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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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Elam JS, Glasser MF, Harms MP, Sotiropoulos SN, Andersson JLR, Burgess GC, Curtiss SW, Oostenveld R, Larson-Prior LJ, Schoffelen JM, Hodge MR, Cler EA, Marcus DM, Barch DM, Yacoub E, Smith SM, Ugurbil K, Van Essen DC. The Human Connectome Project: A retrospective. Neuroimage 2021; 244:118543. [PMID: 34508893 PMCID: PMC9387634 DOI: 10.1016/j.neuroimage.2021.118543] [Citation(s) in RCA: 72] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Revised: 08/13/2021] [Accepted: 08/30/2021] [Indexed: 01/21/2023] Open
Abstract
The Human Connectome Project (HCP) was launched in 2010 as an ambitious effort to accelerate advances in human neuroimaging, particularly for measures of brain connectivity; apply these advances to study a large number of healthy young adults; and freely share the data and tools with the scientific community. NIH awarded grants to two consortia; this retrospective focuses on the "WU-Minn-Ox" HCP consortium centered at Washington University, the University of Minnesota, and University of Oxford. In just over 6 years, the WU-Minn-Ox consortium succeeded in its core objectives by: 1) improving MR scanner hardware, pulse sequence design, and image reconstruction methods, 2) acquiring and analyzing multimodal MRI and MEG data of unprecedented quality together with behavioral measures from more than 1100 HCP participants, and 3) freely sharing the data (via the ConnectomeDB database) and associated analysis and visualization tools. To date, more than 27 Petabytes of data have been shared, and 1538 papers acknowledging HCP data use have been published. The "HCP-style" neuroimaging paradigm has emerged as a set of best-practice strategies for optimizing data acquisition and analysis. This article reviews the history of the HCP, including comments on key events and decisions associated with major project components. We discuss several scientific advances using HCP data, including improved cortical parcellations, analyses of connectivity based on functional and diffusion MRI, and analyses of brain-behavior relationships. We also touch upon our efforts to develop and share a variety of associated data processing and analysis tools along with detailed documentation, tutorials, and an educational course to train the next generation of neuroimagers. We conclude with a look forward at opportunities and challenges facing the human neuroimaging field from the perspective of the HCP consortium.
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Affiliation(s)
| | | | - Michael P Harms
- Washington University School of Medicine, St. Louis, MO, USA
| | - Stamatios N Sotiropoulos
- Sir Peter Mansfield Imaging Centre & NIHR Nottingham Biomedical Research Centre, Queen's Medical Centre, School of Medicine, University of Nottingham, UK; Wellcome Centre for Integrative Neuroimaging, University of Oxford, UK
| | | | | | | | - Robert Oostenveld
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, the Netherlands
| | | | - Jan-Mathijs Schoffelen
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, the Netherlands
| | - Michael R Hodge
- Washington University School of Medicine, St. Louis, MO, USA
| | - Eileen A Cler
- Washington University School of Medicine, St. Louis, MO, USA
| | - Daniel M Marcus
- Washington University School of Medicine, St. Louis, MO, USA
| | - Deanna M Barch
- Washington University School of Medicine, St. Louis, MO, USA
| | - Essa Yacoub
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
| | - Stephen M Smith
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, UK
| | - Kamil Ugurbil
- Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, USA
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Murray AN, Chandler HL, Lancaster TM. Multimodal hippocampal and amygdala subfield volumetry in polygenic risk for Alzheimer's disease. Neurobiol Aging 2020; 98:33-41. [PMID: 33227567 PMCID: PMC7886309 DOI: 10.1016/j.neurobiolaging.2020.08.022] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2020] [Revised: 07/28/2020] [Accepted: 08/02/2020] [Indexed: 11/29/2022]
Abstract
Preclinical models of Alzheimer's disease (AD) suggest that volumetric reductions in medial temporal lobe (MTL) structures manifest before clinical onset. AD polygenic risk scores (PRSs) are further linked to reduced MTL volumes (the hippocampus/amygdala); however, the relationship between the PRS and specific subregions remains unclear. We determine the relationship between the AD-PRSs and MTL subregions in a large sample of young participants (N = 730, aged 22–35 years) using a multimodal (T1w/T2w) approach. We first demonstrate that the PRSs for the hippocampus/amygdala predict their respective volumes and specific hippocampal subregions (pFDR < 0.05). We further observe negative relationships between the AD-PRSs and whole hippocampal/amygdala volumes. Critically, we demonstrate novel associations between the AD-PRSs and specific hippocampal subfields such as CA1 (β = −0.096, pFDR = 0.045) and the fissure (β = −0.101, pFDR = 0.041). We provide evidence that the AD-PRS is linked to specific MTL subfields decades before AD onset. This may help inform preclinical models of AD risk, providing additional specificity for intervention and further insight into mechanisms by which common AD variants confer susceptibility. Polygenic risk for Alzheimer's disease (AD-PRS) explains significant proportion of AD. AD-PRS also linked to hippocampus and amygdala volume. AD-PRS is negatively associated with specific hippocampal subfields. Polygenic AD models help us understand genetic contributions to medial temporal lobe nuclei.
