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Wagemann O, Liu H, Wang G, Shi X, Bittner T, Scelsi MA, Farlow MR, Clifford DB, Supnet-Bell C, Santacruz AM, Aschenbrenner AJ, Hassenstab JJ, Benzinger TLS, Gordon BA, Coalier KA, Cruchaga C, Ibanez L, Perrin RJ, Xiong C, Li Y, Morris JC, Lah JJ, Berman SB, Roberson ED, van Dyck CH, Galasko D, Gauthier S, Hsiung GYR, Brooks WS, Pariente J, Mummery CJ, Day GS, Ringman JM, Mendez PC, St. George-Hyslop P, Fox NC, Suzuki K, Okhravi HR, Chhatwal J, Levin J, Jucker M, Sims JR, Holdridge KC, Proctor NK, Yaari R, Andersen SW, Mancini M, Llibre-Guerra J, Bateman RJ, McDade E. Downstream Biomarker Effects of Gantenerumab or Solanezumab in Dominantly Inherited Alzheimer Disease: The DIAN-TU-001 Randomized Clinical Trial. JAMA Neurol 2024:2817630. [PMID: 38683602 PMCID: PMC11059071 DOI: 10.1001/jamaneurol.2024.0991] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Accepted: 02/01/2024] [Indexed: 05/01/2024]
Abstract
Importance Effects of antiamyloid agents, targeting either fibrillar or soluble monomeric amyloid peptides, on downstream biomarkers in cerebrospinal fluid (CSF) and plasma are largely unknown in dominantly inherited Alzheimer disease (DIAD). Objective To investigate longitudinal biomarker changes of synaptic dysfunction, neuroinflammation, and neurodegeneration in individuals with DIAD who are receiving antiamyloid treatment. Design, Setting, and Participants From 2012 to 2019, the Dominantly Inherited Alzheimer Network Trial Unit (DIAN-TU-001) study, a double-blind, placebo-controlled, randomized clinical trial, investigated gantenerumab and solanezumab in DIAD. Carriers of gene variants were assigned 3:1 to either drug or placebo. The present analysis was conducted from April to June 2023. DIAN-TU-001 spans 25 study sites in 7 countries. Biofluids and neuroimaging from carriers of DIAD gene variants in the gantenerumab, solanezumab, and placebo groups were analyzed. Interventions In 2016, initial dosing of gantenerumab, 225 mg (subcutaneously every 4 weeks) was increased every 8 weeks up to 1200 mg. In 2017, initial dosing of solanezumab, 400 mg (intravenously every 4 weeks) was increased up to 1600 mg every 4 weeks. Main Outcomes and Measures Longitudinal changes in CSF levels of neurogranin, soluble triggering receptor expressed on myeloid cells 2 (sTREM2), chitinase 3-like 1 protein (YKL-40), glial fibrillary acidic protein (GFAP), neurofilament light protein (NfL), and plasma levels of GFAP and NfL. Results Of 236 eligible participants screened, 43 were excluded. A total of 142 participants (mean [SD] age, 44 [10] years; 72 female [51%]) were included in the study (gantenerumab, 52 [37%]; solanezumab, 50 [35%]; placebo, 40 [28%]). Relative to placebo, gantenerumab significantly reduced CSF neurogranin level at year 4 (mean [SD] β = -242.43 [48.04] pg/mL; P < .001); reduced plasma GFAP level at year 1 (mean [SD] β = -0.02 [0.01] ng/mL; P = .02), year 2 (mean [SD] β = -0.03 [0.01] ng/mL; P = .002), and year 4 (mean [SD] β = -0.06 [0.02] ng/mL; P < .001); and increased CSF sTREM2 level at year 2 (mean [SD] β = 1.12 [0.43] ng/mL; P = .01) and year 4 (mean [SD] β = 1.06 [0.52] ng/mL; P = .04). Solanezumab significantly increased CSF NfL (log) at year 4 (mean [SD] β = 0.14 [0.06]; P = .02). Correlation analysis for rates of change found stronger correlations between CSF markers and fluid markers with Pittsburgh compound B positron emission tomography for solanezumab and placebo. Conclusions and Relevance This randomized clinical trial supports the importance of fibrillar amyloid reduction in multiple AD-related processes of neuroinflammation and neurodegeneration in CSF and plasma in DIAD. Additional studies of antiaggregated amyloid therapies in sporadic AD and DIAD are needed to determine the utility of nonamyloid biomarkers in determining disease modification. Trial Registration ClinicalTrials.gov Identifier: NCT04623242.
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Affiliation(s)
- Olivia Wagemann
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
- Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Haiyan Liu
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
| | - Guoqiao Wang
- Department of Biostatistics, Washington University in St Louis, St Louis, Missouri
| | - Xinyu Shi
- Department of Biostatistics, Washington University in St Louis, St Louis, Missouri
| | | | - Marzia A. Scelsi
- F. Hoffmann-La Roche Products Ltd, Welwyn Garden City, United Kingdom
| | - Martin R. Farlow
- Department of Neurology, Indiana University School of Medicine, Indianapolis
| | - David B. Clifford
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
| | - Charlene Supnet-Bell
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
| | - Anna M. Santacruz
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
| | | | - Jason J. Hassenstab
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
| | | | - Brian A. Gordon
- Department of Radiology, Washington University in St Louis, St Louis, Missouri
| | | | - Carlos Cruchaga
- Department of Psychiatry, Washington University in St Louis, St Louis, Missouri
| | - Laura Ibanez
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
- Department of Psychiatry, Washington University in St Louis, St Louis, Missouri
| | - Richard J. Perrin
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
- Department of Pathology and Immunology, Washington University in St Louis, St Louis, Missouri
| | - Chengjie Xiong
- Department of Biostatistics, Washington University in St Louis, St Louis, Missouri
| | - Yan Li
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
| | - John C. Morris
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
| | - James J. Lah
- Department of Neurology, School of Medicine Emory University, Atlanta, Georgia
| | - Sarah B. Berman
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Erik D. Roberson
- Department of Neurology, University of Alabama at Birmingham, Birmingham
| | | | - Douglas Galasko
- Department of Neurology, University of California, San Diego
| | - Serge Gauthier
- Department of Neurology & Psychiatry, McGill University, Montréal, Québec, Canada
| | - Ging-Yuek R. Hsiung
- Department of Neurology, University of British Columbia, Vancouver, British Columbia, Canada
| | - William S. Brooks
- Neuroscience Research Australia, Sydney, New South Wales, Australia
- School of Clinical Medicine, University of New South Wales, Randwick, New South Wales, Australia
| | - Jérémie Pariente
- Department of Neurology, Centre Hospitalier Universitaire de Toulouse, Toulouse, France
| | - Catherine J. Mummery
- Dementia Research Centre, Institute of Neurology, University College London, London, United Kingdom
| | - Gregory S. Day
- Department of Neurology, Mayo Clinic Florida, Jacksonville
| | - John M. Ringman
- Department of Neurology, University of Southern California, Los Angeles
| | - Patricio Chrem Mendez
- Fundación Para la Lucha Contra las Enfermedades Neurológicas de la Infancia (FLENI), Buenos Aires, Argentina
| | | | - Nick C. Fox
- Dementia Research Centre, Institute of Neurology, University College London, London, United Kingdom
| | | | - Hamid R. Okhravi
- Department of Geriatrics, Eastern Virginia Medical School, Norfolk
| | - Jasmeer Chhatwal
- Department of Neurology, Massachusetts General and Brigham & Women’s Hospitals, Harvard Medical School, Boston
| | - Johannes Levin
- Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Mathias Jucker
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
- Department of Cellular Neurology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | | | | | | | - Roy Yaari
- Eli Lilly and Company, Indianapolis, Indiana
| | | | | | - Jorge Llibre-Guerra
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
| | - Randall J. Bateman
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
| | - Eric McDade
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
