 21224, USA
| | - Susan M Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging Intramural Research Program, Baltimore, MD 21224, USA
| | - Leonardo A Rivera-Rivera
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53726, USA
| | - Rebecca Langhough
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53726, USA
| | - Sterling C Johnson
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53726, USA
| | - Tammie Benzinger
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - John C Morris
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Simon M Laws
- Centre for Precision Health, Edith Cowan University, Joondalup, WA 6027, Australia
| | - Jurgen Fripp
- Australian E-Health Research Centre, CSIRO Health & Biosecurity, Herston, QLD 4029, Australia
| | - Colin L Masters
- The Florey Institute, University of Melbourne, Parkville, VIC 3052, Australia
| | - Marilyn S Albert
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
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5
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Altmann A, Aksman LM, Oxtoby NP, Young AL, Alexander DC, Barkhof F, Shoai M, Hardy J, Schott JM. Towards cascading genetic risk in Alzheimer's disease. Brain 2024; 147:2680-2690. [PMID: 38820112 PMCID: PMC11292901 DOI: 10.1093/brain/awae176] [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: 12/21/2023] [Revised: 04/22/2024] [Accepted: 05/06/2024] [Indexed: 06/02/2024] Open
Abstract
Alzheimer's disease typically progresses in stages, which have been defined by the presence of disease-specific biomarkers: amyloid (A), tau (T) and neurodegeneration (N). This progression of biomarkers has been condensed into the ATN framework, in which each of the biomarkers can be either positive (+) or negative (-). Over the past decades, genome-wide association studies have implicated ∼90 different loci involved with the development of late-onset Alzheimer's disease. Here, we investigate whether genetic risk for Alzheimer's disease contributes equally to the progression in different disease stages or whether it exhibits a stage-dependent effect. Amyloid (A) and tau (T) status was defined using a combination of available PET and CSF biomarkers in the Alzheimer's Disease Neuroimaging Initiative cohort. In 312 participants with biomarker-confirmed A-T- status, we used Cox proportional hazards models to estimate the contribution of APOE and polygenic risk scores (beyond APOE) to convert to A+T- status (65 conversions). Furthermore, we repeated the analysis in 290 participants with A+T- status and investigated the genetic contribution to conversion to A+T+ (45 conversions). Both survival analyses were adjusted for age, sex and years of education. For progression from A-T- to A+T-, APOE-e4 burden showed a significant effect [hazard ratio (HR) = 2.88; 95% confidence interval (CI): 1.70-4.89; P < 0.001], whereas polygenic risk did not (HR = 1.09; 95% CI: 0.84-1.42; P = 0.53). Conversely, for the transition from A+T- to A+T+, the contribution of APOE-e4 burden was reduced (HR = 1.62; 95% CI: 1.05-2.51; P = 0.031), whereas the polygenic risk showed an increased contribution (HR = 1.73; 95% CI: 1.27-2.36; P < 0.001). The marginal APOE effect was driven by e4 homozygotes (HR = 2.58; 95% CI: 1.05-6.35; P = 0.039) as opposed to e4 heterozygotes (HR = 1.74; 95% CI: 0.87-3.49; P = 0.12). The genetic risk for late-onset Alzheimer's disease unfolds in a disease stage-dependent fashion. A better understanding of the interplay between disease stage and genetic risk can lead to a more mechanistic understanding of the transition between ATN stages and a better understanding of the molecular processes leading to Alzheimer's disease, in addition to opening therapeutic windows for targeted interventions.
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Affiliation(s)
- Andre Altmann
- UCL Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, WC1E 6BT, UK
| | - Leon M Aksman
- Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Neil P Oxtoby
- UCL Centre for Medical Image Computing, Department of Computer Science, University College London, London, WC1E 6BT, UK
| | - Alexandra L Young
- UCL Centre for Medical Image Computing, Department of Computer Science, University College London, London, WC1E 6BT, UK
| | - Daniel C Alexander
- UCL Centre for Medical Image Computing, Department of Computer Science, University College London, London, WC1E 6BT, UK
| | - Frederik Barkhof
- UCL Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, WC1E 6BT, UK
- UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam, 1081 HV, The Netherlands
| | - Maryam Shoai
- UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
- UK Dementia Research Institute, University College London, London, WC1E 6BT, UK
| | - John Hardy
- UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
- UK Dementia Research Institute, University College London, London, WC1E 6BT, UK
| | - Jonathan M Schott
- UK Dementia Research Institute, University College London, London, WC1E 6BT, UK
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
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Saadmaan G, Dalmasso MC, Ramirez A, Hiltunen M, Kemppainen N, Lehtisalo J, Mangialasche F, Ngandu T, Rinne J, Soininen H, Stephen R, Kivipelto M, Solomon A. Alzheimer's disease genetic risk score and neuroimaging in the FINGER lifestyle trial. Alzheimers Dement 2024; 20:4345-4350. [PMID: 38647197 PMCID: PMC11180864 DOI: 10.1002/alz.13843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Revised: 03/20/2024] [Accepted: 03/21/2024] [Indexed: 04/25/2024]
Abstract
INTRODUCTION We assessed a genetic risk score for Alzheimer's disease (AD-GRS) and apolipoprotein E (APOE4) in an exploratory neuroimaging substudy of the FINGER trial. METHODS 1260 at-risk older individuals without dementia were randomized to multidomain lifestyle intervention or health advice. N = 126 participants underwent magnetic resonance imaging (MRI), and N = 47 positron emission tomography (PET) scans (Pittsburgh Compund B [PiB], Fluorodeoxyglucose) at baseline; N = 107 and N = 38 had repeated 2-year scans. RESULTS The APOE4 allele, but not AD-GRS, was associated with baseline lower hippocampus volume (β = -0.27, p = 0.001), greater amyloid deposition (β = 0.48, p = 0.001), 2-year decline in hippocampus (β = -0.27, p = 0.01), total gray matter volume (β = -0.25, p = 0.01), and cortical thickness (β = -0.28, p = 0.003). In analyses stratified by AD-GRS (below vs above median), the PiB composite score increased less in intervention versus control in the higher AD-GRS group (β = -0.60, p = 0.03). DISCUSSION AD-GRS and APOE4 may have different impacts on potential intervention effects on amyloid, that is, less accumulation in the higher-risk group (AD-GRS) versus lower-risk group (APOE). HIGHLIGHTS First study of neuroimaging and AD genetics in a multidomain lifestyle intervention. Possible intervention effect on brain amyloid deposition may rely on genetic risk. AD-GRS and APOE4 allele may have different impacts on amyloid during intervention.
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Affiliation(s)
- Gazi Saadmaan
- Department of NeurologyInstitute of Clinical MedicineUniversity of Eastern FinlandKuopioFinland
| | - Maria Carolina Dalmasso
- Studies in Neuroscience and Complex Systems Unit (ENyS)CONICET‐HEC‐UNAJFlorencio VarelaArgentina
- Division of Neurogenetics and Molecular PsychiatryDepartment of Psychiatry and PsychotherapyUniversity of CologneMedical FacultyCologneGermany
| | - Alfredo Ramirez
- Division of Neurogenetics and Molecular PsychiatryDepartment of Psychiatry and PsychotherapyUniversity of CologneMedical FacultyCologneGermany
- Department of Neurodegenerative Diseases and Geriatric PsychiatryUniversity Hospital BonnBonnGermany
- German Center for Neurodegenerative DiseasesDZNE BonnBonnGermany
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health Sciences CenterSan AntonioTexasUSA
- Excellence Cluster on Cellular Stress Responses in Aging‐Associated Diseases (CECAD)University of CologneCologneGermany
| | - Mikko Hiltunen
- Institute of BiomedicineUniversity of Eastern FinlandKuopioFinland
| | - Nina Kemppainen
- Turku PET CentreUniversity of TurkuTurkuFinland
- Division of Clinical NeurosciencesTurku University HospitalTurkuFinland
| | - Jenni Lehtisalo
- Department of NeurologyInstitute of Clinical MedicineUniversity of Eastern FinlandKuopioFinland
- Population Health UnitFinnish Institute for Health and WelfareHelsinkiFinland
| | - Francesca Mangialasche
- Division of Clinical GeriatricsCenter for Alzheimer ResearchDepartment of NeurobiologyCare Sciences and SocietyKarolinska InstitutetStockholmSweden
| | - Tiia Ngandu
- Population Health UnitFinnish Institute for Health and WelfareHelsinkiFinland
- Division of Clinical GeriatricsCenter for Alzheimer ResearchDepartment of NeurobiologyCare Sciences and SocietyKarolinska InstitutetStockholmSweden
| | - Juha Rinne
- Turku PET CentreUniversity of TurkuTurkuFinland
- Division of Clinical NeurosciencesTurku University HospitalTurkuFinland
| | - Hilkka Soininen
- Department of NeurologyInstitute of Clinical MedicineUniversity of Eastern FinlandKuopioFinland
| | - Ruth Stephen
- Department of NeurologyInstitute of Clinical MedicineUniversity of Eastern FinlandKuopioFinland
| | - Miia Kivipelto
- Department of NeurologyInstitute of Clinical MedicineUniversity of Eastern FinlandKuopioFinland
- Division of Clinical GeriatricsCenter for Alzheimer ResearchDepartment of NeurobiologyCare Sciences and SocietyKarolinska InstitutetStockholmSweden
- Institute of Public Health and Clinical NutritionUniversity of Eastern FinlandKuopioFinland
- Ageing Epidemiology Research UnitSchool of Public Health, Imperial College LondonLondonUK
| | - Alina Solomon
- Department of NeurologyInstitute of Clinical MedicineUniversity of Eastern FinlandKuopioFinland
- Division of Clinical GeriatricsCenter for Alzheimer ResearchDepartment of NeurobiologyCare Sciences and SocietyKarolinska InstitutetStockholmSweden
- Ageing Epidemiology Research UnitSchool of Public Health, Imperial College LondonLondonUK
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Korologou-Linden R, Xu B, Coulthard E, Walton E, Wearn A, Hemani G, White T, Cecil C, Sharp T, Tiemeier H, Banaschewski T, Bokde A, Desrivières S, Flor H, Grigis A, Garavan H, Gowland P, Heinz A, Brühl R, Martinot JL, Paillère Martinot ML, Artiges E, Nees F, Orfanos DP, Paus T, Poustka L, Millenet S, Fröhner JH, Smolka M, Walter H, Winterer J, Whelan R, Schumann G, Howe LD, Ben-Shlomo Y, Davies NM, Anderson EL. Genetics impact risk of Alzheimer's disease through mechanisms modulating structural brain morphology in late life. J Neurol Neurosurg Psychiatry 2024:jnnp-2023-332969. [PMID: 38663994 PMCID: PMC7616849 DOI: 10.1136/jnnp-2023-332969] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 03/11/2024] [Indexed: 11/27/2024]
Abstract
BACKGROUND Alzheimer's disease (AD)-related neuropathological changes can occur decades before clinical symptoms. We aimed to investigate whether neurodevelopment and/or neurodegeneration affects the risk of AD, through reducing structural brain reserve and/or increasing brain atrophy, respectively. METHODS We used bidirectional two-sample Mendelian randomisation to estimate the effects between genetic liability to AD and global and regional cortical thickness, estimated total intracranial volume, volume of subcortical structures and total white matter in 37 680 participants aged 8-81 years across 5 independent cohorts (Adolescent Brain Cognitive Development, Generation R, IMAGEN, Avon Longitudinal Study of Parents and Children and UK Biobank). We also examined the effects of global and regional cortical thickness and subcortical volumes from the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium on AD risk in up to 37 741 participants. RESULTS Our findings show that AD risk alleles have an age-dependent effect on a range of cortical and subcortical brain measures that starts in mid-life, in non-clinical populations. Evidence for such effects across childhood and young adulthood is weak. Some of the identified structures are not typically implicated in AD, such as those in the striatum (eg, thalamus), with consistent effects from childhood to late adulthood. There was little evidence to suggest brain morphology alters AD risk. CONCLUSIONS Genetic liability to AD is likely to affect risk of AD primarily through mechanisms affecting indicators of brain morphology in later life, rather than structural brain reserve. Future studies with repeated measures are required for a better understanding and certainty of the mechanisms at play.
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Affiliation(s)
- Roxanna Korologou-Linden
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, University of Bristol, Bristol, UK
| | - Bing Xu
- The Generation R Study Group, Erasmus MC University Medical Center, Rotterdam, UK
- Department of Child and Adolescent Psychiatry and Psychology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Elizabeth Coulthard
- Bristol Medical School, University of Bristol, Bristol, UK
- North Bristol NHS Trust, Bristol, UK
| | - Esther Walton
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Department of Psychology, University of Bath, Bath, UK
| | - Alfie Wearn
- Bristol Medical School, University of Bristol, Bristol, UK
| | - Gibran Hemani
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, University of Bristol, Bristol, UK
| | - Tonya White
- The Generation R Study Group, Erasmus MC University Medical Center, Rotterdam, UK
- Department of Radiology and Nuclear Medicine, Erasmus University School of Medicine, Rotterdam, UK
| | - Charlotte Cecil
- Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Tamsin Sharp
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Biostatistics and Health Informatics Department, King's College London, Boston, UK
| | - Henning Tiemeier
- Department of Child and Adolescent Psychiatry and Psychology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Social and Behavioral Sciences, Harvard T H Chan School of Public Health, Boston, Massachusetts, USA
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Heidelberg University, Heidelberg, Germany
| | - Arun Bokde
- Psychiatry, Trinity College Dublin, Dublin, Ireland
| | - Sylvane Desrivières
- Kings College London, Centre for Population Neuroscience and Precision Medicine (PONS), London, UK
| | - Herta Flor
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, University of Mannheim, Mannheim, Germany
- Psychology, School of Social Sciences, University of Mannheim, Mannheim, Germany
| | | | | | | | - Andreas Heinz
- Department of Psychiatry and Psychotherapy CCM, Berlin Institute of Health, Berlin, Germany
| | - Rüdiger Brühl
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig, Germany
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U1299, Paris, France
- Centre Borelli, Cachan, France
| | - Marie-Laure Paillère Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U1299, Paris, France
- Centre Borelli, Cachan, France
| | - Eric Artiges
- Institut National de la Santé et de la Recherche Médicale, INSERM U1299, Paris, France
- Centre Borelli, Cachan, France
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Heidelberg University, Heidelberg, Germany
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, University of Mannheim, Mannheim, Germany
- Institute of Medical Psychology and Medical Sociology, Kiel University, Kiel, Germany
| | | | - Tomáš Paus
- Departments of Psychology and Psychiatry, University of Toronto, Toronto, Ontario, Canada
- Department of Psychiatry, University of Montreal, Montreal, Quebec, Canada
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, Göttingen, Germany
| | - Sabina Millenet
- Department of Child and Adolescent Psychiatry and Psychotherapy, Heidelberg University, Heidelberg, Germany
| | - Juliane H Fröhner
- Department of Psychiatry, Technische Universität Dresden, Dresden, Germany
| | - Michael Smolka
- Department of Psychiatry, Technische Universität Dresden, Dresden, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy CCM, Charité Universitätsmedizin Berlin, Berlin, Germany
- Berlin Institute of Health at Charite, Berlin, Germany
| | - Jeanne Winterer
- Department of Psychiatry and Psychotherapy CCM, Berlin Institute of Health, Berlin, Germany
- Department of Education and Psychology, Freie Universität Berlin, Berlin, Germany
| | - Robert Whelan
- Trinity Centre for Bioengineering, Trinity College Dublin, Dublin, Ireland
| | - Gunter Schumann
- Kings College London, Centre for Population Neuroscience and Precision Medicine (PONS), London, UK
- Fudan University, Shanghai, People's Republic of China
- PONS Centre, Dept. of Psychiatry and Clinical Neuroscience, CCM, Berlin, Germany
| | - Laura D Howe
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, University of Bristol, Bristol, UK
| | - Yoav Ben-Shlomo
- Population Health Sciences, University of Bristol, Bristol, UK
| | - Neil M Davies
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, University of Bristol, Bristol, UK
- University College London Division of Psychiatry, London, UK
| | - Emma Louise Anderson
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, University of Bristol, Bristol, UK
- University College London Division of Psychiatry, London, UK
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Ogonowski NS, García-Marín LM, Fernando AS, Flores-Ocampo V, Rentería ME. Impact of genetic predisposition to late-onset neurodegenerative diseases on early life outcomes and brain structure. Transl Psychiatry 2024; 14:185. [PMID: 38605018 PMCID: PMC11009228 DOI: 10.1038/s41398-024-02898-9] [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: 04/29/2023] [Revised: 03/27/2024] [Accepted: 04/03/2024] [Indexed: 04/13/2024] Open
Abstract
Most patients with late-onset neurodegenerative diseases such as Alzheimer's and Parkinson's have a complex aetiology resulting from numerous genetic risk variants of small effects located across the genome, environmental factors, and the interaction between genes and environment. Over the last decade, genome-wide association studies (GWAS) and post-GWAS analyses have shed light on the polygenic architecture of these diseases, enabling polygenic risk scores (PRS) to estimate an individual's relative genetic liability for presenting with the disease. PRS can screen and stratify individuals based on their genetic risk, potentially years or even decades before the onset of clinical symptoms. An emerging body of evidence from various research studies suggests that genetic susceptibility to late-onset neurodegenerative diseases might impact early life outcomes, including cognitive function, brain structure and function, and behaviour. This article summarises recent findings exploring the potential impact of genetic susceptibility to neurodegenerative diseases on early life outcomes. A better understanding of the impact of genetic susceptibility to neurodegenerative diseases early in life could be valuable in disease screening, detection, and prevention and in informing treatment strategies before significant neural damage has occurred. However, ongoing studies have limitations. Overall, our review found several studies focused on APOE haplotypes and Alzheimer's risk, but a limited number of studies leveraging polygenic risk scores or focused on genetic susceptibility to other late-onset conditions.
