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Shellikeri S, Cho S, Ash S, Gonzalez-Recober C, McMillan CT, Elman L, Quinn C, Amado DA, Baer M, Irwin DJ, Massimo L, Olm C, Liberman M, Grossman M, Nevler N. Digital markers of motor speech impairments in spontaneous speech of patients with ALS-FTD spectrum disorders. Amyotroph Lateral Scler Frontotemporal Degener 2024; 25:317-325. [PMID: 38050971 PMCID: PMC11023759 DOI: 10.1080/21678421.2023.2288106] [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: 10/06/2023] [Accepted: 11/20/2023] [Indexed: 12/07/2023]
Abstract
OBJECTIVE To evaluate automated digital speech measures, derived from spontaneous speech (picture descriptions), in assessing bulbar motor impairments in patients with ALS-FTD spectrum disorders (ALS-FTSD). METHODS Automated vowel algorithms were employed to extract two vowel acoustic measures: vowel space area (VSA), and mean second formant slope (F2 slope). Vowel measures were compared between ALS with and without clinical bulbar symptoms (ALS + bulbar (n = 49, ALSFRS-r bulbar subscore: x¯ = 9.8 (SD = 1.7)) vs. ALS-nonbulbar (n = 23), behavioral variant frontotemporal dementia (bvFTD, n = 25) without a motor syndrome, and healthy controls (HC, n = 32). Correlations with bulbar motor clinical scales, perceived listener effort, and MRI cortical thickness of the orobuccal primary motor cortex (oral PMC) were examined. We compared vowel measures to speaking rate, a conventional metric for assessing bulbar dysfunction. RESULTS ALS + bulbar had significantly reduced VSA and F2 slope than ALS-nonbulbar (|d|=0.94 and |d|=1.04, respectively), bvFTD (|d|=0.89 and |d|=1.47), and HC (|d|=0.73 and |d|=0.99). These reductions correlated with worse bulbar clinical scores (VSA: R = 0.33, p = 0.043; F2 slope: R = 0.38, p = 0.011), greater listener effort (VSA: R=-0.43, p = 0.041; F2 slope: p > 0.05), and cortical thinning in oral PMC (F2 slope: β = 0.0026, p = 0.017). Vowel measures demonstrated greater sensitivity and specificity for bulbar impairment than speaking rate, while showing independence from cognitive and respiratory impairments. CONCLUSION Automatic vowel measures are easily derived from a brief spontaneous speech sample, are sensitive to mild-moderate stage of bulbar disease in ALS-FTSD, and may present better sensitivity to bulbar impairment compared to traditional assessments such as speaking rate.
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Affiliation(s)
- Sanjana Shellikeri
- Penn Frontotemporal Degeneration Center and Department of Neurology, University of Pennsylvania, Philadelphia, PA
| | - Sunghye Cho
- Linguistic Data Consortium, University of Pennsylvania, Philadelphia, PA
| | - Sharon Ash
- Penn Frontotemporal Degeneration Center and Department of Neurology, University of Pennsylvania, Philadelphia, PA
| | - Carmen Gonzalez-Recober
- Penn Frontotemporal Degeneration Center and Department of Neurology, University of Pennsylvania, Philadelphia, PA
| | - Corey T. McMillan
- Penn Frontotemporal Degeneration Center and Department of Neurology, University of Pennsylvania, Philadelphia, PA
| | | | - Colin Quinn
- Penn ALS Clinic, University of Pennsylvania, PA
| | | | | | - David J Irwin
- Penn Frontotemporal Degeneration Center and Department of Neurology, University of Pennsylvania, Philadelphia, PA
| | - Lauren Massimo
- Penn Frontotemporal Degeneration Center and Department of Neurology, University of Pennsylvania, Philadelphia, PA
| | - Chris Olm
- Penn Frontotemporal Degeneration Center and Department of Neurology, University of Pennsylvania, Philadelphia, PA
| | - Mark Liberman
- Linguistic Data Consortium, University of Pennsylvania, Philadelphia, PA
- Department of Linguistics, University of Pennsylvania, Philadelphia, PA
| | - Murray Grossman
- Penn Frontotemporal Degeneration Center and Department of Neurology, University of Pennsylvania, Philadelphia, PA
| | - Naomi Nevler
- Penn Frontotemporal Degeneration Center and Department of Neurology, University of Pennsylvania, Philadelphia, PA
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Cousins KAQ, Phillips JS, Das SR, O'Brien K, Tropea TF, Chen-Plotkin A, Shaw LM, Nasrallah IM, Mechanic-Hamilton D, McMillan CT, Irwin DJ, Lee EB, Wolk DA. Pathologic and cognitive correlates of plasma biomarkers in neurodegenerative disease. Alzheimers Dement 2024. [PMID: 38644682 DOI: 10.1002/alz.13777] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 02/06/2024] [Accepted: 02/07/2024] [Indexed: 04/23/2024]
Abstract
INTRODUCTION We investigate pathological correlates of plasma phosphorylated tau 181 (p-tau181), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) across a clinically diverse spectrum of neurodegenerative disease, including normal cognition (NormCog) and impaired cognition (ImpCog). METHODS Participants were NormCog (n = 132) and ImpCog (n = 461), with confirmed β-amyloid (Aβ+/-) status (cerebrospinal fluid, positron emission tomography, autopsy) and single molecule array plasma measurements. Logistic regression and receiver operating characteristic (ROC) area under the curve (AUC) tested how combining plasma analytes discriminated Aβ+ from Aβ-. Survival analyses tested time to clinical dementia rating (global CDR) progression. RESULTS Multivariable models (p-tau+GFAP+NfL) had the best performance to detect Aβ+ in NormCog (ROCAUC = 0.87) and ImpCog (ROCAUC = 0.87). Survival analyses demonstrated that higher NfL best predicted faster CDR progression for both Aβ+ (hazard ratio [HR] = 2.94; p = 8.1e-06) and Aβ- individuals (HR = 3.11; p = 2.6e-09). DISCUSSION Combining plasma biomarkers can optimize detection of Alzheimer's disease (AD) pathology across cognitively normal and clinically diverse neurodegenerative disease. HIGHLIGHTS Participants were clinically heterogeneous, with autopsy- or biomarker-confirmed Aβ. Combining plasma p-tau181, GFAP, and NfL improved diagnostic accuracy for Aβ status. Diagnosis by plasma biomarkers is more accurate in amnestic AD than nonamnestic AD. Plasma analytes show independent associations with tau PET and post mortem Aβ/tau. Plasma NfL predicted longitudinal cognitive decline in both Aβ+ and Aβ- individuals.
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Affiliation(s)
- Katheryn A Q Cousins
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Jeffrey S Phillips
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Sandhitsu R Das
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Kyra O'Brien
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Thomas F Tropea
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Alice Chen-Plotkin
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Ilya M Nasrallah
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Dawn Mechanic-Hamilton
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Corey T McMillan
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - David J Irwin
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Edward B Lee
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - David A Wolk
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Rhodes E, Alfa S, Jin HA, Massimo L, Elman L, Amado D, Baer M, Quinn C, McMillan CT. Cognitive reserve in ALS: the role of occupational skills and requirements. Amyotroph Lateral Scler Frontotemporal Degener 2024:1-10. [PMID: 38591193 DOI: 10.1080/21678421.2024.2336113] [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: 12/18/2023] [Accepted: 03/18/2024] [Indexed: 04/10/2024]
Abstract
OBJECTIVE Amyotrophic Lateral Sclerosis (ALS) is a heterogeneous neurodegenerative condition featuring variable degrees of motor and cognitive impairment. We assessed the impact of specific, empirically derived occupational skills and requirements on cognitive and motor functioning in ALS. METHODS Individuals with ALS (n = 150) were recruited from the University of Pennsylvania's Comprehensive ALS Clinic. The Edinburgh Cognitive and Behavioral ALS Screen (ECAS) measured cognition, and the Penn Upper Motor Neuron (PUMNS) and ALS Functional Rating Scales (ALSFRS-R) measured motor symptoms. We derived 17 factors representing distinct occupational skills and requirements from the Occupational Information Network (O*NET), which were related to cognitive and motor scores using multiple linear regression. RESULTS Occupational roles involving greater reasoning ability (β = 2.12, p < .05), social ability (β = 1.73, p < .05), analytic skills, (β = 3.12, p < .01) and humanities knowledge (β = 1.83, p<.01) were associated with better performance on the ECAS, while jobs involving more exposure to environmental hazards (β=-2.57, p < .01) and technical skills (β=-2.16, p<.01) were associated with lower ECAS scores. Jobs requiring more precision skills (β = 1.91, p < .05) were associated with greater motor dysfunction on the PUMNS. CONCLUSIONS Occupational histories involving more cognitively complex skills and activities were related to preserved cognitive functioning in ALS consistent with the cognitive reserve hypothesis, while jobs with greater exposure to environmental hazards and technical demands were linked to poorer cognitive functioning. Jobs involving more repetitive movements were associated with worse motor functioning, possibly due to overuse. Occupational history provides insight into protective and risk factors for variable degrees of cognitive and motor dysfunction in ALS.
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Affiliation(s)
- Emma Rhodes
- University of Pennsylvania Frontotemporal Degeneration Center, Philadelphia, PA, USA and
| | - Sebleh Alfa
- University of Pennsylvania Frontotemporal Degeneration Center, Philadelphia, PA, USA and
| | - Hannah A Jin
- University of Pennsylvania Frontotemporal Degeneration Center, Philadelphia, PA, USA and
| | - Lauren Massimo
- University of Pennsylvania Frontotemporal Degeneration Center, Philadelphia, PA, USA and
| | - Lauren Elman
- University of Pennsylvania Comprehensive ALS Center, Philadelphia, PA, USA
| | - Defne Amado
- University of Pennsylvania Comprehensive ALS Center, Philadelphia, PA, USA
| | - Michael Baer
- University of Pennsylvania Comprehensive ALS Center, Philadelphia, PA, USA
| | - Colin Quinn
- University of Pennsylvania Comprehensive ALS Center, Philadelphia, PA, USA
| | - Corey T McMillan
- University of Pennsylvania Frontotemporal Degeneration Center, Philadelphia, PA, USA and
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Ohm DT, Xie SX, Capp N, Arezoumandan S, Cousins KAQ, Rascovsky K, Wolk DA, Van Deerlin VM, Lee EB, McMillan CT, Irwin DJ. Cytoarchitectonic gradients of laminar degeneration in behavioral variant frontotemporal dementia. bioRxiv 2024:2024.04.05.588259. [PMID: 38644997 PMCID: PMC11030243 DOI: 10.1101/2024.04.05.588259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Behavioral variant frontotemporal dementia (bvFTD) is a clinical syndrome primarily caused by either tau (bvFTD-tau) or TDP-43 (bvFTD-TDP) proteinopathies. We previously found lower cortical layers and dorsolateral regions accumulate greater tau than TDP-43 pathology; however, patterns of laminar neurodegeneration across diverse cytoarchitecture in bvFTD is understudied. We hypothesized that bvFTD-tau and bvFTD-TDP have distinct laminar distributions of pyramidal neurodegeneration along cortical gradients, a topologic order of cytoarchitectonic subregions based on increasing pyramidal density and laminar differentiation. Here, we tested this hypothesis in a frontal cortical gradient consisting of five cytoarchitectonic types (i.e., periallocortex, agranular mesocortex, dysgranular mesocortex, eulaminate-I isocortex, eulaminate-II isocortex) spanning anterior cingulate, paracingulate, orbitofrontal, and mid-frontal gyri in bvFTD-tau (n=27), bvFTD-TDP (n=47), and healthy controls (HC; n=32). We immunostained all tissue for total neurons (NeuN; neuronal-nuclear protein) and pyramidal neurons (SMI32; non-phosphorylated neurofilament) and digitally quantified NeuN-immunoreactivity (ir) and SMI32-ir in supragranular II-III, infragranular V-VI, and all I-VI layers in each cytoarchitectonic type. We used linear mixed-effects models adjusted for demographic and biologic variables to compare SMI32-ir between groups and examine relationships with the cortical gradient, long-range pathways, and clinical symptoms. We found regional and laminar distributions of SMI32-ir expected for HC, validating our measures within the cortical gradient framework. While SMI32-ir loss was not related to the cortical gradient in bvFTD-TDP, SMI32-ir progressively decreased along the cortical gradient of bvFTD-tau and included greater SMI32-ir loss in supragranular eulaminate-II isocortex in bvFTD-tau vs bvFTD-TDP ( p =0.039). In a structural model for long-range laminar connectivity between infragranular mesocortex and supragranular isocortex, we found a larger laminar ratio of mesocortex-to-isocortex SMI32-ir in bvFTD-tau vs bvFTD-TDP ( p =0.019), suggesting select long-projecting pathways may contribute to isocortical-predominant degeneration in bvFTD-tau. In cytoarchitectonic types with the highest NeuN-ir, we found lower SMI32-ir in bvFTD-tau vs bvFTD-TDP ( p =0.047), suggesting pyramidal neurodegeneration may occur earlier in bvFTD-tau. Lastly, we found that reduced SMI32-ir related to behavioral severity and frontal-mediated letter fluency, not temporal-mediated confrontation naming, demonstrating the clinical relevance and specificity of frontal pyramidal neurodegeneration to bvFTD-related symptoms. Our data suggest loss of neurofilament-rich pyramidal neurons is a clinically relevant feature of bvFTD that selectively worsens along a frontal cortical gradient in bvFTD-tau, not bvFTD-TDP. Therefore, tau-mediated degeneration may preferentially involve pyramidal-rich layers that connect more distant cytoarchitectonic types. Moreover, the hierarchical arrangement of cytoarchitecture along cortical gradients may be an important neuroanatomical framework for identifying which types of cells and pathways are differentially involved between proteinopathies.
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Kim B, Yannatos I, Blam K, Wiebe D, Xie SX, McMillan CT, Mechanic‐Hamilton D, Wolk DA, Lee EB. Neighborhood disadvantage reduces cognitive reserve independent of neuropathologic change. Alzheimers Dement 2024; 20:2707-2718. [PMID: 38400524 PMCID: PMC11032541 DOI: 10.1002/alz.13736] [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: 10/16/2023] [Revised: 01/12/2024] [Accepted: 01/16/2024] [Indexed: 02/25/2024]
Abstract
INTRODUCTION Individuals in socioeconomically disadvantaged neighborhoods exhibit increased risk for impaired cognitive function. Whether this association relates to the major dementia-related neuropathologies is unknown. METHODS This cross-sectional study included 469 autopsy cases from 2011 to 2023. The relationships between neighborhood disadvantage measured by Area Deprivation Index (ADI) percentiles categorized into tertiles, cognition evaluated by the last Mini-Mental State Examination (MMSE) scores before death, and 10 dementia-associated proteinopathies and cerebrovascular disease were assessed using regression analyses. RESULTS Higher ADI was significantly associated with lower MMSE score. This was mitigated by increasing years of education. ADI was not associated with an increase in dementia-associated neuropathologic change. Moreover, the significant association between ADI and cognition remained even after controlling for changes in major dementia-associated proteinopathies or cerebrovascular disease. DISCUSSION Neighborhood disadvantage appears to be associated with decreased cognitive reserve. This association is modified by education but is independent of the major dementia-associated neuropathologies.
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Affiliation(s)
- Boram Kim
- Translational Neuropathology Research LaboratoryDepartment of Pathology and Laboratory MedicinePerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Isabel Yannatos
- Penn Frontotemporal Degeneration CenterDepartment of NeurologyPerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Kaitlin Blam
- Translational Neuropathology Research LaboratoryDepartment of Pathology and Laboratory MedicinePerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Douglas Wiebe
- Department of Emergency MedicineDepartment of EpidemiologyUniversity of MichiganAnn ArborMichiganUSA
| | - Sharon X. Xie
- Department of BiostatisticsEpidemiology and InformaticsPerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Corey T. McMillan
- Penn Frontotemporal Degeneration CenterDepartment of NeurologyPerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Dawn Mechanic‐Hamilton
- Penn Memory CenterDepartment of NeurologyPerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - David A. Wolk
- Penn Memory CenterDepartment of NeurologyPerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Edward B. Lee
- Translational Neuropathology Research LaboratoryDepartment of Pathology and Laboratory MedicinePerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPennsylvaniaUSA
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Phillips JS, Adluru N, Chung MK, Radhakrishnan H, Olm CA, Cook PA, Gee JC, Cousins KAQ, Arezoumandan S, Wolk DA, McMillan CT, Grossman M, Irwin DJ. Greater white matter degeneration and lower structural connectivity in non-amnestic vs. amnestic Alzheimer's disease. Front Neurosci 2024; 18:1353306. [PMID: 38567286 PMCID: PMC10986184 DOI: 10.3389/fnins.2024.1353306] [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] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Accepted: 02/26/2024] [Indexed: 04/04/2024] Open
Abstract
Introduction Multimodal evidence indicates Alzheimer's disease (AD) is characterized by early white matter (WM) changes that precede overt cognitive impairment. WM changes have overwhelmingly been investigated in typical, amnestic mild cognitive impairment and AD; fewer studies have addressed WM change in atypical, non-amnestic syndromes. We hypothesized each non-amnestic AD syndrome would exhibit WM differences from amnestic and other non-amnestic syndromes. Materials and methods Participants included 45 cognitively normal (CN) individuals; 41 amnestic AD patients; and 67 patients with non-amnestic AD syndromes including logopenic-variant primary progressive aphasia (lvPPA, n = 32), posterior cortical atrophy (PCA, n = 17), behavioral variant AD (bvAD, n = 10), and corticobasal syndrome (CBS, n = 8). All had T1-weighted MRI and 30-direction diffusion-weighted imaging (DWI). We performed whole-brain deterministic tractography between 148 cortical and subcortical regions; connection strength was quantified by tractwise mean generalized fractional anisotropy. Regression models assessed effects of group and phenotype as well as associations with grey matter volume. Topological analyses assessed differences in persistent homology (numbers of graph components and cycles). Additionally, we tested associations of topological metrics with global cognition, disease duration, and DWI microstructural metrics. Results Both amnestic and non-amnestic patients exhibited lower WM connection strength than CN participants in corpus callosum, cingulum, and inferior and superior longitudinal fasciculi. Overall, non-amnestic patients had more WM disease than amnestic patients. LvPPA patients had left-lateralized WM degeneration; PCA patients had reductions in connections to bilateral posterior parietal, occipital, and temporal areas. Topological analysis showed the non-amnestic but not the amnestic group had more connected components than controls, indicating persistently lower connectivity. Longer disease duration and cognitive impairment were associated with more connected components and fewer cycles in individuals' brain graphs. Discussion We have previously reported syndromic differences in GM degeneration and tau accumulation between AD syndromes; here we find corresponding differences in WM tracts connecting syndrome-specific epicenters. Determining the reasons for selective WM degeneration in non-amnestic AD is a research priority that will require integration of knowledge from neuroimaging, biomarker, autopsy, and functional genetic studies. Furthermore, longitudinal studies to determine the chronology of WM vs. GM degeneration will be key to assessing evidence for WM-mediated tau spread.