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Boess FG, Scelsi MA, Grimmer T, Perry RJ, Tonietto M, Klein G, Hofmann C, Salami M, Wojtowicz J, Lansdall CJ, Lane C, Kerchner GA, Smith J, Doody RS. At-Home Administration of Gantenerumab by Care Partners to People with Early Alzheimer's Disease: Feasibility, Safety and Pharmacodynamic Impact. J Prev Alzheimers Dis 2024; 11:537-548. [PMID: 38706270 DOI: 10.14283/jpad.2024.60] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/07/2024]
Abstract
BACKGROUND Monoclonal antibodies that target amyloid-beta and remove amyloid plaques can slow cognitive and functional decline in early Alzheimer's disease. Gantenerumab is a subcutaneously administered fully-human anti-amyloid-beta monoclonal antibody with highest affinity for aggregated amyloid-beta. Since the phase 3 GRADUATE trials did not meet the primary endpoint (change from baseline to Week 116 in Clinical Dementia Rating scale - Sum of Boxes), development of gantenerumab in sporadic Alzheimer's disease was stopped and all ongoing trials were terminated early due to sponsor decision. Subcutaneous administration at the clinic or at home by care partner would be an important option for other therapies in this class in order to increase flexibility and reduce overall burden. The insights obtained from the experience with gantenerumab home administration by care partner in the phase 2 GRADUATION trial will serve to guide the ongoing efforts with other anti-amyloid-beta antibodies. OBJECTIVES To evaluate the pharmacodynamic effects on brain amyloid load of once weekly subcutaneous administration of gantenerumab and the safety and feasibility of home administration by care partners. DESIGN Phase 2, open-label, single arm study. SETTING Multicenter trial conducted in 33 sites in 8 countries from November 2020 to March 2023. PARTICIPANTS Participants aged 50 to 90 with early symptomatic Alzheimer's disease (mild cognitive impairment/mild dementia due to Alzheimer's disease), and evidence of amyloid positron emission tomography positivity. INTERVENTION Participants could receive up to 255 mg gantenerumab once-weekly, administered subcutaneously at site or at home by healthcare professionals or non-healthcare-professional care partners. MEASUREMENTS The primary endpoint was the change from baseline to Week 52 and to Week 104 in brain amyloid load as measured by PET centiloid levels. The secondary endpoints were responses to the home administration questionnaire, plasma concentrations and safety. RESULTS The overall number of participants enrolled was 192, with a mean (standard deviation) amyloid PET load at baseline of 101.80 (29.80) centiloids. At the time of early study termination by sponsor, 149 participants had valid Week 52 amyloid PET data (primary endpoint), and 12 participants had an early termination PET within the pre-defined time range of Week 104. The mean change in amyloid PET from baseline to Week 52 and Week 104 was -26.19 centiloids (range: -75.6-15.8; n=149) and -35.48 centiloids (range: -63.2--7.0; n=12), respectively. Responses to the home administration questionnaire at Week 52 (n=148) indicated that the majority of care partners (88-97%) considered administration of study drug at home easy (30.4%) or very easy (57.4%), and convenient (25.7%) or very convenient (70.9%). Care partners felt confident (31.1%) or very confident (62.2%) and satisfied (29.7%) or very satisfied (64.9%) with giving the injection at home. Responses by care partners at Week 36 (n=72), Week 76 (n=126) and Week 104 (n=29) and participant (patient) assessment of convenience and satisfaction at these time points were similar. There were no new safety findings associated with gantenerumab administered subcutaneously once weekly at 255 mg or safety issues associated with at-home injections by non-healthcare professional care partners. CONCLUSIONS Once-weekly subcutaneous home administration of the anti-amyloid-beta antibody gantenerumab by non-healthcare-professional care partners to participants with early Alzheimer's disease was feasible, safe, well tolerated, and considered as a convenient option by both the care partners and participants with Alzheimer's disease. Although gantenerumab's development has been stopped due to lack of efficacy, this approach has the potential to reduce the frequency of hospital/outpatient clinic visits required for treatment with other anti-amyloid-β antibodies and can increase flexibility of drug administration for people living with Alzheimer's disease and their families.
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Affiliation(s)
- F G Boess
- Frank G. Boess, Ph.D., F. Hoffmann-La Roche Ltd, Grenzacherstrasse 124, 4070 Basel, Switzerland, E-mail:
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Aksman LM, Oxtoby NP, Scelsi MA, Wijeratne PA, Young AL, Alves IL, Collij LE, Vogel JW, Barkhof F, Alexander DC, Altmann A. A data-driven study of Alzheimer's disease related amyloid and tau pathology progression. Brain 2023; 146:4935-4948. [PMID: 37433038 PMCID: PMC10690020 DOI: 10.1093/brain/awad232] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 06/12/2023] [Accepted: 06/29/2023] [Indexed: 07/13/2023] Open
Abstract
Amyloid-β is thought to facilitate the spread of tau throughout the neocortex in Alzheimer's disease, though how this occurs is not well understood. This is because of the spatial discordance between amyloid-β, which accumulates in the neocortex, and tau, which accumulates in the medial temporal lobe during ageing. There is evidence that in some cases amyloid-β-independent tau spreads beyond the medial temporal lobe where it may interact with neocortical amyloid-β. This suggests that there may be multiple distinct spatiotemporal subtypes of Alzheimer's-related protein aggregation, with potentially different demographic and genetic risk profiles. We investigated this hypothesis, applying data-driven disease progression subtyping models to post-mortem neuropathology and in vivo PET-based measures from two large observational studies: the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Religious Orders Study and Rush Memory and Aging Project (ROSMAP). We consistently identified 'amyloid-first' and 'tau-first' subtypes using cross-sectional information from both studies. In the amyloid-first subtype, extensive neocortical amyloid-β precedes the spread of tau beyond the medial temporal lobe, while in the tau-first subtype, mild tau accumulates in medial temporal and neocortical areas prior to interacting with amyloid-β. As expected, we found a higher prevalence of the amyloid-first subtype among apolipoprotein E (APOE) ε4 allele carriers while the tau-first subtype was more common among APOE ε4 non-carriers. Within tau-first APOE ε4 carriers, we found an increased rate of amyloid-β accumulation (via longitudinal amyloid PET), suggesting that this rare group may belong within the Alzheimer's disease continuum. We also found that tau-first APOE ε4 carriers had several fewer years of education than other groups, suggesting a role for modifiable risk factors in facilitating amyloid-β-independent tau. Tau-first APOE ε4 non-carriers, in contrast, recapitulated many of the features of primary age-related tauopathy. The rate of longitudinal amyloid-β and tau accumulation (both measured via PET) within this group did not differ from normal ageing, supporting the distinction of primary age-related tauopathy from Alzheimer's disease. We also found reduced longitudinal subtype consistency within tau-first APOE ε4 non-carriers, suggesting additional heterogeneity within this group. Our findings support the idea that amyloid-β and tau may begin as independent processes in spatially disconnected regions, with widespread neocortical tau resulting from the local interaction of amyloid-β and tau. The site of this interaction may be subtype-dependent: medial temporal lobe in amyloid-first, neocortex in tau-first. These insights into the dynamics of amyloid-β and tau may inform research and clinical trials that target these pathologies.