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Affiliation(s)
- Natalia S Ogonowski
- Mental Health & Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Luis M García-Marín
- Mental Health & Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Amali S Fernando
- Mental Health & Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Victor Flores-Ocampo
- Mental Health & Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Miguel E Rentería
- Mental Health & Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia.
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9
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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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Kuhn HG, Skau S, Nyberg J. A lifetime perspective on risk factors for cognitive decline with a special focus on early events. CEREBRAL CIRCULATION - COGNITION AND BEHAVIOR 2024; 6:100217. [PMID: 39071743 PMCID: PMC11273094 DOI: 10.1016/j.cccb.2024.100217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 03/04/2024] [Accepted: 03/06/2024] [Indexed: 07/30/2024]
Abstract
Both Alzheimer's disease and vascular dementia are the result of disease processes that typically develop over several decades. Population studies have estimated that more than half of the risk for dementia is preventable or at least modifiable through behavioral adaptations. The association between these lifestyle factors and the risk of dementia is most evident for exposure in midlife. However, habits formed in middle age often reflect a lifetime of behavior patterns and living conditions. Therefore, individuals who, for example, are able to maintain healthy diets and regular exercise during their middle years are likely to benefit from these cognition-protective habits they have practiced throughout their lives. For numerous adult diseases, significant risks can often be traced back to early childhood. Suboptimal conditions during the perinatal period, childhood and adolescence can increase the risk of adult diseases, including stroke, heart disease, insulin resistance, hypertension and dementia. This review aims at summarizing some of the evidence for dementia risks from a life-time perspective with the goal of raising awareness for early dementia prevention and successful aging.
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Affiliation(s)
- H. Georg Kuhn
- Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden
| | - Simon Skau
- Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden
- Department of Pedagogical, Curricular and Professional Studies, University of Gothenburg, Gothenburg, Sweden
| | - Jenny Nyberg
- Department of Clinical Neuroscience, Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden
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11
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Buto PT, Wang J, La Joie R, Zimmerman SC, Glymour MM, Ackley SF, Hoffmann TJ, Yaffe K, Zeki Al Hazzouri A, Brenowitz WD. Genetic risk score for Alzheimer's disease predicts brain volume differences in mid and late life in UK biobank participants. Alzheimers Dement 2024; 20:1978-1987. [PMID: 38183377 PMCID: PMC10984491 DOI: 10.1002/alz.13610] [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: 03/03/2023] [Revised: 10/18/2023] [Accepted: 11/26/2023] [Indexed: 01/08/2024]
Abstract
INTRODUCTION We estimated the ages when associations between Alzheimer's disease (AD) genes and brain volumes begin among middle-aged and older adults. METHODS Among 45,616 dementia-free participants aged 45-80, linear regressions tested whether genetic risk score for AD (AD-GRS) had age-dependent associations with 38 regional brain magnetic resonance imaging volumes. Models were adjusted for sex, assessment center, genetic ancestry, and intracranial volume. RESULTS AD-GRS modified the estimated effect of age (per decade) on the amygdala (-0.41 mm3 [-0.42, -0.40]); hippocampus (-0.45 mm3 [-0.45, -0.44]), nucleus accumbens (-0.55 mm3 [-0.56, -0.54]), thalamus (-0.38 mm3 [-0.39, -0.37]), and medial orbitofrontal cortex (-0.23 mm3 [-0.24, -0.22]). Trends began by age 45 for the nucleus accumbens and thalamus, 48 for the hippocampus, 51 for the amygdala, and 53 for the medial orbitofrontal cortex. An AD-GRS excluding apolipoprotein E (APOE) was additionally associated with entorhinal and middle temporal cortices. DISCUSSION APOE and other genes that increase AD risk predict lower hippocampal and other brain volumes by middle age.
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Affiliation(s)
- Peter T. Buto
- Department of Epidemiology & BiostatisticsUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of EpidemiologyBoston University School of Public HealthBostonMassachusettsUSA
| | - Jingxuan Wang
- Department of Epidemiology & BiostatisticsUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of EpidemiologyBoston University School of Public HealthBostonMassachusettsUSA
| | - Renaud La Joie
- Memory and Aging CenterUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Scott C. Zimmerman
- Department of Epidemiology & BiostatisticsUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - M. Maria Glymour
- Department of EpidemiologyBoston University School of Public HealthBostonMassachusettsUSA
| | - Sarah F. Ackley
- Department of EpidemiologyBoston University School of Public HealthBostonMassachusettsUSA
| | - Thomas J. Hoffmann
- Department of Epidemiology & BiostatisticsUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Kristine Yaffe
- Department of Epidemiology & BiostatisticsUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Departments of Psychiatry and Behavioral SciencesUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Departments of NeurologyUniversity of CaliforniaSan FranciscoUSA
| | - Adina Zeki Al Hazzouri
- Department of EpidemiologyMailman School of Public HealthColumbia UniversityNew YorkNew YorkUSA
| | - Willa D. Brenowitz
- Department of Epidemiology & BiostatisticsUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Kaiser Permanente Center for Health ResearchPortlandOregonUSA
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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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Chang T, Fu M, Valiente-Banuet L, Wadhwa S, Pasaniuc B, Vossel K. Improving genetic risk modeling of dementia from real-world data in underrepresented populations. RESEARCH SQUARE 2024:rs.3.rs-3911508. [PMID: 38410460 PMCID: PMC10896371 DOI: 10.21203/rs.3.rs-3911508/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/28/2024]
Abstract
BACKGROUND Genetic risk modeling for dementia offers significant benefits, but studies based on real-world data, particularly for underrepresented populations, are limited. METHODS We employed an Elastic Net model for dementia risk prediction using single-nucleotide polymorphisms prioritized by functional genomic data from multiple neurodegenerative disease genome-wide association studies. We compared this model with APOE and polygenic risk score models across genetic ancestry groups, using electronic health records from UCLA Health for discovery and All of Us cohort for validation. RESULTS Our model significantly outperforms other models across multiple ancestries, improving the area-under-precision-recall curve by 21-61% and the area-under-the-receiver-operating characteristic by 10-21% compared to the APOEand the polygenic risk score models. We identified shared and ancestry-specific risk genes and biological pathways, reinforcing and adding to existing knowledge. CONCLUSIONS Our study highlights benefits of integrating functional mapping, multiple neurodegenerative diseases, and machine learning for genetic risk models in diverse populations. Our findings hold potential for refining precision medicine strategies in dementia diagnosis.
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Affiliation(s)
- Timothy Chang
- David Geffen School of Medicine, University of California, Los Angeles
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14
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Fu M, Valiente-Banuet L, Wadhwa SS, Pasaniuc B, Vossel K, Chang TS. Improving genetic risk modeling of dementia from real-world data in underrepresented populations. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.02.05.24302355. [PMID: 38370649 PMCID: PMC10871463 DOI: 10.1101/2024.02.05.24302355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
BACKGROUND Genetic risk modeling for dementia offers significant benefits, but studies based on real-world data, particularly for underrepresented populations, are limited. METHODS We employed an Elastic Net model for dementia risk prediction using single-nucleotide polymorphisms prioritized by functional genomic data from multiple neurodegenerative disease genome-wide association studies. We compared this model with APOE and polygenic risk score models across genetic ancestry groups, using electronic health records from UCLA Health for discovery and All of Us cohort for validation. RESULTS Our model significantly outperforms other models across multiple ancestries, improving the area-under-precision-recall curve by 21-61% and the area-under-the-receiver-operating characteristic by 10-21% compared to the APOE and the polygenic risk score models. We identified shared and ancestry-specific risk genes and biological pathways, reinforcing and adding to existing knowledge. CONCLUSIONS Our study highlights benefits of integrating functional mapping, multiple neurodegenerative diseases, and machine learning for genetic risk models in diverse populations. Our findings hold potential for refining precision medicine strategies in dementia diagnosis.
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Affiliation(s)
- Mingzhou Fu
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, United States
- Medical Informatics Home Area, Department of Bioinformatics, University of California, Los Angeles, Los Angeles, CA, 90024, United States
| | - Leopoldo Valiente-Banuet
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, United States
| | - Satpal S. Wadhwa
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, United States
| | | | | | - Bogdan Pasaniuc
- Department of Computational Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA
| | - Keith Vossel
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, United States
| | - Timothy S. Chang
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, United States
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Lancaster T, Creese B, Escott-Price V, Driver I, Menzies G, Khan Z, Corbett A, Ballard C, Williams J, Murphy K, Chandler H. Proof-of-concept recall-by-genotype study of extremely low and high Alzheimer's polygenic risk reveals autobiographical deficits and cingulate cortex correlates. Alzheimers Res Ther 2023; 15:213. [PMID: 38087383 PMCID: PMC10714651 DOI: 10.1186/s13195-023-01362-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Accepted: 11/29/2023] [Indexed: 12/18/2023]
Abstract
BACKGROUND Genome-wide association studies demonstrate that Alzheimer's disease (AD) has a highly polygenic architecture, where thousands of independent genetic variants explain risk with high classification accuracy. This AD polygenic risk score (AD-PRS) has been previously linked to preclinical cognitive and neuroimaging features observed in asymptomatic individuals. However, shared variance between AD-PRS and neurocognitive features are small, suggesting limited preclinical utility. METHODS Here, we recruited sixteen clinically asymptomatic individuals (mean age 67; range 58-76) with either extremely low / high AD-PRS (defined as at least 2 standard deviations from the wider sample mean (N = 4504; N EFFECTIVE = 90)) with comparable age sex and education level. We assessed group differences in autobiographical memory and T1-weighted structural neuroimaging features. RESULTS We observed marked reductions in autobiographical recollection (Cohen's d = - 1.66; P FDR = 0.014) and midline structure (cingulate) thickness (Cohen's d = - 1.55, P FDR = 0.05), with no difference in hippocampal volume (P > 0.3). We further confirm the negative association between AD-PRS and cingulate thickness in a larger study with a comparable age (N = 31,966, β = - 0.002, P = 0.011), supporting the validity of our approach. CONCLUSIONS These observations conform with multiple streams of prior evidence suggesting alterations in cingulate structures may occur in individuals with higher AD genetic risk. We were able to use a genetically informed research design strategy that significantly improved the efficiency and power of the study. Thus, we further demonstrate that the recall-by-genotype of AD-PRS from wider samples is a promising approach for the detection, assessment, and intervention in specific individuals with increased AD genetic risk.
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Affiliation(s)
- Thomas Lancaster
- Department of Psychology, University of Bath, Bath, UK.
- School of Physics and Astronomy, Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, UK.
- Dementia Research Institute (UKDRI), Cardiff University, Cardiff, UK.
| | - Byron Creese
- Department of Clinical and Biomedical Science, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
- Department of Life Sciences, Brunel University London, Uxbridge, west London, UK
| | - Valentina Escott-Price
- Division of Neuroscience and Mental Health, School of Medicine, Cardiff University, Cardiff, UK
| | - Ian Driver
- School of Physics and Astronomy, Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, UK
| | - Georgina Menzies
- Dementia Research Institute (UKDRI), Cardiff University, Cardiff, UK
- School of Biosciences, Cardiff University, Cardiff, UK
| | - Zunera Khan
- Institute of Psychiatry, King's College London, Psychology & Neuroscience, London, UK
| | - Anne Corbett
- Deptartment of Health & Community Sciences, University of Exeter, Exeter, UK
| | - Clive Ballard
- Department of Clinical and Biomedical Science, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Julie Williams
- Dementia Research Institute (UKDRI), Cardiff University, Cardiff, UK
| | - Kevin Murphy
- School of Physics and Astronomy, Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, UK
| | - Hannah Chandler
- School of Physics and Astronomy, Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, UK
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16
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Najar J, Thorvaldsson V, Kern S, Skoog J, Waern M, Zetterberg H, Blennow K, Skoog I, Zettergren A. Polygenic risk scores for Alzheimer's disease in relation to cognitive change: A representative sample from the general population followed over 16 years. Neurobiol Dis 2023; 189:106357. [PMID: 37977433 DOI: 10.1016/j.nbd.2023.106357] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 09/22/2023] [Accepted: 11/14/2023] [Indexed: 11/19/2023] Open
Abstract
BACKGROUND Polygenic risk scores for Alzheimer's disease (AD-PRSs) have been associated with cognition. However, few studies have examined the effect of AD-PRS beyond the APOE gene, and the influence of genetic variants related to level of cognitive ability (COG-PRS) on cognitive performance over time in the general older population. METHOD A population-based sample of 965 individuals born in 1930, with genetic and standardized cognitive data on six psychometric tests (Thurstone's picture memory, immediate recall of 10 words, Block design, word fluency, figure identification, delayed recall of 12 items), were examined at age 70, 75, 79, and 85 years. Non-APOE AD-PRSs and COG-PRSs (P < 5e-8, P < 1e-5, P < 1e-3, P < 1e-1) were generated from recent genome-wide association studies. Linear mixed effect models with random intercepts and slope were used to analyze the effect of APOE ε4 allele, AD-PRSs, and COG-PRSs, on cognitive performance and rate of change. Analyses were repeated in samples excluding dementia. RESULTS APOE ε4 and AD-PRS predicted change in cognitive performance (APOE ε4*age: β = -0.03, P < 0.0001 and AD-PRS *age: β = -0.01, P = 0.02). The results remained similar in the sample excluding those with dementia. COG-PRS predicted level of cognitive performance, while APOE ε4 and AD-PRS did not. COG-PRSs did not predict change in cognitive performance. CONCLUSION We found that genetic predisposition of AD predicted cognitive decline among 70-year-olds followed over 16 years, regardless of dementia status, while polygenic risk for general cognitive performance did not.
