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Rhodus EK, Barber J, Kryscio RJ, Abner EL, Bahrani AA, Lewis KES, Carey B, Nelson PT, Van Eldik LJ, Jicha GA. Frontotemporal neurofibrillary tangles and cerebrovascular lesions are associated with autism spectrum behaviors in late-life dementia. J Neurol 2022; 269:5105-5113. [PMID: 35596794 PMCID: PMC9644295 DOI: 10.1007/s00415-022-11167-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] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 04/29/2022] [Accepted: 05/01/2022] [Indexed: 10/18/2022]
Abstract
BACKGROUND AND OBJECTIVES The pathologic substrates or neuroanatomic regions responsible for similarities in behavioral features seen in autism spectrum disorder and late-life dementia remain unknown. The present study examined the neuropathologic features of late-life dementia in research volunteers with and without antemortem behaviors characteristic of autism spectrum disorders. METHODS Antemortem cross-sectional assessment of autistic spectrum behaviors proximal to death in persons with diagnosis of mild cognitive impairment or dementia was completed using the Gilliam Autism Rating Scale, 2nd edition (GARS-2), followed by postmortem quantitative and semiquantitative neuropathologic assessment. All individuals who completed the GARS-2 prior to autopsy were included (n = 56) and we note that no participants had known diagnosis of autism spectrum disorder. The GARS-2 was used as an antemortem screening tool to stratify participants into two groups: "Autism Possible/Very Likely" or "Autism Unlikely." Data were analyzed using nonparametric statistics comparing location and scale to evaluate between-group differences in pathologic features. RESULTS Neurofibrillary tangles (NFT; p = 0.028) density and tau burden (p = 0.032) in the frontal region, the NFT density (p = 0.048) and neuritic plaque burden (p = 0.042), and the tau burden (p = 0.032) of the temporal region, were significantly different in scale between groups. For measures with significant group differences, the medians of the Autism Possible/Very Likely group were roughly equal to the 75th percentile of the Autism Unlikely group (i.e., the distributions were shifted to the right). DISCUSSION This study links behaviors characteristic of autism to increased pathologic tau burden in the frontal and temporal lobes in persons with late-life dementia. Additional studies are needed to determine causal factors and treatment options for behaviors characteristic of autism behaviors in late-life dementias.
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Affiliation(s)
- Elizabeth K Rhodus
- Sanders-Brown Center on Aging, University of Kentucky, 1030 S. Broadway, Ste 5, Lexington, KY, 40536, USA.
- Department of Behavioral Science, University of Kentucky, Lexington, KY, USA.
| | - Justin Barber
- Sanders-Brown Center on Aging, University of Kentucky, 1030 S. Broadway, Ste 5, Lexington, KY, 40536, USA
| | - Richard J Kryscio
- Sanders-Brown Center on Aging, University of Kentucky, 1030 S. Broadway, Ste 5, Lexington, KY, 40536, USA
- Department of Statistics, University of Kentucky, Lexington, KY, USA
- Department of Biostatistics, University of Kentucky, Lexington, KY, USA
| | - Erin L Abner
- Sanders-Brown Center on Aging, University of Kentucky, 1030 S. Broadway, Ste 5, Lexington, KY, 40536, USA
- Department of Epidemiology, University of Kentucky, Lexington, KY, USA
- Department of Biostatistics, University of Kentucky, Lexington, KY, USA
| | - Ahmed A Bahrani
- Sanders-Brown Center on Aging, University of Kentucky, 1030 S. Broadway, Ste 5, Lexington, KY, 40536, USA
| | - Kristine E Shady Lewis
- Sanders-Brown Center on Aging, University of Kentucky, 1030 S. Broadway, Ste 5, Lexington, KY, 40536, USA
| | - Brandi Carey
- Sanders-Brown Center on Aging, University of Kentucky, 1030 S. Broadway, Ste 5, Lexington, KY, 40536, USA
| | - Peter T Nelson
- Sanders-Brown Center on Aging, University of Kentucky, 1030 S. Broadway, Ste 5, Lexington, KY, 40536, USA
- Department of Pathology and Division of Neuropathology, University of Kentucky, Lexington, KY, USA
| | - Linda J Van Eldik
- Sanders-Brown Center on Aging, University of Kentucky, 1030 S. Broadway, Ste 5, Lexington, KY, 40536, USA