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Affiliation(s)
- Leon M Aksman
- Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London WC1V 6LJ, UK
| | - Neil P Oxtoby
- Centre for Medical Image Computing, Department of Computer Science, University College London, London WC1V 6LJ, UK
| | - Marzia A Scelsi
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London WC1V 6LJ, UK
| | - Peter A Wijeratne
- Centre for Medical Image Computing, Department of Computer Science, University College London, London WC1V 6LJ, UK
| | - Alexandra L Young
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
- Centre for Medical Image Computing, Department of Computer Science, University College London, London WC1V 6LJ, UK
| | | | - Lyduine E Collij
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam 1007MB, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam 1081 HV, The Netherlands
| | - Jacob W Vogel
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Frederik Barkhof
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London WC1V 6LJ, UK
- Brain Research Center, Amsterdam 1081 GN, The Netherlands
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam 1007MB, The Netherlands
| | - Daniel C Alexander
- Centre for Medical Image Computing, Department of Computer Science, University College London, London WC1V 6LJ, UK
| | - Andre Altmann
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London WC1V 6LJ, UK
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Bracoud L, Klein G, Lyons M, Scelsi MA, Wojtowicz J, Bullain S, Purcell D, Fiebach JB, Barakos J, Suhy J. Validation of 3- and 5-point severity scales to assess ARIA-E. Alzheimers Dement (Amst) 2023; 15:e12503. [PMID: 38026755 PMCID: PMC10667607 DOI: 10.1002/dad2.12503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 10/03/2023] [Accepted: 10/22/2023] [Indexed: 12/01/2023]
Abstract
INTRODUCTION Anti-amyloid-β (Aβ) monoclonal antibodies (mAbs) offer the promise of disease modification and are emerging treatment options in Alzheimer's disease. Anti-Aβ mAbs require brain magnetic resonance imaging (MRI) examinations to detect anti-amyloid-induced amyloid-related imaging abnormalities (ARIA), important adverse drug reactions associated with some anti-Aβ mAbs currently available in the United States and in clinical development. We present a simple rating system for ARIA-edema (ARIA-E) that can assess severity on a 3- or 5-point scale based upon a single linear measurement of the largest area of lesion, and dissemination in space, termed the 3-point Severity Scale of ARIA-E (SSAE-3) and the 5-point Severity Scale of ARIA-E (SSAE-5), respectively. METHODS MRI results were collected from 75 participants from the SCarlet RoAD (NCT01224106) and Marguerite RoAD (NCT02051608) studies of gantenerumab. Three neuroradiologists experienced with the detection of ARIA-E were selected to read all cases independently. One rater was then chosen for a second read to assess intra-reader reproducibility. RESULTS The three raters had high agreement in identifying and grading ARIA-E. The Cohen/Fleiss kappa (κ) scores (95% confidence interval [CI]) for the inter- and intra-reader comparisons for SSAE-3 and SSAE-5 were 0.79 (0.70-1.00), 0.94 (0.94-1.00), 0.73 (0.66-1.00), and 0.90 (0.90-1.00), respectively. DISCUSSION Our study suggests that SSAE-3 and SSAE-5 are valid ARIA-E rating scales for use in routine clinical practice by experienced radiologists in specialized settings. The application of these scales in everyday use in clinical practice will support the expansion of anti-Aβ mAbs as a treatment option for people living with Alzheimer's disease. Highlights A simple rating scale is needed to rate severity of amyloid-related imaging abnormalities-edema (ARIA-E) in both research and clinical settings.The 3- and 5-point Severity Scales of ARIA-E (SSAE-3/-5) have good inter- and intra-reader agreement.The SSAE-3/-5 have been used in most major Alzheimer's disease (AD) trials to date and are suitable for large-scale use in routine clinical practice, which may help support the expansion of anti-amyloid antibodies as treatment options for AD.
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Affiliation(s)
- Luc Bracoud
- Clario, Inc. (formerly Bioclinica, Inc.)LyonFrance
| | | | | | | | | | | | - Derk Purcell
- California Pacific Medical CenterSan FranciscoCaliforniaUSA
| | - Jochen B. Fiebach
- Center for Stroke Research BerlinCharité – Universitätsmedizin BerlinBerlinGermany
| | - Jerome Barakos
- California Pacific Medical CenterSan FranciscoCaliforniaUSA
| | - Joyce Suhy
- Clario, Inc. (formerly Bioclinica, Inc.)San MateoCaliforniaUSA
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5
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Green RE, Lord J, Scelsi MA, Xu J, Wong A, Naomi-James S, Handy A, Gilchrist L, Williams DM, Parker TD, Lane CA, Malone IB, Cash DM, Sudre CH, Coath W, Thomas DL, Keuss S, Dobson R, Legido-Quigley C, Fox NC, Schott JM, Richards M, Proitsi P. Investigating associations between blood metabolites, later life brain imaging measures, and genetic risk for Alzheimer's disease. Alzheimers Res Ther 2023; 15:38. [PMID: 36814324 PMCID: PMC9945600 DOI: 10.1186/s13195-023-01184-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 02/08/2023] [Indexed: 02/24/2023]
Abstract
BACKGROUND Identifying blood-based signatures of brain health and preclinical pathology may offer insights into early disease mechanisms and highlight avenues for intervention. Here, we systematically profiled associations between blood metabolites and whole-brain volume, hippocampal volume, and amyloid-β status among participants of Insight 46-the neuroscience sub-study of the National Survey of Health and Development (NSHD). We additionally explored whether key metabolites were associated with polygenic risk for Alzheimer's disease (AD). METHODS Following quality control, levels of 1019 metabolites-detected with liquid chromatography-mass spectrometry-were available for 1740 participants at age 60-64. Metabolite data were subsequently clustered into modules of co-expressed metabolites using weighted coexpression network analysis. Accompanying MRI and amyloid-PET imaging data were present for 437 participants (age 69-71). Regression analyses tested relationships between metabolite measures-modules and hub metabolites-and imaging outcomes. Hub metabolites were defined as metabolites that were highly connected within significant (pFDR < 0.05) modules or were identified as a hub in a previous analysis on cognitive function in the same cohort. Regression models included adjustments for age, sex, APOE genotype, lipid medication use, childhood cognitive ability, and social factors. Finally, associations were tested between AD polygenic risk scores (PRS), including and excluding the APOE region, and metabolites and modules that significantly associated (pFDR < 0.05) with an imaging outcome (N = 1638). RESULTS In the fully adjusted model, three lipid modules were associated with a brain volume measure (pFDR < 0.05): one enriched in sphingolipids (hippocampal volume: ß = 0.14, 95% CI = [0.055,0.23]), one in several fatty acid pathways (whole-brain volume: ß = - 0.072, 95%CI = [- 0.12, - 0.026]), and another in diacylglycerols and phosphatidylethanolamines (whole-brain volume: ß = - 0.066, 95% CI = [- 0.11, - 0.020]). Twenty-two hub metabolites were associated (pFDR < 0.05) with an imaging outcome (whole-brain volume: 22; hippocampal volume: 4). Some nominal associations were reported for amyloid-β, and with an AD PRS in our genetic analysis, but none survived multiple testing correction. CONCLUSIONS Our findings highlight key metabolites, with functions in membrane integrity and cell signalling, that associated with structural brain measures in later life. Future research should focus on replicating this work and interrogating causality.