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Affiliation(s)
- Jeffrey S. Phillips
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Nagesh Adluru
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States
| | - Moo K. Chung
- Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
| | - Hamsanandini Radhakrishnan
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Christopher A. Olm
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Philip A. Cook
- Penn Image Computing and Science Laboratory, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - James C. Gee
- Penn Image Computing and Science Laboratory, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Katheryn A. Q. Cousins
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Sanaz Arezoumandan
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - David A. Wolk
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Penn Memory Center, University of Pennsylvania Health System, Philadelphia, PA, United States
| | - Corey T. McMillan
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Murray Grossman
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - David J. Irwin
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
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McHutchison CA, Wuu J, McMillan CT, Rademakers R, Statland J, Wu G, Rampersaud E, Myers J, Hernandez JP, Abrahams S, Benatar M. Temporal course of cognitive and behavioural changes in motor neuron diseases. J Neurol Neurosurg Psychiatry 2024; 95:316-324. [PMID: 37827570 PMCID: PMC10958376 DOI: 10.1136/jnnp-2023-331697] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 09/06/2023] [Indexed: 10/14/2023]
Abstract
BACKGROUND Cognitive and behavioural dysfunction may occur in people with motor neuron disease (MND), with some studies suggesting an association with the C9ORF72 repeat expansion. Their onset and progression, however, is poorly understood. We explored how cognition and behaviour change over time, and whether demographic, clinical and genetic factors impact these changes. METHODS Participants with MND were recruited through the Phenotype-Genotype-Biomarker study. Every 3-6 months, the Edinburgh Cognitive and Behavioural ALS Screen (ECAS) was used to assess amyotrophic lateral sclerosis (ALS) specific (executive functioning, verbal fluency, language) and ALS non-specific (memory, visuospatial) functions. Informants reported on behaviour symptoms via semi-structured interview. RESULTS Participants with neuropsychological data at ≥3 visits were included (n=237, mean age=59, 60% male), of which 18 (8%) were C9ORF72 positive. Baseline cognitive impairment was apparent in 18 (8%), typically in ALS specific domains, and associated with lower education, but not C9ORF72 status. Cognition, on average, remained stable over time, with two exceptions: (1) C9ORF72 carriers declined in all ECAS domains, (2) 8%-9% of participants with baseline cognitive impairment further declined, primarily in the ALS non-specific domain, which was associated with less education. Behavioural symptoms were uncommon. CONCLUSIONS In this study, cognitive dysfunction was less common than previously reported and remained stable over time for most. However, cognition declines longitudinally in a small subset, which is not entirely related to C9ORF72 status. Our findings raise questions about the timing of cognitive impairment in MND, and whether it arises during early clinically manifest disease or even prior to motor manifestations.
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Affiliation(s)
- Caroline A McHutchison
- School of Philosophy, Psychology, and Language Sciences, The University of Edinburgh, Edinburgh, UK
- Euan MacDonald Centre for Motor Neuron Disease Research, The University of Edinburgh, Edinburgh, UK
| | - Joanne Wuu
- Department of Neurology, University of Miami Miller School of Medicine, Miami, Florida, USA
| | - Corey T McMillan
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Rosa Rademakers
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Jeffrey Statland
- Department of Neurology, The University of Kansas Medical Center, Kansas City, Kansas, USA
| | - Gang Wu
- Department of Computational Biology, St Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Evadnie Rampersaud
- Department of Computational Biology, St Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Jason Myers
- Department of Computational Biology, St Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Jessica P Hernandez
- Department of Neurology, University of Miami Miller School of Medicine, Miami, Florida, USA
| | - Sharon Abrahams
- School of Philosophy, Psychology, and Language Sciences, The University of Edinburgh, Edinburgh, UK
- Euan MacDonald Centre for Motor Neuron Disease Research, The University of Edinburgh, Edinburgh, UK
| | - Michael Benatar
- Department of Neurology, University of Miami Miller School of Medicine, Miami, Florida, USA
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Lyu X, Duong MT, Xie L, de Flores R, Richardson H, Hwang G, Wisse LEM, DiCalogero M, McMillan CT, Robinson JL, Xie SX, Lee EB, Irwin DJ, Dickerson BC, Davatzikos C, Nasrallah IM, Yushkevich PA, Wolk DA, Das SR. Tau-neurodegeneration mismatch reveals vulnerability and resilience to comorbidities in Alzheimer's continuum. Alzheimers Dement 2024; 20:1586-1600. [PMID: 38050662 PMCID: PMC10984442 DOI: 10.1002/alz.13559] [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: 06/13/2023] [Revised: 10/23/2023] [Accepted: 10/24/2023] [Indexed: 12/06/2023]
Abstract
INTRODUCTION Variability in relationship of tau-based neurofibrillary tangles (T) and neurodegeneration (N) in Alzheimer's disease (AD) arises from non-specific nature of N, modulated by non-AD co-pathologies, age-related changes, and resilience factors. METHODS We used regional T-N residual patterns to partition 184 patients within the Alzheimer's continuum into data-driven groups. These were compared with groups from 159 non-AD (amyloid "negative") patients partitioned using cortical thickness, and groups in 98 patients with ante mortem MRI and post mortem tissue for measuring N and T, respectively. We applied the initial T-N residual model to classify 71 patients in an independent cohort into predefined groups. RESULTS AD groups displayed spatial T-N mismatch patterns resembling neurodegeneration patterns in non-AD groups, similarly associated with non-AD factors and diverging cognitive outcomes. In the autopsy cohort, limbic T-N mismatch correlated with TDP-43 co-pathology. DISCUSSION T-N mismatch may provide a personalized approach for determining non-AD factors associated with resilience/vulnerability in AD.
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Affiliation(s)
- Xueying Lyu
- Departments of BioengineeringUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Michael Tran Duong
- Departments of BioengineeringUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Long Xie
- Departments of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | | | - Hayley Richardson
- Department of Biostatistics, Epidemiology and InformaticsUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Gyujoon Hwang
- Departments of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | | | - Michael DiCalogero
- Departments of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Corey T. McMillan
- Departments of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - John L. Robinson
- Departments of Pathology and Laboratory MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Sharon X. Xie
- Department of Biostatistics, Epidemiology and InformaticsUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Edward B. Lee
- Departments of Pathology and Laboratory MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - David J. Irwin
- Departments of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | | | - Christos Davatzikos
- Departments of BioengineeringUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Ilya M. Nasrallah
- Departments of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Paul A. Yushkevich
- Departments of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - David A. Wolk
- Departments of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Sandhitsu R. Das
- Departments of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
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Liu J, Massimo L, McMillan CT, Dahodwala N. Novel computerized measure of apathy associates with care partner burden and instrumental activities of daily living in Parkinson's disease. Parkinsonism Relat Disord 2024; 120:105983. [PMID: 38183891 DOI: 10.1016/j.parkreldis.2023.105983] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 12/11/2023] [Accepted: 12/27/2023] [Indexed: 01/08/2024]
Abstract
BACKGROUND Impairment in goal-directed behavior (GDB) contributes to apathy, a prevalent syndrome in Parkinson's disease (PD). The Philadelphia Apathy Computerized Task (PACT) is a performance-based measure of GDB that may be less confounded by reduced patient insight, cognitive impairment, and care partner burnout. OBJECTIVE To examine how the PACT is related to patient function and care partner burden. METHODS PD patients with normal cognition (n = 19) or mild cognitive impairment (n = 14) and their care partners were recruited. Participants completed the PACT, a computerized paradigm consisting of subtasks specific to each component of GDB: initiation, motivation, and planning. Care partners completed the Zarit Burden Interview (ZBI) and the Penn Parkinson's Daily Activities Questionnaire (PDAQ-15). The associations between mean latency on each PACT subtask and ZBI and PDAQ-15 scores, respectively, were tested using Spearman's rank correlation coefficients. Significant associations were further delineated using multivariate regression with the following covariates: age, years of education, MoCA score, daily levodopa equivalency dose, UPDRS Part III score, and GDS-15 score. RESULTS Worse performance on the planning subtask of the PACT related to higher ZBI scores and lower PDAQ-15 scores when adjusting for covariates. Decreased initiation was associated with higher ZBI and decreased motivation with lower PDAQ-15. CONCLUSIONS Specific components of the PACT are related to patient and care partner outcomes in PD. The main advantage of this measure is to minimize the confounds of poor insight and care partner distress. We propose future research directions to refine the PACT for potential use in research and clinical practice.
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Affiliation(s)
- Jennifer Liu
- Department of Neurology, Parkinson's Disease and Movement Disorders Center, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA.
| | - Lauren Massimo
- Frontotemporal Degeneration Center, Perelman School of Medicine, Department of Neurology, Philadelphia, PA, USA; School of Nursing, University of Pennsylvania, Philadelphia, PA, USA
| | - Corey T McMillan
- Frontotemporal Degeneration Center, Perelman School of Medicine, Department of Neurology, Philadelphia, PA, USA
| | - Nabila Dahodwala
- Perelman School of Medicine, Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
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10
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Arezoumandan S, Cousins KA, Ohm DT, Lowe M, Chen M, Gee J, Phillips JS, McMillan CT, Luk KC, Deik A, Spindler MA, Tropea TF, Weintraub D, Wolk DA, Grossman M, Lee V, Chen‐Plotkin AS, Lee EB, Irwin DJ. Tau maturation in the clinicopathological spectrum of Lewy body and Alzheimer's disease. Ann Clin Transl Neurol 2024; 11:673-685. [PMID: 38263854 PMCID: PMC10963284 DOI: 10.1002/acn3.51988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Accepted: 12/22/2023] [Indexed: 01/25/2024] Open
Abstract
OBJECTIVE Alzheimer's disease neuropathologic change and alpha-synucleinopathy commonly co-exist and contribute to the clinical heterogeneity of dementia. Here, we examined tau epitopes marking various stages of tangle maturation to test the hypotheses that tau maturation is more strongly associated with beta-amyloid compared to alpha-synuclein, and within the context of mixed pathology, mature tau is linked to Alzheimer's disease clinical phenotype and negatively associated with Lewy body dementia. METHODS We used digital histology to measure percent area-occupied by pathology in cortical regions among individuals with pure Alzheimer's disease neuropathologic change, pure alpha-synucleinopathy, and a co-pathology group with both Alzheimer's and alpha-synuclein pathologic diagnoses. Multiple tau monoclonal antibodies were used to detect early (AT8, MC1) and mature (TauC3) epitopes of tangle progression. We used linear/logistic regression to compare groups and test the association between pathologies and clinical features. RESULTS There were lower levels of tau pathology (β = 1.86-2.96, p < 0.001) across all tau antibodies in the co-pathology group compared to the pure Alzheimer's pathology group. Among individuals with alpha-synucleinopathy, higher alpha-synuclein was associated with greater early tau (AT8 β = 1.37, p < 0.001; MC1 β = 1.2, p < 0.001) but not mature tau (TauC3 p = 0.18), whereas mature tau was associated with beta-amyloid (β = 0.21, p = 0.01). Finally, lower tau, particularly TauC3 pathology, was associated with lower frequency of both core clinical features and categorical clinical diagnosis of dementia with Lewy bodies. INTERPRETATION Mature tau may be more closely related to beta-amyloidosis than alpha-synucleinopathy, and pathophysiological processes of tangle maturation may influence the clinical features of dementia in mixed Lewy-Alzheimer's pathology.
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Affiliation(s)
- Sanaz Arezoumandan
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | | | - Daniel T. Ohm
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - MaKayla Lowe
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Min Chen
- Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - James Gee
- Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Jeffrey S. Phillips
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Corey T. McMillan
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Kelvin C. Luk
- Department of Pathology and Laboratory MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Andres Deik
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | | | - Thomas F. Tropea
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Daniel Weintraub
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - David A. Wolk
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Murray Grossman
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Virginia Lee
- Department of Pathology and Laboratory MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | | | - Edward B. Lee
- Department of Pathology and Laboratory MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - David J. Irwin
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
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11
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Phillips JS, Robinson JL, Cousins KAQ, Wolk DA, Lee EB, McMillan CT, Trojanowski JQ, Grossman M, Irwin DJ. Polypathologic Associations with Gray Matter Atrophy in Neurodegenerative Disease. J Neurosci 2024; 44:e0808232023. [PMID: 38050082 PMCID: PMC10860605 DOI: 10.1523/jneurosci.0808-23.2023] [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: 05/08/2023] [Revised: 10/01/2023] [Accepted: 10/26/2023] [Indexed: 12/06/2023] Open
Abstract
Mixed pathologies are common in neurodegenerative disease; however, antemortem imaging rarely captures copathologic effects on brain atrophy due to a lack of validated biomarkers for non-Alzheimer's pathologies. We leveraged a dataset comprising antemortem MRI and postmortem histopathology to assess polypathologic associations with atrophy in a clinically heterogeneous sample of 125 human dementia patients (41 female, 84 male) with T1-weighted MRI ≤ 5 years before death and postmortem ordinal ratings of amyloid-[Formula: see text], tau, TDP-43, and [Formula: see text]-synuclein. Regional volumes were related to pathology using linear mixed-effects models; approximately 25% of data were held out for testing. We contrasted a polypathologic model comprising independent factors for each proteinopathy with two alternatives: a model that attributed atrophy entirely to the protein(s) associated with the patient's primary diagnosis and a protein-agnostic model based on the sum of ordinal scores for all pathology types. Model fits were evaluated using log-likelihood and correlations between observed and fitted volume scores. Additionally, we performed exploratory analyses relating atrophy to gliosis, neuronal loss, and angiopathy. The polypathologic model provided superior fits in the training and testing datasets. Tau, TDP-43, and [Formula: see text]-synuclein burden were inversely associated with regional volumes, but amyloid-[Formula: see text] was not. Gliosis and neuronal loss explained residual variance in and mediated the effects of tau, TDP-43, and [Formula: see text]-synuclein on atrophy. Regional brain atrophy reflects not only the primary molecular pathology but also co-occurring proteinopathies; inflammatory immune responses may independently contribute to degeneration. Our findings underscore the importance of antemortem biomarkers for detecting mixed pathology.
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Affiliation(s)
- Jeffrey S Phillips
- Departments of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - John L Robinson
- Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Katheryn A Q Cousins
- Departments of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - David A Wolk
- Departments of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Edward B Lee
- Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Corey T McMillan
- Departments of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - John Q Trojanowski
- Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Murray Grossman
- Departments of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - David J Irwin
- Departments of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania 19104
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12
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Shen T, Vogel JW, Duda J, Phillips JS, Cook PA, Gee J, Elman L, Quinn C, Amado DA, Baer M, Massimo L, Grossman M, Irwin DJ, McMillan CT. Novel data-driven subtypes and stages of brain atrophy in the ALS-FTD spectrum. Transl Neurodegener 2023; 12:57. [PMID: 38062485 PMCID: PMC10701950 DOI: 10.1186/s40035-023-00389-3] [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] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 11/15/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND TDP-43 proteinopathies represent a spectrum of neurological disorders, anchored clinically on either end by amyotrophic lateral sclerosis (ALS) and frontotemporal degeneration (FTD). The ALS-FTD spectrum exhibits a diverse range of clinical presentations with overlapping phenotypes, highlighting its heterogeneity. This study was aimed to use disease progression modeling to identify novel data-driven spatial and temporal subtypes of brain atrophy and its progression in the ALS-FTD spectrum. METHODS We used a data-driven procedure to identify 13 anatomic clusters of brain volume for 57 behavioral variant FTD (bvFTD; with either autopsy-confirmed TDP-43 or TDP-43 proteinopathy-associated genetic variants), 103 ALS, and 47 ALS-FTD patients with likely TDP-43. A Subtype and Stage Inference (SuStaIn) model was trained to identify subtypes of individuals along the ALS-FTD spectrum with distinct brain atrophy patterns, and we related subtypes and stages to clinical, genetic, and neuropathological features of disease. RESULTS SuStaIn identified three novel subtypes: two disease subtypes with predominant brain atrophy in either prefrontal/somatomotor regions or limbic-related regions, and a normal-appearing group without obvious brain atrophy. The limbic-predominant subtype tended to present with more impaired cognition, higher frequencies of pathogenic variants in TBK1 and TARDBP genes, and a higher proportion of TDP-43 types B, E and C. In contrast, the prefrontal/somatomotor-predominant subtype had higher frequencies of pathogenic variants in C9orf72 and GRN genes and higher proportion of TDP-43 type A. The normal-appearing brain group showed higher frequency of ALS relative to ALS-FTD and bvFTD patients, higher cognitive capacity, higher proportion of lower motor neuron onset, milder motor symptoms, and lower frequencies of genetic pathogenic variants. The overall SuStaIn stages also correlated with evidence for clinical progression including longer disease duration, higher King's stage, and cognitive decline. Additionally, SuStaIn stages differed across clinical phenotypes, genotypes and types of TDP-43 pathology. CONCLUSIONS Our findings suggest distinct neurodegenerative subtypes of disease along the ALS-FTD spectrum that can be identified in vivo, each with distinct brain atrophy, clinical, genetic and pathological patterns.
