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Kanakaraj P, Yao T, Cai LY, Lee HH, Newlin NR, Kim ME, Gao C, Pechman KR, Archer D, Hohman T, Jefferson A, Beason-Held LL, Resnick SM, Garyfallidis E, Anderson A, Schilling KG, Landman BA, Moyer D. DeepN4: Learning N4ITK Bias Field Correction for T1-weighted Images. Res Sq 2023:rs.3.rs-3585882. [PMID: 38014176 PMCID: PMC10680935 DOI: 10.21203/rs.3.rs-3585882/v1] [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] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
T1-weighted (T1w) MRI has low frequency intensity artifacts due to magnetic field inhomogeneities. Removal of these biases in T1w MRI images is a critical preprocessing step to ensure spatially consistent image interpretation. N4ITK bias field correction, the current state-of-the-art, is implemented in such a way that makes it difficult to port between different pipelines and workflows, thus making it hard to reimplement and reproduce results across local, cloud, and edge platforms. Moreover, N4ITK is opaque to optimization before and after its application, meaning that methodological development must work around the inhomogeneity correction step. Given the importance of bias fields correction in structural preprocessing and flexible implementation, we pursue a deep learning approximation / reinterpretation of the N4ITK bias fields correction to create a method which is portable, flexible, and fully differentiable. In this paper, we trained a deep learning network "DeepN4" on eight independent cohorts from 72 different scanners and age ranges with N4ITK-corrected T1w MRI and bias field for supervision in log space. We found that we can closely approximate N4ITK bias fields correction with naïve networks. We evaluate the peak signal to noise ratio (PSNR) in test dataset against the N4ITK corrected images. The median PSNR of corrected images between N4ITK and DeepN4 was 47.96 dB. In addition, we assess the DeepN4 model on eight additional external datasets and show the generalizability of the approach. This study establishes that incompatible N4ITK preprocessing steps can be closely approximated by naïve deep neural networks, facilitating more flexibility. All code and models are released at https://github.com/MASILab/DeepN4.
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Affiliation(s)
| | - Tianyuan Yao
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Leon Y. Cai
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
| | - Ho Hin Lee
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Nancy R. Newlin
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | - Michael E. Kim
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
| | | | - Kimberly R. Pechman
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Derek Archer
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Timothy Hohman
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Angela Jefferson
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lori L. Beason-Held
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Susan M. Resnick
- Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | | | | | | | - Adam Anderson
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
- Department of Radiology and Radiological Services, Vanderbilt University Medical Center, Vanderbilt University Medical, Nashville, TN, USA
| | - Kurt G. Schilling
- Vanderbilt University Institute for Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Bennett A. Landman
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
- Department of Radiology and Radiological Services, Vanderbilt University Medical Center, Vanderbilt University Medical, Nashville, TN, USA
- Vanderbilt University Institute for Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Daniel Moyer
- Department of Computer Science, Vanderbilt University, Nashville, TN, USA
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2
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Eissman JM, Dumitrescu L, Mahoney ER, Smith AN, Mukherjee S, Lee ML, Scollard P, Choi SE, Bush WS, Engelman CD, Lu Q, Fardo DW, Trittschuh EH, Mez J, Kaczorowski CC, Hernandez Saucedo H, Widaman KF, Buckley RF, Properzi MJ, Mormino EC, Yang HS, Harrison TM, Hedden T, Nho K, Andrews SJ, Tommet D, Hadad N, Sanders RE, Ruderfer DM, Gifford KA, Zhong X, Raghavan NS, Vardarajan BN, Pericak-Vance MA, Farrer LA, Wang LS, Cruchaga C, Schellenberg GD, Cox NJ, Haines JL, Keene CD, Saykin AJ, Larson EB, Sperling RA, Mayeux R, Cuccaro ML, Bennett DA, Schneider JA, Crane PK, Jefferson AL, Hohman TJ. Sex differences in the genetic architecture of cognitive resilience to Alzheimer's disease. Brain 2022; 145:2541-2554. [PMID: 35552371 PMCID: PMC9337804 DOI: 10.1093/brain/awac177] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [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: 12/23/2021] [Revised: 04/07/2022] [Accepted: 04/14/2022] [Indexed: 12/04/2022] Open