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Affiliation(s)
- Rebecca E Green
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AB, UK.,UK National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre, South London and Maudsley Trust, London, UK
| | - Jodie Lord
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AB, UK
| | - Marzia A Scelsi
- Department of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing (CMIC), University College London (UCL), London, UK
| | - Jin Xu
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AB, UK.,Institute of Pharmaceutical Science, King's College London, London, UK
| | - Andrew Wong
- MRC Unit for Lifelong Health & Ageing at UCL, University College London, Floor 5, MRC LHA at UCL, 1 - 19 Torrington Place, London, WC1E 7HB, UK
| | - Sarah Naomi-James
- MRC Unit for Lifelong Health & Ageing at UCL, University College London, Floor 5, MRC LHA at UCL, 1 - 19 Torrington Place, London, WC1E 7HB, UK.,Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK
| | - Alex Handy
- University College London, Institute of Health Informatics, London, UK
| | - Lachlan Gilchrist
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AB, UK
| | - Dylan M Williams
- MRC Unit for Lifelong Health & Ageing at UCL, University College London, Floor 5, MRC LHA at UCL, 1 - 19 Torrington Place, London, WC1E 7HB, UK.,Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Thomas D Parker
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK.,Department of Brain Sciences, Imperial College London, London, W12 0NN, UK.,UK DRI Centre for Care Research and Technology, Imperial College London, London, W12 0BZ, UK
| | - Christopher A Lane
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK
| | - Ian B Malone
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK
| | - David M Cash
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK.,UK Dementia Research Institute at University College London, London, UK
| | - Carole H Sudre
- Department of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing (CMIC), University College London (UCL), London, UK.,MRC Unit for Lifelong Health & Ageing at UCL, University College London, Floor 5, MRC LHA at UCL, 1 - 19 Torrington Place, London, WC1E 7HB, UK.,Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK.,School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - William Coath
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK
| | - David L Thomas
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK.,Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Sarah Keuss
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK
| | - Richard Dobson
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AB, UK.,UK National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre, South London and Maudsley Trust, London, UK.,University College London, Institute of Health Informatics, London, UK.,Health Data Research UK London, University College London, London, UK.,NIHR Biomedical Research Centre at University College London Hospitals NHS Foundation Trust, London, UK
| | - Cristina Legido-Quigley
- Institute of Pharmaceutical Science, King's College London, London, UK.,Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - Nick C Fox
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK.,UK Dementia Research Institute at University College London, London, UK
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, 8-11 Queen Square, London, WC1N 3BG, UK.
| | - Marcus Richards
- MRC Unit for Lifelong Health & Ageing at UCL, University College London, Floor 5, MRC LHA at UCL, 1 - 19 Torrington Place, London, WC1E 7HB, UK.
| | - Petroula Proitsi
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, 16 De Crespigny Park, London, SE5 8AB, UK.
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6
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Klein G, Scelsi MA, Barakos J, Fiebach JB, Bracoud L, Suhy J, Delmar P, Lyons M, Wojtowicz J, Bullain S, Barkhof F, Purcell D. Comparing ARIA-E severity scales and effects of treatment management thresholds. Alzheimers Dement (Amst) 2022; 14:e12376. [PMID: 36474747 PMCID: PMC9716634 DOI: 10.1002/dad2.12376] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 10/14/2022] [Accepted: 10/19/2022] [Indexed: 11/25/2023]
Abstract
INTRODUCTION Amyloid-related imaging abnormalities-edema (ARIA-E) is associated with anti-amyloid beta monoclonal antibody treatment. ARIA-E severity may be assessed using the Barkhof Grand Total Scale (BGTS) or the 3- or 5-point Severity Scales of ARIA-E (SSAE-3/SSAE-5). We assessed inter- and intra-reader correlations between SSAE-3/5 and BGTS. METHODS Magnetic resonance imaging scans were collected from 75 participants in the SCarlet RoAD and Marguerite RoAD studies. Three neuroradiologists reviewed scans at baseline and at follow-up. Concordance in dichotomized ARIA-E ratings was assessed for a range of BGTS thresholds. RESULTS SSAE-3/5 scores correlated with BGTS scores, with high inter-reader intraclass correlation coefficients across all scales. There was high agreement in dichotomized ratings for SSAE-3 > 1 versus BGTS > 3 for all readers (accuracy 0.85-0.93) and between pairs of readers. DISCUSSION SSAE-3/5 showed high degrees of correlation with BGTS, potentially allowing seamless transition from the BGTS to SSAE-3/5 for ARIA-E management.
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Affiliation(s)
| | | | - Jerome Barakos
- California Pacific Medical CenterSan FranciscoCaliforniaUSA
| | - Jochen B. Fiebach
- Center for Stroke Research BerlinCharité Universitätsmedizin BerlinBerlinGermany
| | - Luc Bracoud
- ClarioInc. (formerly Bioclinica, Inc.)LyonFrance
| | - Joyce Suhy
- ClarioInc. (formerly Bioclinica, Inc.)San MateoCaliforniaUSA
| | | | | | | | | | - Frederik Barkhof
- Department of Radiology & Nuclear MedicineAmsterdam UMCVrije UniversiteitAmsterdamNetherlands
- Queen Square Institute of Neurology and Centre for Medical Image ComputingUniversity College LondonLondonUK
| | - Derk Purcell
- California Pacific Medical CenterSan FranciscoCaliforniaUSA
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7
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Bittner T, Scelsi MA, Kollmorgen G, Jethwa A, Kerchner GA, Fontoura P, Baudler M, Doody RS. Gantenerumab treatment increases plasma beta‐amyloid(1–42) and decreases plasma pTau. Alzheimers Dement 2022. [DOI: 10.1002/alz.065684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
- Tobias Bittner
- F. Hoffmann‐La Roche Ltd. Basel Switzerland
- Genentech, Inc. South San Francisco CA USA
| | | | | | | | | | | | | | - Rachelle S. Doody
- Genentech, Inc. South San Francisco CA USA
- F. Hoffmann‐La Roche Ltd Basel Switzerland
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8
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Boess F, Lane C, Scelsi MA, Delmar P, Hofmann C, Tonietto M, Klein G, Kerchner GA, Baudler M, Doody RS. Baseline participant characteristics of GRADUATION: a study to evaluate once‐weekly subcutaneous administration of gantenerumab. Alzheimers Dement 2022. [DOI: 10.1002/alz.061781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
| | | | | | | | - Carsten Hofmann
- Roche Pharma Research and Early Development, Roche Innovation Center Basel Switzerland
| | - Matteo Tonietto
- Roche Pharma Research and Early Development, FHoffmann‐La RocheLtd Basel Switzerland
| | - Gregory Klein
- Pharma Research and Early Development, F. Hoffmann‐La Roche Ltd. Basel Switzerland
| | | | | | - Rachelle S. Doody
- F. Hoffmann‐La Roche Ltd Basel Switzerland
- Genentech, Inc. South San Francisco CA USA
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9
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Klein G, Bracoud L, Purcell D, Barakos J, Fiebach JB, Scelsi MA, Delmar P, Lyons M, Wojtowicz J, Bullain S, Barkhof F, Fontoura P, Baudler M, Doody RS. Comparing ARIA‐E severity scales and effects of treatment management thresholds. Alzheimers Dement 2022. [DOI: 10.1002/alz.063848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Affiliation(s)
- Gregory Klein
- Pharma Research and Early Development, F. Hoffmann‐La Roche Ltd. Basel Switzerland
| | | | - Derk Purcell
- California Pacific Medical Center San Francisco CA USA
| | | | - Jochen B. Fiebach
- Center for Stroke Research Berlin, Charité Universitätsmedizin Berlin Berlin Germany
| | | | | | - Marco Lyons
- Roche Products Ltd. Welwyn Garden City United Kingdom
| | | | | | - Frederik Barkhof
- Institute of Neurology, University College London London United Kingdom
- Amsterdam University Medical Centers Amsterdam Netherlands
| | | | | | - Rachelle S. Doody
- F. Hoffmann‐La Roche Ltd Basel Switzerland
- Genentech, Inc. South San Francisco CA USA
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10
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de Silva E, Sudre CH, Barnes J, Scelsi MA, Altmann A. Polygenic coronary artery disease association with brain atrophy in the cognitively impaired. Brain Commun 2022; 4:fcac314. [PMID: 36523268 PMCID: PMC9746681 DOI: 10.1093/braincomms/fcac314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Revised: 09/09/2022] [Accepted: 11/28/2022] [Indexed: 12/03/2022] Open
Abstract