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Affiliation(s)
- Ting Shen
- Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Jacob W Vogel
- Department of Clinical Sciences, SciLifeLab, Lund University, 222 42, Lund, Sweden
| | - Jeffrey Duda
- Penn Image Computing and Science Lab (PICSL), Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Jeffrey S Phillips
- Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Philip A Cook
- Penn Image Computing and Science Lab (PICSL), Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - James Gee
- Penn Image Computing and Science Lab (PICSL), Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Lauren Elman
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Colin Quinn
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Defne A Amado
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Michael Baer
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Lauren Massimo
- Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Murray Grossman
- Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - David J Irwin
- Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Corey T McMillan
- Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
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13
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Kerestes R, Laansma MA, Owens-Walton C, Perry A, van Heese EM, Al-Bachari S, Anderson TJ, Assogna F, Aventurato ÍK, van Balkom TD, Berendse HW, van den Berg KR, Mphys RB, Brioschi R, Carr J, Cendes F, Clark LR, Dalrymple-Alford JC, Dirkx MF, Druzgal J, Durrant H, Emsley HC, Garraux G, Haroon HA, Helmich RC, van den Heuvel OA, João RB, Johansson ME, Khachatryan S, Lochner C, McMillan CT, Melzer TR, Mosley P, Newman B, Opriessnig P, Parkes LM, Pellicano C, Piras F, Pitcher TL, Poston KL, Rango M, Roos A, Rummel C, Schmidt R, Schwingenschuh P, Silva LS, Smith V, Squarcina L, Stein DJ, Tavadyan Z, Tsai CC, Vecchio D, Vriend C, Wang JJ, Wiest R, Yasuda CL, Young CB, Jahanshad N, Thompson PM, van der Werf YD, Harding IH. Cerebellar Volume and Disease Staging in Parkinson's Disease: An ENIGMA-PD Study. Mov Disord 2023; 38:2269-2281. [PMID: 37964373 PMCID: PMC10754393 DOI: 10.1002/mds.29611] [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: 05/29/2023] [Revised: 08/14/2023] [Accepted: 09/11/2023] [Indexed: 11/16/2023] Open
Abstract
BACKGROUND Increasing evidence points to a pathophysiological role for the cerebellum in Parkinson's disease (PD). However, regional cerebellar changes associated with motor and non-motor functioning remain to be elucidated. OBJECTIVE To quantify cross-sectional regional cerebellar lobule volumes using three dimensional T1-weighted anatomical brain magnetic resonance imaging from the global ENIGMA-PD working group. METHODS Cerebellar parcellation was performed using a deep learning-based approach from 2487 people with PD and 1212 age and sex-matched controls across 22 sites. Linear mixed effects models compared total and regional cerebellar volume in people with PD at each Hoehn and Yahr (HY) disease stage, to an age- and sex- matched control group. Associations with motor symptom severity and Montreal Cognitive Assessment scores were investigated. RESULTS Overall, people with PD had a regionally smaller posterior lobe (dmax = -0.15). HY stage-specific analyses revealed a larger anterior lobule V bilaterally (dmax = 0.28) in people with PD in HY stage 1 compared to controls. In contrast, smaller bilateral lobule VII volume in the posterior lobe was observed in HY stages 3, 4, and 5 (dmax = -0.76), which was incrementally lower with higher disease stage. Within PD, cognitively impaired individuals had lower total cerebellar volume compared to cognitively normal individuals (d = -0.17). CONCLUSIONS We provide evidence of a dissociation between anterior "motor" lobe and posterior "non-motor" lobe cerebellar regions in PD. Whereas less severe stages of the disease are associated with larger motor lobe regions, more severe stages of the disease are marked by smaller non-motor regions. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Rebecca Kerestes
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
| | - Max A. Laansma
- Amsterdam UMC, Dept. Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
| | - Conor Owens-Walton
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Andrew Perry
- Monash Bioinformatics Platform, Monash University, Melbourne, VIC, Australia
| | - Eva M. van Heese
- Amsterdam UMC, Dept. Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
| | - Sarah Al-Bachari
- Faculty of Health and Medicine, The University of Lancaster, Lancaster, UK
| | - Tim J. Anderson
- Department of Medicine, University of Otago, Christchurch, Christchurch, New Zealand
- New Zealand Brain Research Institute, Christchurch, New Zealand
- Neurology Department, Te Wahtu Ora - Health New Zealand Waitaha Canterbury, Christchurch, New Zew Zealand
| | - Francesca Assogna
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Ítalo K. Aventurato
- Department of Neurology, University of Campinas - UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Tim D. van Balkom
- Amsterdam UMC, Dept. Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Amsterdam UMC, Dept. Psychiatry, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Henk W. Berendse
- Amsterdam UMC, Dept. Neurology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Kevin R.E. van den Berg
- Department of Neurology and Center of Expertise for Parkinson & Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
- Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Rebecca Betts Mphys
- School of Physics and Astronomy, Faculty of Science and Engineering, The University of Manchester, Manchester, UK
| | - Ricardo Brioschi
- Department of Neurology, University of Campinas - UNICAMP, Campinas, Brazil
| | - Jonathan Carr
- Division of Neurology, Tygerberg Hospital and Stellenbosch University, Cape Town, South Africa
| | - Fernando Cendes
- Department of Neurology, University of Campinas - UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Lyles R. Clark
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - John C. Dalrymple-Alford
- New Zealand Brain Research Institute, Christchurch, New Zealand
- School of Psychology, Speech and Hearing, University of Canterbury, Christchurch, New Zealand
| | - Michiel F. Dirkx
- Department of Neurology and Center of Expertise for Parkinson & Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
| | - Jason Druzgal
- Department of Radiology and Medical Imaging, University of Virginia, USA
| | - Helena Durrant
- School of Physics and Astronomy, Faculty of Science and Engineering, The University of Manchester, Manchester, UK
| | - Hedley C.A. Emsley
- Lancaster Medical School, Lancaster University, Lancaster, UK
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Gaëtan Garraux
- GIGA-CRC in vivo imaging, University of Liège, Belgium
- Department of Neurology, CHU Liège, Liège, Belgium
| | - Hamied A. Haroon
- Division of Psychology, Communication & Human Neuroscience, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Rick C. Helmich
- Department of Neurology and Center of Expertise for Parkinson & Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
- Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Odile A. van den Heuvel
- Amsterdam UMC, Dept. Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Amsterdam UMC, Dept. Psychiatry, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Rafael B. João
- Department of Neurology, University of Campinas - UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Martin E. Johansson
- Department of Neurology and Center of Expertise for Parkinson & Movement Disorders, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands
| | - Samson Khachatryan
- Department of Neurology and Neurosurgery, National Institute of Health, Yerevan, Armenia
- Centers for Sleep and Movement Disorders, Somnus Neurology Clinic, Yerevan, Armenia
| | - Christine Lochner
- SA MRC Unit on Risk and Resilience in Mental Disorders, Department of Psychiatry, Stellenbosch University, Cape Town, South Africa
| | - Corey T. McMillan
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Tracy R. Melzer
- Department of Medicine, University of Otago, Christchurch, Christchurch, New Zealand
- New Zealand Brain Research Institute, Christchurch, New Zealand
- School of Psychology, Speech and Hearing, University of Canterbury, Christchurch, New Zealand
| | - Philip Mosley
- Clinical Brain Networks Group, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
- The Australian eHealth Research Centre, CSIRO Health and Biosecurity, Brisbane, Queensland, Australia
| | - Benjamin Newman
- Department of Radiology and Medical Imaging, University of Virginia, USA
| | - Peter Opriessnig
- Department of Neurology, Clinical Division of Neurogeriatrics, Medical University Graz, Graz, Austria
| | - Laura M. Parkes
- Division of Psychology, Communication and Human Neuroscience, School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Northern Care Alliance & University of Manchester, Manchester, UK
| | - Clelia Pellicano
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Fabrizio Piras
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Toni L. Pitcher
- Department of Medicine, University of Otago, Christchurch, Christchurch, New Zealand
- New Zealand Brain Research Institute, Christchurch, New Zealand
| | - Kathleen L. Poston
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, CA, USA
| | - Mario Rango
- Excellence Center for Advanced MR Techniques and Parkinson’s Disease Center, Neurology unit, Fondazione IRCCS Cà Granda Maggiore Policlinico Hospital, University of Milan, Milan, Italy
- Dept of Neurosciences, Neurology Unit, Fondazione Ca’ Granda, IRCCS, Ospedale Policlinico, Univeristy of Milan, Milano, Italy
| | - Annerine Roos
- SA MRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Christian Rummel
- Support Center for Advanced Neuroimaging, (SCAN) University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Reinhold Schmidt
- Department of Neurology, Medical University of Graz, Graz, Austria
| | | | - Lucas S. Silva
- Department of Neurology, University of Campinas - UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Viktorija Smith
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, CA, USA
| | - Letizia Squarcina
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Dan J. Stein
- SA MRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Zaruhi Tavadyan
- Department of Neurology and Neurosurgery, National Institute of Health, Yerevan, Armenia
- Centers for Sleep and Movement Disorders, Somnus Neurology Clinic, Yerevan, Armenia
| | - Chih-Chien Tsai
- Healthy Aging Research Center, Chang Gung University, Taoyuan, Taiwan
| | - Daniela Vecchio
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Chris Vriend
- Amsterdam UMC, Dept. Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam UMC, Dept. Psychiatry, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Brain imaging, Amsterdam, the Netherlands
| | - Jiun-Jie Wang
- Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan City, Taiwan
- Department of Diagnostic Radiology, Chang Gung Memorial Hospital, Keelung Branch Keelung City, Taiwan
- Healthy Ageing Research Center, ChangGung University, Taiwan
- Department of Chemical Engineering, Ming-Chi University of Technology, New Taipei City, Taiwan
| | - Roland Wiest
- Support Center for Advanced Neuroimaging, (SCAN) University Institute of Diagnostic and Interventional Neuroradiology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Clarissa L. Yasuda
- Department of Neurology, University of Campinas - UNICAMP, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Christina B. Young
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, CA, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Ysbrand D. van der Werf
- Amsterdam UMC, Dept. Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
| | - Ian H. Harding
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, VIC, Australia
- Monash Biomedical Imaging, Monash University, Melbourne, VIC, Australia
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Jin HA, McMillan CT, Yannatos I, Fisher L, Rhodes E, Jacoby SF, Irwin DJ, Massimo L. Racial Differences in Clinical Presentation in Individuals Diagnosed With Frontotemporal Dementia. JAMA Neurol 2023; 80:1191-1198. [PMID: 37695629 PMCID: PMC10495924 DOI: 10.1001/jamaneurol.2023.3093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 07/18/2023] [Indexed: 09/12/2023]
Abstract
Importance Prior research suggests there are racial disparities in the presentation of dementia, but this has not been investigated in the context of frontotemporal dementia (FTD). Objective To explore racial disparities in dementia severity, functional impairment, and neuropsychiatric symptoms in individuals with a diagnosis of FTD. Design, Setting, and Participants This exploratory cross-sectional study of National Alzheimer's Coordinating Center (NACC) data collected between June 2005 to August 2021 evaluated Asian, Black, and White individuals with a diagnosis of FTD (behavioral variant FTD or primary progressive aphasia). Excluded were races with limited data, including American Indian or Alaska Native (n = 4), Native Hawaiian or other Pacific Islander (n = 3), other (n = 13), and unknown (n = 24), and participants with symptom duration more than 4 SDs above the mean. Main Outcomes and Measures Racial differences at initial NACC visit were examined on Clinical Dementia Rating Dementia Staging Instrument plus NACC Frontotemporal Lobar Degeneration Behavior & Language Domains (FTLD-CDR), Functional Assessment Scale, and Neuropsychiatric Inventory using regression models. Matching was also performed to address the imbalance between racial groups. Results The final sample comprised 2478 individuals, of which 59 (2.4%) were Asian, 63 (2.5%) were Black, and 2356 (95.1%) were White. The mean (SD) age at initial visit was 65.3 (9.4) years and symptom duration at initial visit was 67.5 (35.6) months. Asian and Black individuals were considerably underrepresented, comprising a small percent of the sample. Black individuals had a higher degree of dementia severity on FTLD-CDR (β = 0.64; SE = 0.24; P = .006) and FTLD-CDR sum of boxes (β = 1.21; SE = 0.57; P = .03) and greater functional impairment (β = 3.83; SE = 1.49; P = .01). There were no differences on FTLD-CDR and Functional Assessment Scale between Asian and White individuals. Black individuals were found to exhibit a higher frequency of delusions, agitation, and depression (delusions: odds ratio [OR], 2.18; 95% CI, 1.15-3.93; P = .01; agitation: OR, 1.73; 95% CI, 1.03-2.93; P = .04; depression: OR, 1.75; 95% CI, 1.05-2.92; P = .03). Asian individuals were found to exhibit a higher frequency of apathy (OR, 1.89; 95% CI, 1.09-3.78; P = .03), nighttime behaviors (OR, 1.72; 95% CI, 1.01-2.91; P = .04), and appetite/eating (OR, 1.99; 95% CI, 1.17-3.47; P = .01) compared to White individuals. Conclusions and Relevance This exploratory study suggests there are racial disparities in dementia severity, functional impairment, and neuropsychiatric symptoms. Future work must address racial disparities and their underlying determinants as well as the lack of representation of racially minoritized individuals in nationally representative dementia registries.
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Affiliation(s)
- Hannah A. Jin
- Penn Frontotemporal Degeneration Center, Department of Neurology, School of Medicine, University of Pennsylvania, Philadelphia
| | - Corey T. McMillan
- Penn Frontotemporal Degeneration Center, Department of Neurology, School of Medicine, University of Pennsylvania, Philadelphia
| | - Isabel Yannatos
- Penn Frontotemporal Degeneration Center, Department of Neurology, School of Medicine, University of Pennsylvania, Philadelphia
| | - Lauren Fisher
- Penn Frontotemporal Degeneration Center, Department of Neurology, School of Medicine, University of Pennsylvania, Philadelphia
| | - Emma Rhodes
- Penn Frontotemporal Degeneration Center, Department of Neurology, School of Medicine, University of Pennsylvania, Philadelphia
| | - Sarah F. Jacoby
- Department of Family and Community Health, School of Nursing, University of Pennsylvania, Philadelphia
| | - David J. Irwin
- Penn Frontotemporal Degeneration Center, Department of Neurology, School of Medicine, University of Pennsylvania, Philadelphia
| | - Lauren Massimo
- Penn Frontotemporal Degeneration Center, Department of Neurology, School of Medicine, University of Pennsylvania, Philadelphia
- Department of Biobehavioral Health Sciences, School of Nursing, University of Pennsylvania, Philadelphia
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15
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Harper L, de Boer S, Lindberg O, Lätt J, Cullen N, Clark L, Irwin D, Massimo L, Grossman M, Hansson O, Pijnenburg Y, McMillan CT, Santillo AF. Anterior cingulate sulcation is associated with onset and survival in frontotemporal dementia. Brain Commun 2023; 5:fcad264. [PMID: 37869576 PMCID: PMC10586312 DOI: 10.1093/braincomms/fcad264] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Revised: 09/05/2023] [Accepted: 10/07/2023] [Indexed: 10/24/2023] Open
Abstract
Frontotemporal dementia is the second most common form of early onset dementia (<65 years). Despite this, there are few known disease-modifying factors. The anterior cingulate is a focal point of pathology in behavioural variant frontotemporal dementia. Sulcation of the anterior cingulate is denoted by the presence of a paracingulate sulcus, a tertiary sulcus developing, where present during the third gestational trimester and remaining stable throughout life. This study aims to examine the impact of right paracingulate sulcal presence on the expression and prognosis of behavioural variant frontotemporal dementia. This retrospective analysis drew its population from two clinical samples recruited from memory clinics at university hospitals in the USA and The Netherlands. Individuals with sporadic behavioural variant frontotemporal dementia were enrolled between 2000 and 2022 and followed up for an average of 7.71 years. T1-MRI data were evaluated for hemispheric paracingulate sulcal presence in accordance with an established protocol by two blinded raters. Outcome measures included age at onset, survival, cortical thickness and Frontotemporal Lobar Degeneration-modified Clinical Dementia Rating determined clinical disease progression. The study population consisted of 186 individuals with sporadic behavioural variant frontotemporal dementia (113 males and 73 females), mean age 63.28 years (SD 8.32). The mean age at onset was 2.44 years later in individuals possessing a right paracingulate sulcus [60.2 years (8.54)] versus individuals who did not [57.76 (8.05)], 95% confidence interval > 0.41, P = 0.02. Education was not associated with age at onset (β = -0.05, P = 0.75). The presence of a right paracingulate sulcus was associated with an 83% increased risk of death per year after age at onset (hazard ratio 1.83, confidence interval [1.09-3.07], P < 0.02), whilst the mean age at death was similar for individuals with a present and absent right paracingulate sulcus (P = 0.7). Right paracingulate sulcal presence was not associated with baseline cortical thickness. Right paracingulate sulcal presence is associated with disease expression and survival in sporadic behavioural variant frontotemporal dementia. Findings provide evidence of neurodevelopmental brain reserve in behavioural variant frontotemporal dementia that may be important in the design of trials for future therapeutic approaches.
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Affiliation(s)
- Luke Harper
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö 20502, Sweden
| | - Sterre de Boer
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam 1081 HZ, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam 1105 BA, The Netherlands
| | - Olof Lindberg
- Division of Clinical Geriatrics, Karolinska Institute, Stockholm 17165, Sweden
| | - Jimmy Lätt
- Centre for Medical Imaging and Physiology, Skane University Hospital, Lund 22242, Sweden
| | - Nicholas Cullen
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö 20502, Sweden
| | - Lyles Clark
- Penn Frontotemporal Degeneration Center (FTDC), University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - David Irwin
- Penn Frontotemporal Degeneration Center (FTDC), University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Lauren Massimo
- Penn Frontotemporal Degeneration Center (FTDC), University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Murray Grossman
- Penn Frontotemporal Degeneration Center (FTDC), University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö 20502, Sweden
- Memory Clinic, Skåne University Hospital, Malmö 22100, Sweden
| | - Yolande Pijnenburg
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam 1081 HZ, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam 1105 BA, The Netherlands
| | - Corey T McMillan
- Penn Frontotemporal Degeneration Center (FTDC), University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Alexander F Santillo
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö 20502, Sweden
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16
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Yannatos I, Stites SD, Boen C, Xie SX, Brown RT, McMillan CT. Epigenetic age and socioeconomic status contribute to racial disparities in cognitive and functional aging between Black and White older Americans. medRxiv 2023:2023.09.29.23296351. [PMID: 37873230 PMCID: PMC10592997 DOI: 10.1101/2023.09.29.23296351] [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: 10/25/2023]
Abstract
Epigenetic age, a biological aging marker measured by DNA methylation, is a potential mechanism by which social factors drive disparities in age-related health. Epigenetic age gap is the residual between epigenetic age measures and chronological age. Previous studies showed associations between epigenetic age gap and age-related outcomes including cognitive capacity and performance on some functional measures, but whether epigenetic age gap contributes to disparities in these outcomes is unknown. We use data from the Health and Retirement Study to examine the role of epigenetic age gap in racial disparities in cognitive and functional outcomes and consider the role of socioeconomic status (SES). Epigenetic age measures are GrimAge or Dunedin Pace of Aging methylation (DPoAm). Cognitive outcomes are cross-sectional score and two-year change in Telephone Interview for Cognitive Status (TICS). Functional outcomes are prevalence and incidence of limitations performing Instrumental Activities of Daily Living (IADLs). We find, relative to White participants, Black participants have lower scores and greater decline in TICS, higher prevalence and incidence rates of IADL limitations, and higher epigenetic age gap. Age- and gender-adjusted analyses reveal that higher GrimAge and DPoAm gap are both associated with worse cognitive and functional outcomes and mediate 6-11% of racial disparities in cognitive outcomes and 19-39% of disparities in functional outcomes. Adjusting for SES attenuates most DPoAm associations and most mediation effects. These results support that epigenetic age gap contributes to racial disparities in cognition and functioning and may be an important mechanism linking social factors to disparities in health outcomes.