Abstract
Approximately 30% of elderly adults are cognitively unimpaired at time of death despite the presence of Alzheimer's disease neuropathology at autopsy. Studying individuals who are resilient to the cognitive consequences of Alzheimer's disease neuropathology may uncover novel therapeutic targets to treat Alzheimer's disease. It is well established that there are sex differences in response to Alzheimer's disease pathology, and growing evidence suggests that genetic factors may contribute to these differences. Taken together, we sought to elucidate sex-specific genetic drivers of resilience. We extended our recent large scale genomic analysis of resilience in which we harmonized cognitive data across four cohorts of cognitive ageing, in vivo amyloid PET across two cohorts, and autopsy measures of amyloid neuritic plaque burden across two cohorts. These data were leveraged to build robust, continuous resilience phenotypes. With these phenotypes, we performed sex-stratified [n (males) = 2093, n (females) = 2931] and sex-interaction [n (both sexes) = 5024] genome-wide association studies (GWAS), gene and pathway-based tests, and genetic correlation analyses to clarify the variants, genes and molecular pathways that relate to resilience in a sex-specific manner. Estimated among cognitively normal individuals of both sexes, resilience was 20-25% heritable, and when estimated in either sex among cognitively normal individuals, resilience was 15-44% heritable. In our GWAS, we identified a female-specific locus on chromosome 10 [rs827389, β (females) = 0.08, P (females) = 5.76 × 10-09, β (males) = -0.01, P(males) = 0.70, β (interaction) = 0.09, P (interaction) = 1.01 × 10-04] in which the minor allele was associated with higher resilience scores among females. This locus is located within chromatin loops that interact with promoters of genes involved in RNA processing, including GATA3. Finally, our genetic correlation analyses revealed shared genetic architecture between resilience phenotypes and other complex traits, including a female-specific association with frontotemporal dementia and male-specific associations with heart rate variability traits. We also observed opposing associations between sexes for multiple sclerosis, such that more resilient females had a lower genetic susceptibility to multiple sclerosis, and more resilient males had a higher genetic susceptibility to multiple sclerosis. Overall, we identified sex differences in the genetic architecture of resilience, identified a female-specific resilience locus and highlighted numerous sex-specific molecular pathways that may underly resilience to Alzheimer's disease pathology. This study illustrates the need to conduct sex-aware genomic analyses to identify novel targets that are unidentified in sex-agnostic models. Our findings support the theory that the most successful treatment for an individual with Alzheimer's disease may be personalized based on their biological sex and genetic context.
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Affiliation(s)
- Jaclyn M Eissman
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical
Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical
Center, Nashville, TN, USA
| | - Logan Dumitrescu
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical
Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical
Center, Nashville, TN, USA
| | - Emily R Mahoney
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical
Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical
Center, Nashville, TN, USA
| | - Alexandra N Smith
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical
Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical
Center, Nashville, TN, USA
| | | | - Michael L Lee
- Department of Medicine, University of Washington,
Seattle, WA, USA
| | - Phoebe Scollard
- Department of Medicine, University of Washington,
Seattle, WA, USA
| | - Seo Eun Choi
- Department of Medicine, University of Washington,
Seattle, WA, USA
| | - William S Bush
- Cleveland Institute for Computational Biology, Department of Population and
Quantitative Health Sciences, Case Western Reserve University,
Cleveland, OH, USA
| | - Corinne D Engelman
- Department of Population Health Sciences, School of Medicine and Public
Health, University of Wisconsin-Madison, Madison,
WI, USA
| | - Qiongshi Lu
- Department of Statistics, University of Wisconsin-Madison,