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Affiliation(s)
- Jenna Najar
- 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, Sweden; Region Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg, Sweden; Department of Human Genetics, Genomics of Neurodegenerative Diseases and Aging at the Amsterdam University Medical Center, Amsterdam, the Netherlands.
| | - Valgeir Thorvaldsson
- Department of Psychology, and Centre for Ageing and Health (AGECAP), at the University of Gothenburg, Sweden.
| | - Silke Kern
- 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, Sweden; Region Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg, Sweden.
| | - Johan Skoog
- 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, Sweden.
| | - Margda Waern
- 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, Sweden; Region Västra Götaland, Sahlgrenska University Hospital, Psychosis Clinic, Gothenburg, Sweden.
| | - Henrik Zetterberg
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, United Kingdom; 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; Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China; Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA.
| | - Kaj Blennow
- 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.
| | - Ingmar Skoog
- 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, Sweden; Region Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg, Sweden.
| | - 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, Sweden.
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17
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Yang HS, Teng L, Kang D, Menon V, Ge T, Finucane HK, Schultz AP, Properzi M, Klein HU, Chibnik LB, Schneider JA, Bennett DA, Hohman TJ, Mayeux RP, Johnson KA, De Jager PL, Sperling RA. Cell-type-specific Alzheimer's disease polygenic risk scores are associated with distinct disease processes in Alzheimer's disease. Nat Commun 2023; 14:7659. [PMID: 38036535 PMCID: PMC10689816 DOI: 10.1038/s41467-023-43132-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Accepted: 11/01/2023] [Indexed: 12/02/2023] Open
Abstract
Many of the Alzheimer's disease (AD) risk genes are specifically expressed in microglia and astrocytes, but how and when the genetic risk localizing to these cell types contributes to AD pathophysiology remains unclear. Here, we derive cell-type-specific AD polygenic risk scores (ADPRS) from two extensively characterized datasets and uncover the impact of cell-type-specific genetic risk on AD endophenotypes. In an autopsy dataset spanning all stages of AD (n = 1457), the astrocytic ADPRS affected diffuse and neuritic plaques (amyloid-β), while microglial ADPRS affected neuritic plaques, microglial activation, neurofibrillary tangles (tau), and cognitive decline. In an independent neuroimaging dataset of cognitively unimpaired elderly (n = 2921), astrocytic ADPRS was associated with amyloid-β, and microglial ADPRS was associated with amyloid-β and tau, connecting cell-type-specific genetic risk with AD pathology even before symptom onset. Together, our study provides human genetic evidence implicating multiple glial cell types in AD pathophysiology, starting from the preclinical stage.
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Affiliation(s)
- Hyun-Sik Yang
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA.
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
- Harvard Medical School, Boston, MA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Ling Teng
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Daniel Kang
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Vilas Menon
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
- Department of Neurology and the Taub Institute for the Study of Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | - Tian Ge
- Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Precision Psychiatry, Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Hilary K Finucane
- Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Aaron P Schultz
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Michael Properzi
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Hans-Ulrich Klein
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
- Department of Neurology and the Taub Institute for the Study of Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | - Lori B Chibnik
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Julie A Schneider
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Timothy J Hohman
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Richard P Mayeux
- Department of Neurology and the Taub Institute for the Study of Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | - Keith A Johnson
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Philip L De Jager
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
- Department of Neurology and the Taub Institute for the Study of Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | - Reisa A Sperling
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
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18
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Wang KW, Yuan YX, Zhu B, Zhang Y, Wei YF, Meng FS, Zhang S, Wang JX, Zhou JY. X chromosome-wide association study of quantitative biomarkers from the Alzheimer's Disease Neuroimaging Initiative study. Front Aging Neurosci 2023; 15:1277731. [PMID: 38035272 PMCID: PMC10682795 DOI: 10.3389/fnagi.2023.1277731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 10/20/2023] [Indexed: 12/02/2023] Open
Abstract
Introduction Alzheimer's disease (AD) is a complex neurodegenerative disease with high heritability. Compared to autosomes, a higher proportion of disorder-associated genes on X chromosome are expressed in the brain. However, only a few studies focused on the identification of the susceptibility loci for AD on X chromosome. Methods Using the data from the Alzheimer's Disease Neuroimaging Initiative Study, we conducted an X chromosome-wide association study between 16 AD quantitative biomarkers and 19,692 single nucleotide polymorphisms (SNPs) based on both the cross-sectional and longitudinal studies. Results We identified 15 SNPs statistically significantly associated with different quantitative biomarkers of the AD. For the cross-sectional study, six SNPs (rs5927116, rs4596772, rs5929538, rs2213488, rs5920524, and rs5945306) are located in or near to six genes DMD, TBX22, LOC101928437, TENM1, SPANXN1, and ZFP92, which have been reported to be associated with schizophrenia or neuropsychiatric diseases in literature. For the longitudinal study, four SNPs (rs4829868, rs5931111, rs6540385, and rs763320) are included in or near to two genes RAC1P4 and AFF2, which have been demonstrated to be associated with brain development or intellectual disability in literature, while the functional annotations of other five novel SNPs (rs12157031, rs428303, rs5953487, rs10284107, and rs5955016) have not been found. Discussion 15 SNPs were found statistically significantly associated with the quantitative biomarkers of the AD. Follow-up study in molecular genetics is needed to verify whether they are indeed related to AD. The findings in this article expand our understanding of the role of the X chromosome in exploring disease susceptibility, introduce new insights into the molecular genetics behind the AD, and may provide a mechanistic clue to further AD-related studies.
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Affiliation(s)
- Kai-Wen Wang
- State Key Laboratory of Organ Failure Research, Ministry of Education, Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangzhou, China
| | - Yu-Xin Yuan
- State Key Laboratory of Organ Failure Research, Ministry of Education, Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangzhou, China
| | - Bin Zhu
- State Key Laboratory of Organ Failure Research, Ministry of Education, Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangzhou, China
| | - Yi Zhang
- State Key Laboratory of Organ Failure Research, Ministry of Education, Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangzhou, China
| | - Yi-Fang Wei
- State Key Laboratory of Organ Failure Research, Ministry of Education, Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangzhou, China
| | - Fan-Shuo Meng
- State Key Laboratory of Organ Failure Research, Ministry of Education, Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangzhou, China
| | - Shun Zhang
- State Key Laboratory of Organ Failure Research, Ministry of Education, Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
| | - Jing-Xuan Wang
- State Key Laboratory of Organ Failure Research, Ministry of Education, Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
| | - Ji-Yuan Zhou
- State Key Laboratory of Organ Failure Research, Ministry of Education, Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangzhou, China
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Ikonnikova A, Morozova A, Antonova O, Ochneva A, Fedoseeva E, Abramova O, Emelyanova M, Filippova M, Morozova I, Zorkina Y, Syunyakov T, Andryushchenko A, Andreuyk D, Kostyuk G, Gryadunov D. Evaluation of the Polygenic Risk Score for Alzheimer's Disease in Russian Patients with Dementia Using a Low-Density Hydrogel Oligonucleotide Microarray. Int J Mol Sci 2023; 24:14765. [PMID: 37834213 PMCID: PMC10572681 DOI: 10.3390/ijms241914765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 09/25/2023] [Accepted: 09/28/2023] [Indexed: 10/15/2023] Open
Abstract
The polygenic risk score (PRS), together with the ɛ4 allele of the APOE gene (APOE-ɛ4), has shown high potential for Alzheimer's disease (AD) risk prediction. The aim of this study was to validate the model of polygenic risk in Russian patients with dementia. A microarray-based assay was developed to identify 21 markers of polygenic risk and ɛ alleles of the APOE gene. This case-control study included 348 dementia patients and 519 cognitively normal volunteers. Cerebrospinal fluid (CSF) amyloid-β (Aβ) and tau protein levels were assessed in 57 dementia patients. PRS and APOE-ɛ4 were significant genetic risk factors for dementia. Adjusted for APOE-ɛ4, individuals with PRS corresponding to the fourth quartile had an increased risk of dementia compared to the first quartile (OR 1.85; p-value 0.002). The area under the curve (AUC) was 0.559 for the PRS model only, and the inclusion of APOE-ɛ4 improved the AUC to 0.604. PRS was positively correlated with tTau and pTau181 and inversely correlated with Aβ42/Aβ40 ratio. Carriers of APOE-ɛ4 had higher levels of tTau and pTau181 and lower levels of Aβ42 and Aβ42/Aβ40. The developed assay can be part of a strategy for assessing individuals for AD risk, with the purpose of assisting primary preventive interventions.
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Affiliation(s)
- Anna Ikonnikova
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia; (O.A.); (E.F.); (M.E.); (M.F.); (D.G.)
| | - Anna Morozova
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia; (A.M.); (A.O.); (O.A.); (I.M.); (Y.Z.); (T.S.); (A.A.); (D.A.); (G.K.)
- Department of Basic and Applied Neurobiology, V. Serbsky Federal Medical Research Centre of Psychiatry and Narcology, Kropotkinsky per. 23, 119034 Moscow, Russia
| | - Olga Antonova
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia; (O.A.); (E.F.); (M.E.); (M.F.); (D.G.)
| | - Alexandra Ochneva
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia; (A.M.); (A.O.); (O.A.); (I.M.); (Y.Z.); (T.S.); (A.A.); (D.A.); (G.K.)
| | - Elena Fedoseeva
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia; (O.A.); (E.F.); (M.E.); (M.F.); (D.G.)
| | - Olga Abramova
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia; (A.M.); (A.O.); (O.A.); (I.M.); (Y.Z.); (T.S.); (A.A.); (D.A.); (G.K.)
- Department of Basic and Applied Neurobiology, V. Serbsky Federal Medical Research Centre of Psychiatry and Narcology, Kropotkinsky per. 23, 119034 Moscow, Russia
| | - Marina Emelyanova
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia; (O.A.); (E.F.); (M.E.); (M.F.); (D.G.)
| | - Marina Filippova
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia; (O.A.); (E.F.); (M.E.); (M.F.); (D.G.)
| | - Irina Morozova
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia; (A.M.); (A.O.); (O.A.); (I.M.); (Y.Z.); (T.S.); (A.A.); (D.A.); (G.K.)
| | - Yana Zorkina
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia; (A.M.); (A.O.); (O.A.); (I.M.); (Y.Z.); (T.S.); (A.A.); (D.A.); (G.K.)
- Department of Basic and Applied Neurobiology, V. Serbsky Federal Medical Research Centre of Psychiatry and Narcology, Kropotkinsky per. 23, 119034 Moscow, Russia
| | - Timur Syunyakov
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia; (A.M.); (A.O.); (O.A.); (I.M.); (Y.Z.); (T.S.); (A.A.); (D.A.); (G.K.)
- International Centre for Education and Research in Neuropsychiatry (ICERN), Samara State Medical University, 443016 Samara, Russia
| | - Alisa Andryushchenko
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia; (A.M.); (A.O.); (O.A.); (I.M.); (Y.Z.); (T.S.); (A.A.); (D.A.); (G.K.)
| | - Denis Andreuyk
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia; (A.M.); (A.O.); (O.A.); (I.M.); (Y.Z.); (T.S.); (A.A.); (D.A.); (G.K.)
- Economy Faculty, M.V. Lomonosov Moscow State University, 119991 Moscow, Russia
| | - Georgy Kostyuk
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia; (A.M.); (A.O.); (O.A.); (I.M.); (Y.Z.); (T.S.); (A.A.); (D.A.); (G.K.)
- Department of Psychiatry, Federal State Budgetary Educational Institution of Higher Education “Moscow State University of Food Production”, Volokolamskoye Highway 11, 125080 Moscow, Russia
| | - Dmitry Gryadunov
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia; (O.A.); (E.F.); (M.E.); (M.F.); (D.G.)
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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: 0.5] [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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21
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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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22
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Insel PS, Kumar A, Hansson O, Mattsson-Carlgren N. Genetic Moderation of the Association of β-Amyloid With Cognition and MRI Brain Structure in Alzheimer Disease. Neurology 2023; 101:e20-e29. [PMID: 37085326 PMCID: PMC10351305 DOI: 10.1212/wnl.0000000000207305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Accepted: 03/03/2023] [Indexed: 04/23/2023] Open
Abstract
BACKGROUND AND OBJECTIVES There is considerable heterogeneity in the association between increasing β-amyloid (Aβ) pathology and early cognitive dysfunction in preclinical Alzheimer disease (AD). At this stage, some individuals show no signs of cognitive dysfunction, while others show clear signs of decline. The factors explaining this heterogeneity are particularly important for understanding progression in AD but remain largely unknown. In this study, we examined an array of genetic variants that may influence the relationships among Aβ, brain structure, and cognitive performance in 2 large cohorts. METHODS In 2,953 cognitively unimpaired participants from the Anti-Amyloid Treatment in Asymptomatic Alzheimer disease (A4) study, interactions between genetic variants and 18F-Florbetapir PET standardized uptake value ratio (SUVR) to predict the Preclinical Alzheimer Cognitive Composite (PACC) were assessed. Genetic variants identified in the A4 study were evaluated in the Alzheimer Disease Neuroimaging Initiative (ADNI, N = 527) for their association with longitudinal cognition and brain atrophy in both cognitively unimpaired participants and those with mild cognitive impairment. RESULTS In the A4 study, 4 genetic variants significantly moderated the association between Aβ load and cognition. Minor alleles of 3 variants were associated with additional decreases in PACC scores with increasing Aβ SUVR (rs78021285, β = -2.29, SE = 0.40, p FDR = 0.02, nearest gene ARPP21; rs71567499, β = -2.16, SE = 0.38, p FDR = 0.02, nearest gene PPARD; and rs10974405, β = -1.68, SE = 0.29, p FDR = 0.02, nearest gene GLIS3). The minor allele of rs7825645 was associated with less decrease in PACC scores with increasing Aβ SUVR (β = 0.71, SE = 0.13, p FDR = 0.04, nearest gene FGF20). The genetic variant rs76366637, in linkage disequilibrium with rs78021285, was available in both the A4 and ADNI. In the A4, rs76366637 was strongly associated with reduced PACC scores with increasing Aβ SUVR (β = -1.01, SE = 0.21, t = -4.90, p < 0.001). In the ADNI, rs76366637 was associated with accelerated cognitive decline (χ2 = 15.3, p = 0.004) and atrophy over time (χ2 = 26.8, p < 0.001), with increasing Aβ SUVR. DISCUSSION Patterns of increased cognitive dysfunction and accelerated atrophy due to specific genetic variation may explain some of the heterogeneity in cognition in preclinical and prodromal AD. The genetic variant near ARPP21 associated with lower cognitive scores in the A4 and accelerated cognitive decline and brain atrophy in the ADNI may help to identify those at the highest risk of accelerated progression of AD.