- Department of Neuroscience, University of Kentucky, Lexington, KY, USA
| | - Gregory A Jicha
- Sanders-Brown Center on Aging, University of Kentucky, 1030 S. Broadway, Ste 5, Lexington, KY, 40536, USA
- Department of Behavioral Science, University of Kentucky, Lexington, KY, USA
- Department of Neurology, University of Kentucky, Lexington, KY, USA
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Dincer A, Gordon BA, Hari-Raj A, Keefe SJ, Flores S, McKay NS, Paulick AM, Shady Lewis KE, Feldman RL, Hornbeck RC, Allegri R, Ances BM, Berman SB, Brickman AM, Brooks WS, Cash DM, Chhatwal JP, Farlow MR, la Fougère C, Fox NC, Fulham MJ, Jack CR, Joseph-Mathurin N, Karch CM, Lee A, Levin J, Masters CL, McDade EM, Oh H, Perrin RJ, Raji C, Salloway SP, Schofield PR, Su Y, Villemagne VL, Wang Q, Weiner MW, Xiong C, Yakushev I, Morris JC, Bateman RJ, L S Benzinger T. Comparing cortical signatures of atrophy between late-onset and autosomal dominant Alzheimer disease. Neuroimage Clin 2020; 28:102491. [PMID: 33395982 PMCID: PMC7689410 DOI: 10.1016/j.nicl.2020.102491] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [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: 05/20/2020] [Revised: 09/18/2020] [Accepted: 10/30/2020] [Indexed: 11/30/2022]
Abstract
Cortical signatures selective to AD could provide an early MRI biomarker. Autosomal dominant Alzheimer disease (ADAD) may model an ideal AD signature. ADAD and late-onset maps overlap in parietal cortex but contain unique features. Signatures predicted increasing amyloid within their own, but not across cohorts. These results indicate atrophy in AD can take multiple spatial patterns.
Defining a signature of cortical regions of interest preferentially affected by Alzheimer disease (AD) pathology may offer improved sensitivity to early AD compared to hippocampal volume or mesial temporal lobe alone. Since late-onset Alzheimer disease (LOAD) participants tend to have age-related comorbidities, the younger-onset age in autosomal dominant AD (ADAD) may provide a more idealized model of cortical thinning in AD. To test this, the goals of this study were to compare the degree of overlap between the ADAD and LOAD cortical thinning maps and to evaluate the ability of the ADAD cortical signature regions to predict early pathological changes in cognitively normal individuals. We defined and analyzed the LOAD cortical maps of cortical thickness in 588 participants from the Knight Alzheimer Disease Research Center (Knight ADRC) and the ADAD cortical maps in 269 participants from the Dominantly Inherited Alzheimer Network (DIAN) observational study. Both cohorts were divided into three groups: cognitively normal controls (nADRC = 381; nDIAN = 145), preclinical (nADRC = 153; nDIAN = 76), and cognitively impaired (nADRC = 54; nDIAN = 48). Both cohorts underwent clinical assessments, 3T MRI, and amyloid PET imaging with either 11C-Pittsburgh compound B or 18F-florbetapir. To generate cortical signature maps of cortical thickness, we performed a vertex-wise analysis between the cognitively normal controls and impaired groups within each cohort using six increasingly conservative statistical thresholds to determine significance. The optimal cortical map among the six statistical thresholds was determined from a receiver operating characteristic analysis testing the performance of each map in discriminating between the cognitively normal controls and preclinical groups. We then performed within-cohort and cross-cohort (e.g. ADAD maps evaluated in the Knight ADRC cohort) analyses to examine the sensitivity of the optimal cortical signature maps to the amyloid levels using only the cognitively normal individuals (cognitively normal controls and preclinical groups) in comparison to hippocampal volume. We found the optimal cortical signature maps were sensitive to early increases in amyloid for the asymptomatic individuals within their respective cohorts and were significant beyond the inclusion of hippocampus volume, but the cortical signature maps performed poorly when analyzing across cohorts. These results suggest the cortical signature maps are a useful MRI biomarker of early AD-related neurodegeneration in preclinical individuals and the pattern of decline differs between LOAD and ADAD.