Madison, WI, USA
- Department of Biostatistics and Medical Informatics, University of
Wisconsin-Madison, Madison, WI, USA
| | - David W Fardo
- Department of Biostatistics, College of Public Health, University of
Kentucky, Lexington, KY, USA
- Sanders-Brown Center on Aging, University of Kentucky,
Lexington, KY, USA
| | - Emily H Trittschuh
- Department of Psychiatry and Behavioral Sciences, University of Washington
School of Medicine, Seattle, WA, USA
- VA Puget Sound Health Care System, GRECC, Seattle,
WA, USA
| | - Jesse Mez
- Department of Neurology, Boston University School of
Medicine, Boston, MA, USA
| | | | - Hector Hernandez Saucedo
- UC Davis Alzheimer's Disease Research Center, Department of Neurology,
University of California Davis Medical Center, Sacramento,
CA, USA
| | | | - Rachel F Buckley
- Department of Neurology, Massachusetts General Hospital/Harvard Medical
School, Boston, MA, USA
- Center for Alzheimer's Research and Treatment, Department of Neurology,
Brigham and Women’s Hospital/Harvard Medical School, Boston,
MA, USA
- Melbourne School of Psychological Sciences, University of
Melbourne, Melbourne, Australia
| | - Michael J Properzi
- Department of Neurology, Massachusetts General Hospital/Harvard Medical
School, Boston, MA, USA
| | - Elizabeth C Mormino
- Department of Neurology and Neurological Sciences, Stanford
University, Stanford, CA, USA
| | - Hyun Sik Yang
- Department of Neurology, Massachusetts General Hospital/Harvard Medical
School, Boston, MA, USA
- Center for Alzheimer's Research and Treatment, Department of Neurology,
Brigham and Women’s Hospital/Harvard Medical School, Boston,
MA, USA
| | - Theresa M Harrison
- Helen Wills Neuroscience Institute, University of California
Berkeley, Berkeley, CA, USA
| | - Trey Hedden
- Icahn School of Medicine at Mount Sinai, New York
City, NY, USA
| | - Kwangsik Nho
- Department of Radiology and Imaging Sciences, Indiana Alzheimer Disease
Center, Indiana University School of Medicine, Indianapolis,
IN, USA
- Center for Computational Biology and Bioinformatics, Indiana University
School of Medicine, Indianapolis, IN, USA
| | - Shea J Andrews
- Icahn School of Medicine at Mount Sinai, New York
City, NY, USA
| | - Douglas Tommet
- Department of Psychiatry and Human Behavior, Brown University School of
Medicine, Providence, RI, USA
| | | | | | - Douglas M Ruderfer
- Vanderbilt Genetics Institute, Vanderbilt University Medical
Center, Nashville, TN, USA
| | - Katherine A Gifford
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical
Center, Nashville, TN, USA
| | - Xiaoyuan Zhong
- Department of Statistics, University of Wisconsin-Madison,
Madison, WI, USA
- Department of Biostatistics and Medical Informatics, University of
Wisconsin-Madison, Madison, WI, USA
| | - Neha S Raghavan
- Department of Neurology, Columbia University, New
York, NY, USA
- The Taub Institute for Research on Alzheimer's Disease and The Aging Brain,
Columbia University, New York, NY, USA
- The Institute for Genomic Medicine, Columbia University Medical Center and
The New York Presbyterian Hospital, New York, NY,
USA
| | - Badri N Vardarajan
- Department of Neurology, Columbia University, New
York, NY, USA
- The Taub Institute for Research on Alzheimer's Disease and The Aging Brain,
Columbia University, New York, NY, USA
- The Institute for Genomic Medicine, Columbia University Medical Center and
The New York Presbyterian Hospital, New York, NY,
USA
| | | | | | | | - Margaret A Pericak-Vance
- John P. Hussman Institute for Human Genomics, University of Miami School of
Medicine, Miami, FL, USA
| | - Lindsay A Farrer
- Department of Neurology, Boston University School of
Medicine, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public
Health, Boston, MA, USA
- Department of Medicine (Biomedical Genetics), Boston University School of
Medicine, Boston, MA, USA
| | - Li San Wang
- Penn Neurodegeneration Genomics Center, Department of Pathology and
Laboratory Medicine, University of Pennsylvania Perelman School of
Medicine, Philadelphia, PA, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of
Medicine, St. Louis, MO, USA
| | - Gerard D Schellenberg
- Penn Neurodegeneration Genomics Center, Department of Pathology and
Laboratory Medicine, University of Pennsylvania Perelman School of
Medicine, Philadelphia, PA, USA
| | - Nancy J Cox
- Vanderbilt Genetics Institute, Vanderbilt University Medical
Center, Nashville, TN, USA
| | - Jonathan L Haines
- Cleveland Institute for Computational Biology, Department of Population and
Quantitative Health Sciences, Case Western Reserve University,
Cleveland, OH, USA
| | - C Dirk Keene
- Department of Pathology, University of Washington,