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Affiliation(s)
- Philip S Insel
- From the Clinical Memory Research Unit (P.S.I., A.K., O.H., N.M.-C.), Faculty of Medicine, Lund University, Sweden; Department of Psychiatry and Behavioral Sciences (P.S.I.), University of California, San Francisco; Memory Clinic (O.H.), Department of Neurology (N.M.-C.), Skåne University Hospital, and Wallenberg Center for Molecular Medicine (N.M.-C.), Lund University, Sweden.
| | - Atul Kumar
- From the Clinical Memory Research Unit (P.S.I., A.K., O.H., N.M.-C.), Faculty of Medicine, Lund University, Sweden; Department of Psychiatry and Behavioral Sciences (P.S.I.), University of California, San Francisco; Memory Clinic (O.H.), Department of Neurology (N.M.-C.), Skåne University Hospital, and Wallenberg Center for Molecular Medicine (N.M.-C.), Lund University, Sweden
| | - Oskar Hansson
- From the Clinical Memory Research Unit (P.S.I., A.K., O.H., N.M.-C.), Faculty of Medicine, Lund University, Sweden; Department of Psychiatry and Behavioral Sciences (P.S.I.), University of California, San Francisco; Memory Clinic (O.H.), Department of Neurology (N.M.-C.), Skåne University Hospital, and Wallenberg Center for Molecular Medicine (N.M.-C.), Lund University, Sweden
| | - Niklas Mattsson-Carlgren
- From the Clinical Memory Research Unit (P.S.I., A.K., O.H., N.M.-C.), Faculty of Medicine, Lund University, Sweden; Department of Psychiatry and Behavioral Sciences (P.S.I.), University of California, San Francisco; Memory Clinic (O.H.), Department of Neurology (N.M.-C.), Skåne University Hospital, and Wallenberg Center for Molecular Medicine (N.M.-C.), Lund University, Sweden
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23
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Lambert JC, Ramirez A, Grenier-Boley B, Bellenguez C. Step by step: towards a better understanding of the genetic architecture of Alzheimer's disease. Mol Psychiatry 2023; 28:2716-2727. [PMID: 37131074 PMCID: PMC10615767 DOI: 10.1038/s41380-023-02076-1] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 04/12/2023] [Accepted: 04/14/2023] [Indexed: 05/04/2023]
Abstract
Alzheimer's disease (AD) is considered to have a large genetic component. Our knowledge of this component has progressed over the last 10 years, thanks notably to the advent of genome-wide association studies and the establishment of large consortia that make it possible to analyze hundreds of thousands of cases and controls. The characterization of dozens of chromosomal regions associated with the risk of developing AD and (in some loci) the causal genes responsible for the observed disease signal has confirmed the involvement of major pathophysiological pathways (such as amyloid precursor protein metabolism) and opened up new perspectives (such as the central role of microglia and inflammation). Furthermore, large-scale sequencing projects are starting to reveal the major impact of rare variants - even in genes like APOE - on the AD risk. This increasingly comprehensive knowledge is now being disseminated through translational research; in particular, the development of genetic risk/polygenic risk scores is helping to identify the subpopulations more at risk or less at risk of developing AD. Although it is difficult to assess the efforts still needed to comprehensively characterize the genetic component of AD, several lines of research can be improved or initiated. Ultimately, genetics (in combination with other biomarkers) might help to redefine the boundaries and relationships between various neurodegenerative diseases.
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Affiliation(s)
- Jean-Charles Lambert
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement, Lille, France.
| | - Alfredo Ramirez
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Department of Neurodegenerative diseases and Geriatric Psychiatry, University Hospital Bonn, Medical Faculty, Bonn, Germany
- Department of Psychiatry & Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, San Antonio, TX, USA
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Cluster of Excellence Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - Benjamin Grenier-Boley
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement, Lille, France
| | - Céline Bellenguez
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement, Lille, France
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24
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Yang HS, Teng L, Kang D, Menon V, Ge T, Finucane HK, Schultz AP, Properzi M, Klein HU, Chibnik LB, Schneider JA, Bennett DA, Hohman TJ, Mayeux RP, Johnson KA, De Jager PL, Sperling RA. Cell-type-specific Alzheimer's disease polygenic risk scores are associated with distinct disease processes in Alzheimer's disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.01.23290850. [PMID: 37333223 PMCID: PMC10274993 DOI: 10.1101/2023.06.01.23290850] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Alzheimer's disease (AD) heritability is enriched in glial genes, but how and when cell-type-specific genetic risk contributes to AD remains unclear. Here, we derive cell-type-specific AD polygenic risk scores (ADPRS) from two extensively characterized datasets. In an autopsy dataset spanning all stages of AD (n=1,457), astrocytic (Ast) ADPRS was associated with both diffuse and neuritic Aβ plaques, while microglial (Mic) ADPRS was associated with neuritic Aβ plaques, microglial activation, tau, and cognitive decline. Causal modeling analyses further clarified these relationships. In an independent neuroimaging dataset of cognitively unimpaired elderly (n=2,921), Ast-ADPRS were associated with Aβ, and Mic-ADPRS was associated with Aβ and tau, showing a consistent pattern with the autopsy dataset. Oligodendrocytic and excitatory neuronal ADPRSs were associated with tau, but only in the autopsy dataset including symptomatic AD cases. Together, our study provides human genetic evidence implicating multiple glial cell types in AD pathophysiology, starting from the preclinical stage.
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Affiliation(s)
- Hyun-Sik Yang
- Department of Neurology, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA
- Broad Institute of MIT and Harvard, Cambridge, MA
| | - Ling Teng
- Department of Neurology, Brigham and Women’s Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA
| | - Daniel Kang
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Vilas Menon
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
| | - Tian Ge
- Harvard Medical School, Boston, MA
- Broad Institute of MIT and Harvard, Cambridge, MA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Hilary K. Finucane
- Harvard Medical School, Boston, MA
- Broad Institute of MIT and Harvard, Cambridge, MA
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Aaron P. Schultz
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA
| | - Michael Properzi
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Hans-Ulrich Klein
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
| | - Lori B. Chibnik
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Julie A. Schneider
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - David A. Bennett
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Timothy J. Hohman
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Richard P. Mayeux
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
| | - Keith A. Johnson
- Department of Neurology, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - Philip L. De Jager
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
| | - Reisa A. Sperling
- Department of Neurology, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA
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25
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Bourquard T, Lee K, Al-Ramahi I, Pham M, Shapiro D, Lagisetty Y, Soleimani S, Mota S, Wilhelm K, Samieinasab M, Kim YW, Huh E, Asmussen J, Katsonis P, Botas J, Lichtarge O. Functional variants identify sex-specific genes and pathways in Alzheimer's Disease. Nat Commun 2023; 14:2765. [PMID: 37179358 PMCID: PMC10183026 DOI: 10.1038/s41467-023-38374-z] [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: 01/27/2022] [Accepted: 04/28/2023] [Indexed: 05/15/2023] Open
Abstract
The incidence of Alzheimer's Disease in females is almost double that of males. To search for sex-specific gene associations, we build a machine learning approach focused on functionally impactful coding variants. This method can detect differences between sequenced cases and controls in small cohorts. In the Alzheimer's Disease Sequencing Project with mixed sexes, this approach identified genes enriched for immune response pathways. After sex-separation, genes become specifically enriched for stress-response pathways in male and cell-cycle pathways in female. These genes improve disease risk prediction in silico and modulate Drosophila neurodegeneration in vivo. Thus, a general approach for machine learning on functionally impactful variants can uncover sex-specific candidates towards diagnostic biomarkers and therapeutic targets.
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Affiliation(s)
- Thomas Bourquard
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Kwanghyuk Lee
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Ismael Al-Ramahi
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, 77030, USA
- Center for Alzheimer's and Neurodegenerative Diseases, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Minh Pham
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Dillon Shapiro
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Yashwanth Lagisetty
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
- Department of Biology and Pharmacology, UTHealth McGovern Medical School, Houston, TX, 77030, USA
| | - Shirin Soleimani
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Samantha Mota
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Kevin Wilhelm
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Maryam Samieinasab
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Young Won Kim
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Eunna Huh
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Jennifer Asmussen
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Panagiotis Katsonis
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Juan Botas
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA
- Jan and Dan Duncan Neurological Research Institute, Texas Children's Hospital, Houston, TX, 77030, USA
- Center for Alzheimer's and Neurodegenerative Diseases, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Olivier Lichtarge
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, 77030, USA.
- Center for Alzheimer's and Neurodegenerative Diseases, Baylor College of Medicine, Houston, TX, 77030, USA.
- Computational and Integrative Biomedical Research Center, Baylor College of Medicine, Houston, TX, 77030, USA.
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26
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Ochneva AG, Soloveva KP, Savenkova VI, Ikonnikova AY, Gryadunov DA, Andryuschenko AV. Modern Approaches to the Diagnosis of Cognitive Impairment and Alzheimer's Disease: A Narrative Literature Review. CONSORTIUM PSYCHIATRICUM 2023; 4:53-62. [PMID: 38239570 PMCID: PMC10790729 DOI: 10.17816/cp716] [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: 02/03/2023] [Accepted: 03/13/2023] [Indexed: 04/03/2023] Open
Abstract
BACKGROUND The aging of the worlds population leads to an increase in the prevalence of age-related diseases, including cognitive impairment. At the stage of dementia, therapeutic interventions become usually ineffective. Therefore, researchers and clinical practitioners today are looking for methods that allow for early diagnosis of cognitive impairment, including techniques that are based on the use of biological markers. AIM The aim of this literature review is to delve into scientific papers that are centered on modern laboratory tests for Alzheimers disease, including tests for biological markers at the early stages of cognitive impairment. METHODS The authors have carried out a descriptive review of scientific papers published from 2015 to 2023. Studies that are included in the PubMed and Web of Science electronic databases were analyzed. A descriptive analysis was used to summarized the gleaned information. RESULTS Blood and cerebrospinal fluid (CSF) biomarkers, as well as the advantages and disadvantages of their use, are reviewed. The most promising neurotrophic, neuroinflammatory, and genetic markers, including polygenic risk models, are also discussed. CONCLUSION The use of biomarkers in clinical practice will contribute to the early diagnosis of cognitive impairment associated with Alzheimers disease. Genetic screening tests can improve the detection threshold of preclinical abnormalities in the absence of obvious symptoms of cognitive decline. The active use of biomarkers in clinical practice, in combination with genetic screening for the early diagnosis of cognitive impairment in Alzheimers disease, can improve the timeliness and effectiveness of medical interventions.
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27
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Pettigrew C, Nazarovs J, Soldan A, Singh V, Wang J, Hohman T, Dumitrescu L, Libby J, Kunkle B, Gross AL, Johnson S, Lu Q, Engelman C, Masters CL, Maruff P, Laws SM, Morris JC, Hassenstab J, Cruchaga C, Resnick SM, Kitner-Triolo MH, An Y, Albert M. Alzheimer's disease genetic risk and cognitive reserve in relationship to long-term cognitive trajectories among cognitively normal individuals. Alzheimers Res Ther 2023; 15:66. [PMID: 36978190 PMCID: PMC10045505 DOI: 10.1186/s13195-023-01206-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 03/12/2023] [Indexed: 03/30/2023]
Abstract
BACKGROUND Both Alzheimer's disease (AD) genetic risk factors and indices of cognitive reserve (CR) influence risk of cognitive decline, but it remains unclear whether they interact. This study examined whether a CR index score modifies the relationship between AD genetic risk factors and long-term cognitive trajectories in a large sample of individuals with normal cognition. METHODS Analyses used data from the Preclinical AD Consortium, including harmonized data from 5 longitudinal cohort studies. Participants were cognitively normal at baseline (M baseline age = 64 years, 59% female) and underwent 10 years of follow-up, on average. AD genetic risk was measured by (i) apolipoprotein-E (APOE) genetic status (APOE-ε2 and APOE-ε4 vs. APOE-ε3; N = 1819) and (ii) AD polygenic risk scores (AD-PRS; N = 1175). A CR index was calculated by combining years of education and literacy scores. Longitudinal cognitive performance was measured by harmonized factor scores for global cognition, episodic memory, and executive function. RESULTS In mixed-effects models, higher CR index scores were associated with better baseline cognitive performance for all cognitive outcomes. APOE-ε4 genotype and AD-PRS that included the APOE region (AD-PRSAPOE) were associated with declines in all cognitive domains, whereas AD-PRS that excluded the APOE region (AD-PRSw/oAPOE) was associated with declines in executive function and global cognition, but not memory. There were significant 3-way CR index score × APOE-ε4 × time interactions for the global (p = 0.04, effect size = 0.16) and memory scores (p = 0.01, effect size = 0.22), indicating the negative effect of APOE-ε4 genotype on global and episodic memory score change was attenuated among individuals with higher CR index scores. In contrast, levels of CR did not attenuate APOE-ε4-related declines in executive function or declines associated with higher AD-PRS. APOE-ε2 genotype was unrelated to cognition. CONCLUSIONS These results suggest that APOE-ε4 and non-APOE-ε4 AD polygenic risk are independently associated with global cognitive and executive function declines among individuals with normal cognition at baseline, but only APOE-ε4 is associated with declines in episodic memory. Importantly, higher levels of CR may mitigate APOE-ε4-related declines in some cognitive domains. Future research is needed to address study limitations, including generalizability due to cohort demographic characteristics.
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Affiliation(s)
- Corinne Pettigrew
- Johns Hopkins University School of Medicine, 1600 McElderry St, Baltimore, MD, 21205, USA.
| | - Jurijs Nazarovs
- University of Wisconsin-Madison School of Medicine and Public Health, 750 Highland Ave, Madison, WI, 53726, USA
| | - Anja Soldan
- Johns Hopkins University School of Medicine, 1600 McElderry St, Baltimore, MD, 21205, USA
| | - Vikas Singh
- University of Wisconsin-Madison School of Medicine and Public Health, 750 Highland Ave, Madison, WI, 53726, USA
| | - Jiangxia Wang
- Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe St, Baltimore, MD, 21205, USA
| | - Timothy Hohman
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, 1207 17th Ave South, Nashville, TN, 37212, USA
| | - Logan Dumitrescu
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, 1207 17th Ave South, Nashville, TN, 37212, USA
| | - Julia Libby
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, 1207 17th Ave South, Nashville, TN, 37212, USA
| | - Brian Kunkle
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Alden L Gross
- Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe St, Baltimore, MD, 21205, USA
| | - Sterling Johnson
- University of Wisconsin-Madison School of Medicine and Public Health, 750 Highland Ave, Madison, WI, 53726, USA
| | - Qiongshi Lu
- University of Wisconsin-Madison School of Medicine and Public Health, 750 Highland Ave, Madison, WI, 53726, USA
| | - Corinne Engelman
- University of Wisconsin-Madison School of Medicine and Public Health, 750 Highland Ave, Madison, WI, 53726, USA
| | - Colin L Masters
- The Florey Institute, University of Melbourne, 30 Royal Parade, Parkville, VIC, 3052, Australia
| | - Paul Maruff
- The Florey Institute, University of Melbourne, 30 Royal Parade, Parkville, VIC, 3052, Australia
| | - Simon M Laws
- Centre for Precision Health and Collaborative Genomics and Translation Group, Edith Cowan University, 270 Jundaloop Drive, Jundaloop, WA, 6027, Australia
- Curtin Medical School, Curtin University, Kent Street, Bentley, WA, 6102, Australia
| | - John C Morris
- Washington University School of Medicine, 660 S Euclid Ave, St. Louis, MO, 63110, USA
| | - Jason Hassenstab
- Washington University School of Medicine, 660 S Euclid Ave, St. Louis, MO, 63110, USA
| | - Carlos Cruchaga
- Washington University School of Medicine, 660 S Euclid Ave, St. Louis, MO, 63110, USA
| | - Susan M Resnick
- National Institute on Aging Intramural Research Program, 251 Bayview Blvd, Baltimore, MD, 21224, USA
| | - Melissa H Kitner-Triolo
- National Institute on Aging Intramural Research Program, 251 Bayview Blvd, Baltimore, MD, 21224, USA
| | - Yang An
- National Institute on Aging Intramural Research Program, 251 Bayview Blvd, Baltimore, MD, 21224, USA
| | - Marilyn Albert
- Johns Hopkins University School of Medicine, 1600 McElderry St, Baltimore, MD, 21205, USA
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28
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Schork NJ, Elman JA. Pathway-specific polygenic risk scores correlate with clinical status and Alzheimer's-related biomarkers. RESEARCH SQUARE 2023:rs.3.rs-2583037. [PMID: 36909609 PMCID: PMC10002839 DOI: 10.21203/rs.3.rs-2583037/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/05/2023]
Abstract
Background: APOE is the largest genetic risk factor for sporadic Alzheimer's disease (AD), but there is a substantial polygenic component as well. Polygenic risk scores (PRS) can summarize small effects across the genome but may obscure differential risk associated with different molecular processes and pathways. Variability at the genetic level may contribute to the extensive phenotypic heterogeneity of Alzheimer's disease (AD). Here, we examine polygenic risk impacting specific pathways associated with AD and examined its relationship with clinical status and AD biomarkers of amyloid, tau, and neurodegeneration (A/T/N). Methods: A total of 1,411 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) with genotyping data were included. Sets of variants identified from a pathway analysis of AD GWAS summary statistics were combined into clusters based on their assigned pathway. We constructed pathway-specific PRSs for each participant and tested their associations with diagnostic status (AD vs cognitively normal), abnormal levels of amyloid and ptau (positive vs negative), and hippocampal volume. The APOE region was excluded from all PRSs, and analyses controlled for APOE -ε4 carrier status. Results: Thirteen pathway clusters were identified relating to categories such as immune response, amyloid precursor processing, protein localization, lipid transport and binding, tyrosine kinase, and endocytosis. Eight pathway-specific PRSs were significantly associated with AD dementia diagnosis. Amyloid-positivity was associated with endocytosis and fibril formation, response misfolded protein, and regulation protein tyrosine PRSs. Ptau positivity and hippocampal volume were both related to protein localization and mitophagy PRS, and ptau positivity was additionally associated with an immune signaling PRS. A global AD PRS showed stronger associations with diagnosis and all biomarkers compared to pathway PRSs, suggesting a strong synergistic effect of all loci contributing to the global AD PRS. Conclusions: Pathway PRS may contribute to understanding separable disease processes, but do not appear to add significant power for predictive purposes. These findings demonstrate that, although genetic risk for AD is widely distributed, AD-phenotypes may be preferentially associated with risk in specific pathways. Defining genetic risk along multiple dimensions at the individual level may help clarify the etiological heterogeneity in AD.