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Affiliation(s)
- Isabel Yannatos
- Department of Neurology, University of Pennsylvania, Philadelphia, USA
| | - Shana D. Stites
- Department of Psychiatry, Perelman School of Medicine, Philadelphia, USA
| | - Courtney Boen
- Department of Sociology, University of Pennsylvania, Philadelphia, USA
| | - Sharon X. Xie
- Deptartment of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, USA
- Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, USA
| | - Rebecca T. Brown
- Division of Geriatric Medicine, Perelman School of Medicine, Philadelphia, USA
- Geriatrics and Extended Care Program, Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, USA
- Center for Health Equity Research and Promotion, Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, USA
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, USA
| | - Corey T. McMillan
- Department of Neurology, University of Pennsylvania, Philadelphia, USA
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17
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Shen T, Vogel JW, Duda J, Phillips JS, Cook PA, Gee J, Elman L, Quinn C, Amado DA, Baer M, Massimo L, Grossman M, Irwin DJ, McMillan CT. Novel data-driven subtypes and stages of brain atrophy in the ALS-FTD spectrum. Res Sq 2023:rs.3.rs-3183113. [PMID: 37609205 PMCID: PMC10441467 DOI: 10.21203/rs.3.rs-3183113/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: 08/24/2023]
Abstract
Background TDP-43 proteinopathies represents a spectrum of neurological disorders, anchored clinically on either end by amyotrophic lateral sclerosis (ALS) and frontotemporal degeneration (FTD). The ALS-FTD spectrum exhibits a diverse range of clinical presentations with overlapping phenotypes, highlighting its heterogeneity. This study aimed to use disease progression modeling to identify novel data-driven spatial and temporal subtypes of brain atrophy and its progression in the ALS-FTD spectrum. Methods We used a data-driven procedure to identify 13 anatomic clusters of brain volumes for 57 behavioral variant FTD (bvFTD; with either autopsy-confirmed TDP-43 or TDP-43 proteinopathy-associated genetic variants), 103 ALS, and 47 ALS-FTD patients with likely TDP-43. A Subtype and Stage Inference (SuStaIn) model was trained to identify subtypes of individuals along the ALS-FTD spectrum with distinct brain atrophy patterns, and we related subtypes and stages to clinical, genetic, and neuropathological features of disease. Results SuStaIn identified three novel subtypes: two disease subtypes with predominant brain atrophy either in prefrontal/somatomotor regions or limbic-related regions, and a normal-appearing group without obvious brain atrophy. The Limbic-predominant subtype tended to present with more impaired cognition, higher frequencies of pathogenic variants in TBK1 and TARDBP genes, and a higher proportion of TDP-43 type B, E and C. In contrast, the Prefrontal/Somatomotor-predominant subtype had higher frequencies of pathogenic variants in C9orf72 and GRN genes and higher proportion of TDP-43 type A. The normal-appearing brain group showed higher frequency of ALS relative to ALS-FTD and bvFTD patients, higher cognitive capacity, higher proportion of lower motor neuron onset, milder motor symptoms, and lower frequencies of genetic pathogenic variants. Overall SuStaIn stages also correlated with evidence for clinical progression including longer disease duration, higher King's stage, and cognitive decline. Additionally, SuStaIn stages differed across clinical phenotypes, genotypes and types of TDP-43 pathology. Conclusions Our findings suggest distinct neurodegenerative subtypes of disease along the ALS-FTD spectrum that can be identified in vivo, each with distinct brain atrophy, clinical, genetic and pathological patterns.
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Affiliation(s)
- Ting Shen
- University of Pennsylvania Perelman School of Medicine
| | | | - Jeffrey Duda
- University of Pennsylvania Perelman School of Medicine
| | | | - Philip A Cook
- University of Pennsylvania Perelman School of Medicine
| | - James Gee
- University of Pennsylvania Perelman School of Medicine
| | - Lauren Elman
- University of Pennsylvania Perelman School of Medicine
| | - Colin Quinn
- University of Pennsylvania Perelman School of Medicine
| | - Defne A Amado
- University of Pennsylvania Perelman School of Medicine
| | - Michael Baer
- University of Pennsylvania Perelman School of Medicine
| | | | | | - David J Irwin
- University of Pennsylvania Perelman School of Medicine
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18
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Yannatos I, Stites S, Brown RT, McMillan CT. Contributions of neighborhood social environment and air pollution exposure to Black-White disparities in epigenetic aging. PLoS One 2023; 18:e0287112. [PMID: 37405974 PMCID: PMC10321643 DOI: 10.1371/journal.pone.0287112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 05/29/2023] [Indexed: 07/07/2023] Open
Abstract
Racial disparities in many aging-related health outcomes are persistent and pervasive among older Americans, reflecting accelerated biological aging for Black Americans compared to White, known as weathering. Environmental determinants that contribute to weathering are poorly understood. Having a higher biological age, measured by DNA methylation (DNAm), than chronological age is robustly associated with worse age-related outcomes and higher social adversity. We hypothesize that individual socioeconomic status (SES), neighborhood social environment, and air pollution exposures contribute to racial disparities in DNAm aging according to GrimAge and Dunedin Pace of Aging methylation (DPoAm). We perform retrospective cross-sectional analyses among 2,960 non-Hispanic participants (82% White, 18% Black) in the Health and Retirement Study whose 2016 DNAm age is linked to survey responses and geographic data. DNAm aging is defined as the residual after regressing DNAm age on chronological age. We observe Black individuals have significantly accelerated DNAm aging on average compared to White individuals according to GrimAge (239%) and DPoAm (238%). We implement multivariable linear regression models and threefold decomposition to identify exposures that contribute to this disparity. Exposure measures include individual-level SES, census-tract-level socioeconomic deprivation and air pollution (fine particulate matter, nitrogen dioxide, and ozone), and perceived neighborhood social and physical disorder. Race and gender are included as covariates. Regression and decomposition results show that individual-level SES is strongly associated with and accounts for a large portion of the disparity in both GrimAge and DPoAm aging. Higher neighborhood deprivation for Black participants significantly contributes to the disparity in GrimAge aging. Black participants are more vulnerable to fine particulate matter exposure for DPoAm, perhaps due to individual- and neighborhood-level SES, which may contribute to the disparity in DPoAm aging. DNAm aging may play a role in the environment "getting under the skin", contributing to age-related health disparities between older Black and White Americans.
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Affiliation(s)
- Isabel Yannatos
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Shana Stites
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Rebecca T. Brown
- Division of Geriatric Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Geriatrics and Extended Care, Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania, United States of America
- Center for Health Equity Research and Promotion, Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania, United States of America
- Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Corey T. McMillan
- Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
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19
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Young AL, Vogel JW, Robinson JL, McMillan CT, Ossenkoppele R, Wolk DA, Irwin DJ, Elman L, Grossman M, Lee VMY, Lee EB, Hansson O. Data-driven neuropathological staging and subtyping of TDP-43 proteinopathies. Brain 2023; 146:2975-2988. [PMID: 37150879 PMCID: PMC10317181 DOI: 10.1093/brain/awad145] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [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: 01/31/2023] [Revised: 03/27/2023] [Accepted: 04/16/2023] [Indexed: 05/09/2023] Open
Abstract
TAR DNA-binding protein-43 (TDP-43) accumulation is the primary pathology underlying several neurodegenerative diseases. Charting the progression and heterogeneity of TDP-43 accumulation is necessary to better characterize TDP-43 proteinopathies, but current TDP-43 staging systems are heuristic and assume each syndrome is homogeneous. Here, we use data-driven disease progression modelling to derive a fine-grained empirical staging system for the classification and differentiation of frontotemporal lobar degeneration due to TDP-43 (FTLD-TDP, n = 126), amyotrophic lateral sclerosis (ALS, n = 141) and limbic-predominant age-related TDP-43 encephalopathy neuropathologic change (LATE-NC) with and without Alzheimer's disease (n = 304). The data-driven staging of ALS and FTLD-TDP complement and extend previously described human-defined staging schema for ALS and behavioural variant frontotemporal dementia. In LATE-NC individuals, progression along data-driven stages was positively associated with age, but negatively associated with age in individuals with FTLD-TDP. Using only regional TDP-43 severity, our data driven model distinguished individuals diagnosed with ALS, FTLD-TDP or LATE-NC with a cross-validated accuracy of 85.9%, with misclassifications associated with mixed pathological diagnosis, age and genetic mutations. Adding age and SuStaIn stage to this model increased accuracy to 92.3%. Our model differentiates LATE-NC from FTLD-TDP, though some overlap was observed between late-stage LATE-NC and early-stage FTLD-TDP. We further tested for the presence of subtypes with distinct regional TDP-43 progression patterns within each diagnostic group, identifying two distinct cortical-predominant and brainstem-predominant subtypes within FTLD-TDP and a further two subcortical-predominant and corticolimbic-predominant subtypes within ALS. The FTLD-TDP subtypes exhibited differing proportions of TDP-43 type, while there was a trend for age differing between ALS subtypes. Interestingly, a negative relationship between age and SuStaIn stage was seen in the brainstem/subcortical-predominant subtype of each proteinopathy. No subtypes were observed for the LATE-NC group, despite aggregating individuals with and without Alzheimer's disease and a larger sample size for this group. Overall, we provide an empirical pathological TDP-43 staging system for ALS, FTLD-TDP and LATE-NC, which yielded accurate classification. We further demonstrate that there is substantial heterogeneity amongst ALS and FTLD-TDP progression patterns that warrants further investigation in larger cross-cohort studies.
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Affiliation(s)
- 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
| | - Jacob W Vogel
- Department of Clinical Sciences, SciLifeLab, Lund University, SE-222 42 Lund, Sweden
- Clinical Memory Research Unit, Lund University, SE-222 42 Lund, Sweden
| | - John L Robinson
- Penn Center for Neurodegenerative Disease Research, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
| | - Corey T McMillan
- Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Lund University, SE-222 42 Lund, Sweden
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, 1081 HZ Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, 1081 HV Amsterdam, The Netherlands
| | - David A Wolk
- Department of Neurology, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
| | - David J Irwin
- Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
- Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Lauren Elman
- Department of Neurology, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
| | - Murray Grossman
- Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
| | - Virginia M Y Lee
- Penn Center for Neurodegenerative Disease Research, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
| | - Edward B Lee
- Penn Center for Neurodegenerative Disease Research, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania School of Medicine, Philadelphia, PA 19104, USA
| | - Oskar Hansson
- Clinical Memory Research Unit, Lund University, SE-222 42 Lund, Sweden
- Memory Clinic, Skåne University Hospital, SE-205 02 Malmö, Sweden
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20
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Rhodes E, Alfa S, Jin H, Massimo L, Elman L, Amado D, Baer M, Quinn C, McMillan CT. Cognitive reserve in ALS: The role of occupational skills and requirements. medRxiv 2023:2023.06.21.23291677. [PMID: 37425709 PMCID: PMC10327222 DOI: 10.1101/2023.06.21.23291677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Background Amyotrophic Lateral Sclerosis (ALS) is a heterogeneous neurodegenerative condition featuring variable degrees of motor decline and cognitive impairment. We test the hypothesis that cognitive reserve (CR), defined by occupational histories involving more complex cognitive demands, may protect against cognitive decline, while motor reserve (MR), defined by working jobs requiring complex motor skills, may protect against motor dysfunction. Methods Individuals with ALS (n=150) were recruited from the University of Pennsylvania's Comprehensive ALS Clinic. Cognitive performance was evaluated using the Edinburgh Cognitive and Behavioral ALS Screen (ECAS), and motor functioning was measured using Penn Upper Motor Neuron (PUMNS) scale and ALS Functional Rating Scales (ALSFRS-R). The Occupational Information Network (O*NET) Database was used to derive 17 factors representing distinct worker characteristics, occupational requirements, and worker requirements, which were related to ECAS, PUMNS, and ALSFRS-R scores using multiple linear regression. Results A history of working jobs involving greater reasoning ability (β=2.12, p<.05), social ability (β=1.73, p<.05), analytic skills, (β=3.12, p<.01) and humanities knowledge (β=1.83, p<.01) was associated with better performance on the ECAS, while jobs involving more exposure to environmental hazards (β=-2.57, p<.01) and technical skills (β=-2.16, p<.01) were associated with lower ECAS Total Scores. Jobs involving greater precision skills (β=1.91, p<.05) were associated with greater disease severity on the PUMNS. Findings for the ALSFRS-R did not survive correction for multiple comparisons. Discussion Jobs requiring greater reasoning abilities, social skills, and humanities knowledge were related to preserved cognitive functioning consistent with CR, while jobs with greater exposure to environmental hazards and technical demands were linked to poorer cognitive functioning. We did not find evidence of MR as no protective effects of occupational skills and requirements were found for motor symptoms, and jobs involving greater precision skills and reasoning abilities were associated with worse motor functioning. Occupational history provides insight into protective and risk factors for variable degrees of cognitive and motor dysfunction in ALS.
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21
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Shellikeri S, Cho S, Ash S, Gonzalez-Recober C, McMillan CT, Elman L, Quinn C, Amado DA, Baer M, Irwin DJ, Massimo L, Olm C, Liberman M, Grossman M, Nevler N. Digital markers of motor speech impairments in natural speech of patients with ALS-FTD spectrum disorders. medRxiv 2023:2023.04.29.23289308. [PMID: 37205390 PMCID: PMC10187360 DOI: 10.1101/2023.04.29.23289308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Background and objectives Patients with ALS-FTD spectrum disorders (ALS-FTSD) have mixed motor and cognitive impairments and require valid and quantitative assessment tools to support diagnosis and tracking of bulbar motor disease. This study aimed to validate a novel automated digital speech tool that analyzes vowel acoustics from natural, connected speech as a marker for impaired articulation due to bulbar motor disease in ALS-FTSD. Methods We used an automatic algorithm called Forced Alignment Vowel Extraction (FAVE) to detect spoken vowels and extract vowel acoustics from 1 minute audio-recorded picture descriptions. Using automated acoustic analysis scripts, we derived two articulatory-acoustic measures: vowel space area (VSA, in Bark 2 ) which represents tongue range-of-motion (size), and average second formant slope of vowel trajectories (F2 slope) which represents tongue movement speed. We compared vowel measures between ALS with and without clinically-evident bulbar motor disease (ALS+bulbar vs. ALS-bulbar), behavioral variant frontotemporal dementia (bvFTD) without a motor syndrome, and healthy controls (HC). We correlated impaired vowel measures with bulbar disease severity, estimated by clinical bulbar scores and perceived listener effort, and with MRI cortical thickness of the orobuccal part of the primary motor cortex innervating the tongue (oralPMC). We also tested correlations with respiratory capacity and cognitive impairment. Results Participants were 45 ALS+bulbar (30 males, mean age=61±11), 22 ALS-nonbulbar (11 males, age=62±10), 22 bvFTD (13 males, age=63±7), and 34 HC (14 males, age=69±8). ALS+bulbar had smaller VSA and shallower average F2 slopes than ALS-bulbar (VSA: | d |=0.86, p =0.0088; F2 slope: | d |=0.98, p =0.0054), bvFTD (VSA: | d |=0.67, p =0.043; F2 slope: | d |=1.4, p <0.001), and HC (VSA: | d |=0.73, p =0.024; F2 slope: | d |=1.0, p <0.001). Vowel measures declined with worsening bulbar clinical scores (VSA: R=0.33, p =0.033; F2 slope: R=0.25, p =0.048), and smaller VSA was associated with greater listener effort (R=-0.43, p =0.041). Shallower F2 slopes were related to cortical thinning in oralPMC (R=0.50, p =0.03). Neither vowel measure was associated with respiratory nor cognitive test scores. Conclusions Vowel measures extracted with automatic processing from natural speech are sensitive to bulbar motor disease in ALS-FTD and are robust to cognitive impairment.
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Kim BJ, Grossman M, Aleman TS, Song D, Cousins KAQ, McMillan CT, Saludades A, Yu Y, Lee EB, Wolk D, Van Deerlin VM, Shaw LM, Ying GS, Irwin DJ. Retinal photoreceptor layer thickness has disease specificity and distinguishes predicted FTLD-Tau from biomarker-determined Alzheimer's disease. Neurobiol Aging 2023; 125:74-82. [PMID: 36857870 PMCID: PMC10038934 DOI: 10.1016/j.neurobiolaging.2023.01.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2022] [Revised: 01/23/2023] [Accepted: 01/25/2023] [Indexed: 02/04/2023]
Abstract
While Alzheimer's disease (AD) is associated with inner retina thinning (retinal nerve fiber layer and ganglion cell layer), we have observed photoreceptor outer nuclear layer (ONL) thinning in patients with frontotemporal lobar degeneration tauopathy (FTLD-Tau) compared to normal controls. We hypothesized that ONL thinning may distinguish FTLD-Tau from patients with biomarker evidence of AD neuropathologic change (ADNC) and will correlate with FTLD-Tau disease severity. Predicted FTLD-Tau (pFTLD-Tau; n = 21; 33 eyes) and predicted ADNC (pADNC; n = 24; 46 eyes) patients were consecutively enrolled, underwent optical coherence tomography macula imaging, and disease was categorized (pFTLD-Tau vs. pADNC) with cerebrospinal fluid biomarkers, genetic testing, and autopsy data when available. Adjusting for age, sex, and race, pFTLD-Tau patients had a thinner ONL compared to pADNC, while retinal nerve fiber layer and ganglion cell layer were not significantly different. Reduced ONL thickness correlated with worse performance on Folstein Mini-Mental State Examination and clinical dementia rating plus frontotemporal dementia sum of boxes for pFTLD-Tau but not pADNC. Photoreceptor ONL thickness may serve as an important noninvasive diagnostic marker that distinguishes FTLD-Tau from AD neuropathologic change.
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Affiliation(s)
- Benjamin J Kim
- Department of Ophthalmology, Scheie Eye Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
| | - Murray Grossman
- Department of Neurology, Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Tomas S Aleman
- Department of Ophthalmology, Scheie Eye Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Delu Song
- Department of Ophthalmology, Scheie Eye Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Katheryn A Q Cousins
- Department of Neurology, Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Corey T McMillan
- Department of Neurology, Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Adrienne Saludades
- Department of Ophthalmology, Scheie Eye Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Yinxi Yu
- Department of Ophthalmology, Scheie Eye Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Edward B Lee
- Department of Pathology and Laboratory Medicine, Translational Neuropathology Research Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Disease Research, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Institute on Aging, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - David Wolk
- Department of Neurology, Penn Alzheimer's Disease Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Institute on Aging, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Vivianna M Van Deerlin
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Gui-Shuang Ying
- Department of Ophthalmology, Scheie Eye Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - David J Irwin
- Department of Neurology, Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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23
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Harper L, de Boer S, Lindberg O, Lätt J, Cullen N, Clark L, Irwin D, Massimo L, Grossman M, Hansson O, Pijnenburg Y, McMillan CT, Santillo AF. Anterior cingulate sulcation is associated with onset and survival in frontotemporal dementia. medRxiv 2023:2023.03.30.23287945. [PMID: 37034647 PMCID: PMC10081407 DOI: 10.1101/2023.03.30.23287945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Background Frontotemporal dementia is the second most common form of early onset dementia (< 65 years). Despite this there are few known disease modifying factors. The anterior cingulate is a focal point of pathology in behavioural variant frontotemporal dementia. Sulcation of the anterior cingulate is denoted by the presence of a paracingulate sulcus, a tertiary sulcus developing, where present during the third gestational trimester and remaining stable throughout life. This study aims to examine the impact of right paracingulate sulcal presence on the expression and prognosis of behavioural variant Frontotemporal Dementia. Methods This retrospective analysis drew it's population from two clinical samples recruited from memory clinics at University Hospitals in The United States of America and The Netherlands. Individuals with sporadic behavioural variant Frontotemporal Dementia were enrolled between 2004 and 2022 and followed up for an average of 7.71 years. T1-MRI data were evaluated for hemispheric paracingulate sulcal presence in accordance with an established protocol by two blinded raters. Outcome measures included age at onset, survival, cortical thickness, and Frontotemporal Lobar Degeneration-modified Clinical Dementia Rating determined clinical disease progression. Results The study population consisted of 186 individuals with sporadic behavioural variant Frontotemporal Dementia, (113 males and 73 females) mean age 63.28 years (SD 8.32). The mean age at onset was 2.44 years later in individuals possessing a right paracingulate sulcus (60.2 years (SD 8.54)) versus individuals who did not (57.76 (8.05)), 95% CI >0.41, P = 0.02. Education was not associated with age at onset (β = -0.05, P =0.75). Presence of a right paracingulate sulcus was associated with a 119% increased risk of death per year after age at onset (HR 2.19, CI [1.21 - 3.96], P <0.01), whilst the mean age at death was similar for individuals with a present and absent right paracingulate sulcus ( P = 0.7). Right paracingulate sulcal presence was not associated with baseline cortical thickness. Conclusion Right paracingulate sulcal presence is associated with disease expression and survival in sporadic behavioural variant Frontotemporal Dementia. Findings provide evidence of neurodevelopmental brain reserve in behavioural variant Frontotemporal Dementia which may be important in the design of trials for future therapeutic approaches.