Seattle, WA, USA
| | - Andrew J Saykin
- Department of Radiology and Imaging Sciences, Indiana University School of
Medicine, Indianapolis, IN, USA
| | - Eric B Larson
- Department of Medicine, University of Washington,
Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute,
Seattle, WA, USA
| | - Reisa A Sperling
- Department of Neurology, Massachusetts General Hospital/Harvard Medical
School, Boston, MA, USA
| | - Richard Mayeux
- Department of Neurology, Columbia University, New
York, NY, USA
- The Taub Institute for Research on Alzheimer's Disease and The Aging Brain,
Columbia University, New York, NY, USA
- The Institute for Genomic Medicine, Columbia University Medical Center and
The New York Presbyterian Hospital, New York, NY,
USA
| | - Michael L Cuccaro
- John P. Hussman Institute for Human Genomics, University of Miami School of
Medicine, Miami, FL, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical
Center, Chicago, IL, USA
| | - Julie A Schneider
- Rush Alzheimer's Disease Center, Rush University Medical
Center, Chicago, IL, USA
| | - Paul K Crane
- Department of Medicine, University of Washington,
Seattle, WA, USA
| | - Angela L Jefferson
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical
Center, Nashville, TN, USA
| | - Timothy J Hohman
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical
Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical
Center, Nashville, TN, USA
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3
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Tijms BM, Gobom J, Reus L, Jansen I, Hong S, Dobricic V, Kilpert F, ten Kate M, Barkhof F, Tsolaki M, Verhey FRJ, Popp J, Martinez-Lage P, Vandenberghe R, Lleó A, Molinuevo JL, Engelborghs S, Bertram L, Lovestone S, Streffer J, Vos S, Bos I, Blennow K, Scheltens P, Teunissen CE, Zetterberg H, Visser PJ. Pathophysiological subtypes of Alzheimer's disease based on cerebrospinal fluid proteomics. Brain 2020; 143:3776-3792. [PMID: 33439986 PMCID: PMC7805814 DOI: 10.1093/brain/awaa325] [Citation(s) in RCA: 70] [Impact Index Per Article: 17.5] [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: 03/23/2020] [Revised: 08/03/2020] [Accepted: 08/06/2020] [Indexed: 12/17/2022] Open
Abstract
Alzheimer's disease is biologically heterogeneous, and detailed understanding of the processes involved in patients is critical for development of treatments. CSF contains hundreds of proteins, with concentrations reflecting ongoing (patho)physiological processes. This provides the opportunity to study many biological processes at the same time in patients. We studied whether Alzheimer's disease biological subtypes can be detected in CSF proteomics using the dual clustering technique non-negative matrix factorization. In two independent cohorts (EMIF-AD MBD and ADNI) we found that 705 (77% of 911 tested) proteins differed between Alzheimer's disease (defined as having abnormal amyloid, n = 425) and controls (defined as having normal CSF amyloid and tau and normal cognition, n = 127). Using these proteins for data-driven clustering, we identified three robust pathophysiological Alzheimer's disease subtypes within each cohort showing (i) hyperplasticity and increased BACE1 levels; (ii) innate immune activation; and (iii) blood-brain barrier dysfunction with low BACE1 levels. In both cohorts, the majority of individuals were labelled as having subtype 1 (80, 36% in EMIF-AD MBD; 117, 59% in ADNI), 71 (32%) in EMIF-AD MBD and 41 (21%) in ADNI were labelled as subtype 2, and 72 (32%) in EMIF-AD MBD and 39 (20%) individuals in ADNI were labelled as subtype 3. Genetic analyses showed that all subtypes had an excess of genetic risk for Alzheimer's disease (all P > 0.01). Additional pathological comparisons that were available for a subset in ADNI suggested that subtypes showed similar severity of Alzheimer's disease pathology, and did not differ in the frequencies of co-pathologies, providing further support that found subtypes truly reflect Alzheimer's disease heterogeneity. Compared to controls, all non-demented Alzheimer's disease individuals had increased risk of showing clinical progression (all P < 0.01). Compared to subtype 1, subtype 2 showed faster clinical progression after correcting for age, sex, level of education and tau levels (hazard ratio = 2.5; 95% confidence interval = 1.2, 5.1; P = 0.01), and subtype 3 at trend level (hazard ratio = 2.1; 95% confidence interval = 1.0, 4.4; P = 0.06). Together, these results demonstrate the value of CSF proteomics in studying the biological heterogeneity in Alzheimer's disease patients, and suggest that subtypes may require tailored therapy.