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Affiliation(s)
- Amy N Murray
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Hannah L Chandler
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
| | - Thomas M Lancaster
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom; Dementia Research Institute at Cardiff University, School of Medicine, Cardiff University, Cardiff, United Kingdom; School of Psychology, Bath University, Bath, United Kingdom.
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Olive C, Ibanez L, Farias FHG, Wang F, Budde JP, Norton JB, Gentsch J, Morris JC, Li Z, Dube U, Del-Aguila J, Bergmann K, Bradley J, Benitez BA, Harari O, Fagan A, Ances B, Cruchaga C, Fernandez MV. Examination of the Effect of Rare Variants in TREM2, ABI3, and PLCG2 in LOAD Through Multiple Phenotypes. J Alzheimers Dis 2020; 77:1469-1482. [PMID: 32894242 PMCID: PMC7927150 DOI: 10.3233/jad-200019] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
BACKGROUND Rare variants in PLCG2 (p.P522R), ABI3 (p.S209F), and TREM2 (p.R47H, p.R62H) have been associated with late onset Alzheimer's disease (LOAD) risk in Caucasians. After the initial report, several studies have found positive results in cohorts of different ethnic background and with different phenotype. OBJECTIVE In this study, we aim to evaluate the association of rare coding variants in PLCG2, ABI3, and TREM2 with LOAD risk and their effect at different time points of the disease. METHODS We used a European American cohort to assess the association of the variants prior onset (using CSF Aβ42, tau, and pTau levels, and amyloid imaging as endophenotypes) and after onset (measured as rate of memory decline). RESULTS We confirm the association with LOAD risk of TREM2 p.R47H, p.R62H and ABI3 p.S209F variants, and the protective effect of PLCG2 p.P522R. In addition, ABI3 and TREM2 gene-sets showed significant association with LOAD risk. TREM2 p.R47H and PLCG2 p.P522R variants were also statistically associated with increase of amyloid imaging and AD progression, respectively. We did not observe any association of ABI3 p.S209F with any of the other AD endophenotypes. CONCLUSION The results of this study highlight the importance of including biomarkers and alternative phenotypes to better understand the role of novel candidate genes with the disease.
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Affiliation(s)
- Claudia Olive
- Neurogenomics and Informatics Center, Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Laura Ibanez
- Neurogenomics and Informatics Center, Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Fabiana H. Geraldo Farias
- Neurogenomics and Informatics Center, Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Fengxian Wang
- Neurogenomics and Informatics Center, Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - John P. Budde
- Neurogenomics and Informatics Center, Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Joanne B. Norton
- Neurogenomics and Informatics Center, Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Jen Gentsch
- Neurogenomics and Informatics Center, Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - John C. Morris
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Zeran Li
- Neurogenomics and Informatics Center, Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Umber Dube
- Neurogenomics and Informatics Center, Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Jorge Del-Aguila
- Neurogenomics and Informatics Center, Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Kristy Bergmann
- Neurogenomics and Informatics Center, Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Joseph Bradley
- Neurogenomics and Informatics Center, Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Bruno A. Benitez
- Neurogenomics and Informatics Center, Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Oscar Harari
- Neurogenomics and Informatics Center, Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Anne Fagan
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Beau Ances
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Carlos Cruchaga
- Neurogenomics and Informatics Center, Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Maria Victoria Fernandez
- Neurogenomics and Informatics Center, Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
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