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24
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Robinson JL, Xie SX, Baer DR, Suh E, Van Deerlin VM, Loh NJ, Irwin D, McMillan CT, Wolk D, Chen-Plotkin A, Weintraub D, Schuck T, Lee VMY, Trojanowski JQ, Lee EB. Pathological combinations in neurodegenerative disease are heterogeneous and disease-associated. Brain 2023:7067885. [PMID: 36864661 PMCID: PMC10232273 DOI: 10.1093/brain/awad059] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [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: 09/08/2022] [Revised: 02/07/2023] [Accepted: 02/12/2023] [Indexed: 03/04/2023] Open
Abstract
Pathologies that are causative for neurodegenerative disease (ND) are also frequently present in unimpaired, older individuals. In this retrospective study of 1,647 autopsied individuals, we report the incidence of ten pathologies across ND and normal ageing in attempt to clarify which pathological combinations are disease-associated and which are ageing-related. Eight clinically defined groups were examined including unimpaired individuals and those with clinical Alzheimer's disease, mixed dementia, amyotrophic lateral sclerosis, frontotemporal degeneration, multiple system atrophy, probable Lewy body disease, or probable tauopathies. Up to seven pathologies were observed concurrently resulting in a heterogenous mix of 161 pathological combinations. The presence of multiple, additive pathologies associated with older age, increasing disease duration, APOE e4 allele, and presence of dementia across the clinical groups. 15-67 combinations occurred in each group with the unimpaired group defined by 35 combinations. Most combinations occurred at a < 5% prevalence included 86 that were present in only 1-2 individuals. To better understand this heterogeneity, we organized the pathologic combinations into five broad categories based on their age-related frequency: 1) Ageing only for the unimpaired group combinations, 2) ND only if only the expected pathology for that individual's clinical phenotype was present, 3) Other ND if the expected pathology was not present, 4) ND + ageing if the expected pathology was present together with aging-related pathologies at a similar prevalence as the unimpaired group, and 5) ND + associated if the expected pathology was present together with other pathologies either not observed in the unimpaired group or observed at a greater frequency. ND only cases comprised a minority of cases (19-45%) except in the amyotrophic lateral sclerosis (56%) and multiple system atrophy (65%) groups. The ND + ageing category represented 9-28% of each group, but was rare in Alzheimer's disease (1%). ND + associated combinations were common in Alzheimer's disease (58%) and Lewy body disease (37%) and were observed in all groups. The Ageing only and Other ND categories accounted for a minority of individuals in each group. This observed heterogeneity indicates that the total pathological burden in ND is frequently more than a primary expected clinicopathological correlation with a high frequency of additional disease- or age-associated pathologies.
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Affiliation(s)
- John L Robinson
- Center for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, Institute on Aging, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Sharon X Xie
- Center for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, Institute on Aging, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.,Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Daniel R Baer
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - EunRan Suh
- Center for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, Institute on Aging, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Vivianna M Van Deerlin
- Center for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, Institute on Aging, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Nicholas J Loh
- Center for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, Institute on Aging, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - David Irwin
- Center for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, Institute on Aging, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.,Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Corey T McMillan
- Center for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, Institute on Aging, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.,Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - David Wolk
- Center for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, Institute on Aging, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.,Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Alice Chen-Plotkin
- Center for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, Institute on Aging, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.,Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Daniel Weintraub
- Center for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, Institute on Aging, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.,Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Theresa Schuck
- Center for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, Institute on Aging, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Virginia M-Y Lee
- Center for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, Institute on Aging, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - John Q Trojanowski
- Center for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, Institute on Aging, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Edward B Lee
- Center for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, Institute on Aging, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.,Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
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25
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Lyu X, Duong MT, Xie L, de Flores R, Richardson H, Hwang G, Wisse LEM, DiCalogero M, McMillan CT, Robinson JL, Xie SX, Grossman M, Lee EB, Irwin DJ, Dickerson BC, Davatzikos C, Nasrallah IM, Yushkevich PA, Wolk DA, Das SR. Tau-Neurodegeneration mismatch reveals vulnerability and resilience to comorbidities in Alzheimer's continuum. medRxiv 2023:2023.02.12.23285594. [PMID: 36824762 PMCID: PMC9949174 DOI: 10.1101/2023.02.12.23285594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/17/2023]
Abstract
Variability in the relationship of tau-based neurofibrillary tangles (T) and degree of neurodegeneration (N) in Alzheimer's Disease (AD) is likely attributable to the non-specific nature of N, which is also modulated by such factors as other co-pathologies, age-related changes, and developmental differences. We studied this variability by partitioning patients within the Alzheimer's continuum into data-driven groups based on their regional T-N dissociation, which reflects the residuals after the effect of tau pathology is "removed". We found six groups displaying distinct spatial T-N mismatch and thickness patterns despite similar tau burden. Their T-N patterns resembled the neurodegeneration patterns of non-AD groups partitioned on the basis of z-scores of cortical thickness alone and were similarly associated with surrogates of non-AD factors. In an additional sample of individuals with antemortem imaging and autopsy, T-N mismatch was associated with TDP-43 co-pathology. Finally, T-N mismatch training was then applied to a separate cohort to determine the ability to classify individual patients within these groups. These findings suggest that T-N mismatch may provide a personalized approach for determining non-AD factors associated with resilience/vulnerability to Alzheimer's disease.
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26
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Young AL, Vogel JW, Robinson JL, McMillan CT, Ossenkoppele R, Wolk DA, Irwin DJ, Elman L, Grossman M, Lee VMY, Lee EB, Hansson O. Data-driven neuropathological staging and subtyping of TDP-43 proteinopathies. medRxiv 2023:2023.01.31.23285242. [PMID: 36778217 PMCID: PMC9915837 DOI: 10.1101/2023.01.31.23285242] [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] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
TAR DNA-binding protein-43 (TDP-43) accumulation is the primary pathology underlying several neurodegenerative diseases. Charting the progression and heterogeneity of TDP-43 accumulation is necessary to better characterise TDP-43 proteinopathies, but current TDP-43 staging systems are heuristic and assume each syndrome is homogeneous. Here, we use data-driven disease progression modelling to derive a fine-grained empirical staging system for the classification and differentiation of frontotemporal lobar degeneration due to TDP-43 (FTLD-TDP, n=126), amyotrophic lateral sclerosis (ALS, n=141) and limbic-predominant age-related TDP-43 encephalopathy neuropathologic change (LATE-NC) with and without Alzheimer’s disease (n=304). The data-driven staging of ALS and FTLD-TDP complement and extend previously described human-defined staging schema for ALS and behavioural variant frontotemporal dementia. In LATE-NC individuals, progression along data-driven stages was positively associated with age, but negatively associated with age in individuals with FTLD-TDP. Using only regional TDP-43 severity, our data driven model distinguished individuals diagnosed with ALS, FTLD-TDP or LATE-NC with a cross-validated accuracy of 85.9%, with misclassifications associated with mixed pathological diagnosis, age and genetic mutations. Adding age and SuStaIn stage to this model increased accuracy to 92.3%. Our model differentiates LATE-NC from FTLD-TDP, though some overlap was observed between late-stage LATE-NC and early-stage FTLD-TDP. We further tested for the presence of subtypes with distinct regional TDP-43 progression patterns within each diagnostic group, identifying two distinct cortical-predominant and brainstem-predominant subtypes within FTLD-TDP and a further two subcortical-predominant and corticolimbic-predominant subtypes within ALS. The FTLD-TDP subtypes exhibited differing proportions of TDP-43 type, while there was a trend for age differing between ALS subtypes. Interestingly, a negative relationship between age and SuStaIn stage was seen in the brainstem/subcortical-predominant subtype of each proteinopathy. No subtypes were observed for the LATE-NC group, despite aggregating AD+ and AD-individuals and a larger sample size for this group. Overall, we provide an empirical pathological TDP-43 staging system for ALS, FTLD-TDP and LATE-NC, which yielded accurate classification. We further demonstrate that there is substantial heterogeneity amongst ALS and FTLD-TDP progression patterns that warrants further investigation in larger cross-cohort studies.
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Affiliation(s)
- Alexandra L Young
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, UK
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
| | - Jacob W Vogel
- Department of Clinical Sciences, SciLifeLab, Lund University, Lund, Sweden
- Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - John L Robinson
- Penn Center for Neurodegenerative Disease Research, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Corey T McMillan
- Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Lund University, Lund, Sweden
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - David A Wolk
- Department of Neurology, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - David J Irwin
- Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Lauren Elman
- Department of Neurology, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Murray Grossman
- Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Virginia M-Y Lee
- Penn Center for Neurodegenerative Disease Research, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Edward B Lee
- Penn Center for Neurodegenerative Disease Research, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Oskar Hansson
- Clinical Memory Research Unit, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
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Spencer BE, Irwin DJ, Van Deerlin VM, Lee EB, Elman L, Quinn C, Grossman M, Wolk DA, McMillan CT. Modules of genotypic variance reflect heterogeneity across TDP‐43 proteinopathies. Alzheimers Dement 2022. [DOI: 10.1002/alz.066820] [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)
| | | | - Vivianna M Van Deerlin
- Center for Neurodegenerative Disease Research, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - Eddie B Lee
- University of Pennsylvania Philadelphia PA USA
| | | | - Colin Quinn
- University of Pennsylvania Philadelphia PA USA
| | | | | | - Corey T McMillan
- Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
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Sihag S, Massimo L, Burke SE, Phillips JS, Cook P, Duda JT, Gee JC, Satterthwaite T, Grossman M, Benatar M, McMillan CT. Structural Modularity is a Feature of C9orf72 Intrinsic Network Degeneration. Alzheimers Dement 2022. [DOI: 10.1002/alz.066119] [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)
| | | | - Sarah E Burke
- Penn FTD Center, Perelman School of Medicine at the University of Pennsylvania Philadelphia PA USA
| | - Jeffrey S Phillips
- Penn FTD Center, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - Philip Cook
- Penn Image Computing and Science Laboratory, University of Pennsylvania Philadelphia PA USA
| | | | - James C. Gee
- Penn Image Computing and Science Laboratory (PICSL), Department of Radiology, University of Pennsylvania Philadelphia PA USA
| | | | - Murray Grossman
- Penn FTD Center, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
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29
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Zhao Y, van Heese E, Laansma MA, Al‐Bachari S, Anderson T, Assogna F, Berendse HW, Bright J, Cendes F, Dalrymple‐Alford J, Debove I, Dirkx M, Druzgal TJ, Emsley H, Fouche JP, Garraux G, Guimarães R, Helmich R, Jahanshad N, Kim HB, Klein JC, Lochner C, Mackay C, McMillan CT, Melzer TR, Newman BT, Owens‐Walton C, Parkes L, Piras F, Pitcher T, Poston KL, Rango M, Ribeiro LF, Rocha C, Roos A, Rummel C, Santos L, Schmidt R, Spalletta G, Squarcina L, Schwingenschuh P, Vecchio D, Vriend C, Wang J, Weintraub D, Wiest R, Yasuda C, Thompson PM, van der Werf YD, Gutman BA. TV‐L1 Ordinal Logistic Regression Reveals New Morphometric Patterns Related to Parkinsonian Symptom Severity: An ENIGMA‐PD study. Alzheimers Dement 2022. [DOI: 10.1002/alz.067037] [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)
- Yuji Zhao
- Illinois Institute of Technology Chicago IL USA
| | | | | | | | | | | | - Henk W. Berendse
- Department of Neurology, Neuroscience Amsterdam, VU University Medical Center Amsterdam Netherlands
| | - Joanna Bright
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California Marina del Rey CA USA
| | | | | | | | | | | | | | - JP Fouche
- Stellenbosch University Stellenbosch South Africa
| | | | | | - Rick Helmich
- Radboud University Nijmegen Nijmegen Netherlands
| | - Neda Jahanshad
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California Marina del Rey CA USA
| | | | | | | | | | - Corey T McMillan
- Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
- Penn Alzheimer’s Disease Research Center, Perelman School of Medicine Philadelphia PA USA
| | - Tracy R Melzer
- University of Otago Christchurch New Zealand
- Brain Research, Christchurch New Zealand New Zealand
| | | | - Conor Owens‐Walton
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California Marina del Rey CA USA
| | - Laura Parkes
- University of Manchester Manchester United Kingdom
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Chris Vriend
- Vrije Universiteit Amsterdam Amsterdam Netherlands
| | | | | | | | | | | | - Ysbrand D. van der Werf
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC Amsterdam Netherlands
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30
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Kim B, Suh E, Nguyen AT, Prokop S, Mikytuck B, Olatunji OA, Robinson JL, Grossman M, Phillips JS, Irwin DJ, Mechanic-Hamilton D, Wolk DA, Trojanowski JQ, McMillan CT, Van Deerlin VM, Lee EB. TREM2 risk variants are associated with atypical Alzheimer's disease. Acta Neuropathol 2022; 144:1085-1102. [PMID: 36112222 PMCID: PMC9643636 DOI: 10.1007/s00401-022-02495-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [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: 05/25/2022] [Revised: 09/07/2022] [Accepted: 09/08/2022] [Indexed: 01/26/2023]
Abstract
Alzheimer's disease (AD) has multiple clinically and pathologically defined subtypes where the underlying causes of such heterogeneity are not well established. Rare TREM2 variants confer significantly increased risk for clinical AD in addition to other neurodegenerative disease clinical phenotypes. Whether TREM2 variants are associated with atypical clinical or pathologically defined subtypes of AD is not known. We studied here the clinical and pathological features associated with TREM2 risk variants in an autopsy-confirmed cohort. TREM2 variant cases were more frequently associated with non-amnestic clinical syndromes. Pathologically, TREM2 variant cases were associated with an atypical distribution of neurofibrillary tangle density with significantly lower hippocampal NFT burden relative to neocortical NFT accumulation. In addition, NFT density but not amyloid burden was associated with an increase of dystrophic microglia. TREM2 variant cases were not associated with an increased prevalence, extent, or severity of co-pathologies. These clinicopathological features suggest that TREM2 variants contribute to clinical and pathologic AD heterogeneity by altering the distribution of neurofibrillary degeneration and tau-dependent microglial dystrophy, resulting in hippocampal-sparing and non-amnestic AD phenotypes.
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Affiliation(s)
- Boram Kim
- Translational Neuropathology Research Laboratory, Department of Pathology and Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, 613A Stellar Chance Laboratories, 422 Curie Blvd, Philadelphia, PA, 19104, USA
| | - EunRan Suh
- Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Disease Research, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Aivi T Nguyen
- Translational Neuropathology Research Laboratory, Department of Pathology and Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, 613A Stellar Chance Laboratories, 422 Curie Blvd, Philadelphia, PA, 19104, USA
| | - Stefan Prokop
- Department of Pathology, Immunology, and Laboratory Medicine, University of Florida, Gainesville, FL, USA
| | - Bailey Mikytuck
- Translational Neuropathology Research Laboratory, Department of Pathology and Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, 613A Stellar Chance Laboratories, 422 Curie Blvd, Philadelphia, PA, 19104, USA
| | - Olamide A Olatunji
- Translational Neuropathology Research Laboratory, Department of Pathology and Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, 613A Stellar Chance Laboratories, 422 Curie Blvd, Philadelphia, PA, 19104, USA
| | - John L Robinson
- Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Disease Research, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Murray Grossman
- Department of Neurology, Penn Frontotemporal Degeneration Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Jeffrey S Phillips
- Department of Neurology, Penn Frontotemporal Degeneration Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - David J Irwin
- Department of Neurology, Penn Frontotemporal Degeneration Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Dawn Mechanic-Hamilton
- Department of Neurology, Penn Memory Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - David A Wolk
- Department of Neurology, Penn Memory Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - John Q Trojanowski
- Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Disease Research, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Corey T McMillan
- Department of Neurology, Penn Frontotemporal Degeneration Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Vivianna M Van Deerlin
- Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Disease Research, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Edward B Lee
- Translational Neuropathology Research Laboratory, Department of Pathology and Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, 613A Stellar Chance Laboratories, 422 Curie Blvd, Philadelphia, PA, 19104, USA.