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Affiliation(s)
- Betty M Tijms
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC - Location VUmc, The Netherlands
| | - Johan Gobom
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Lianne Reus
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC - Location VUmc, The Netherlands
| | - Iris Jansen
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC - Location VUmc, The Netherlands
| | - Shengjun Hong
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Lübeck, Germany
| | - Valerija Dobricic
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Lübeck, Germany
| | - Fabian Kilpert
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Lübeck, Germany
| | - Mara ten Kate
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC - Location VUmc, The Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC - location VUmc, Amsterdam, The Netherlands
- Institutes of Neurology and Healthcare Engineering, UCL London, London, UK
| | - Magda Tsolaki
- 1st Department of Neurology, AHEPA University Hospital, Makedonia, Thessaloniki, Greece
| | - Frans R J Verhey
- Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Julius Popp
- University Hospital Lausanne, Lausanne, Switzerland
- Geriatric Psychiatry, Department of Psychiatry, Geneva University Hospital, Geneva, Switzerland
| | | | - Rik Vandenberghe
- Neurology Service, University Hospitals Leuven, Leuven, Belgium
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Alberto Lleó
- IIB-Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autonoma de Barcelona, Barcelona, Spain
| | - José Luís Molinuevo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Alzheimer’s Disease Unit and Other Cognitive Disorders Unit, Hospital Clinic de Barcelona, Barcelona, Spain
| | - Sebastiaan Engelborghs
- Institute Born-Bunge, Reference Center for Biological Markers of Dementia (BIODEM), Institute Born-Bunge, University of Antwerp, Belgium
- Department of Neurology, UZ Brussel and Center for Neurosciences (C4N), Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Lübeck, Germany
| | - Simon Lovestone
- University of Oxford, Oxford, UK
- Janssen R&D, Beerse, Belgium
| | - Johannes Streffer
- Institute Born-Bunge, Reference Center for Biological Markers of Dementia (BIODEM), Institute Born-Bunge, University of Antwerp, Belgium
- UCB Biopharma SPRL, Brain-l'Alleud, Belgium
| | - Stephanie Vos
- Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Isabelle Bos
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC - Location VUmc, The Netherlands
- Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | | | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC - Location VUmc, The Netherlands
| | - Charlotte E Teunissen
- Neurochemistry laboratory, Department of Clinical Chemistry, Amsterdam UMC - location VUmc, Amsterdam Neuroscience, The Netherlands
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC - Location VUmc, The Netherlands
- Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Department of Neurobiology, Care Sciences and Society, Division of Neurogeriatrics, Karolinska Institutet, Stockholm Sweden
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4
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Dumitrescu L, Mahoney ER, Mukherjee S, Lee ML, Bush WS, Engelman CD, Lu Q, Fardo DW, Trittschuh EH, Mez J, Kaczorowski C, Hernandez Saucedo H, Widaman KF, Buckley R, Properzi M, Mormino E, Yang HS, Harrison T, Hedden T, Nho K, Andrews SJ, Tommet D, Hadad N, Sanders RE, Ruderfer DM, Gifford KA, Moore AM, Cambronero F, Zhong X, Raghavan NS, Vardarajan B, Pericak-Vance MA, Farrer LA, Wang LS, Cruchaga C, Schellenberg G, Cox NJ, Haines JL, Keene CD, Saykin AJ, Larson EB, Sperling RA, Mayeux R, Bennett DA, Schneider JA, Crane PK, Jefferson AL, Hohman TJ. Genetic variants and functional pathways associated with resilience to Alzheimer's disease. Brain 2020; 143:2561-2575. [PMID: 32844198 PMCID: PMC7447518 DOI: 10.1093/brain/awaa209] [Citation(s) in RCA: 85] [Impact Index Per Article: 21.3] [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: 01/30/2020] [Revised: 04/22/2020] [Accepted: 05/08/2020] [Indexed: 12/23/2022] Open
Abstract
Approximately 30% of older adults exhibit the neuropathological features of Alzheimer's disease without signs of cognitive impairment. Yet, little is known about the genetic factors that allow these potentially resilient individuals to remain cognitively unimpaired in the face of substantial neuropathology. We performed a large, genome-wide association study (GWAS) of two previously validated metrics of cognitive resilience quantified using a latent variable modelling approach and representing better-than-predicted cognitive performance for a given level of neuropathology. Data were harmonized across 5108 participants from a clinical trial of Alzheimer's disease and three longitudinal cohort studies of cognitive ageing. All analyses were run across all participants and repeated restricting the sample to individuals with unimpaired cognition to identify variants at the earliest stages of disease. As expected, all resilience metrics were genetically correlated with cognitive performance and education attainment traits (P-values < 2.5 × 10-20), and we observed novel correlations with neuropsychiatric conditions (P-values < 7.9 × 10-4). Notably, neither resilience metric was genetically correlated with clinical Alzheimer's disease (P-values > 0.42) nor associated with APOE (P-values > 0.13). In single variant analyses, we observed a genome-wide significant locus among participants with unimpaired cognition on chromosome 18 upstream of ATP8B1 (index single nucleotide polymorphism rs2571244, minor allele frequency = 0.08, P = 2.3 × 10-8). The top variant at this locus (rs2571244) was significantly associated with methylation in prefrontal cortex tissue at multiple CpG sites, including one just upstream of ATPB81 (cg19596477; P = 2 × 10-13). Overall, this comprehensive genetic analysis of resilience implicates a putative role of vascular risk, metabolism, and mental health in protection from the cognitive consequences of neuropathology, while also providing evidence for a novel resilience gene along the bile acid metabolism pathway. Furthermore, the genetic architecture of resilience appears to be distinct from that of clinical Alzheimer's disease, suggesting that a shift in focus to molecular contributors to resilience may identify novel pathways for therapeutic targets.