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Brenowitz WD, Fornage M, Launer LJ, Habes M, Davatzikos C, Yaffe K. Alzheimer's Disease Genetic Risk, Cognition, and Brain Aging in Midlife. Ann Neurol 2023; 93:629-634. [PMID: 36511390 PMCID: PMC9974745 DOI: 10.1002/ana.26569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 11/10/2022] [Accepted: 12/04/2022] [Indexed: 12/14/2022]
Abstract
We examined associations of an Alzheimer's disease (AD) Genetic Risk Score (AD-GRS) and midlife cognitive and neuroimaging outcomes in 1,252 middle-aged participants (311 with brain MRI). A higher AD-GRS based on 25 previously identified loci (excluding apolipoprotein E [APOE]) was associated with worse Montreal Cognitive Assessment (-0.14 standard deviation [SD] [95% confidence interval {CI}: -0.26, -0.02]), older machine learning predicted brain age (2.35 years[95%CI: 0.01, 4.69]), and white matter hyperintensity volume (0.35 SD [95% CI: 0.00, 0.71]), but not with a composite cognitive outcome, total brain, or hippocampal volume. APOE ε4 allele was not associated with any outcomes. AD risk genes beyond APOE may contribute to subclinical differences in cognition and brain health in midlife. ANN NEUROL 2023;93:629-634.
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Affiliation(s)
- Willa D Brenowitz
- Departments of Psychiatry and Behavioral Sciences, Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California, USA
| | - Myriam Fornage
- The University of Texas, Health Science Center at Houston, Houston, Texas, USA
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Science, National Institute on Aging, Bethesda, Maryland, USA
| | - Mohamad Habes
- Neuroimage Analytics Laboratory and Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Neurodegenerative Disorders, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Christos Davatzikos
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Kristine Yaffe
- Departments of Psychiatry and Behavioral Sciences, Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California, USA
- Department of Neurology, University of California, San Francisco, San Francisco, California, USA
- San Francisco VA Medical Center, San Francisco, California, USA
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Schork NJ, Elman JA. Pathway-Specific Polygenic Risk Scores Correlate with Clinical Status and Alzheimer's Disease-Related Biomarkers. J Alzheimers Dis 2023; 95:915-929. [PMID: 37661888 PMCID: PMC10697039 DOI: 10.3233/jad-230548] [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] [Indexed: 09/05/2023]
Abstract
BACKGROUND APOE is the largest genetic risk factor for Alzheimer's disease (AD), but there is a substantial polygenic component. Polygenic risk scores (PRS) can summarize small effects across the genome but may obscure differential risk across molecular processes and pathways that contribute to heterogeneity of disease presentation. OBJECTIVE We examined polygenic risk impacting specific AD-associated pathways and its relationship with clinical status and biomarkers of amyloid, tau, and neurodegeneration (A/T/N). METHODS We analyzed data from 1,411 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We applied pathway analysis and clustering to identify AD-associated "pathway clusters" and construct pathway-specific PRSs (excluding the APOE region). We tested associations with diagnostic status, abnormal levels of amyloid and ptau, and hippocampal volume. RESULTS Thirteen pathway clusters were identified, and eight pathway-specific PRSs were significantly associated with AD diagnosis. Amyloid-positivity was associated with endocytosis and fibril formation, response misfolded protein, and regulation protein tyrosine PRSs. Ptau positivity and hippocampal volume were both related to protein localization and mitophagy PRS, and ptau-positivity was also associated with an immune signaling PRS. A global AD PRS showed stronger associations with diagnosis and all biomarkers compared to pathway PRSs. CONCLUSIONS Pathway PRS may contribute to understanding separable disease processes, but do not add significant power for predictive purposes. These findings demonstrate that AD-phenotypes may be preferentially associated with risk in specific pathways, and defining genetic risk along multiple dimensions may clarify etiological heterogeneity in AD. This approach to delineate pathway-specific PRS can be used to study other complex diseases.
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Affiliation(s)
- Nicholas J. Schork
- The Translational Genomics Research Institute, Quantitative Medicine and Systems Biology, Phoenix, AZ, USA
- Department of Psychiatry University of California, San Diego, La Jolla, CA, USA
| | - Jeremy A. Elman
- Department of Psychiatry University of California, San Diego, La Jolla, CA, USA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
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Essers E, Binter AC, Neumann A, White T, Alemany S, Guxens M. Air pollution exposure during pregnancy and childhood, APOE ε4 status and Alzheimer polygenic risk score, and brain structural morphology in preadolescents. ENVIRONMENTAL RESEARCH 2023; 216:114595. [PMID: 36257450 DOI: 10.1016/j.envres.2022.114595] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 09/27/2022] [Accepted: 10/12/2022] [Indexed: 06/16/2023]
Abstract
BACKGROUND Air pollution exposure is associated with impaired neurodevelopment, altered structural brain morphology in children, and neurodegenerative disorders. Differential susceptibility to air pollution may be influenced by genetic features. OBJECTIVES To evaluate whether the apolipoprotein E (APOE) genotype or the polygenic risk score (PRS) for Alzheimer's Disease (AD) modify the association between air pollution exposure during pregnancy and childhood and structural brain morphology in preadolescents. METHODS We included 1186 children from the Generation R Study. Concentrations of fourteen air pollutants were calculated at participants' home addresses during pregnancy and childhood using land-use-regression models. Structural brain images were collected at age 9-12 years to assess cortical and subcortical brain volumes. APOE status and PRS for AD were examined as genetic modifiers. Linear regression models were used to conduct single-pollutant and multi-pollutant (using the Deletion/Substitution/Addition algorithm) analyses with a two-way interaction between air pollution and each genetic modifier. RESULTS Higher pregnancy coarse particulate matter (PMcoarse) and childhood polycyclic aromatic hydrocarbons exposure was differentially associated with larger cerebral white matter volume in APOE ε4 carriers compared to non-carriers (29,485 mm3 (95% CI 6,189; 52,781) and 18,663 mm3 (469; 36,856), respectively). Higher pregnancy PMcoarse exposure was differentially associated with larger cortical grey matter volume in children with higher compared to lower PRS for AD (19436 mm3 (825, 38,046)). DISCUSSION APOE status and PRS for AD possibly modify the association between air pollution exposure and brain structural morphology in preadolescents. Higher air pollution exposure is associated with larger cortical volumes in APOE ε4 carriers and children with a high PRS for AD. This is in line with typical brain development, suggesting an antagonistic pleiotropic effect of these genetic features (i.e., protective effect in early-life, but neurodegenerative effect in adulthood). However, we cannot discard chance findings. Future studies should evaluate trajectorial brain development using a longitudinal design.
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Affiliation(s)
- Esmée Essers
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra, Barcelona, Spain; Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain; Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Centre, Rotterdam, the Netherlands.
| | - Anne-Claire Binter
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra, Barcelona, Spain; Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Instituto de Salud Carlos III, Madrid, Spain.
| | - Alexander Neumann
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Centre, Rotterdam, the Netherlands; Complex Genetics of Alzheimer's Disease Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium; Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium.
| | - Tonya White
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Centre, Rotterdam, the Netherlands; Department of Radiology and Nuclear Medicine, Erasmus Medical Centre, Rotterdam, the Netherlands.
| | - Silvia Alemany
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health, and Addiction, Vall d'Hebron Research Institute, Barcelona, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Barcelona, Spain; Department of Psychiatry and Forensic Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain.
| | - Mònica Guxens
- ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra, Barcelona, Spain; Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Centre, Rotterdam, the Netherlands.
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Wu BS, Zhang YR, Yang L, Zhang W, Deng YT, Chen SD, Feng JF, Cheng W, Yu JT. Polygenic Liability to Alzheimer's Disease Is Associated with a Wide Range of Chronic Diseases: A Cohort Study of 312,305 Participants. J Alzheimers Dis 2023; 91:437-447. [PMID: 36442194 DOI: 10.3233/jad-220740] [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: 11/24/2022]
Abstract
BACKGROUND Alzheimer's disease (AD) patients rank among the highest levels of comorbidities compared to persons with other diseases. However, it is unclear whether the conditions are caused by shared pathophysiology due to the genetic pleiotropy for AD risk genes. OBJECTIVE To figure out the genetic pleiotropy for AD risk genes in a wide range of diseases. METHODS We estimated the polygenic risk score (PRS) for AD and tested the association between PRS and 16 ICD10 main chapters, 136 ICD10 level-1 chapters, and 377 diseases with cases more than 1,000 in 312,305 individuals without AD diagnosis from the UK Biobank. RESULTS After correction for multiple testing, AD PRS was associated with two main ICD10 chapters: Chapter IV (endocrine, nutritional and metabolic diseases) and Chapter VII (eye and adnexa disorders). When narrowing the definition of the phenotypes, positive associations were observed between AD PRS and other types of dementia (OR = 1.39, 95% CI [1.34, 1.45], p = 1.96E-59) and other degenerative diseases of the nervous system (OR = 1.18, 95% CI [1.13, 1.24], p = 7.74E-10). In contrast, we detected negative associations between AD PRS and diabetes mellitus, obesity, chronic bronchitis, other retinal disorders, pancreas diseases, and cholecystitis without cholelithiasis (ORs range from 0.94 to 0.97, FDR < 0.05). CONCLUSION Our study confirms several associations reported previously and finds some novel results, which extends the knowledge of genetic pleiotropy for AD in a range of diseases. Further mechanistic studies are necessary to illustrate the molecular mechanisms behind these associations.
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Affiliation(s)
- Bang-Sheng Wu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ya-Ru Zhang
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Liu Yang
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Wei Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Yue-Ting Deng
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Shi-Dong Chen
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jian-Feng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Department of Computer Science, University of Warwick, Coventry, UK
| | - Wei Cheng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China
| | - Jin-Tai Yu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
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Eissman JM, Wells G, Khan OA, Liu D, Petyuk VA, Gifford KA, Dumitrescu L, Jefferson AL, Hohman TJ. Polygenic resilience score may be sensitive to preclinical Alzheimer's disease changes. PACIFIC SYMPOSIUM ON BIOCOMPUTING. PACIFIC SYMPOSIUM ON BIOCOMPUTING 2023; 28:449-460. [PMID: 36540999 PMCID: PMC9888419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Late-onset Alzheimer's disease (LOAD) is a polygenic disorder with a long prodromal phase, making early diagnosis challenging. Twin studies estimate LOAD as 60-80% heritable, and while common genetic variants can account for 30% of this heritability, nearly 70% remains "missing". Polygenic risk scores (PRS) leverage combined effects of many loci to predict LOAD risk, but often lack sensitivity to preclinical disease changes, limiting clinical utility. Our group has built and published on a resilience phenotype to model better-than-expected cognition give amyloid pathology burden and hypothesized it may assist in preclinical polygenic risk prediction. Thus, we built a LOAD PRS and a resilience PRS and evaluated both in predicting cognition in a dementia-free cohort (N=254). The LOAD PRS had a significant main effect on baseline memory (β=-0.18, P=1.68E-03). Both the LOAD PRS (β=-0.03, P=1.19E-03) and the resilience PRS (β=0.02, P=0.03) had significant main effects on annual memory decline. The resilience PRS interacted with CSF Aβ on baseline memory (β=-6.04E-04, P=0.02), whereby it predicted baseline memory among Aβ+ individuals (β=0.44, P=0.01) but not among Aβ- individuals (β=0.06, P=0.46). Excluding APOE from PRS resulted in mainly LOAD PRS associations attenuating, but notably the resilience PRS interaction with CSF Aβ and selective prediction among Aβ+ individuals was consistent. Although the resilience PRS is currently somewhat limited in scope from the phenotype's cross-sectional nature, our results suggest that the resilience PRS may be a promising tool in assisting in preclinical disease risk prediction among dementia-free and Aβ+ individuals, though replication and fine-tuning are needed.
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Affiliation(s)
- Jaclyn M. Eissman
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN 37212, USA,Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Greyson Wells
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Omair A. Khan
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Dandan Liu
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Vladislav A. Petyuk
- Biological Sciences Division and Environmental Molecular Sciences Laboratory, Pacific Northwest, National Laboratory, Richland, WA 99354, USA
| | - Katherine A. Gifford
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Logan Dumitrescu
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN 37212, USA,Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Angela L. Jefferson
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Timothy J. Hohman
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN 37212, USA,Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37212, USA,
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Tomassen J, den Braber A, van der Lee SJ, Reus LM, Konijnenberg E, Carter SF, Yaqub M, van Berckel BNM, Collij LE, Boomsma DI, de Geus EJC, Scheltens P, Herholz K, Tijms BM, Visser PJ. Amyloid-β and APOE genotype predict memory decline in cognitively unimpaired older individuals independently of Alzheimer's disease polygenic risk score. BMC Neurol 2022; 22:484. [PMID: 36522743 PMCID: PMC9753236 DOI: 10.1186/s12883-022-02925-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 10/14/2022] [Accepted: 10/19/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND What combination of risk factors for Alzheimer's disease (AD) are most predictive of cognitive decline in cognitively unimpaired individuals remains largely unclear. We studied associations between APOE genotype, AD-Polygenic Risk Scores (AD-PRS), amyloid-β pathology and decline in cognitive functioning over time in a large sample of cognitively unimpaired older individuals. METHODS We included 276 cognitively unimpaired older individuals (75 ± 10 years, 63% female) from the EMIF-AD PreclinAD cohort. An AD-PRS was calculated including 83 genome-wide significant variants. The APOE gene was not included in the PRS and was analyzed separately. Baseline amyloid-β status was assessed by visual read of [18F]flutemetamol-PET standardized uptake value images. At baseline and follow-up (2.0 ± 0.4 years), the cognitive domains of memory, attention, executive function, and language were measured. We used generalized estimating equations corrected for age, sex and center to examine associations between APOE genotype and AD-PRS with amyloid-β status. Linear mixed models corrected for age, sex, center and education were used to examine associations between APOE genotype, AD-PRS and amyloid-β status, and their interaction on changes in cognitive functioning over time. RESULTS Fifty-two participants (19%) had abnormal amyloid-β, and 84 participants (31%) carried at least one APOE ε4 allele. APOE genotype and AD-PRS were both associated with abnormal amyloid-β status. Increasingly more risk-full APOE genotype, a high AD-PRS and an abnormal amyloid-β status were associated with steeper decline in memory functioning in separate models (all p ≤ 0.02). A model including 4-way interaction term (APOE×AD-PRS×amyloid-β×time) was not significant. When modelled together, both APOE genotype and AD-PRS predicted steeper decline in memory functioning (APOE β(SE)=-0.05(0.02); AD-PRS β(SE)=-0.04(0.01)). Additionally, when modelled together, both amyloid-β status and AD-PRS predicted a steeper decline in memory functioning (amyloid-β β(SE)=-0.07(0.04); AD-PRS β(SE)=-0.04(0.01)). Modelling both APOE genotype and amyloid-β status, we observed an interaction, in which APOE genotype was related to steeper decline in memory and language functioning in amyloid-β abnormal individuals only (β(SE)=-0.13(0.06); β(SE)=-0.22(0.07), respectively). CONCLUSION Our results suggest that APOE genotype is related to steeper decline in memory and language functioning in individuals with abnormal amyloid-β only. Furthermore, independent of amyloid-β status other genetic risk variants contribute to memory decline in initially cognitively unimpaired older individuals.