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31
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Young AL, Vogel JW, Robinson J, McMillan CT, Ossenkoppele R, Wolk DA, Irwin DJ, Elman L, Grossman M, Lee VM, Lee EB, Trojanowski JQ, Hansson O. Empirical pathological staging and subtyping of TDP‐43 proteinopathies. Alzheimers Dement 2022. [DOI: 10.1002/alz.063390] [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)
- Alexandra L. Young
- Centre for Medical Image Computing, University College London London United Kingdom
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London London United Kingdom
| | | | | | - Corey T McMillan
- Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - Rik Ossenkoppele
- VU University Medical Center, Amsterdam UMC Amsterdam Netherlands
- Clinical Memory Research Unit, Lund University, Sweden Lund Sweden
| | | | | | | | | | | | - Eddie B Lee
- University of Pennsylvania Philadelphia PA USA
| | | | - Oskar Hansson
- Clinical Memory Research Unit, Lund University, Malmö Sweden
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32
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McMillan CT, Adhikari B, Farrell KW, Wolk DA, Lee EB, Crary JF, Johnson FB. Short Telomeres Associate with Hyperphosphorylated Tau Burden in Primary Age‐Related Tauopathy. Alzheimers Dement 2022. [DOI: 10.1002/alz.067329] [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)
| | | | | | | | - Eddie B Lee
- University of Pennsylvania Philadelphia PA USA
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33
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Phillips JS, Burke SE, Cousins KAQ, Arezoumandan S, Ohm DT, Chen M, Cook P, Dubroff JG, Nasrallah IM, McMillan CT, Grossman M, Wolk DA, Irwin DJ. Tau accumulation and degeneration differ across functional networks in atypical Alzheimer's disease phenotypes. Alzheimers Dement 2022. [DOI: 10.1002/alz.064638] [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)
- Jeffrey S Phillips
- Penn FTD Center, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - Sarah E Burke
- Penn FTD Center, Perelman School of Medicine at the University of Pennsylvania Philadelphia PA USA
| | | | - Sanaz Arezoumandan
- Penn FTD Center, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
- Digital Neuropathology Laboratory, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - Daniel T Ohm
- Penn FTD Center, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
- Digital Neuropathology Laboratory, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - Min Chen
- University of Pennsylvania Philadelphia PA USA
| | - Philip Cook
- Penn Image Computing and Science Laboratory, University of Pennsylvania Philadelphia PA USA
| | - Jacob G. Dubroff
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - Ilya M. Nasrallah
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania Philadelphia PA USA
| | | | - Murray Grossman
- Penn FTD Center, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - David A. Wolk
- Penn Alzheimer’s Disease Research Center, University of Pennsylvania Philadelphia PA USA
| | - David J. Irwin
- Penn FTD Center, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
- Digital Neuropathology Laboratory, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
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34
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Khandelwal P, Duong MT, Chung E, Sadaghiani S, Lim SA, Ravikumar S, Arezoumandan S, Peterson C, Bedard ML, Capp N, Ittyerah R, Migdal E, Choi G, Kopp E, Patino BL, Hasan E, Li J, Prabhakaran K, Mizsei G, Gabrielyan M, Schuck T, Robinson JL, Ohm DT, Nasrallah IM, Lee EB, Trojanowski JQ, McMillan CT, Grossman M, Irwin DJ, Tisdall DM, Das SR, Wisse LEM, Wolk DA, Yushkevich PA. Deep Learning for Ultra High Resolution T2‐weighted 7 Tesla
Ex vivo
Magnetic Resonance Imaging Reveals Differential Subcortical Atrophy across Neurodegenerative Diseases. Alzheimers Dement 2022. [DOI: 10.1002/alz.062628] [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)
- Pulkit Khandelwal
- University of Pennsylvania Philadelphia PA USA
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania Philadelphia PA USA
| | | | | | | | | | | | - Sanaz Arezoumandan
- Penn FTD Center, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
- Digital Neuropathology Laboratory, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - Claire Peterson
- Penn FTD Center, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
- Digital Neuropathology Laboratory, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - Madigan L Bedard
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania Philadelphia PA USA
| | - Noah Capp
- University of Pennsylvania Philadelphia PA USA
| | - Ranjit Ittyerah
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania Philadelphia PA USA
- Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | | | - Grace Choi
- University of Pennsylvania Philadelphia PA USA
| | - Emily Kopp
- University of Pennsylvania Philadelphia PA USA
| | | | - Eusha Hasan
- University of Pennsylvania Philadelphia PA USA
| | - Jiacheng Li
- University of Pennsylvania Philadelphia PA USA
| | | | | | | | | | | | - Daniel T Ohm
- Penn FTD Center, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
- Digital Neuropathology Laboratory, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - Ilya M. Nasrallah
- University of Pennsylvania Philadelphia PA USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - Eddie B Lee
- Perelman School of Medicine at the University of Pennsylvania Philadelphia PA USA
- Translational Neuropathology Research Laboratory, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
- Center for Neurodegenerative Disease Research, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - John Q Trojanowski
- Center for Neurodegenerative Disease Research, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
- Department of Pathology and Laboratory Medicine Philadelphia PA USA
| | - Corey T McMillan
- University of Pennsylvania Philadelphia PA USA
- Penn Alzheimer’s Disease Research Center, Perelman School of Medicine Philadelphia PA USA
| | - Murray Grossman
- Penn FTD Center, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
- Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - David J. Irwin
- Penn FTD Center, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
- Digital Neuropathology Laboratory, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - Dylan M Tisdall
- Perelman School of Medicine, University og Pennsylvania Philadelphia PA USA
| | - Sandhitsu R. Das
- University of Pennsylvania Philadelphia PA USA
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania Philadelphia PA USA
| | - Laura EM Wisse
- Department of Diagnostic Radiology, Clinical Sciences, Lund University Lund Sweden
- Lund University Lund Sweden
| | - David A. Wolk
- Department of Neurology, University of Pennsylvania School of Medicine Philadelphia PA USA
- Penn Alzheimer’s Disease Research Center, University of Pennsylvania Philadelphia PA USA
| | - Paul A. Yushkevich
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania Philadelphia PA USA
- Penn Alzheimer’s Disease Research Center, Perelman School of Medicine Philadelphia PA USA
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35
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Rhodes E, Massimo L, Mechanic‐Hamilton D, McMillan CT, Phillips JS, Burke SE, Hlava Q, Cook P, Gee JC, Grossman M. Factors associated with the Big 5 personality traits in Alzheimer’s disease and related dementias (ADRD). Alzheimers Dement 2022. [DOI: 10.1002/alz.067714] [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)
- Emma Rhodes
- University of Pennsylvania Frontotemporal Degeneration Center Philadelphia PA USA
| | | | - Dawn Mechanic‐Hamilton
- Penn Alzheimer’s Disease Research Center, University of Pennsylvania Philadelphia PA USA
| | - Corey T McMillan
- Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | | | - Sarah E Burke
- Penn FTD Center, Perelman School of Medicine at the University of Pennsylvania Philadelphia PA USA
| | - Quinn Hlava
- University of Pennsylvania Frontotemporal Degeneration Center PHILADELPHIA PA USA
| | - Philip Cook
- Penn Image Computing and Science Laboratory, University of Pennsylvania Philadelphia PA USA
| | - James C. Gee
- Penn Image Computing and Science Laboratory (PICSL), Department of Radiology, University of Pennsylvania Philadelphia PA USA
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36
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Yannatos I, Xie SX, Brown R, McMillan CT. Social epigenetics of racial disparities in aging. Alzheimers Dement 2022. [DOI: 10.1002/alz.067179] [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)
- Isabel Yannatos
- Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - Sharon X Xie
- Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - Rebecca Brown
- Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
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37
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Arezoumandan S, Xie SX, Cousins KAQ, Mechanic-Hamilton DJ, Peterson CS, Huang CY, Ohm DT, Ittyerah R, McMillan CT, Wolk DA, Yushkevich P, Trojanowski JQ, Lee EB, Grossman M, Phillips JS, Irwin DJ. Regional distribution and maturation of tau pathology among phenotypic variants of Alzheimer's disease. Acta Neuropathol 2022; 144:1103-1116. [PMID: 35871112 PMCID: PMC9936795 DOI: 10.1007/s00401-022-02472-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [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: 04/25/2022] [Revised: 07/02/2022] [Accepted: 07/14/2022] [Indexed: 01/26/2023]
Abstract
Alzheimer's disease neuropathologic change (ADNC) is clinically heterogenous and can present with a classic multidomain amnestic syndrome or focal non-amnestic syndromes. Here, we investigated the distribution and burden of phosphorylated and C-terminally cleaved tau pathologies across hippocampal subfields and cortical regions among phenotypic variants of Alzheimer's disease (AD). In this study, autopsy-confirmed patients with ADNC, were classified into amnestic (aAD, N = 40) and non-amnestic (naAD, N = 39) groups based on clinical criteria. We performed digital assessment of tissue sections immunostained for phosphorylated-tau (AT8 detects pretangles and mature tangles), D421-truncated tau (TauC3, a marker for mature tangles and ghost tangles), and E391-truncated tau (MN423, a marker that primarily detects ghost tangles), in hippocampal subfields and three cortical regions. Linear mixed-effect models were used to test regional and group differences while adjusting for demographics. Both groups showed AT8-reactivity across hippocampal subfields that mirrored traditional Braak staging with higher burden of phosphorylated-tau in subregions implicated as affected early in Braak staging. The burden of phosphorylated-tau and TauC3-immunoreactive tau in the hippocampus was largely similar between the aAD and naAD groups. In contrast, the naAD group had lower relative distribution of MN423-reactive tangles in CA1 (β = - 0.2, SE = 0.09, p = 0.001) and CA2 (β = - 0.25, SE = 0.09, p = 0.005) compared to the aAD. While the two groups had similar levels of phosphorylated-tau pathology in cortical regions, there was higher burden of TauC3 reactivity in sup/mid temporal cortex (β = 0.16, SE = 0.07, p = 0.02) and MN423 reactivity in all cortical regions (β = 0.4-0.43, SE = 0.09, p < 0.001) in the naAD compared to aAD. In conclusion, AD clinical variants may have a signature distribution of overall phosphorylated-tau pathology within the hippocampus reflecting traditional Braak staging; however, non-amnestic AD has greater relative mature tangle pathology in the neocortex compared to patients with clinical amnestic AD, where the hippocampus had greatest relative burden of C-terminally cleaved tau reactivity. Thus, varying neuronal susceptibility to tau-mediated neurodegeneration may influence the clinical expression of ADNC.
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Affiliation(s)
- Sanaz Arezoumandan
- Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Sharon X Xie
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Katheryn A Q Cousins
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Dawn J Mechanic-Hamilton
- Department of Neurology, Penn Memory Center, Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Department of Neurology, Penn Alzheimer's Disease Research Center, Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Claire S Peterson
- Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Camille Y Huang
- Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Daniel T Ohm
- Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Ranjit Ittyerah
- Penn Image Computing and Science Lab, Department of Radiology, Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Corey T McMillan
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Department of Neurology, Penn Alzheimer's Disease Research Center, Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - David A Wolk
- Department of Neurology, Penn Memory Center, Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Department of Neurology, Penn Alzheimer's Disease Research Center, Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Paul Yushkevich
- Department of Neurology, Penn Alzheimer's Disease Research Center, Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Penn Image Computing and Science Lab, Department of Radiology, Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - John Q Trojanowski
- Department of Neurology, Penn Alzheimer's Disease Research Center, Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Center for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Edward B Lee
- Department of Neurology, Penn Alzheimer's Disease Research Center, Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Center for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, Philadelphia, PA, 19104, USA
- Translational Neuropathology Research Laboratory, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Murray Grossman
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - Jeffrey S Phillips
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, Philadelphia, PA, 19104, USA
| | - David J Irwin
- Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, Philadelphia, PA, 19104, USA.
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, Philadelphia, PA, 19104, USA.
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38
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Khandelwal P, Sadaghiani S, Chung E, Lim SA, Duong MT, Ravikumar S, Arezoumandan S, Peterson C, Bedard ML, Capp N, Ittyerah R, Migdal E, Choi G, Kopp E, Patino BL, Hasan E, Li J, Prabhakaran K, Mizsei G, Gabrielyan M, Schuck T, Robinson J, Ohm DT, Lee EB, Trojanowski JQ, McMillan CT, Grossman M, Irwin DJ, Tisdall DM, Das SR, Wisse LEM, Wolk DA, Yushkevich PA. Deep learning pipeline for cortical gray matter segmentation and thickness analysis in Ultra High Resolution T2w 7 Tesla
Ex vivo
MRI across neurodegenerative diseases reveals associations with underlying neuropathology. Alzheimers Dement 2022. [DOI: 10.1002/alz.065737] [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)
- Pulkit Khandelwal
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania Philadelphia PA USA
| | | | | | | | | | | | - Sanaz Arezoumandan
- Penn FTD Center, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
- Digital Neuropathology Laboratory, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - Claire Peterson
- Penn FTD Center, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
- Digital Neuropathology Laboratory, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - Madigan L Bedard
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania Philadelphia PA USA
| | - Noah Capp
- University of Pennsylvania Philadelphia PA USA
| | - Ranjit Ittyerah
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania Philadelphia PA USA
- Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | | | - Grace Choi
- University of Pennsylvania Philadelphia PA USA
| | - Emily Kopp
- University of Pennsylvania Philadelphia PA USA
| | | | - Eusha Hasan
- University of Pennsylvania Philadelphia PA USA
| | - Jiacheng Li
- University of Pennsylvania Philadelphia PA USA
| | | | | | | | | | | | - Daniel T Ohm
- Penn FTD Center, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
- Digital Neuropathology Laboratory, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - Eddie B Lee
- Perelman School of Medicine at the University of Pennsylvania Philadelphia PA USA
- Translational Neuropathology Research Laboratory, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
- Center for Neurodegenerative Disease Research, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - John Q Trojanowski
- Center for Neurodegenerative Disease Research, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
- Department of Pathology and Laboratory Medicine Philadelphia PA USA
| | - Corey T McMillan
- University of Pennsylvania Philadelphia PA USA
- Penn Alzheimer’s Disease Research Center, Perelman School of Medicine Philadelphia PA USA
| | - Murray Grossman
- Penn FTD Center, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
- Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - David J. Irwin
- Penn FTD Center, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
- Digital Neuropathology Laboratory, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | | | - Sandhitsu R. Das
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania Philadelphia PA USA
- University of Pennsylvania Philadelphia PA USA
| | - Laura EM Wisse
- Department of Diagnostic Radiology, Clinical Sciences, Lund University Lund Sweden
- Lund University Lund Sweden
| | - David A. Wolk
- Department of Neurology, University of Pennsylvania School of Medicine Philadelphia PA USA
- Penn Alzheimer’s Disease Research Center, University of Pennsylvania Philadelphia PA USA
| | - Paul A. Yushkevich
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania Philadelphia PA USA
- Penn Alzheimer’s Disease Research Center, Perelman School of Medicine Philadelphia PA USA
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39
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Cousins KAQ, Shaw LM, Chen‐Plotkin A, Lee EB, Trojanowski JQ, Van Deerlin VM, McMillan CT, Grossman M, Irwin DJ. Plasma GFAP:NfL discriminates FTLD‐tau from FTLD‐TDP. Alzheimers Dement 2022. [DOI: 10.1002/alz.064010] [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)
| | - Leslie M. Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - Alice Chen‐Plotkin
- Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - Eddie B Lee
- Translational Neuropathology Research Laboratory, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
- Center for Neurodegenerative Disease Research, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - John Q Trojanowski
- Center for Neurodegenerative Disease Research, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
- Department of Pathology and Laboratory Medicine Philadelphia PA USA
| | - Vivianna M Van Deerlin
- Center for Neurodegenerative Disease Research, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - Corey T McMillan
- University of Pennsylvania Philadelphia PA USA
- Penn Alzheimer’s Disease Research Center, Perelman School of Medicine Philadelphia PA USA
| | - Murray Grossman
- Penn FTD Center, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - David J. Irwin
- Penn FTD Center, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
- Digital Neuropathology Laboratory, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
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40
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Lyu X, Duong MT, Xie L, Richardson H, de Flores R, DiCalogero M, McMillan CT, Robinson J, Trojanowski JQ, Grossman M, Lee EB, Irwin DJ, Dickerson BC, Xie SX, Nasrallah IM, Yushkevich PA, Wolk DA, Das SR. Tau‐Neurodegeneration mismatch reveals vulnerability and resilience in Alzheimer’s continuum and Non‐Alzheimer’s pathophysiology. Alzheimers Dement 2022. [DOI: 10.1002/alz.062542] [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)
- Xueying Lyu
- University of Pennsylvania Philadelphia PA USA
| | | | - Long Xie
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania Philadelphia PA USA
| | | | - Robin de Flores
- Normandie University, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen‐Normandie, Cyceron Caen France
| | | | | | | | - John Q Trojanowski
- Center for Neurodegenerative Disease Research, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - Murray Grossman
- Penn FTD Center, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - Eddie B Lee
- Center for Neurodegenerative Disease Research, University of Pennsylvania Philadelphia PA USA
| | - David J. Irwin
- Penn FTD Center, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | | | - Sharon X Xie
- Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | | | - Paul A. Yushkevich
- Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania Philadelphia PA USA
| | - David A. Wolk
- Penn Alzheimer’s Disease Research Center, University of Pennsylvania Philadelphia PA USA
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Cousins KAQ, Arezoumandan S, Shellikeri S, Ohm D, Shaw LM, Grossman M, Wolk D, McMillan CT, Chen-Plotkin A, Lee E, Trojanowski JQ, Zetterberg H, Blennow K, Irwin DJ. CSF Biomarkers of Alzheimer Disease in Patients With Concomitant α-Synuclein Pathology. Neurology 2022; 99:e2303-e2312. [PMID: 36041863 PMCID: PMC9694837 DOI: 10.1212/wnl.0000000000201202] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Accepted: 07/19/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES CSF biomarkers β-amyloid 1-42 (Aβ42), phosphorylated tau 181 (p-tau181), total tau (t-tau), and neurogranin (Ng) can diagnose Alzheimer disease (AD) in life. However, it is unknown whether CSF concentrations, and thus their accuracies, are affected by concomitant pathologies common in AD, such as α-synuclein (αSyn). Our primary goal was to test whether biomarkers in patients with AD are altered by concomitant αSyn. We compared CSF Aβ42, p-tau181, t-tau, and Ng levels across autopsy-confirmed AD and concomitant AD and αSyn (AD + αSyn). Antemortem CSF levels were related to postmortem accumulations of αSyn. Finally, we tested how concommitant AD + αSyn affected the diagnostic accuracy of 2 CSF-based strategies: the amyloid/tau/neurodegeneration (ATN) framework and the t-tau/Aβ42 ratio. METHODS Inclusion criteria were neuropathologic diagnoses of AD, mixed AD + αSyn, and αSyn. A convenience sample of nonimpaired controls was selected with available CSF and a Mini-Mental State Examination (MMSE) ≥ 27. αSyn without AD and controls were included as reference groups. Analyses of covariance (ANCOVAs) tested planned comparisons were CSF Aβ42, p-tau181, t-tau, and Ng differences across AD and AD + αSyn. Linear models tested how biomarkers were altered by αSyn accumulation in AD, accounting for pathologic β-amyloid and tau. Receiver operating characteristic and area under the curve (AUC), including 95% CI, evaluated diagnostic accuracy. RESULTS Participants were 61 patients with AD, 39 patients with mixed AD + αSyn, 20 patients with αSyn, and 61 controls. AD had similar median age (73 [interquartile range {IQR} = 12] years), MMSE (23 [IQR = 9]), and sex distribution (male = 49%) compared with AD + αSyn age (70 [IQR = 13] years; p = 0.3), MMSE (25 [IQR = 9.5]; p = 0.19), and sex distribution (male = 69%; p = 0.077). ANCOVAs showed that AD + αSyn had lower p-tau181 (F(1,94) = 17, p < 2.6e-16), t-tau (F(1,93) = 11, p = 0.0004), and Ng levels (F(1,50) = 12, p = 0.0004) than AD; there was no difference in Aβ42 (p = 0.44). Models showed increasing αSyn related to lower p-tau181 (β = -0.26, SE = 0.092, p = 0.0065), t-tau (β = -0.19, SE = 0.092, p = 0.041), and Ng levels (β = -0.2, SE = 0.066, p = 0.0046); αSyn was not a significant factor for Aβ42 (p = 1). T-tau/Aβ42 had the highest accuracy when detecting AD, including mixed AD + αSyn cases (AUC = 0.95; CI 0.92-0.98). DISCUSSION Findings demonstrate that concomitant αSyn pathology in AD is associated with lower CSF p-tau181, t-tau, and Ng levels and can affect diagnostic accuracy in patients with AD.