While a number of low-frequency genetic variants of large effect size have been shown to underlie both cardiovascular disease and dementia, recent studies have highlighted the importance of common genetic variants of small effect size, which, in aggregate, are embodied by a polygenic risk score. We investigate the effect of polygenic risk for coronary artery disease on brain atrophy in Alzheimer's disease using whole-brain volume and put our findings in context with the polygenic risk for Alzheimer's disease and presumed small vessel disease as quantified by white-matter hyperintensities. We use 730 subjects from the Alzheimer's disease neuroimaging initiative database to investigate polygenic risk score effects (beyond APOE) on whole-brain volumes, total and regional white-matter hyperintensities and amyloid beta across diagnostic groups. In a subset of these subjects (N = 602), we utilized longitudinal changes in whole-brain volume over 24 months using the boundary shift integral approach. Linear regression and linear mixed-effects models were used to investigate the effect of white-matter hyperintensities at baseline as well as Alzheimer's disease-polygenic risk score and coronary artery disease-polygenic risk score on whole-brain atrophy and whole-brain atrophy acceleration, respectively. All genetic associations were examined under the oligogenic (P = 1e-5) and the more variant-inclusive polygenic (P = 0.5) scenarios. Results suggest no evidence for a link between the polygenic risk score and markers of Alzheimer's disease pathology at baseline (when stratified by diagnostic group). However, both Alzheimer's disease-polygenic risk score and coronary artery disease-polygenic risk score were associated with longitudinal decline in whole-brain volume (Alzheimer's disease-polygenic risk score t = 3.3, P FDR = 0.007 over 24 months in healthy controls) and surprisingly, under certain conditions, whole-brain volume atrophy is statistically more correlated with cardiac polygenic risk score than Alzheimer's disease-polygenic risk score (coronary artery disease-polygenic risk score t = 2.1, P FDR = 0.04 over 24 months in the mild cognitive impairment group). Further, in our regional analysis of white-matter hyperintensities, Alzheimer's disease-polygenic risk score beyond APOE is predictive of white-matter volume in the occipital lobe in Alzheimer's disease subjects in the polygenic regime. Finally, the rate of change of brain volume (or atrophy acceleration) may be sensitive to Alzheimer's disease-polygenic risk beyond APOE in healthy individuals (t = 2, P = 0.04). For subjects with mild cognitive impairment, beyond APOE, a more inclusive polygenic risk score including more variants, shows coronary artery disease-polygenic risk score to be more predictive of whole-brain volume atrophy, than an oligogenic approach including fewer larger effect size variants.
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Affiliation(s)
- Eric de Silva
- Centre for Medical Image Computing, University College London, London, UK.,NIHR University College London Hospitals Biomedical Research Centre, London, UK
| | - Carole H Sudre
- Centre for Medical Image Computing, University College London, London, UK.,MRC Unit for Lifelong Health and Ageing, University College London, London, UK.,School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Josephine Barnes
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Marzia A Scelsi
- Centre for Medical Image Computing, University College London, London, UK
| | - Andre Altmann
- Centre for Medical Image Computing, University College London, London, UK
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11
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Zainul Abidin FN, Scelsi MA, Dawson SJ, Altmann A. Glucose hypometabolism in the Auditory Pathway in Age Related Hearing Loss in the ADNI cohort. Neuroimage Clin 2021; 32:102823. [PMID: 34624637 PMCID: PMC8503577 DOI: 10.1016/j.nicl.2021.102823] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Revised: 08/25/2021] [Accepted: 09/07/2021] [Indexed: 11/23/2022]
Abstract
PURPOSE Hearing loss (HL) is one of the most common age-related diseases. Here, we investigate the central auditory correlates of HL in people with normal cognition and mild cognitive impairment (MCI) and test their association with genetic markers with the aim of revealing pathogenic mechanisms. METHODS Brain glucose metabolism based on FDG-PET, self-reported HL status, and genetic data were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. FDG-PET data was analysed from 742 control subjects (non-HL with normal cognition or MCI) and 162 cases (HL with normal cognition or MCI) with age ranges of 72.2 ± 7.1 and 77.4 ± 6.4, respectively. Voxel-wise statistics of FDG uptake differences between cases and controls were computed using the generalised linear model in SPM12. An additional 1515 FDG-PET scans of 618 participants were analysed using linear mixed effect models to assess longitudinal HL effects. Furthermore, a quantitative trait genome-wide association study (GWAS) was conducted on the glucose uptake within regions of interest (ROIs), which were defined by the voxel-wise comparison, using genotyping data with 5,082,878 variants available for HL cases and HL controls (N = 817). RESULTS The HL group exhibited hypometabolism in the bilateral Heschl's gyrus (kleft = 323; kright = 151; Tleft = 4.55; Tright = 4.14; peak Puncorr < 0.001), the inferior colliculus (k = 219;T = 3.53; peak Puncorr < 0.001) and cochlear nucleus (k = 18;T = 3.55; peak Puncorr < 0.001) after age correction and using a cluster forming height threshold P < 0.005 (FWE-uncorrected). Moreover, in an age-matched subset, the cluster comprising the left Heschl's gyrus survived the FWE-correction (kleft = 1903; Tleft = 4.39; cluster PFWE-corr = 0.001). The quantitative trait GWAS identified no genome-wide significant locus in the three HL ROIs. However, various loci were associated at the suggestive threshold (p < 1e-05). CONCLUSION Compared to the non-HL group, glucose metabolism in the HL group was lower in the auditory cortex, the inferior colliculus, and the cochlear nucleus although the effect sizes were small. The GWAS identified candidate genes that might influence FDG uptake in these regions. However, the specific biological pathway(s) underlying the role of these genes in FDG-hypometabolism in the auditory pathway requires further investigation.
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Affiliation(s)
- Fatin N Zainul Abidin
- UCL Ear Institute, University College London, London, UK; Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Marzia A Scelsi
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Sally J Dawson
- UCL Ear Institute, University College London, London, UK
| | - Andre Altmann
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK.
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12
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Napolioni V, Scelsi MA, Khan RR, Altmann A, Greicius MD. Recent Consanguinity and Outbred Autozygosity Are Associated With Increased Risk of Late-Onset Alzheimer's Disease. Front Genet 2021; 11:629373. [PMID: 33584820 PMCID: PMC7879576 DOI: 10.3389/fgene.2020.629373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2020] [Accepted: 12/31/2020] [Indexed: 11/13/2022] Open
Abstract
Prior work in late-onset Alzheimer's disease (LOAD) has resulted in discrepant findings as to whether recent consanguinity and outbred autozygosity are associated with LOAD risk. In the current study, we tested the association between consanguinity and outbred autozygosity with LOAD in the largest such analysis to date, in which 20 LOAD GWAS datasets were retrieved through public databases. Our analyses were restricted to eight distinct ethnic groups: African-Caribbean, Ashkenazi-Jewish European, European-Caribbean, French-Canadian, Finnish European, North-Western European, South-Eastern European, and Yoruba African for a total of 21,492 unrelated subjects (11,196 LOAD and 10,296 controls). Recent consanguinity determination was performed using FSuite v1.0.3, according to subjects' ancestral background. The level of autozygosity in the outbred population was assessed by calculating inbreeding estimates based on the proportion (FROH) and the number (NROH) of runs of homozygosity (ROHs). We analyzed all eight ethnic groups using a fixed-effect meta-analysis, which showed a significant association of recent consanguinity with LOAD (N = 21,481; OR = 1.262, P = 3.6 × 10-4), independently of APOE ∗4 (N = 21,468, OR = 1.237, P = 0.002), and years of education (N = 9,257; OR = 1.274, P = 0.020). Autozygosity in the outbred population was also associated with an increased risk of LOAD, both for F ROH (N = 20,237; OR = 1.204, P = 0.030) and N ROH metrics (N = 20,237; OR = 1.019, P = 0.006), independently of APOE ∗4 [(F ROH, N = 20,225; OR = 1.222, P = 0.029) (N ROH, N = 20,225; OR = 1.019, P = 0.007)]. By leveraging the Alzheimer's Disease Sequencing Project (ADSP) whole-exome sequencing (WES) data, we determined that LOAD subjects do not show an enrichment of rare, risk-enhancing minor homozygote variants compared to the control population. A two-stage recessive GWAS using ADSP data from 201 consanguineous subjects in the discovery phase followed by validation in 10,469 subjects led to the identification of RPH3AL p.A303V (rs117190076) as a rare minor homozygote variant increasing the risk of LOAD [discovery: Genotype Relative Risk (GRR) = 46, P = 2.16 × 10-6; validation: GRR = 1.9, P = 8.0 × 10-4]. These results confirm that recent consanguinity and autozygosity in the outbred population increase risk for LOAD. Subsequent work, with increased samples sizes of consanguineous subjects, should accelerate the discovery of non-additive genetic effects in LOAD.