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Affiliation(s)
- Logan Dumitrescu
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Emily R Mahoney
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | - Michael L Lee
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - William S Bush
- Cleveland Institute for Computational Biology, Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Corinne D Engelman
- Department of Population Health Sciences, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Qiongshi Lu
- Department of Statistics, University of Wisconsin-Madison, Madison, WI, USA
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA
| | - David W Fardo
- Department of Biostatistics, College of Public Health, University of Kentucky, Lexington, KY, USA
- Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY, USA
| | - Emily H Trittschuh
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA, USA
- VA Puget Sound Health Care System, GRECC, Seattle, WA, USA
| | - Jesse Mez
- Deparment of Neurology, Boston University School of Medicine, Boston, MA, USA
| | | | - Hector Hernandez Saucedo
- UC Davis Alzheimer’s Disease Research Center, Department of Neurology, University of California Davis Medical Center, Sacramento, CA, USA
| | | | - Rachel Buckley
- Department of Neurology, Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA
- Center for Alzheimer’s Research and Treatment, Department of Neurology, Brigham and Women’s Hospital/Harvard Medical School, Boston, MA, USA
- Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, Australia
| | - Michael Properzi
- Department of Neurology, Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA
| | - Elizabeth Mormino
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Hyun-Sik Yang
- Department of Neurology, Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA
- Center for Alzheimer’s Research and Treatment, Department of Neurology, Brigham and Women’s Hospital/Harvard Medical School, Boston, MA, USA
| | - Tessa Harrison
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA
| | - Trey Hedden
- Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Kwangsik Nho
- Department of Radiology and Imaging Sciences, Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Shea J Andrews
- Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | - Doug Tommet
- Department of Psychiatry and Human Behavior, Brown University School of Medicine, Providence, RI, USA
| | | | | | - Douglas M Ruderfer
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Katherine A Gifford
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Annah M Moore
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Francis Cambronero
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Xiaoyuan Zhong
- Department of Statistics, University of Wisconsin-Madison, Madison, WI, USA
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, USA
| | - Neha S Raghavan
- Department of Neurology, Columbia University, New York, NY, USA
- The Taub Institute for Research on Alzheimer’s Disease and The Aging Brain, Columbia University, New York, NY, USA
- The Institute for Genomic Medicine, Columbia University Medical Center and The New York Presbyterian Hospital, New York, NY, USA
| | - Badri Vardarajan
- Department of Neurology, Columbia University, New York, NY, USA
- The Taub Institute for Research on Alzheimer’s Disease and The Aging Brain, Columbia University, New York, NY, USA
- The Institute for Genomic Medicine, Columbia University Medical Center and The New York Presbyterian Hospital, New York, NY, USA
| | | | | | - Margaret A Pericak-Vance
- John P. Hussman Institute for Human Genomics, University of Miami School of Medicine, Miami, FL, USA
| | - Lindsay A Farrer
- Deparment of Neurology, Boston University School of Medicine, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA
| | - Li-San Wang
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Gerard Schellenberg
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Nancy J Cox
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jonathan L Haines
- Cleveland Institute for Computational Biology, Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - C Dirk Keene
- Department of Pathology, University of Washington, Seattle, WA, USA
| | - Andrew J Saykin
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Eric B Larson
- Department of Medicine, University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Reisa A Sperling
- Department of Neurology, Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA
| | - Richard Mayeux
- Department of Neurology, Columbia University, New York, NY, USA
- The Taub Institute for Research on Alzheimer’s Disease and The Aging Brain, Columbia University, New York, NY, USA
- The Institute for Genomic Medicine, Columbia University Medical Center and The New York Presbyterian Hospital, New York, NY, USA
| | - David A Bennett
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Julie A Schneider
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Paul K Crane
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Angela L Jefferson
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Timothy J Hohman
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
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