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Affiliation(s)
- Katheryn Alexandra Quilico Cousins
- From the Departments of Neurology (K.A.Q.C., S.A., S.S., D.O., M.G., D.W., C.T.M., A.C.-P., D.J.I.), Pathology and Laboratory Medicine (L.M.S., E.L., J.Q.T.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Department of Psychiatry and Neurochemistry (H.Z., K.B.), Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden; and Department of Neurodegenerative Disease (H.Z.), Institute of Neurology, University College London, UK.
| | - Sanaz Arezoumandan
- From the Departments of Neurology (K.A.Q.C., S.A., S.S., D.O., M.G., D.W., C.T.M., A.C.-P., D.J.I.), Pathology and Laboratory Medicine (L.M.S., E.L., J.Q.T.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Department of Psychiatry and Neurochemistry (H.Z., K.B.), Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden; and Department of Neurodegenerative Disease (H.Z.), Institute of Neurology, University College London, UK
| | - Sanjana Shellikeri
- From the Departments of Neurology (K.A.Q.C., S.A., S.S., D.O., M.G., D.W., C.T.M., A.C.-P., D.J.I.), Pathology and Laboratory Medicine (L.M.S., E.L., J.Q.T.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Department of Psychiatry and Neurochemistry (H.Z., K.B.), Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden; and Department of Neurodegenerative Disease (H.Z.), Institute of Neurology, University College London, UK
| | - Daniel Ohm
- From the Departments of Neurology (K.A.Q.C., S.A., S.S., D.O., M.G., D.W., C.T.M., A.C.-P., D.J.I.), Pathology and Laboratory Medicine (L.M.S., E.L., J.Q.T.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Department of Psychiatry and Neurochemistry (H.Z., K.B.), Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden; and Department of Neurodegenerative Disease (H.Z.), Institute of Neurology, University College London, UK
| | - Leslie M Shaw
- From the Departments of Neurology (K.A.Q.C., S.A., S.S., D.O., M.G., D.W., C.T.M., A.C.-P., D.J.I.), Pathology and Laboratory Medicine (L.M.S., E.L., J.Q.T.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Department of Psychiatry and Neurochemistry (H.Z., K.B.), Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden; and Department of Neurodegenerative Disease (H.Z.), Institute of Neurology, University College London, UK
| | - Murray Grossman
- From the Departments of Neurology (K.A.Q.C., S.A., S.S., D.O., M.G., D.W., C.T.M., A.C.-P., D.J.I.), Pathology and Laboratory Medicine (L.M.S., E.L., J.Q.T.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Department of Psychiatry and Neurochemistry (H.Z., K.B.), Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden; and Department of Neurodegenerative Disease (H.Z.), Institute of Neurology, University College London, UK
| | - David Wolk
- From the Departments of Neurology (K.A.Q.C., S.A., S.S., D.O., M.G., D.W., C.T.M., A.C.-P., D.J.I.), Pathology and Laboratory Medicine (L.M.S., E.L., J.Q.T.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Department of Psychiatry and Neurochemistry (H.Z., K.B.), Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden; and Department of Neurodegenerative Disease (H.Z.), Institute of Neurology, University College London, UK
| | - Corey T McMillan
- From the Departments of Neurology (K.A.Q.C., S.A., S.S., D.O., M.G., D.W., C.T.M., A.C.-P., D.J.I.), Pathology and Laboratory Medicine (L.M.S., E.L., J.Q.T.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Department of Psychiatry and Neurochemistry (H.Z., K.B.), Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden; and Department of Neurodegenerative Disease (H.Z.), Institute of Neurology, University College London, UK
| | - Alice Chen-Plotkin
- From the Departments of Neurology (K.A.Q.C., S.A., S.S., D.O., M.G., D.W., C.T.M., A.C.-P., D.J.I.), Pathology and Laboratory Medicine (L.M.S., E.L., J.Q.T.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Department of Psychiatry and Neurochemistry (H.Z., K.B.), Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden; and Department of Neurodegenerative Disease (H.Z.), Institute of Neurology, University College London, UK
| | - Edward Lee
- From the Departments of Neurology (K.A.Q.C., S.A., S.S., D.O., M.G., D.W., C.T.M., A.C.-P., D.J.I.), Pathology and Laboratory Medicine (L.M.S., E.L., J.Q.T.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Department of Psychiatry and Neurochemistry (H.Z., K.B.), Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden; and Department of Neurodegenerative Disease (H.Z.), Institute of Neurology, University College London, UK
| | - John Q Trojanowski
- From the Departments of Neurology (K.A.Q.C., S.A., S.S., D.O., M.G., D.W., C.T.M., A.C.-P., D.J.I.), Pathology and Laboratory Medicine (L.M.S., E.L., J.Q.T.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Department of Psychiatry and Neurochemistry (H.Z., K.B.), Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden; and Department of Neurodegenerative Disease (H.Z.), Institute of Neurology, University College London, UK
| | - Henrik Zetterberg
- From the Departments of Neurology (K.A.Q.C., S.A., S.S., D.O., M.G., D.W., C.T.M., A.C.-P., D.J.I.), Pathology and Laboratory Medicine (L.M.S., E.L., J.Q.T.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Department of Psychiatry and Neurochemistry (H.Z., K.B.), Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden; and Department of Neurodegenerative Disease (H.Z.), Institute of Neurology, University College London, UK
| | - Kaj Blennow
- From the Departments of Neurology (K.A.Q.C., S.A., S.S., D.O., M.G., D.W., C.T.M., A.C.-P., D.J.I.), Pathology and Laboratory Medicine (L.M.S., E.L., J.Q.T.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Department of Psychiatry and Neurochemistry (H.Z., K.B.), Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden; and Department of Neurodegenerative Disease (H.Z.), Institute of Neurology, University College London, UK
| | - David John Irwin
- From the Departments of Neurology (K.A.Q.C., S.A., S.S., D.O., M.G., D.W., C.T.M., A.C.-P., D.J.I.), Pathology and Laboratory Medicine (L.M.S., E.L., J.Q.T.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Department of Psychiatry and Neurochemistry (H.Z., K.B.), Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Sweden; and Department of Neurodegenerative Disease (H.Z.), Institute of Neurology, University College London, UK
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McMillan CT, Wuu J, Rascovsky K, Cosentino S, Grossman M, Elman L, Quinn C, Rosario L, Stark JH, Granit V, Briemberg H, Chenji S, Dionne A, Genge A, Johnston W, Korngut L, Shoesmith C, Zinman L, Kalra S, Benatar M. Defining cognitive impairment in amyotrophic lateral sclerosis: an evaluation of empirical approaches. Amyotroph Lateral Scler Frontotemporal Degener 2022; 23:517-526. [PMID: 35253557 PMCID: PMC9448823 DOI: 10.1080/21678421.2022.2039713] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [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: 07/08/2021] [Revised: 01/17/2022] [Accepted: 01/30/2022] [Indexed: 11/01/2022]
Abstract
Objective: Amyotrophic lateral sclerosis (ALS) is a multi-system disorder characterized primarily by motor neuron degeneration, but may be accompanied by cognitive dysfunction. Statistically appropriate criteria for establishing cognitive impairment (CI) in ALS are lacking. We evaluate quantile regression (QR), that accounts for age and education, relative to a traditional two standard deviation (SD) cutoff for defining CI. Methods: QR of cross-sectional data from a multi-center North American Control (NAC) cohort of 269 healthy adults was used to model the 5th percentile of cognitive scores on the Edinburgh Cognitive and Behavioral ALS Screen (ECAS). The QR approach was compared to traditional two SD cutoff approach using the same NAC cohort (2SD-NAC) and to existing UK-based normative data derived using the 2SD approach (2SD-UK) to assess the impact of cohort selection and statistical model in identifying CI in 182 ALS patients. Results: QR-NAC models revealed that age and education impact cognitive performance on the ECAS. Based on QR-NAC normative cutoffs, the frequency of CI in the 182 PENN ALS patients was 15.9% for ALS specific, 12.6% for ALS nonspecific, and 15.4% for ECAS total. This frequency of CI is substantially more conservative in comparison to the 2SD-UK (20.3%-34.6%) and modestly more conservative to the 2SD-NAC (14.3%-16.5%) approaches for estimating CI. Conclusions: The choice of normative cohort has a substantial impact and choice of statistical method a modest impact on defining CI in ALS. This report establishes normative ECAS thresholds to identify whether ALS patients in the North American population have CI.
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Affiliation(s)
- Corey T. McMillan
- University of Pennsylvania Perelman School of Medicine, Department of Neurology, Philadelphia, PA, USA
| | - Joanne Wuu
- University of Miami Miller School of Medicine, Department of Neurology, Miami, FL, USA
| | - Katya Rascovsky
- University of Pennsylvania Perelman School of Medicine, Department of Neurology, Philadelphia, PA, USA
| | - Stephanie Cosentino
- Columbia University, The Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, New York, NY, USA
| | - Murray Grossman
- University of Pennsylvania Perelman School of Medicine, Department of Neurology, Philadelphia, PA, USA
| | - Lauren Elman
- University of Pennsylvania Perelman School of Medicine, Department of Neurology, Philadelphia, PA, USA
| | - Colin Quinn
- University of Pennsylvania Perelman School of Medicine, Department of Neurology, Philadelphia, PA, USA
| | - Luis Rosario
- University of Pennsylvania Perelman School of Medicine, Department of Neurology, Philadelphia, PA, USA
| | - Jessica H. Stark
- University of Miami Miller School of Medicine, Department of Neurology, Miami, FL, USA
| | - Volkan Granit
- University of Miami Miller School of Medicine, Department of Neurology, Miami, FL, USA
| | - Hannah Briemberg
- Division of Neurology, Department of Medicine, University of British Columbia, Vancouver, Canada
| | - Sneha Chenji
- Department of Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
| | - Annie Dionne
- Department of Medicine, Université Laval, Québec, Canada
| | - Angela Genge
- Montreal Neurological Institute and Hospital, McGill University, Montreal, Canada
| | - Wendy Johnston
- Division of Neurology, Department of Medicine, University of Alberta, Edmonton, Canada
| | - Lawrence Korngut
- Department of Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
| | | | - Lorne Zinman
- Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | | | - Sanjay Kalra
- Division of Neurology, Department of Medicine, University of Alberta, Edmonton, Canada
- Neuroscience and Mental Health Institute, University of Alberta, Edmonton, Canada
| | - Michael Benatar
- University of Miami Miller School of Medicine, Department of Neurology, Miami, FL, USA
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43
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Cousins KAQ, Shaw LM, Shellikeri S, Dratch L, Rosario L, Elman LB, Quinn C, Amado DA, Wolk DA, Tropea TF, Chen-Plotkin A, Irwin DJ, Grossman M, Lee EB, Trojanowski JQ, McMillan CT. Elevated Plasma Phosphorylated Tau 181 in Amyotrophic Lateral Sclerosis. Ann Neurol 2022; 92:807-818. [PMID: 35877814 PMCID: PMC9588516 DOI: 10.1002/ana.26462] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Revised: 07/21/2022] [Accepted: 07/23/2022] [Indexed: 11/10/2022]
Abstract
OBJECTIVE Plasma phosphorylated tau (p-tau181 ) is reliably elevated in Alzheimer's disease (AD), but less explored is its specificity relative to other neurodegenerative conditions. Here, we find novel evidence that plasma p-tau181 is elevated in amyotrophic lateral sclerosis (ALS), a neurodegenerative condition typically lacking tau pathology. We performed a detailed evaluation to identify the clinical correlates of elevated p-tau181 in ALS. METHODS Patients were clinically or pathologically diagnosed with ALS (n = 130) or AD (n = 79), or were healthy non-impaired controls (n = 26). Receiver operating characteristic (ROC) curves were analyzed and area under the curve (AUC) was used to discriminate AD from ALS. Within ALS, Mann-Whitney-Wilcoxon tests compared analytes by presence/absence of upper motor neuron and lower motor neuron (LMN) signs. Spearman correlations tested associations between plasma p-tau181 and postmortem neuron loss. RESULTS A Wilcoxon test showed plasma p-tau181 was higher in ALS than controls (W = 2,600, p = 0.000015), and ROC analyses showed plasma p-tau181 poorly discriminated AD and ALS (AUC = 0.60). In ALS, elevated plasma p-tau181 was associated with LMN signs in cervical (W = 827, p = 0.0072), thoracic (W = 469, p = 0.00025), and lumbosacral regions (W = 851, p = 0.0000029). In support of LMN findings, plasma p-tau181 was associated with neuron loss in the spinal cord (rho = 0.46, p = 0.017), but not in the motor cortex (p = 0.41). Cerebrospinal spinal fluid p-tau181 and plasma neurofilament light chain were included as reference analytes, and demonstrate specificity of findings. INTERPRETATION We found strong evidence that plasma p-tau181 is elevated in ALS and may be a novel marker specific to LMN dysfunction. ANN NEUROL 2022;92:807-818.
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Affiliation(s)
- Katheryn A Q Cousins
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA
| | - Sanjana Shellikeri
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Laynie Dratch
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Luis Rosario
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Lauren B Elman
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Colin Quinn
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Defne A Amado
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - David A Wolk
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Thomas F Tropea
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Alice Chen-Plotkin
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - David J Irwin
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Murray Grossman
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Edward B Lee
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA
| | - John Q Trojanowski
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA
| | - Corey T McMillan
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
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44
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Cousins KAQ, Shaw LM, Chen-Plotkin A, Wolk DA, Van Deerlin VM, Lee EB, McMillan CT, Grossman M, Irwin DJ. Distinguishing Frontotemporal Lobar Degeneration Tau From TDP-43 Using Plasma Biomarkers. JAMA Neurol 2022; 79:1155-1164. [PMID: 36215050 PMCID: PMC9552044 DOI: 10.1001/jamaneurol.2022.3265] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Accepted: 08/05/2022] [Indexed: 01/14/2023]
Abstract
Importance Biomarkers are lacking that can discriminate frontotemporal lobar degeneration (FTLD) associated with tau (FTLD-tau) or TDP-43 (FTLD-TDP). Objective To test whether plasma biomarkers glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), or their ratio (GFAP/NfL) differ between FTLD-tau and FTLD-TDP. Design, Setting, and Participants This retrospective cross-sectional study included data from 2009 to 2020 from the University of Pennsylvania Integrated Neurodegenerative Disease Database, with a median (IQR) follow-up duration of 2 (0.3-4.2) years. The training sample was composed of patients with autopsy-confirmed and familial FTLD; nonimpaired controls were included as a reference group. The independent validation sample included patients with FTD with a clinical diagnosis of progressive supranuclear palsy syndrome (PSPS) associated with tau (PSPS-tau) or amytrophic lateral sclerosis (ALS) associated with TDP-43 (ALS-TDP). In patients with FTLD with autopsy-confirmed or variant-confirmed pathology, receiver operating characteristic (ROC) curves tested the GFAP/NfL ratio and established a pathology-confirmed cut point. The cut point was validated in an independent sample of patients with clinical frontotemporal dementia (FTD). Data were analyzed from February to July 2022. Exposures Clinical, postmortem histopathological assessments, and plasma collection. Main Outcomes and Measures ROC and area under the ROC curve (AUC) with 90% CIs evaluated discrimination of pure FTLD-tau from pure FTLD-TDP using plasma GFAP/NfL ratio; the Youden index established optimal cut points. Sensitivity and specificity of cut points were assessed in an independent validation sample. Results Of 349 participants with available plasma data, 234 met inclusion criteria (31 controls, 141 in the training sample, and 62 in the validation sample). In the training sample, patients with FTLD-tau were older than patients with FTLD-TDP (FTLD-tau: n = 46; mean [SD] age, 65.8 [8.29] years; FTLD-TDP: n = 95; mean [SD] age, 62.3 [7.82] years; t84.6 = 2.45; mean difference, 3.57; 95% CI, 0.67-6.48; P = .02) but with similar sex distribution (FTLD-tau: 27 of 46 [59%] were male; FTLD-TDP: 51 of 95 [54%] were male; χ21 = 0.14; P = .70). In the validation sample, patients with PSPS-tau were older than those with ALS-TDP (PSPS-tau: n = 31; mean [SD] age, 69.3 [7.35] years; ALS-TDP: n = 31; mean [SD] age, 54.6 [10.17] years; t54.6 = 6.53; mean difference, 14.71; 95% CI, 10.19-19.23; P < .001) and had fewer patients who were male (PSPS-tau: 9 of 31 [29%] were male; ALS-TDP: 22 of 31 [71%] were male; χ21 = 9.3; P = .002). ROC revealed excellent discrimination of FTLD-tau from FTLD-TDP by plasma GFAP/NfL ratio (AUC = 0.89; 90% CI, 0.82-0.95; sensitivity = 0.73; 90% CI, 0.65-0.89; specificity = 0.89; 90% CI, 0.78-0.98), which was higher than either GFAP level alone (AUC = 0.65; 90% CI, 0.54-0.76) or NfL levels alone (AUC = 0.75; 90% CI, 0.64-0.85). In the validation sample, there was sensitivity of 0.84 (90% CI, 0.66-0.94) and specificity of 0.81 (90% CI, 0.62-0.91) when applying the autopsy-derived plasma GFAP/NfL threshold. Conclusions and Relevance The plasma ratio of GFAP/NfL may discriminate FTLD-tau from FTLD-TDP.
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Affiliation(s)
- Katheryn A. Q. Cousins
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Leslie M. Shaw
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia
| | - Alice Chen-Plotkin
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - David A. Wolk
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | | | - Edward B. Lee
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia
| | - Corey T. McMillan
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Murray Grossman
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - David J. Irwin
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
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Perez SD, Phillips JS, Norise C, Kinney NG, Vaddi P, Halpin A, Rascovsky K, Irwin DJ, McMillan CT, Xie L, Wisse LE, Yushkevich PA, Kallogjeri D, Grossman M, Cousins KA. Neuropsychological and Neuroanatomical Features of Patients with Behavioral/Dysexecutive Variant Alzheimer’s disease (AD): A Comparison to Behavioral Variant Frontotemporal Dementia and Amnestic AD Groups. J Alzheimers Dis 2022; 89:641-658. [PMID: 35938245 PMCID: PMC10117623 DOI: 10.3233/jad-215728] [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] [Indexed: 11/15/2022]
Abstract
Background: An understudied variant of Alzheimer’s disease (AD), the behavioral/dysexecutive variant of AD (bvAD), is associated with progressive personality, behavior, and/or executive dysfunction and frontal atrophy. Objective: This study characterizes the neuropsychological and neuroanatomical features associated with bvAD by comparing it to behavioral variant frontotemporal dementia (bvFTD), amnestic AD (aAD), and subjects with normal cognition. Methods: Subjects included 16 bvAD, 67 bvFTD, and 18 aAD patients, and 26 healthy controls. Neuropsychological assessment and MRI data were compared between these groups. Results: Compared to bvFTD, bvAD showed more significant visuospatial impairments (Rey Figure copy and recall), more irritability (Neuropsychological Inventory), and equivalent verbal memory (Philadelphia Verbal Learning Test). Compared to aAD, bvAD indicated more executive dysfunction (F-letter fluency) and better visuospatial performance. Neuroimaging analysis found that bvAD showed cortical thinning relative to bvFTD posteriorly in left temporal-occipital regions; bvFTD had cortical thinning relative to bvAD in left inferior frontal cortex. bvAD had cortical thinning relative to aAD in prefrontal and anterior temporal regions. All patient groups had lower volumes than controls in both anterior and posterior hippocampus. However, bvAD patients had higher average volume than aAD patients in posterior hippocampus and higher volume than bvFTD patients in anterior hippocampus after adjustment for age and intracranial volume. Conclusion: Findings demonstrated that underlying pathology mediates disease presentation in bvAD and bvFTD.