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Affiliation(s)
- Valerio Napolioni
- Genomic and Molecular Epidemiology (GAME) Lab, School of Biosciences and Veterinary Medicine, University of Camerino, Camerino, Italy
| | - Marzia A. Scelsi
- Computational Biology in Imaging and Genetics (COMBINE) Lab, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Raiyan R. Khan
- Department of Computer Science, Columbia University, New York, NY, United States
| | - Andre Altmann
- Computational Biology in Imaging and Genetics (COMBINE) Lab, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Michael D. Greicius
- Functional Imaging in Neuropsychiatric Disorders (FIND) Lab, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
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13
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Belloy ME, Eger SJ, Le Guen Y, Napolioni V, Deters KD, Yang HS, Scelsi MA, Porter T, James SN, Wong A, Schott JM, Sperling RA, Laws SM, Mormino EC, He Z, Han SS, Altmann A, Greicius MD. KL∗VS heterozygosity reduces brain amyloid in asymptomatic at-risk APOE∗4 carriers. Neurobiol Aging 2021; 101:123-129. [PMID: 33610961 DOI: 10.1016/j.neurobiolaging.2021.01.008] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Revised: 11/30/2020] [Accepted: 01/09/2021] [Indexed: 11/15/2022]
Abstract
KLOTHO∗VS heterozygosity (KL∗VSHET+) was recently shown to be associated with reduced risk of Alzheimer's disease (AD) in APOE∗4 carriers. Additional studies suggest that KL∗VSHET+ protects against amyloid burden in cognitively normal older subjects, but sample sizes were too small to draw definitive conclusions. We performed a well-powered meta-analysis across 5 independent studies, comprising 3581 pre-clinical participants ages 60-80, to investigate whether KL∗VSHET+ reduces the risk of having an amyloid-positive positron emission tomography scan. Analyses were stratified by APOE∗4 status. KL∗VSHET+ reduced the risk of amyloid positivity in APOE∗4 carriers (odds ratio = 0.67 [0.52-0.88]; p = 3.5 × 10-3), but not in APOE∗4 non-carriers (odds ratio = 0.94 [0.73-1.21]; p = 0.63). The combination of APOE∗4 and KL∗VS genotypes should help enrich AD clinical trials for pre-symptomatic subjects at increased risk of developing amyloid aggregation and AD. KL-related pathways may help elucidate protective mechanisms against amyloid accumulation and merit exploration for novel AD drug targets. Future investigation of the biological mechanisms by which KL interacts with APOE∗4 and AD are warranted.
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Affiliation(s)
- Michael E Belloy
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA.
| | - Sarah J Eger
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Yann Le Guen
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Valerio Napolioni
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Kacie D Deters
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Hyun-Sik Yang
- Department of Neurology, Brigham and Women's Hospital, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Marzia A Scelsi
- Centre for Medical Image Computing (CMIC), University College London, London, UK
| | - Tenielle Porter
- Collaborative Genomics and Translation Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, Australia; School of Pharmacy and Biomedical Sciences, Faculty of Health Sciences, Curtin Health Innovation Research Institute, Curtin University, Bentley, Western Australia, Australia
| | - Sarah-Naomi James
- Medical Research Council Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Andrew Wong
- Medical Research Council Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Jonathan M Schott
- Dementia Research Centre, University College London Queen Square Institute of Neurology, University College London, London, UK; UK Dementia Research Institute, University College London, London, UK
| | - Reisa A Sperling
- Department of Neurology, Brigham and Women's Hospital, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Simon M Laws
- Collaborative Genomics and Translation Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, Australia; School of Pharmacy and Biomedical Sciences, Faculty of Health Sciences, Curtin Health Innovation Research Institute, Curtin University, Bentley, Western Australia, Australia
| | - Elisabeth C Mormino
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Zihuai He
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA; Department of Medicine, Quantitative Sciences Unit, Stanford University, Stanford, CA, USA
| | - Summer S Han
- Department of Medicine, Quantitative Sciences Unit, Stanford University, Stanford, CA, USA; Department of Neurosurgery, Stanford University, Stanford, CA, USA
| | - Andre Altmann
- Centre for Medical Image Computing (CMIC), University College London, London, UK
| | - Michael D Greicius
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
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14
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Altmann A, Scelsi MA, Shoai M, de Silva E, Aksman LM, Cash DM, Hardy J, Schott JM. A comprehensive analysis of methods for assessing polygenic burden on Alzheimer's disease pathology and risk beyond APOE. Brain Commun 2019; 2:fcz047. [PMID: 32226939 PMCID: PMC7100005 DOI: 10.1093/braincomms/fcz047] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Genome-wide association studies have identified dozens of loci that alter the risk to develop Alzheimer's disease. However, with the exception of the APOE-ε4 allele, most variants bear only little individual effect and have, therefore, limited diagnostic and prognostic value. Polygenic risk scores aim to collate the disease risk distributed across the genome in a single score. Recent works have demonstrated that polygenic risk scores designed for Alzheimer's disease are predictive of clinical diagnosis, pathology confirmed diagnosis and changes in imaging biomarkers. Methodological innovations in polygenic risk modelling include the polygenic hazard score, which derives effect estimates for individual single nucleotide polymorphisms from survival analysis, and methods that account for linkage disequilibrium between genomic loci. In this work, using data from the Alzheimer's disease neuroimaging initiative, we compared different approaches to quantify polygenic disease burden for Alzheimer's disease and their association (beyond the APOE locus) with a broad range of Alzheimer's disease-related traits: cross-sectional CSF biomarker levels, cross-sectional cortical amyloid burden, clinical diagnosis, clinical progression, longitudinal loss of grey matter and longitudinal decline in cognitive function. We found that polygenic scores were associated beyond APOE with clinical diagnosis, CSF-tau levels and, to a minor degree, with progressive atrophy. However, for many other tested traits such as clinical disease progression, CSF amyloid, cognitive decline and cortical amyloid load, the additional effects of polygenic burden beyond APOE were of minor nature. Overall, polygenic risk scores and the polygenic hazard score performed equally and given the ease with which polygenic risk scores can be derived; they constitute the more practical choice in comparison with polygenic hazard scores. Furthermore, our results demonstrate that incomplete adjustment for the APOE locus, i.e. only adjusting for APOE-ε4 carrier status, can lead to overestimated effects of polygenic scores due to APOE-ε4 homozygous participants. Lastly, on many of the tested traits, the major driving factor remained the APOE locus, with the exception of quantitative CSF-tau and p-tau measures.