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Affiliation(s)
- Jori Tomassen
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands.
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands.
- Alzheimer Center Amsterdam, Neurology, Amsterdam UMC location VUmc, 1007 MB, Amsterdam, PO Box 7057, The Netherlands.
| | - Anouk den Braber
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Sven J van der Lee
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Genomics of Neurodegenerative Diseases and Aging, Human Genetics, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
| | - Lianne M Reus
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Elles Konijnenberg
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Stephen F Carter
- Wolfson Molecular Imaging Centre, Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, UK
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Maqsood Yaqub
- Department of Radiology & Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Bart N M van Berckel
- Department of Radiology & Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Lyduine E Collij
- Department of Radiology & Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Eco J C de Geus
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Karl Herholz
- Wolfson Molecular Imaging Centre, Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, UK
| | - Betty M Tijms
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
- Department of Neurobiology, Care Sciences and Society, Division of Neurogeriatrics, Karolinska Institutet, Stockholm, Sweden
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Mirza-Davies A, Foley S, Caseras X, Baker E, Holmans P, Escott-Price V, Jones DK, Harrison JR, Messaritaki E. The impact of genetic risk for Alzheimer's disease on the structural brain networks of young adults. Front Neurosci 2022; 16:987677. [PMID: 36532292 PMCID: PMC9748570 DOI: 10.3389/fnins.2022.987677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 11/09/2022] [Indexed: 12/02/2022] Open
Abstract
Introduction We investigated the structural brain networks of 562 young adults in relation to polygenic risk for Alzheimer's disease, using magnetic resonance imaging (MRI) and genotype data from the Avon Longitudinal Study of Parents and Children. Methods Diffusion MRI data were used to perform whole-brain tractography and generate structural brain networks for the whole-brain connectome, and for the default mode, limbic and visual subnetworks. The mean clustering coefficient, mean betweenness centrality, characteristic path length, global efficiency and mean nodal strength were calculated for these networks, for each participant. The connectivity of the rich-club, feeder and local connections was also calculated. Polygenic risk scores (PRS), estimating each participant's genetic risk, were calculated at genome-wide level and for nine specific disease pathways. Correlations were calculated between the PRS and (a) the graph theoretical metrics of the structural networks and (b) the rich-club, feeder and local connectivity of the whole-brain networks. Results In the visual subnetwork, the mean nodal strength was negatively correlated with the genome-wide PRS (r = -0.19, p = 1.4 × 10-3), the mean betweenness centrality was positively correlated with the plasma lipoprotein particle assembly PRS (r = 0.16, p = 5.5 × 10-3), and the mean clustering coefficient was negatively correlated with the tau-protein binding PRS (r = -0.16, p = 0.016). In the default mode network, the mean nodal strength was negatively correlated with the genome-wide PRS (r = -0.14, p = 0.044). The rich-club and feeder connectivities were negatively correlated with the genome-wide PRS (r = -0.16, p = 0.035; r = -0.15, p = 0.036). Discussion We identified small reductions in brain connectivity in young adults at risk of developing Alzheimer's disease in later life.
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Affiliation(s)
- Anastasia Mirza-Davies
- School of Medicine, University Hospital Wales, Cardiff University, Cardiff, United Kingdom
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Sonya Foley
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Xavier Caseras
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
| | - Emily Baker
- UK Dementia Research Institute, Cardiff University, Cardiff, United Kingdom
| | - Peter Holmans
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
| | - Valentina Escott-Price
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
- UK Dementia Research Institute, Cardiff University, Cardiff, United Kingdom
| | - Derek K. Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Judith R. Harrison
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
- Institute for Translational and Clinical Research, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Eirini Messaritaki
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
- BRAIN Biomedical Research Unit, School of Medicine, Cardiff University, Cardiff, United Kingdom
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Schilling LP, Balthazar MLF, Radanovic M, Forlenza OV, Silagi ML, Smid J, Barbosa BJAP, Frota NAF, Souza LCD, Vale FAC, Caramelli P, Bertolucci PHF, Chaves MLF, Brucki SMD, Damasceno BP, Nitrini R. Diagnosis of Alzheimer’s disease: recommendations of the Scientific Department of Cognitive Neurology and Aging of the Brazilian Academy of Neurology. Dement Neuropsychol 2022. [DOI: 10.1590/1980-5764-dn-2022-s102en] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/02/2023] Open
Abstract
ABSTRACT This paper presents the consensus of the Scientific Department of Cognitive Neurology and Aging from the Brazilian Academy of Neurology on the diagnostic criteria for Alzheimer’s disease (AD) in Brazil. The authors conducted a literature review regarding clinical and research criteria for AD diagnosis and proposed protocols for use at primary, secondary, and tertiary care levels. Within this clinical scenario, the diagnostic criteria for typical and atypical AD are presented as well as clinical, cognitive, and functional assessment tools and complementary propaedeutics with laboratory and neuroimaging tests. The use of biomarkers is also discussed for both clinical diagnosis (in specific conditions) and research.
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Affiliation(s)
- Lucas Porcello Schilling
- Pontifícia Universidade do Rio Grande do Sul, Brasil; Pontifícia Universidade do Rio Grande do Sul, Brasil; Pontifícia Universidade do Rio Grande do Sul, Brasil
| | | | | | | | - Marcela Lima Silagi
- Universidade Federal de São Paulo, Brasil; Universidade de São Paulo, Brasil
| | | | - Breno José Alencar Pires Barbosa
- Universidade de São Paulo, Brasil; Universidade Federal de Pernambuco, Brasil; Instituto de Medicina Integral Prof. Fernando Figueira, Brasil
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Schilling LP, Balthazar MLF, Radanovic M, Forlenza OV, Silagi ML, Smid J, Barbosa BJAP, Frota NAF, de Souza LC, Vale FAC, Caramelli P, Bertolucci PHF, Chaves MLF, Brucki SMD, Damasceno BP, Nitrini R. Diagnosis of Alzheimer's disease: recommendations of the Scientific Department of Cognitive Neurology and Aging of the Brazilian Academy of Neurology. Dement Neuropsychol 2022; 16:25-39. [PMID: 36533157 PMCID: PMC9745995 DOI: 10.1590/1980-5764-dn-2022-s102pt] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Revised: 11/22/2021] [Accepted: 04/27/2022] [Indexed: 01/25/2023] Open
Abstract
This paper presents the consensus of the Scientific Department of Cognitive Neurology and Aging from the Brazilian Academy of Neurology on the diagnostic criteria for Alzheimer's disease (AD) in Brazil. The authors conducted a literature review regarding clinical and research criteria for AD diagnosis and proposed protocols for use at primary, secondary, and tertiary care levels. Within this clinical scenario, the diagnostic criteria for typical and atypical AD are presented as well as clinical, cognitive, and functional assessment tools and complementary propaedeutics with laboratory and neuroimaging tests. The use of biomarkers is also discussed for both clinical diagnosis (in specific conditions) and research.
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Affiliation(s)
- Lucas Porcello Schilling
- Pontifícia Universidade do Rio Grande do Sul, Escola de Medicina, Serviço de Neurologia, Porto Alegre RS, Brasil
- Pontifícia Universidade do Rio Grande do Sul, Instituto do Cérebro do Rio Grande do Sul, Porto Alegre RS, Brasil
- Pontifícia Universidade do Rio Grande do Sul, Programa de Pós-Graduação em Gerontologia Biomédica, Porto Alegre RS, Brasil
| | | | - Márcia Radanovic
- Universidade de São Paulo, Faculdade de Medicina, Hospital das Clínicas, Instituto de Psiquiatria, Laboratório de Neurociências, São Paulo SP, Brasil
| | - Orestes Vicente Forlenza
- Universidade de São Paulo, Faculdade de Medicina, Hospital das Clínicas, Instituto de Psiquiatria, Laboratório de Neurociências, São Paulo SP, Brasil
- Universidade de São Paulo, Faculdade de Medicina, Departamento de Psiquiatria, São Paulo SP, Brasil
| | - Marcela Lima Silagi
- Universidade Federal de São Paulo, Departamento de Fonoaudiologia, São Paulo SP, Brasil
- Universidade de São Paulo, Faculdade de Medicina, Departamento de Neurologia, Grupo de Neurologia Cognitiva e do Comportamento, São Paulo SP, Brasil
| | - Jerusa Smid
- Universidade de São Paulo, Faculdade de Medicina, Departamento de Neurologia, Grupo de Neurologia Cognitiva e do Comportamento, São Paulo SP, Brasil
| | - Breno José Alencar Pires Barbosa
- Universidade de São Paulo, Faculdade de Medicina, Departamento de Neurologia, Grupo de Neurologia Cognitiva e do Comportamento, São Paulo SP, Brasil
- Universidade Federal de Pernambuco, Centro de Ciências Médicas, Área Acadêmica de Neuropsiquiatria, Recife PE, Brasil
- Instituto de Medicina Integral Prof. Fernando Figueira, Recife PE, Brasil
| | | | - Leonardo Cruz de Souza
- Universidade Federal de Minas Gerais, Departamento de Clínica Médica, Belo Horizonte MG, Brasil
| | - Francisco Assis Carvalho Vale
- Universidade Federal de São Carlos, Centro de Ciências Biológicas e da Saúde, Departamento de Medicina, São Carlos SP, Brasil
| | - Paulo Caramelli
- Universidade Federal de Minas Gerais, Departamento de Clínica Médica, Belo Horizonte MG, Brasil
| | | | - Márcia Lorena Fagundes Chaves
- Hospital de Clínicas de Porto Alegre, Serviço de Neurologia, Porto Alegre RS, Brasil
- Universidade Federal do Rio Grande do Sul, Faculdade de Medicina, Departamento de Medicina Interna, Porto Alegre RS, Brasil
| | - Sonia Maria Dozzi Brucki
- Universidade de São Paulo, Faculdade de Medicina, Departamento de Neurologia, Grupo de Neurologia Cognitiva e do Comportamento, São Paulo SP, Brasil
| | - Benito Pereira Damasceno
- Universidade Estadual de Campinas, Faculdade de Ciências Médicas, Departamento de Neurologia, Campinas SP, Brasil
| | - Ricardo Nitrini
- Universidade de São Paulo, Faculdade de Medicina, Departamento de Neurologia, Grupo de Neurologia Cognitiva e do Comportamento, São Paulo SP, Brasil
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Manzali SB, Yu E, Ravona-Springer R, Livny A, Golan S, Ouyang Y, Lesman-Segev O, Liu L, Ganmore I, Alkelai A, Gan-Or Z, Lin HM, Heymann A, Schnaider Beeri M, Greenbaum L. Alzheimer’s Disease Polygenic Risk Score Is Not Associated With Cognitive Decline Among Older Adults With Type 2 Diabetes. Front Aging Neurosci 2022; 14:853695. [PMID: 36110429 PMCID: PMC9468264 DOI: 10.3389/fnagi.2022.853695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 06/06/2022] [Indexed: 11/13/2022] Open
Abstract
ObjectivesMultiple risk loci for late-onset Alzheimer’s disease (LOAD) have been identified. Type 2 diabetes (T2D) is a risk factor for cognitive decline, dementia and Alzheimer’s disease (AD). We investigated the association of polygenic risk score (PRS) for LOAD with overall cognitive functioning and longitudinal decline, among older adults with T2D.MethodsThe study included 1046 Jewish participants from the Israel Diabetes and Cognitive Decline (IDCD) study, aged ≥ 65 years, diagnosed with T2D, and cognitively normal at baseline. The PRS included variants from 26 LOAD associated loci (at genome-wide significance level), and was calculated with and without APOE. Outcome measures, assessed in 18 months intervals, were global cognition and the specific domains of episodic memory, attention/working memory, executive functions, and language/semantic categorization. Random coefficient models were used for analysis, adjusting for demographic variables, T2D-related characteristics, and cardiovascular factors. Additionally, in a subsample of 202 individuals, we analyzed the association of PRS with the volumes of total gray matter, frontal lobe, hippocampus, amygdala, and white matter hyperintensities. Last, the association of PRS with amyloid beta (Aβ) burden was examined in 44 participants who underwent an 18F-flutemetamol PET scan.ResultsThe PRS was not significantly associated with overall functioning or decline in global cognition or any of the specific cognitive domains. Similarly, following correction for multiple testing, there was no association with Aβ burden and other brain imaging phenotypes.ConclusionOur results suggest that the cumulative effect of LOAD susceptibility loci is not associated with a greater rate of cognitive decline in older adults with T2D, and other pathways may underlie this link.
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Affiliation(s)
- Sigalit B. Manzali
- Department of Pathology, Sheba Medical Center, Tel Hashomer, Israel
- The Joseph Sagol Neuroscience Center, Sheba Medical Center, Tel Hashomer, Israel
| | - Eric Yu
- Department of Human Genetics, McGill University, Montréal, QC, Canada
- Montreal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Ramit Ravona-Springer
- The Joseph Sagol Neuroscience Center, Sheba Medical Center, Tel Hashomer, Israel
- Memory Clinic, Sheba Medical Center, Tel Hashomer, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Abigail Livny
- The Joseph Sagol Neuroscience Center, Sheba Medical Center, Tel Hashomer, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- Department of Diagnostic Imaging, Sheba Medical Center, Tel Hashomer, Israel
| | - Sapir Golan
- The Joseph Sagol Neuroscience Center, Sheba Medical Center, Tel Hashomer, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Yuxia Ouyang
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Orit Lesman-Segev
- The Joseph Sagol Neuroscience Center, Sheba Medical Center, Tel Hashomer, Israel
- Department of Diagnostic Imaging, Sheba Medical Center, Tel Hashomer, Israel
| | - Lang Liu
- Department of Human Genetics, McGill University, Montréal, QC, Canada
- Montreal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Ithamar Ganmore
- The Joseph Sagol Neuroscience Center, Sheba Medical Center, Tel Hashomer, Israel
- Memory Clinic, Sheba Medical Center, Tel Hashomer, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Anna Alkelai
- Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, United States
| | - Ziv Gan-Or
- Department of Human Genetics, McGill University, Montréal, QC, Canada
- Montreal Neurological Institute, McGill University, Montréal, QC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montréal, QC, Canada
| | - Hung-Mo Lin
- Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Anthony Heymann
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- Maccabi Healthcare Services, Tel Aviv, Israel
| | - Michal Schnaider Beeri
- The Joseph Sagol Neuroscience Center, Sheba Medical Center, Tel Hashomer, Israel
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Lior Greenbaum
- The Joseph Sagol Neuroscience Center, Sheba Medical Center, Tel Hashomer, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- The Danek Gertner Institute of Human Genetics, Sheba Medical Center, Tel Hashomer, Israel
- *Correspondence: Lior Greenbaum,
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Coors A, Imtiaz MA, Boenniger MM, Aziz NA, Ettinger U, Breteler MMB. Associations of genetic liability for Alzheimer's disease with cognition and eye movements in a large, population-based cohort study. Transl Psychiatry 2022; 12:337. [PMID: 35982049 PMCID: PMC9388528 DOI: 10.1038/s41398-022-02093-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Revised: 07/14/2022] [Accepted: 07/22/2022] [Indexed: 11/08/2022] Open
Abstract
To identify cognitive measures that may be particularly sensitive to early cognitive decline in preclinical Alzheimer's disease (AD), we investigated the relation between genetic risk for AD and cognitive task performance in a large population-based cohort study. We measured performance on memory, processing speed, executive function, crystallized intelligence and eye movement tasks in 5182 participants of the Rhineland Study, aged 30 to 95 years. We quantified genetic risk for AD by creating three weighted polygenic risk scores (PRS) based on the genome-wide significant single-nucleotide polymorphisms coming from three different genetic association studies. We assessed the relation of AD PRS with cognitive performance using generalized linear models. Three PRS were associated with lower performance on the Corsi forward task, and two PRS were associated with a lower probability of correcting antisaccade errors, but none of these associations remained significant after correction for multiple testing. Associations between age and trail-making test A (TMT-A) performance were modified by AD genetic risk, with individuals at high genetic risk showing the strongest association. We conclude that no single measure of our cognitive test battery robustly captures genetic liability for AD as quantified by current PRS. However, Corsi forward performance and the probability of correcting antisaccade errors may represent promising candidates whose ability to capture genetic liability for AD should be investigated further. Additionally, our finding on TMT-A performance suggests that processing speed represents a sensitive marker of AD genetic risk in old age and supports the processing speed theory of age-related cognitive decline.