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Affiliation(s)
- Aylin Dincer
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Brian A Gordon
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Amrita Hari-Raj
- The Ohio State University College of Medicine, Columbus, OH, USA
| | - Sarah J Keefe
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Shaney Flores
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Nicole S McKay
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Angela M Paulick
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Kristine E Shady Lewis
- Sanders Brown Center on Aging & Alzheimer's, University of Kentucky College of Medicine, Lexington, KY, USA
| | - Rebecca L Feldman
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Russ C Hornbeck
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Ricardo Allegri
- Department of Cognitive Neurology, Neuropsychology and Neuropsychiatry, FLENI, Buenos Aires, Argentina
| | - Beau M Ances
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Sarah B Berman
- Department of Neurology and Clinical & Translational Science, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Adam M Brickman
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain and Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - William S Brooks
- Neuroscience Research Australia, Sydney, NSW, Australia; Prince of Wales Clinical School, University of New South Wales, Sydney, NSW, Australia
| | - David M Cash
- Dementia Research Centre and UK Dementia Research Institute, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Jasmeer P Chhatwal
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Martin R Farlow
- Department of Neurology, Department of Radiology and Imaging Science, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Christian la Fougère
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany; Department of Nuclear Medicine and Clinical Molecular Imaging, University Hospital of Tübingen, Tübingen, Germany
| | - Nick C Fox
- Dementia Research Centre and UK Dementia Research Institute, UCL Queen Square Institute of Neurology, London, United Kingdom
| | - Michael J Fulham
- Department of Molecular Imaging, Royal Prince Alfred Hospital and University of Sydney, Sydney, NSW, Australia
| | | | - Nelly Joseph-Mathurin
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Celeste M Karch
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Athene Lee
- Department of Psychiatry and Human Behavior, Department of Neurology, Butler Hospital, Warren Alpert Medical School of Brown University, Providence, RI, USA
| | - Johannes Levin
- German Center for Neurodegenerative Diseases (DZNE) Munich, Munich, Germany; Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany; Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Colin L Masters
- The Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, VIC, Australia
| | - Eric M McDade
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Hwamee Oh
- Department of Psychiatry and Human Behavior, Department of Neurology, Butler Hospital, Warren Alpert Medical School of Brown University, Providence, RI, USA
| | - Richard J Perrin
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Cyrus Raji
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Stephen P Salloway
- Department of Psychiatry and Human Behavior, Department of Neurology, Butler Hospital, Warren Alpert Medical School of Brown University, Providence, RI, USA
| | - Peter R Schofield
- Neuroscience Research Australia, Sydney, NSW, Australia; School of Medical Sciences, University of New South Wales, Sydney, NSW, Australia
| | - Yi Su
- Banner Alzheimer's Institute, Phoenix, AZ, USA
| | - Victor L Villemagne
- Department of Molecular Imaging and Therapy, Department of Medicine, Austin Health, University of Melbourne, Melbourne, VIC, Australia
| | - Qing Wang
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Michael W Weiner
- Department of Radiology and Biomedical Imaging, School of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Chengjie Xiong
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Igor Yakushev
- Department of Nuclear Medicine, Technical University of Munich, Munich, Germany
| | - John C Morris
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Randall J Bateman
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA
| | - Tammie L S Benzinger
- Department of Radiology, Department of Neurology, Department of Psychiatry, Department of Pathology and Immunology, Division of Biostatistics, Washington University School of Medicine, Saint Louis, MO, USA.
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