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Affiliation(s)
- Andre Altmann
- Department of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing (CMIC), University College London (UCL), London WC1V 6LJ, UK
| | - Marzia A Scelsi
- Department of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing (CMIC), University College London (UCL), London WC1V 6LJ, UK
| | - Maryam Shoai
- Reta Lilla Research Laboratories, Department of Neurodegeneration, Queen Square Institute of Neurology, University College London (UCL), London WC1V 6LJ, UK.,UK Dementia Research Institute, University College London (UCL), London WC1V 6LJ, UK
| | - Eric de Silva
- Department of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing (CMIC), University College London (UCL), London WC1V 6LJ, UK.,Institute for Health Informatics, University College London (UCL), London WC1V 6LJ, UK
| | - Leon M Aksman
- Department of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing (CMIC), University College London (UCL), London WC1V 6LJ, UK
| | - David M Cash
- UK Dementia Research Institute, University College London (UCL), London WC1V 6LJ, UK.,Dementia Research Centre, Queen Square Institute of Neurology, University College London (UCL), London WC1V 6LJ, UK
| | - John Hardy
- Reta Lilla Research Laboratories, Department of Neurodegeneration, Queen Square Institute of Neurology, University College London (UCL), London WC1V 6LJ, UK.,UK Dementia Research Institute, University College London (UCL), London WC1V 6LJ, UK
| | - Jonathan M Schott
- UK Dementia Research Institute, University College London (UCL), London WC1V 6LJ, UK.,Dementia Research Centre, Queen Square Institute of Neurology, University College London (UCL), London WC1V 6LJ, UK
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15
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Aksman LM, Scelsi MA, Marquand AF, Alexander DC, Ourselin S, Altmann A. Modeling longitudinal imaging biomarkers with parametric Bayesian multi-task learning. Hum Brain Mapp 2019; 40:3982-4000. [PMID: 31168892 PMCID: PMC6679792 DOI: 10.1002/hbm.24682] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2018] [Revised: 05/03/2019] [Accepted: 05/19/2019] [Indexed: 01/09/2023] Open
Abstract
Longitudinal imaging biomarkers are invaluable for understanding the course of neurodegeneration, promising the ability to track disease progression and to detect disease earlier than cross-sectional biomarkers. To properly realize their potential, biomarker trajectory models must be robust to both under-sampling and measurement errors and should be able to integrate multi-modal information to improve trajectory inference and prediction. Here we present a parametric Bayesian multi-task learning based approach to modeling univariate trajectories across subjects that addresses these criteria. Our approach learns multiple subjects' trajectories within a single model that allows for different types of information sharing, that is, coupling, across subjects. It optimizes a combination of uncoupled, fully coupled and kernel coupled models. Kernel-based coupling allows linking subjects' trajectories based on one or more biomarker measures. We demonstrate this using Alzheimer's Disease Neuroimaging Initiative (ADNI) data, where we model longitudinal trajectories of MRI-derived cortical volumes in neurodegeneration, with coupling based on APOE genotype, cerebrospinal fluid (CSF) and amyloid PET-based biomarkers. In addition to detecting established disease effects, we detect disease related changes within the insula that have not received much attention within the literature. Due to its sensitivity in detecting disease effects, its competitive predictive performance and its ability to learn the optimal parameter covariance from data rather than choosing a specific set of random and fixed effects a priori, we propose that our model can be used in place of or in addition to linear mixed effects models when modeling biomarker trajectories. A software implementation of the method is publicly available.
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Affiliation(s)
- Leon M. Aksman
- Centre for Medical Image ComputingUniversity College LondonLondonUK
| | - Marzia A. Scelsi
- Centre for Medical Image ComputingUniversity College LondonLondonUK
| | - Andre F. Marquand
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and BehaviourRadboud UniversityNijmegenThe Netherlands
| | | | - Sebastien Ourselin
- Centre for Medical Image ComputingUniversity College LondonLondonUK
- School of Biomedical Engineering and Imaging SciencesSt Thomas' Hospital, King's College LondonLondonUK
| | - Andre Altmann
- Centre for Medical Image ComputingUniversity College LondonLondonUK
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16
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Bocchetta M, Iglesias JE, Scelsi MA, Cash DM, Cardoso MJ, Modat M, Altmann A, Ourselin S, Warren JD, Rohrer JD. Hippocampal Subfield Volumetry: Differential Pattern of Atrophy in Different Forms of Genetic Frontotemporal Dementia. J Alzheimers Dis 2019; 64:497-504. [PMID: 29889066 PMCID: PMC6027942 DOI: 10.3233/jad-180195] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Background: Frontotemporal dementia (FTD) is a heterogeneous neurodegenerative disorder, with a strong genetic component. Previous research has shown that medial temporal lobe atrophy is a common feature of FTD. However, no study has so far investigated the differential vulnerability of the hippocampal subfields in FTD. Objectives: We aimed to investigate hippocampal subfield volumes in genetic FTD. Methods: We in6/2/2018vestigated hippocampal subfield volumes in a cohort of 75 patients with genetic FTD (age: mean (standard deviation) 59.3 (7.7) years; disease duration: 5.1 (3.4) years; 29 with MAPT, 28 with C9orf72, and 18 with GRN mutations) compared with 97 age-matched controls (age: 62.1 (11.1) years). We performed a segmentation of their volumetric T1-weighted MRI scans to extract hippocampal subfields volumes. Left and right volumes were summed and corrected for total intracranial volumes. Results: All three groups had smaller hippocampi than controls. The MAPT group had the most atrophic hippocampi, with the subfields showing the largest difference from controls being CA1-4 (24–27%, p < 0.0005). For C9orf72, the CA4, CA1, and dentate gyrus regions (8–11%, p < 0.0005), and for GRN the presubiculum and subiculum (10–14%, p < 0.0005) showed the largest differences from controls. Conclusions: The hippocampus was affected in all mutation types but a different pattern of subfield involvement was found in the three genetic groups, consistent with differential cortical-subcortical network vulnerability.