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Affiliation(s)
- Annabell Coors
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Mohammed-Aslam Imtiaz
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Meta M Boenniger
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - N Ahmad Aziz
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurology, Faculty of Medicine, University of Bonn, Bonn, Germany
| | | | - Monique M B Breteler
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.
- Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, Bonn, Germany.
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Xicota L, Gyorgy B, Grenier-Boley B, Lecoeur A, Fontaine G, Danjou F, Gonzalez JS, Colliot O, Amouyel P, Martin G, Levy M, Villain N, Habert MO, Dubois B, Lambert JC, Potier MC. Association of APOE-Independent Alzheimer Disease Polygenic Risk Score With Brain Amyloid Deposition in Asymptomatic Older Adults. Neurology 2022; 99:e462-e475. [PMID: 35606148 PMCID: PMC9421597 DOI: 10.1212/wnl.0000000000200544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Accepted: 03/02/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Brain amyloid deposition, a major risk factor for Alzheimer disease (AD), is currently estimated by measuring CSF or plasma amyloid peptide levels or by PET imaging. Assessing genetic risks relating to amyloid deposition before any accumulation has occurred would allow for earlier intervention in persons at increased risk for developing AD. Previous work linking amyloid burden and genetic risk relied almost exclusively on APOE, a major AD genetic risk factor. Here, we ask whether a polygenic risk score (PRS) that incorporates an optimized list of common variants linked to AD and excludes APOE is associated with brain amyloid load in cognitively unimpaired older adults. METHODS We included 291 asymptomatic older participants from the INveStIGation of AlzHeimer's PredicTors (INSIGHT pre-AD) cohort who underwent amyloid imaging, including 83 amyloid-positive (+) participants. We used an Alzheimer's (A) PRS composed of 33 AD risk variants excluding APOE and selected the 17 variants that showed the strongest association with amyloid positivity to define an optimized (oA) PRS. Participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study (228 participants, 90 amyloid [+]) were tested as a validation cohort. Finally, 2,300 patients with AD and 6,994 controls from the European Alzheimer's Disease Initiative (EADI) were evaluated. RESULTS A-PRS was not significantly associated with amyloid burden in the INSIGHT or ADNI cohorts with or without correction for the APOE genotype. However, oA-PRS was significantly associated with amyloid status independently of APOE adjustment (INSIGHT odds ratio [OR]: 5.26 [1.71-16.88]; ADNI OR: 3.38 [1.02-11.63]). Of interest, oA-PRS accurately discriminated amyloid (+) and (-) APOE ε4 carriers (INSIGHT OR: 181.6 [7.53-10,674.6]; ADNI OR: 44.94 [3.03-1,277]). A-PRS and oA-PRS showed a significant association with disease status in the EADI cohort (OR: 1.68 [1.53-1.85] and 2.06 [1.73-2.45], respectively). Genes assigned to oA-PRS variants were enriched in ontologies related to β-amyloid metabolism and deposition. DISCUSSION PRSs relying on AD genetic risk factors excluding APOE may improve risk prediction for brain amyloid, allowing stratification of cognitively unimpaired individuals at risk of AD independent of their APOE status.
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Affiliation(s)
- Laura Xicota
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France
| | - Beata Gyorgy
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France
| | - Benjamin Grenier-Boley
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France
| | - Alexandre Lecoeur
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France
| | - Gaëlle Fontaine
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France
| | - Fabrice Danjou
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France
| | - Jorge Samper Gonzalez
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France
| | - Olivier Colliot
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France
| | - Philippe Amouyel
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France
| | - Garance Martin
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France
| | - Marcel Levy
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France
| | - Nicolas Villain
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France
| | - Marie-Odile Habert
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France
| | - Bruno Dubois
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France
| | - Jean-Charles Lambert
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France
| | - Marie-Claude Potier
- From the ICM Paris Brain Institute (L.X., B.G., A.L., G.«F., F.D., J.S.G., O.C., N.V., B.D., M.-C.P.), CNRS UMR7225, INSERM U1127, Sorbonne University, Hôpital de la Pitié-Salpêtrière; Univ. Lille (B.G.-B., P.A., J.-C.L.), Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement; Inria (J.S.G., O.C.), Aramis-Project Team, Paris; Centre d'Acquisition et Traitement des Images (CATI platform) (G.M., M.-O.H.), cati-neuroimaging.com, Paris; Centre des Maladies Cognitives et Comportementales (M.L., M.-O.H., B.D.), IM2A, AP-HP, Sorbonne Université, Hôpital de la Salpêtrière; Department of Neurology (N.V., B.D.), Hôpital Pitié-Salpêtrière, AP-HP Sorbonne Université; Sorbonne Université (M.-O.H.), CNRS, INSERM, Laboratoire d'Imagerie Biomédicale, LIB; and AP-HP (M.-O.H.), Hôpital Pitié-Salpêtrière, Médecine Nucléaire, Paris, France.
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Li Y, Xia M, Meng S, Wu D, Ling S, Chen X, Liu C. MicroRNA-29c-3p in dual-labeled exosome is a potential diagnostic marker of subjective cognitive decline. Neurobiol Dis 2022; 171:105800. [PMID: 35752392 DOI: 10.1016/j.nbd.2022.105800] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Revised: 04/25/2022] [Accepted: 06/19/2022] [Indexed: 11/19/2022] Open
Abstract
OBJECTIVE The present study aimed to determine whether peripheral blood neural cell adhesion molecule (NCAM)/amphiphysin 1 dual-labeled exosomal proteins and microRNAs (miRs) might serve as a marker for the early diagnosis of Alzheimer's disease (AD). METHODS This observational, retrospective, multicenter study used a two-stage design conducted in Beijing and Shanghai, China. The subjects included 76 patients with subjective cognitive decline (SCD), 80 with amnestic mild cognitive impairment (aMCI), 76 with dementia of Alzheimer's type (AD), 40 with vascular dementia (VaD), and 40 controls in the discovery stage. These results were confirmed in the verification stage. The levels of Aβ42, Aβ42/40, T-Tau, P-T181-tau, neurofilament light chain (NfL), and miR-29c-3p in peripheral blood amphiphysin 1 single-labeled and NCAM/amphiphysin 1 dual-labeled exosomes were captured and detected by immunoassay. RESULTS In the discovery stage, the levels of Aβ42 and miR-29c-3p in peripheral blood NCAM/amphiphysin 1 dual-labeled exosome of the SCD group were significantly higher than those in control and VaD groups (all P < 0.05). The verification stage further confirmed the results of the discovery stage. Plasma NCAM/amphiphysin 1 dual-labeled exosomal miR-29c-3p showed a good diagnostic performance. The NCAM/amphiphysin 1 dual-labeled exosomal miR-29c-3p had the highest AUC for diagnosis of SCD. The levels of Aβ42, Aβ42/40, Tau, P-T181-tau, and miR-29c-3p in peripheral blood exosomes were correlated to those in CSF (all P < 0.05). The combination of exosomal biomarkers had slightly higher diagnostic efficiency than the individual biomarkers and that the exosomal biomarkers had the same diagnostic power as the CSF biomarkers. CONCLUSION The plasma NCAM/amphiphysin 1 dual-labeled exosomal miR-29c-3p had potential advantages in the diagnosis of SCD.
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Affiliation(s)
- Ying Li
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing 100088, China; Clinical Laboratory of Air Force General Hospital, Chinese People's Liberation Army, Beijing 100142, China
| | - Ming Xia
- Clinical Laboratory of Minhang Hospital, Fudan University, Shanghai 201199, China
| | - Shuang Meng
- State Key Laboratory for Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Beijing 102206, China
| | - Di Wu
- Clinical Laboratory of Xuanwu Hospital, Captital Medcial University, Beijing 100053, China
| | - Sihai Ling
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing 100088, China
| | - Xiali Chen
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing 100088, China
| | - Chengeng Liu
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing 100088, China.
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Le Grand Q, Satizabal CL, Sargurupremraj M, Mishra A, Soumaré A, Laurent A, Crivello F, Tsuchida A, Shin J, Macalli M, Singh B, Beiser AS, DeCarli C, Fletcher E, Paus T, Lathrop M, Adams HHH, Bis JC, Seshadri S, Tzourio C, Mazoyer B, Debette S. Genomic Studies Across the Lifespan Point to Early Mechanisms Determining Subcortical Volumes. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2022; 7:616-628. [PMID: 34700051 PMCID: PMC9395126 DOI: 10.1016/j.bpsc.2021.10.011] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 09/28/2021] [Accepted: 10/14/2021] [Indexed: 11/17/2022]
Abstract
BACKGROUND Subcortical brain structures play a key role in pathological processes of age-related neurodegenerative disorders. Mounting evidence also suggests that early-life factors may have an impact on the development of common late-life neurological diseases, including genetic factors that can influence both brain maturation and neurodegeneration. METHODS Using large population-based brain imaging datasets across the lifespan (N ≤ 40,628), we aimed to 1) estimate the heritability of subcortical volumes in young (18-35 years), middle (35-65 years), and older (65+ years) age, and their genetic correlation across age groups; 2) identify whether genetic loci associated with subcortical volumes in older persons also show associations in early adulthood, and explore underlying genes using transcriptome-wide association studies; and 3) explore their association with neurological phenotypes. RESULTS Heritability of subcortical volumes consistently decreased with increasing age. Genetic risk scores for smaller caudate nucleus, putamen, and hippocampus volume in older adults were associated with smaller volumes in young adults. Individually, 10 loci associated with subcortical volumes in older adults also showed associations in young adults. Within these loci, transcriptome-wide association studies showed that expression of several genes in brain tissues (especially MYLK2 and TUFM) was associated with subcortical volumes in both age groups. One risk variant for smaller caudate nucleus volume (TUFM locus) was associated with lower cognitive performance. Genetically predicted Alzheimer's disease was associated with smaller subcortical volumes in middle and older age. CONCLUSIONS Our findings provide novel insights into the genetic determinants of subcortical volumes across the lifespan. More studies are needed to decipher the underlying biology and clinical impact.
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Affiliation(s)
- Quentin Le Grand
- University of Bordeaux, INSERM, Bordeaux Population Health Center, UMR1219, Bordeaux, France
| | - Claudia L Satizabal
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas; Department of Population Health Sciences, UT Health San Antonio, San Antonio, Texas; Framingham Heart Study, Framingham, Massachusetts; Department of Neurology, Boston University School of Medicine, Boston, Massachusetts
| | - Muralidharan Sargurupremraj
- University of Bordeaux, INSERM, Bordeaux Population Health Center, UMR1219, Bordeaux, France; Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas
| | - Aniket Mishra
- University of Bordeaux, INSERM, Bordeaux Population Health Center, UMR1219, Bordeaux, France
| | - Aicha Soumaré
- University of Bordeaux, INSERM, Bordeaux Population Health Center, UMR1219, Bordeaux, France
| | - Alexandre Laurent
- University of Bordeaux, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional imaging group, Bordeaux, France; CNRS, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional imaging group, Bordeaux, France; CEA, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional imaging group, Bordeaux, France
| | - Fabrice Crivello
- University of Bordeaux, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional imaging group, Bordeaux, France; CNRS, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional imaging group, Bordeaux, France; CEA, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional imaging group, Bordeaux, France
| | - Ami Tsuchida
- University of Bordeaux, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional imaging group, Bordeaux, France; CNRS, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional imaging group, Bordeaux, France; CEA, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional imaging group, Bordeaux, France
| | - Jean Shin
- Department of Physiology, Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada; Department of Nutritional Sciences, Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada
| | - Mélissa Macalli
- University of Bordeaux, INSERM, Bordeaux Population Health Center, UMR1219, Bordeaux, France
| | - Baljeet Singh
- Imaging of Dementia and Aging Laboratory, Department of Neurology, University of California Davis, Davis, California
| | - Alexa S Beiser
- Framingham Heart Study, Framingham, Massachusetts; Department of Neurology, Boston University School of Medicine, Boston, Massachusetts; Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - Charles DeCarli
- Imaging of Dementia and Aging Laboratory, Department of Neurology, University of California Davis, Davis, California
| | - Evan Fletcher
- Imaging of Dementia and Aging Laboratory, Department of Neurology, University of California Davis, Davis, California
| | - Tomas Paus
- Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada; Department of Psychology, University of Toronto, Toronto, Ontario, Canada; Department of Psychiatry, Centre Hospitalier Universitaire Sainte-Justine, Faculty of Medicine, University of Montreal, Montreal, Quebec, Canada
| | - Mark Lathrop
- McGill Genome Center, McGill University, Montreal, Quebec, Canada
| | - Hieab H H Adams
- Department of Radiology and Nuclear Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands; Department of Clinical Genetics, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas; Department of Population Health Sciences, UT Health San Antonio, San Antonio, Texas; Framingham Heart Study, Framingham, Massachusetts; Department of Neurology, Boston University School of Medicine, Boston, Massachusetts
| | - Christophe Tzourio
- University of Bordeaux, INSERM, Bordeaux Population Health Center, UMR1219, Bordeaux, France; Bordeaux University Hospital, Department of Medical Informatics, Bordeaux, France
| | - Bernard Mazoyer
- University of Bordeaux, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional imaging group, Bordeaux, France; CNRS, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional imaging group, Bordeaux, France; CEA, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional imaging group, Bordeaux, France; Bordeaux University Hospital, Department of Neuroradiology, Bordeaux, France
| | - Stéphanie Debette
- University of Bordeaux, INSERM, Bordeaux Population Health Center, UMR1219, Bordeaux, France; Bordeaux University Hospital, Department of Neurology, Institute of Neurodegenerative Diseases, Bordeaux, France.