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Affiliation(s)
- Martina Bocchetta
- Dementia Research Centre, Department of Neurodegenerative Disease, Institute of Neurology, University College London, London, UK
| | - Juan Eugenio Iglesias
- Translational Imaging Group, Centre for Medical Image Computing, University College London, London, UK
| | - Marzia A Scelsi
- Translational Imaging Group, Centre for Medical Image Computing, University College London, London, UK
| | - David M Cash
- Dementia Research Centre, Department of Neurodegenerative Disease, Institute of Neurology, University College London, London, UK.,Translational Imaging Group, Centre for Medical Image Computing, University College London, London, UK
| | - M Jorge Cardoso
- Translational Imaging Group, Centre for Medical Image Computing, University College London, London, UK
| | - Marc Modat
- Translational Imaging Group, Centre for Medical Image Computing, University College London, London, UK
| | - Andre Altmann
- Translational Imaging Group, Centre for Medical Image Computing, University College London, London, UK
| | - Sebastien Ourselin
- Translational Imaging Group, Centre for Medical Image Computing, University College London, London, UK
| | - Jason D Warren
- Dementia Research Centre, Department of Neurodegenerative Disease, Institute of Neurology, University College London, London, UK
| | - Jonathan D Rohrer
- Dementia Research Centre, Department of Neurodegenerative Disease, Institute of Neurology, University College London, London, UK
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17
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Bocchetta M, Iglesias JE, Russell LL, Greaves CV, Marshall CR, Scelsi MA, Cash DM, Ourselin S, Warren JD, Rohrer JD. Segmentation of medial temporal subregions reveals early right-sided involvement in semantic variant PPA. Alzheimers Res Ther 2019; 11:41. [PMID: 31077248 PMCID: PMC6511178 DOI: 10.1186/s13195-019-0489-9] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/03/2019] [Accepted: 04/02/2019] [Indexed: 12/03/2022]
Abstract
Background Semantic variant of primary progressive aphasia (svPPA) is a subtype of frontotemporal dementia characterized by asymmetric temporal atrophy. Methods We investigated the pattern of medial temporal lobe atrophy in 24 svPPA patients compared to 72 controls using novel approaches to segment the hippocampal and amygdalar subregions on MRIs. Based on semantic knowledge scores, we split the svPPA group into 3 subgroups of early, middle and late disease stage. Results Early stage: all left amygdalar and hippocampal subregions (except the tail) were affected in svPPA (21–35% smaller than controls), together with the following amygdalar nuclei in the right hemisphere: lateral, accessory basal and superficial (15–23%). On the right, only the temporal pole was affected among the cortical regions. Middle stage: the left hippocampal tail became affected (28%), together with the other amygdalar nuclei (22–26%), and CA4 (15%) on the right, with orbitofrontal cortex and subcortical structures involvement on the left, and more posterior temporal lobe on the right. Late stage: the remaining right hippocampal regions (except the tail) (19–24%) became affected, with more posterior left cortical and right extra-temporal anterior cortical involvement. Conclusions With advanced subregions segmentation, it is possible to detect early involvement of the right medial temporal lobe in svPPA that is not detectable by measuring the amygdala or hippocampus as a whole. Electronic supplementary material The online version of this article (10.1186/s13195-019-0489-9) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Martina Bocchetta
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, 8-11 Queen Square, London, WC1N 3BG, UK
| | - Juan Eugenio Iglesias
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Lucy L Russell
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, 8-11 Queen Square, London, WC1N 3BG, UK
| | - Caroline V Greaves
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, 8-11 Queen Square, London, WC1N 3BG, UK
| | - Charles R Marshall
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, 8-11 Queen Square, London, WC1N 3BG, UK
| | - Marzia A Scelsi
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - David M Cash
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, 8-11 Queen Square, London, WC1N 3BG, UK.,Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Sebastien Ourselin
- School of Biomedical Engineering and Imaging Sciences, St Thomas' Hospital, King's College London, London, UK
| | - Jason D Warren
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, 8-11 Queen Square, London, WC1N 3BG, UK
| | - Jonathan D Rohrer
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, 8-11 Queen Square, London, WC1N 3BG, UK.
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Bielczyk N, Veldsman M, Ando A, Caldinelli C, Makary MM, Nikolaidis A, Scelsi MA, Stefan M, Badhwar A. Establishing online mentorship for early career researchers: Lessons from the Organization for Human Brain Mapping International Mentoring Programme. Eur J Neurosci 2019; 49:1069-1076. [DOI: 10.1111/ejn.14320] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2018] [Revised: 12/05/2018] [Accepted: 12/20/2018] [Indexed: 10/27/2022]
Affiliation(s)
- Natalia Bielczyk
- Stichting Solaris Onderzoek en Ontwikkeling; Nijmegen the Netherlands
| | - Michele Veldsman
- Department of Experimental Psychology; University of Oxford; Oxford UK
- The Florey Institute of Neuroscience and Mental Health; University of Melbourne; Melbourne Victoria Australia
| | - Ayaka Ando
- Department of Child and Adolescent Psychiatry; Centre for Psychosocial Medicine; University of Heidel-berg; Heidelberg Germany
| | - Chiara Caldinelli
- Trinity College Institute of Neuroscience; Trinity College Dublin; Dublin 2 Ireland
| | - Meena M. Makary
- Department of Psychiatry; Yale University School of Medicine; New Haven Connecticut
- The John B. Pierce Laboratory; New Haven Connecticut
- Faculty of Engineering; Systems and Biomedical Engineering Department; Cairo University; Giza Egypt
| | - Aki Nikolaidis
- Center for the Developing Brain; Child Mind Institute; New York city New York
| | - Marzia A. Scelsi
- Department of Medical Physics and Bioengineering; Centre for Medical Image Computing; University College London; London UK
| | - Melanie Stefan
- Centre for Discovery Brain Sciences; University of Edinburgh; Edinburgh UK
- ZJU-UoE Institute; Zhejiang University School of Medicine; Zhejiang University; Haining Zhejiang China
| | - AmanPreet Badhwar
- Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal (CRIUGM); Montreal Quebec Canada
- Université de Montréal; Montreal Quebec Canada
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19
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Scelsi MA, Khan RR, Lorenzi M, Christopher L, Greicius MD, Schott JM, Ourselin S, Altmann A. Genetic study of multimodal imaging Alzheimer's disease progression score implicates novel loci. Brain 2018; 141:2167-2180. [PMID: 29860282 PMCID: PMC6022660 DOI: 10.1093/brain/awy141] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2017] [Revised: 03/16/2018] [Accepted: 04/03/2018] [Indexed: 01/08/2023] Open
Abstract
Identifying genetic risk factors underpinning different aspects of Alzheimer's disease has the potential to provide important insights into pathogenesis. Moving away from simple case-control definitions, there is considerable interest in using quantitative endophenotypes, such as those derived from imaging as outcome measures. Previous genome-wide association studies of imaging-derived biomarkers in sporadic late-onset Alzheimer's disease focused only on phenotypes derived from single imaging modalities. In contrast, we computed a novel multi-modal neuroimaging phenotype comprising cortical amyloid burden and bilateral hippocampal volume. Both imaging biomarkers were used as input to a disease progression modelling algorithm, which estimates the biomarkers' long-term evolution curves from population-based longitudinal data. Among other parameters, the algorithm computes the shift in time required to optimally align a subjects' biomarker trajectories with these population curves. This time shift serves as a disease progression score and it was used as a quantitative trait in a discovery genome-wide association study with n = 944 subjects from the Alzheimer's Disease Neuroimaging Initiative database diagnosed as Alzheimer's disease, mild cognitive impairment or healthy at the time of imaging. We identified a genome-wide significant locus implicating LCORL (rs6850306, chromosome 4; P = 1.03 × 10-8). The top variant rs6850306 was found to act as an expression quantitative trait locus for LCORL in brain tissue. The clinical role of rs6850306 in conversion from healthy ageing to mild cognitive impairment or Alzheimer's disease was further validated in an independent cohort comprising healthy, older subjects from the National Alzheimer's Coordinating Center database. Specifically, possession of a minor allele at rs6850306 was protective against conversion from mild cognitive impairment to Alzheimer's disease in the National Alzheimer's Coordinating Center cohort (hazard ratio = 0.593, 95% confidence interval = 0.387-0.907, n = 911, PBonf = 0.032), in keeping with the negative direction of effect reported in the genome-wide association study (βdisease progression score = -0.07 ± 0.01). The implicated locus is linked to genes with known connections to Alzheimer's disease pathophysiology and other neurodegenerative diseases. Using multimodal imaging phenotypes in association studies may assist in unveiling the genetic drivers of the onset and progression of complex diseases.
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Affiliation(s)
- Marzia A Scelsi
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, Gower Street NW1 2HE, London, UK
| | - Raiyan R Khan
- Functional Imaging in Neuropsychiatric Disorders (FIND) Lab, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA 94304-5777, USA
| | - Marco Lorenzi
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, Gower Street NW1 2HE, London, UK
- Epione Research Project, Université Côte d'Azur, BP 93 06 902, Inria Sophia Antipolis, France
| | - Leigh Christopher
- Functional Imaging in Neuropsychiatric Disorders (FIND) Lab, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA 94304-5777, USA
| | - Michael D Greicius
- Functional Imaging in Neuropsychiatric Disorders (FIND) Lab, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA 94304-5777, USA
| | - Jonathan M Schott
- Functional Imaging in Neuropsychiatric Disorders (FIND) Lab, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA 94304-5777, USA
| | - Sebastien Ourselin
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, Gower Street NW1 2HE, London, UK
- UCL Institute of Neurology, Queen Square WC1N 3BG, London, UK
| | - Andre Altmann
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, Gower Street NW1 2HE, London, UK
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