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Ibnidris A, Fußer F, Kranz TM, Prvulovic D, Reif A, Pantel J, Albanese E, Karakaya T, Matura S. Investigating the Association Between Polygenic Risk Scores for Alzheimer’s Disease With Cognitive Performance and Intrinsic Functional Connectivity in Healthy Adults. Front Aging Neurosci 2022; 14:837284. [PMID: 35645768 PMCID: PMC9131016 DOI: 10.3389/fnagi.2022.837284] [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: 12/16/2021] [Accepted: 04/08/2022] [Indexed: 11/23/2022] Open
Abstract
Background Alzheimer’s disease (AD) pathology is present many years before the onset of clinical symptoms. AD dementia cannot be treated. Timely and early detection of people at risk of developing AD is key for primary and secondary prevention. Moreover, understanding the underlying pathology that is present in the earliest stages of AD, and the genetic predisposition to that might contribute to the development of targeted disease-modifying treatments. Objectives In this study, we aimed to explore whether genetic disposition to AD in asymptomatic individuals is associated with altered intrinsic functional connectivity as well as cognitive performance on neuropsychological tests. Methods We examined 136 cognitively healthy adults (old group: mean age = 69.32, SD = 4.23; young group: mean age = 31.34, SD = 13.12). All participants had undergone resting-state functional magnetic resonance imagining (fMRI), DNA genotyping to ascertain polygenic risk scores (PRS), and neuropsychological testing for global cognition, working memory, verbal fluency, and executive functions. Results Two-step hierarchical regression analysis revealed that higher PRS was significantly associated with lower scores in working memory tasks [Letter Number Span: ΔR2 = 0.077 (p < 0.05); Spatial Span: ΔR2 = 0.072 (p < 0.05)] in older adults (>60 years). PRS did not show significant modulations of the intrinsic functional connectivity of the posterior cingulate cortex (PCC) with other regions of interest in the brain that are affected in AD. Conclusion Allele polymorphisms may modify the effect of other AD risk factors. This potential modulation warrants further investigations, particularly in cognitively healthy adults.
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Affiliation(s)
- Aliaa Ibnidris
- Faculty of Biomedical Sciences, Università della Svizzera Italiana, Lugano, Switzerland
- Department of Psychiatry and Mental Health, University of Cape Town, Cape Town, South Africa
- *Correspondence: Aliaa Ibnidris,
| | - Fabian Fußer
- Department of Gerontopsychiatry, Psychosomatic Medicine, and Psychotherapy, Pfalzklinikum, Klingenmünster, Germany
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital, Goethe University Frankfurt, Frankfurt, Germany
| | - Thorsten M. Kranz
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital, Goethe University Frankfurt, Frankfurt, Germany
| | - David Prvulovic
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital, Goethe University Frankfurt, Frankfurt, Germany
| | - Andreas Reif
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital, Goethe University Frankfurt, Frankfurt, Germany
| | - Johannes Pantel
- Institute of General Practice, Goethe University Frankfurt, Frankfurt, Germany
| | - Emiliano Albanese
- Faculty of Biomedical Sciences, Università della Svizzera Italiana, Lugano, Switzerland
| | - Tarik Karakaya
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital, Goethe University Frankfurt, Frankfurt, Germany
| | - Silke Matura
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital, Goethe University Frankfurt, Frankfurt, Germany
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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] [Key Words] [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
| | - 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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Wu J, Chen Y, Wang P, Caselli RJ, Thompson PM, Wang J, Wang Y. Integrating Transcriptomics, Genomics, and Imaging in Alzheimer's Disease: A Federated Model. FRONTIERS IN RADIOLOGY 2022; 1:777030. [PMID: 37492173 PMCID: PMC10365097 DOI: 10.3389/fradi.2021.777030] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 12/21/2021] [Indexed: 07/27/2023]
Abstract
Alzheimer's disease (AD) affects more than 1 in 9 people age 65 and older and becomes an urgent public health concern as the global population ages. In clinical practice, structural magnetic resonance imaging (sMRI) is the most accessible and widely used diagnostic imaging modality. Additionally, genome-wide association studies (GWAS) and transcriptomics-the study of gene expression-also play an important role in understanding AD etiology and progression. Sophisticated imaging genetics systems have been developed to discover genetic factors that consistently affect brain function and structure. However, most studies to date focused on the relationships between brain sMRI and GWAS or brain sMRI and transcriptomics. To our knowledge, few methods have been developed to discover and infer multimodal relationships among sMRI, GWAS, and transcriptomics. To address this, we propose a novel federated model, Genotype-Expression-Imaging Data Integration (GEIDI), to identify genetic and transcriptomic influences on brain sMRI measures. The relationships between brain imaging measures and gene expression are allowed to depend on a person's genotype at the single-nucleotide polymorphism (SNP) level, making the inferences adaptive and personalized. We performed extensive experiments on publicly available Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. Experimental results demonstrated our proposed method outperformed state-of-the-art expression quantitative trait loci (eQTL) methods for detecting genetic and transcriptomic factors related to AD and has stable performance when data are integrated from multiple sites. Our GEIDI approach may offer novel insights into the relationship among image biomarkers, genotypes, and gene expression and help discover novel genetic targets for potential AD drug treatments.
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Affiliation(s)
- Jianfeng Wu
- School of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ, United States
| | - Yanxi Chen
- School of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ, United States
| | - Panwen Wang
- Department of Health Sciences Research and Center for Individualized Medicine, Mayo Clinic Arizona, Scottsdale, AZ, United States
| | - Richard J. Caselli
- Department of Neurology, Mayo Clinic Arizona, Scottsdale, AZ, United States
| | - Paul M. Thompson
- Imaging Genetics Center, Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Junwen Wang
- Department of Health Sciences Research and Center for Individualized Medicine, Mayo Clinic Arizona, Scottsdale, AZ, United States
| | - Yalin Wang
- School of Computing and Augmented Intelligence, Arizona State University, Tempe, AZ, United States
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46
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Clark K, Leung YY, Lee WP, Voight B, Wang LS. Polygenic Risk Scores in Alzheimer's Disease Genetics: Methodology, Applications, Inclusion, and Diversity. J Alzheimers Dis 2022; 89:1-12. [PMID: 35848019 PMCID: PMC9484091 DOI: 10.3233/jad-220025] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
The success of genome-wide association studies (GWAS) completed in the last 15 years has reinforced a key fact: polygenic architecture makes a substantial contribution to variation of susceptibility to complex disease, including Alzheimer's disease. One straight-forward way to capture this architecture and predict which individuals in a population are most at risk is to calculate a polygenic risk score (PRS). This score aggregates the risk conferred across multiple genetic variants, ultimately representing an individual's predicted genetic susceptibility for a disease. PRS have received increasing attention after having been successfully used in complex traits. This has brought with it renewed attention on new methods which improve the accuracy of risk prediction. While these applications are initially informative, their utility is far from equitable: the majority of PRS models use samples heavily if not entirely of individuals of European descent. This basic approach opens concerns of health equity if applied inaccurately to other population groups, or health disparity if we fail to use them at all. In this review we will examine the methods of calculating PRS and some of their previous uses in disease prediction. We also advocate for, with supporting scientific evidence, inclusion of data from diverse populations in these existing and future studies of population risk via PRS.
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Affiliation(s)
- Kaylyn Clark
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Yuk Yee Leung
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Wan-Ping Lee
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Benjamin Voight
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Institute of Translational Medicine and Therapeutics, Perelman School or Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Li-San Wang
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.,Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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47
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Tank R, Ward J, Flegal KE, Smith DJ, Bailey MES, Cavanagh J, Lyall DM. Association between polygenic risk for Alzheimer's disease, brain structure and cognitive abilities in UK Biobank. Neuropsychopharmacology 2022; 47:564-569. [PMID: 34621014 PMCID: PMC8674313 DOI: 10.1038/s41386-021-01190-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 08/05/2021] [Accepted: 09/14/2021] [Indexed: 02/07/2023]
Abstract
Previous studies testing associations between polygenic risk for late-onset Alzheimer's disease (LOAD-PGR) and brain magnetic resonance imaging (MRI) measures have been limited by small samples and inconsistent consideration of potential confounders. This study investigates whether higher LOAD-PGR is associated with differences in structural brain imaging and cognitive values in a relatively large sample of non-demented, generally healthy adults (UK Biobank). Summary statistics were used to create PGR scores for n = 32,790 participants using LDpred. Outcomes included 12 structural MRI volumes and 6 concurrent cognitive measures. Models were adjusted for age, sex, body mass index, genotyping chip, 8 genetic principal components, lifetime smoking, apolipoprotein (APOE) e4 genotype and socioeconomic deprivation. We tested for statistical interactions between APOE e4 allele dose and LOAD-PGR vs. all outcomes. In fully adjusted models, LOAD-PGR was associated with worse fluid intelligence (standardised beta [β] = -0.080 per LOAD-PGR standard deviation, p = 0.002), matrix completion (β = -0.102, p = 0.003), smaller left hippocampal total (β = -0.118, p = 0.002) and body (β = -0.069, p = 0.002) volumes, but not other hippocampal subdivisions. There were no significant APOE x LOAD-PGR score interactions for any outcomes in fully adjusted models. This is the largest study to date investigating LOAD-PGR and non-demented structural brain MRI and cognition phenotypes. LOAD-PGR was associated with smaller hippocampal volumes and aspects of cognitive ability in healthy adults and could supplement APOE status in risk stratification of cognitive impairment/LOAD.
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Affiliation(s)
- Rachana Tank
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Joey Ward
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Kristin E Flegal
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, UK
| | - Daniel J Smith
- Centre for Clinical Brain Sciences, Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Mark E S Bailey
- School of Life Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK
| | - Jonathan Cavanagh
- Institute of Infection, Immunity & Inflammation, University of Glasgow, Glasgow, UK
| | - Donald M Lyall
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.
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Sun Y, Wang M, Zhao Y, Hu K, Liu Y, Liu B. A Pathway-Specific Polygenic Risk Score is Associated with Tau Pathology and Cognitive Decline. J Alzheimers Dis 2021; 85:1745-1754. [DOI: 10.3233/jad-215163] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Background: Tauopathy is a primary neuropathological hallmark of Alzheimer’s disease with a strong relationship to cognitive impairment. In the brain, tau aggregation is associated with the regulation of tau kinases and the binding ability of tau to microtubules. Objective: To explore the potential for using specific polygenic risk scores (PRSs), combining the genetic influences involved in tau-protein kinases and the tau-protein binding pathway, as predictors of tau pathology and cognitive decline in non-demented individuals. Methods: We computed a pathway-specific PRS using summary statistics from previous large-scale genome-wide association studies of dementia. We examined whether PRS is related to tau uptake in positron emission tomography (PET), tau levels, and the rate of tau level changes in cerebrospinal fluid (CSF). We further assessed whether PRS is associated with memory impairment mediated by CSF tau levels. Results: A higher PRS was related to elevated CSF tau levels and tau-PET uptake at baseline, as well as greater rates of change in CSF tau levels. Moreover, PRS was associated with memory impairment, mediated by increased CSF tau levels. The association between PRS and tau pathology was significant when APOE was excluded, even among females. However, the effect of PRS on cognitive decline appeared to be driven by the inclusion of APOE. Conclusion: The influence of genetic risk in a specific tau-related biological pathway may make an individual more susceptible to tau pathology, resulting in cognitive dysfunction in an early preclinical phase of the disease.
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Affiliation(s)
- Yuqing Sun
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Meng Wang
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Yuxin Zhao
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Ke Hu
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Yong Liu
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | - Bing Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
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Dickson SP, Hendrix SB, Brown BL, Ridge PG, Nicodemus-Johnson J, Hardy ML, McKeany AM, Booth SB, Fortna RR, Kauwe JSK. GenoRisk: A polygenic risk score for Alzheimer's disease. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2021; 7:e12211. [PMID: 34621978 PMCID: PMC8485054 DOI: 10.1002/trc2.12211] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
INTRODUCTION Recent clinical trials are considering inclusion of more than just apolipoprotein E (APOE) ε4 genotype as a way of reducing variability in analysis of outcomes. METHODS Case-control data were used to compare the capacity of age, sex, and 58 Alzheimer's disease (AD)-associated single nucleotide polymorphisms (SNPs) to predict AD status using several statistical models. Model performance was assessed with Brier scores and tenfold cross-validation. Genotype and sex × age estimates from the best performing model were combined with age and intercept estimates from the general population to develop a personalized genetic risk score, termed age, and sex-adjusted GenoRisk. RESULTS The elastic net model that included age, age x sex interaction, allelic APOE terms, and 29 additional SNPs performed the best. This model explained an additional 19% of the heritable risk compared to APOE genotype alone and achieved an area under the curve of 0.747. DISCUSSION GenoRisk could improve the risk assessment of individuals identified for prevention studies.
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Affiliation(s)
| | | | - Bruce L Brown
- Department of Psychology Brigham Young University Provo Utah USA
| | - Perry G Ridge
- Department of Biology Brigham Young University-Hawaii Laie Hawaii USA
| | | | | | | | | | | | - John S K Kauwe
- Department of Psychology Brigham Young University Provo Utah USA
- Department of Biology Brigham Young University-Hawaii Laie Hawaii USA
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50
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Ebenau JL, van der Lee SJ, Hulsman M, Tesi N, Jansen IE, Verberk IM, van Leeuwenstijn M, Teunissen CE, Barkhof F, Prins ND, Scheltens P, Holstege H, van Berckel BN, van der Flier WM. Risk of dementia in APOE ε4 carriers is mitigated by a polygenic risk score. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2021; 13:e12229. [PMID: 34541285 PMCID: PMC8438688 DOI: 10.1002/dad2.12229] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Revised: 06/09/2021] [Accepted: 06/28/2021] [Indexed: 12/22/2022]
Abstract
INTRODUCTION We investigated relationships among genetic determinants of Alzheimer's disease (AD), amyloid/tau/neurodegenaration (ATN) biomarkers, and risk of dementia. METHODS We studied cognitively normal individuals with subjective cognitive decline (SCD) from the Amsterdam Dementia Cohort and SCIENCe project. We examined associations between genetic variants and ATN biomarkers, and evaluated their predictive value for incident dementia. A polygenic risk score (PRS) was calculated based on 39 genetic variants. The APOE gene was not included in the PRS and was analyzed separately. RESULTS The PRS and APOE ε4 were associated with amyloid-positive ATN profiles, and APOE ε4 additionally with isolated increased tau (A-T+N-). A high PRS and APOE ε4 separately predicted AD dementia. Combined, a high PRS increased while a low PRS attenuated the risk associated with ε4 carriers. DISCUSSION Genetic variants beyond APOE are clinically relevant and contribute to the pathophysiology of AD. In the future, a PRS might be used in individualized risk profiling.
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Affiliation(s)
- Jarith L. Ebenau
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Sven J. van der Lee
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Department of Clinical GeneticsAmsterdam UMCAmsterdamthe Netherlands
| | - Marc Hulsman
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Department of Clinical GeneticsAmsterdam UMCAmsterdamthe Netherlands
- Delft Bioinformatics LabDelft University of TechnologyDelftthe Netherlands
| | - Niccolò Tesi
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Department of Clinical GeneticsAmsterdam UMCAmsterdamthe Netherlands
- Delft Bioinformatics LabDelft University of TechnologyDelftthe Netherlands
| | - Iris E. Jansen
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Department of Complex Trait GeneticsCenter for Neurogenomics and Cognitive ResearchAmsterdam NeuroscienceVU UniversityAmsterdamthe Netherlands
| | - Inge M.W. Verberk
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Neurochemistry LaboratoryDepartment of Clinical ChemistryVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Mardou van Leeuwenstijn
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Charlotte E. Teunissen
- Neurochemistry LaboratoryDepartment of Clinical ChemistryVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Frederik Barkhof
- Department of Radiology & Nuclear MedicineAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image ComputingUniversity College LondonLondonUK
| | - Niels D. Prins
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Philip Scheltens
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Henne Holstege
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Department of Clinical GeneticsAmsterdam UMCAmsterdamthe Netherlands
- Delft Bioinformatics LabDelft University of TechnologyDelftthe Netherlands
| | - Bart N.M. van Berckel
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Department of Radiology & Nuclear MedicineAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Wiesje M. van der Flier
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Department of Epidemiology and BiostatisticsAmsterdam UMCAmsterdamthe Netherlands
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