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Affiliation(s)
- Sophia Dominguez Perez
- Penn Frontotemporal Degeneration Center (FTDC), University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychological Sciences, University of Connecticut, Storrs, CT, USA
| | - Jeffrey S. Phillips
- Penn Frontotemporal Degeneration Center (FTDC), University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Catherine Norise
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Nikolas G. Kinney
- Penn Frontotemporal Degeneration Center (FTDC), University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Prerana Vaddi
- Penn Frontotemporal Degeneration Center (FTDC), University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Amy Halpin
- Penn Frontotemporal Degeneration Center (FTDC), University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychology, University of Maine, Orono, ME, USA
| | - Katya Rascovsky
- Penn Frontotemporal Degeneration Center (FTDC), University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - David J. Irwin
- Penn Frontotemporal Degeneration Center (FTDC), University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Disease Research, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Corey T. McMillan
- Penn Frontotemporal Degeneration Center (FTDC), University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Long Xie
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Image Computing and Science Lab & Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Laura E.M. Wisse
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Image Computing and Science Lab & Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Diagnostic Radiology, Lund University, Lund, Sweden
| | - Paul A. Yushkevich
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Image Computing and Science Lab & Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Dorina Kallogjeri
- Department of Otolaryngology, Washington University, St. Louis, MO, USA
| | - Murray Grossman
- Penn Frontotemporal Degeneration Center (FTDC), University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Katheryn A.Q. Cousins
- Penn Frontotemporal Degeneration Center (FTDC), University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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Chen M, Ohm DT, Phillips JS, McMillan CT, Capp N, Peterson C, Xie E, Wolk DA, Trojanowski JQ, Lee EB, Gee J, Grossman M, Irwin DJ. Divergent Histopathological Networks of Frontotemporal Degeneration Proteinopathy Subytpes. J Neurosci 2022; 42:3868-3877. [PMID: 35318284 PMCID: PMC9087810 DOI: 10.1523/jneurosci.2061-21.2022] [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] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 02/22/2022] [Accepted: 03/01/2022] [Indexed: 11/21/2022] Open
Abstract
Network analyses inform complex systems such as human brain connectivity, but this approach is seldom applied to gold-standard histopathology. Here, we use two complimentary computational approaches to model microscopic progression of the main subtypes of tauopathy versus TDP-43 proteinopathy in the human brain. Digital histopathology measures were obtained in up to 13 gray matter (GM) and adjacent white matter (WM) cortical brain regions sampled from 53 tauopathy and 66 TDP-43 proteinopathy autopsy patients. First, we constructed a weighted non-directed graph for each group, where nodes are defined as GM and WM regions sampled and edges in the graph are weighted using the group-level Pearson's correlation coefficient for each pairwise node comparison. Additionally, we performed mediation analyses to test mediation effects of WM pathology between anterior frontotemporal and posterior parietal GM nodes. We find greater correlation (i.e., edges) between GM and WM node pairs in tauopathies compared with TDP-43 proteinopathies. Moreover, WM pathology strongly correlated with a graph metric of pathology spread (i.e., node-strength) in tauopathies (r = 0.60, p < 0.03) but not in TDP-43 proteinopathies (r = 0.03, p = 0.9). Finally, we found mediation effects for WM pathology on the association between anterior and posterior GM pathology in FTLD-Tau but not in FTLD-TDP. These data suggest distinct tau and TDP-43 proteinopathies may have divergent patterns of cellular propagation in GM and WM. More specifically, axonal spread may be more influential in FTLD-Tau progression. Network analyses of digital histopathological measurements can inform models of disease progression of cellular degeneration in the human brain.SIGNIFICANCE STATEMENT In this study, we uniquely perform two complimentary computational approaches to model and contrast microscopic disease progression between common frontotemporal lobar degeneration (FTLD) proteinopathy subtypes with similar clinical syndromes during life. Our models suggest white matter (WM) pathology influences cortical spread of disease in tauopathies that is less evident in TDP-43 proteinopathies. These data support the hypothesis that there are neuropathologic signatures of cellular degeneration within neurocognitive networks for specific protienopathies. These distinctive patterns of cellular pathology can guide future efforts to develop tissue-sensitive imaging and biological markers with diagnostic and prognostic utility for FTLD. Moreover, our novel computational approach can be used in future work to model various neurodegenerative disorders with mixed proteinopathy within the human brain connectome.
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Affiliation(s)
- Min Chen
- Penn Image Computing and Science Lab, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Daniel T Ohm
- Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Jeffrey S Phillips
- Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Corey T McMillan
- Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Noah Capp
- Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Claire Peterson
- Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Emily Xie
- Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - David A Wolk
- Alzheimer's Disease Research Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - John Q Trojanowski
- Center for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Edward B Lee
- Translational Neuropathology Research Laboratory, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - James Gee
- Penn Image Computing and Science Lab, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - Murray Grossman
- Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
| | - David J Irwin
- Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
- Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104
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Cervantes González A, Irwin DJ, Alcolea D, McMillan CT, Chen-Plotkin A, Wolk D, Sirisi S, Dols-Icardo O, Querol-Vilaseca M, Illán-Gala I, Santos-Santos MA, Fortea J, Lee EB, Trojanowski JQ, Grossman M, Lleó A, Belbin O. Multimarker synaptic protein cerebrospinal fluid panels reflect TDP-43 pathology and cognitive performance in a pathological cohort of frontotemporal lobar degeneration. Mol Neurodegener 2022; 17:29. [PMID: 35395770 PMCID: PMC8991834 DOI: 10.1186/s13024-022-00534-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [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] [Received: 09/13/2021] [Accepted: 03/30/2022] [Indexed: 12/13/2022] Open
Abstract
Background Synapse degeneration is an early event in pathological frontotemporal lobar degeneration (FTLD). Consequently, a surrogate marker of synapse loss could be used to monitor early pathologic changes in patients with underlying FTLD. The aim of this study was to evaluate the relationship of antemortem cerebrospinal fluid (CSF) levels of 8 synaptic proteins with postmortem global tau and TDP-43 burden and cognitive performance and to assess their diagnostic capacity in a neuropathological FTLD cohort. Methods We included patients with a neuropathological confirmation of FTLD-Tau (n = 24, mean age-at-CSF 67 years ± 11), FTLD-TDP (n = 25, 66 years ± 9) or AD (n = 25, 73 years ± 6) as well as cognitively normal controls (n = 35, 69 years ± 7) from the Penn FTD Center and ADRC. We used a semi-quantitative measure of tau and TDP-43 inclusions to quantify pathological burden across 16 brain regions. Statistical methods included Spearman rank correlations, one-way analysis of covariance, ordinal regression, step-wise multiple linear regression and receiver-operating characteristic curves. Result CSF calsyntenin-1 and neurexin-2a were correlated in all patient groups (rs = .55 to .88). In FTLD-TDP, we observed low antemortem CSF levels of calsyntenin-1 and neurexin-2a compared to AD (.72-fold, p = .001, .77-fold, p = .04, respectively) and controls (.80-fold, p = .02, .78-fold, p = .02, respectively), which were inversely associated with post-mortem global TDP-43 burden (regression r2 = .56, p = .007 and r2 = .57, p = .006, respectively). A multimarker panel including calsyntenin-1 was associated with TDP-43 burden (r2 = .69, p = .003) and MMSE score (r2 = .19, p = .03) in FTLD. A second multimarker synaptic panel, also including calsyntenin-1, was associated with MMSE score in FTLD-tau (r2 = .49, p = .04) and improved diagnostic performance to discriminate FTLD-Tau and FTLD-TDP neuropathologic subtypes (AUC = .83). Conclusion These synaptic panels have potential in the differential diagnosis of FTLD neuropathologic subtypes and as surrogate markers of cognitive performance in future clinical trials targeting TDP-43 or tau. Supplementary Information The online version contains supplementary material available at 10.1186/s13024-022-00534-y.
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Affiliation(s)
- Alba Cervantes González
- Hospital de La Santa Creu I Sant Pau, Universitat Autonoma de Barcelona, Barcelona, Spain.,Centre of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain.,Memory Unit and Biomedical Research Institute, IIB Sant Pau, c/Sant Quintí 77, 08041, Barcelona, Spain
| | - David J Irwin
- Penn FTD Center, Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Daniel Alcolea
- Hospital de La Santa Creu I Sant Pau, Universitat Autonoma de Barcelona, Barcelona, Spain.,Centre of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain.,Memory Unit and Biomedical Research Institute, IIB Sant Pau, c/Sant Quintí 77, 08041, Barcelona, Spain
| | - Corey T McMillan
- Penn FTD Center, Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Alice Chen-Plotkin
- Penn Alzheimer's Disease Research Center, Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - David Wolk
- Penn Alzheimer's Disease Research Center, Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Sònia Sirisi
- Hospital de La Santa Creu I Sant Pau, Universitat Autonoma de Barcelona, Barcelona, Spain.,Centre of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain.,Memory Unit and Biomedical Research Institute, IIB Sant Pau, c/Sant Quintí 77, 08041, Barcelona, Spain
| | - Oriol Dols-Icardo
- Hospital de La Santa Creu I Sant Pau, Universitat Autonoma de Barcelona, Barcelona, Spain.,Centre of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain.,Memory Unit and Biomedical Research Institute, IIB Sant Pau, c/Sant Quintí 77, 08041, Barcelona, Spain
| | - Marta Querol-Vilaseca
- Hospital de La Santa Creu I Sant Pau, Universitat Autonoma de Barcelona, Barcelona, Spain.,Centre of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain.,Memory Unit and Biomedical Research Institute, IIB Sant Pau, c/Sant Quintí 77, 08041, Barcelona, Spain
| | - Ignacio Illán-Gala
- Hospital de La Santa Creu I Sant Pau, Universitat Autonoma de Barcelona, Barcelona, Spain.,Centre of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain.,Memory Unit and Biomedical Research Institute, IIB Sant Pau, c/Sant Quintí 77, 08041, Barcelona, Spain
| | - Miguel Angel Santos-Santos
- Hospital de La Santa Creu I Sant Pau, Universitat Autonoma de Barcelona, Barcelona, Spain.,Centre of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain.,Memory Unit and Biomedical Research Institute, IIB Sant Pau, c/Sant Quintí 77, 08041, Barcelona, Spain
| | - Juan Fortea
- Hospital de La Santa Creu I Sant Pau, Universitat Autonoma de Barcelona, Barcelona, Spain.,Centre of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain.,Memory Unit and Biomedical Research Institute, IIB Sant Pau, c/Sant Quintí 77, 08041, Barcelona, Spain
| | - Edward B Lee
- Center for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - John Q Trojanowski
- Center for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Murray Grossman
- Penn FTD Center, Department of Neurology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Alberto Lleó
- Hospital de La Santa Creu I Sant Pau, Universitat Autonoma de Barcelona, Barcelona, Spain.,Centre of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain.,Memory Unit and Biomedical Research Institute, IIB Sant Pau, c/Sant Quintí 77, 08041, Barcelona, Spain
| | - Olivia Belbin
- Hospital de La Santa Creu I Sant Pau, Universitat Autonoma de Barcelona, Barcelona, Spain. .,Centre of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain. .,Memory Unit and Biomedical Research Institute, IIB Sant Pau, c/Sant Quintí 77, 08041, Barcelona, Spain.
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Benatar M, Wuu J, McHutchison C, Postuma RB, Boeve BF, Petersen R, Ross CA, Rosen H, Arias JJ, Fradette S, McDermott MP, Shefner J, Stanislaw C, Abrahams S, Cosentino S, Andersen PM, Finkel RS, Granit V, Grignon AL, Rohrer JD, McMillan CT, Grossman M, Al-Chalabi A, Turner MR. Preventing amyotrophic lateral sclerosis: insights from pre-symptomatic neurodegenerative diseases. Brain 2022; 145:27-44. [PMID: 34677606 PMCID: PMC8967095 DOI: 10.1093/brain/awab404] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [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] [Received: 06/07/2021] [Revised: 09/16/2021] [Accepted: 10/08/2021] [Indexed: 11/12/2022] Open
Abstract
Significant progress has been made in understanding the pre-symptomatic phase of amyotrophic lateral sclerosis. While much is still unknown, advances in other neurodegenerative diseases offer valuable insights. Indeed, it is increasingly clear that the well-recognized clinical syndromes of Alzheimer's disease, Parkinson's disease, Huntington's disease, spinal muscular atrophy and frontotemporal dementia are also each preceded by a pre-symptomatic or prodromal period of varying duration, during which the underlying disease process unfolds, with associated compensatory changes and loss of inherent system redundancy. Key insights from these diseases highlight opportunities for discovery in amyotrophic lateral sclerosis. The development of biomarkers reflecting amyloid and tau has led to a shift in defining Alzheimer's disease based on inferred underlying histopathology. Parkinson's disease is unique among neurodegenerative diseases in the number and diversity of non-genetic biomarkers of pre-symptomatic disease, most notably REM sleep behaviour disorder. Huntington's disease benefits from an ability to predict the likely timing of clinically manifest disease based on age and CAG-repeat length alongside reliable neuroimaging markers of atrophy. Spinal muscular atrophy clinical trials have highlighted the transformational value of early therapeutic intervention, and studies in frontotemporal dementia illustrate the differential role of biomarkers based on genotype. Similar advances in amyotrophic lateral sclerosis would transform our understanding of key events in pathogenesis, thereby dramatically accelerating progress towards disease prevention. Deciphering the biology of pre-symptomatic amyotrophic lateral sclerosis relies on a clear conceptual framework for defining the earliest stages of disease. Clinically manifest amyotrophic lateral sclerosis may emerge abruptly, especially among those who harbour genetic mutations associated with rapidly progressive amyotrophic lateral sclerosis. However, the disease may also evolve more gradually, revealing a prodromal period of mild motor impairment preceding phenoconversion to clinically manifest disease. Similarly, cognitive and behavioural impairment, when present, may emerge gradually, evolving through a prodromal period of mild cognitive impairment or mild behavioural impairment before progression to amyotrophic lateral sclerosis. Biomarkers are critically important to studying pre-symptomatic amyotrophic lateral sclerosis and essential to efforts to intervene therapeutically before clinically manifest disease emerges. The use of non-genetic biomarkers, however, presents challenges related to counselling, informed consent, communication of results and limited protections afforded by existing legislation. Experiences from pre-symptomatic genetic testing and counselling, and the legal protections against discrimination based on genetic data, may serve as a guide. Building on what we have learned-more broadly from other pre-symptomatic neurodegenerative diseases and specifically from amyotrophic lateral sclerosis gene mutation carriers-we present a road map to early intervention, and perhaps even disease prevention, for all forms of amyotrophic lateral sclerosis.
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Affiliation(s)
- Michael Benatar
- Department of Neurology, University of Miami, Miami, FL, USA
| | - Joanne Wuu
- Department of Neurology, University of Miami, Miami, FL, USA
| | - Caroline McHutchison
- Human Cognitive Neuroscience, Department of Psychology, University of Edinburgh, Edinburgh, UK.,Euan MacDonald Centre for MND Research, University of Edinburgh, Edinburgh, UK
| | - Ronald B Postuma
- Department of Neurology, Montreal Neurological Institute, McGill University, Montreal, Canada
| | | | | | - Christopher A Ross
- Division of Neurobiology, Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,Solomon H. Snyder Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,Department of Pharmacology and Molecular Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Howard Rosen
- Department of Neurology, University of California San Francisco, CA, USA
| | - Jalayne J Arias
- Department of Neurology, University of California San Francisco, CA, USA
| | | | - Michael P McDermott
- Department of Biostatistics and Computational Biology, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA.,Department of Neurology, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA
| | - Jeremy Shefner
- Department of Neurology, Barrow Neurological Institute, Phoenix, AZ, USA
| | | | - Sharon Abrahams
- Human Cognitive Neuroscience, Department of Psychology, University of Edinburgh, Edinburgh, UK.,Euan MacDonald Centre for MND Research, University of Edinburgh, Edinburgh, UK
| | | | - Peter M Andersen
- Department of Clinical Science, Neurosciences, Umeå University, Sweden
| | - Richard S Finkel
- Department of Pediatric Medicine, Center for Experimental Neurotherapeutics, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Volkan Granit
- Department of Neurology, University of Miami, Miami, FL, USA
| | | | - Jonathan D Rohrer
- Department of Neurodegenerative Disease, Dementia Research Centre, UCL Institute of Neurology, Queen Square, London, UK
| | - Corey T McMillan
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Murray Grossman
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Ammar Al-Chalabi
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, King's College London, London, UK.,Department of Neurology, King's College Hospital, London, UK
| | - Martin R Turner
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
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Tisdall MD, Ohm DT, Lobrovich R, Das SR, Mizsei G, Prabhakaran K, Ittyerah R, Lim S, McMillan CT, Wolk DA, Gee J, Trojanowski JQ, Lee EB, Detre JA, Yushkevich P, Grossman M, Irwin DJ. Ex vivo MRI and histopathology detect novel iron-rich cortical inflammation in frontotemporal lobar degeneration with tau versus TDP-43 pathology. Neuroimage Clin 2022; 33:102913. [PMID: 34952351 PMCID: PMC8715243 DOI: 10.1016/j.nicl.2021.102913] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 10/28/2021] [Accepted: 12/08/2021] [Indexed: 02/08/2023]
Abstract
Comparative study of whole-hemisphere ex vivo T2*-weighted MRI and histopathology. Sample of FTLD-Tau and FTLD-TDP subtypes with reference to healthy and AD brain. Novel focal upper cortical-layer iron-rich pathology distinguishes FTLD-TDP from clinically-similar FTLD-Tau and AD. Distinct novel iron-rich FTLD-Tau pathology in mid-to-deep cortical-layers and WM. T2*-weighted MRI signatures offer in vivo biomarker targets for FTLD proteinopathy.
Frontotemporal lobar degeneration (FTLD) is a heterogeneous spectrum of age-associated neurodegenerative diseases that include two main pathologic categories of tau (FTLD-Tau) and TDP-43 (FTLD-TDP) proteinopathies. These distinct proteinopathies are often clinically indistinguishable during life, posing a major obstacle for diagnosis and emerging therapeutic trials tailored to disease-specific mechanisms. Moreover, MRI-derived measures have had limited success to date discriminating between FTLD-Tau or FTLD-TDP. T2*-weighted (T2*w) ex vivo MRI has previously been shown to be sensitive to non-heme iron in healthy intracortical lamination and myelin, and to pathological iron deposits in amyloid-beta plaques and activated microglia in Alzheimer’s disease neuropathologic change (ADNC). However, an integrated, ex vivo MRI and histopathology approach is understudied in FTLD. We apply joint, whole-hemisphere ex vivo MRI at 7 T and histopathology to the study autopsy-confirmed FTLD-Tau (n = 4) and FTLD-TDP (n = 3), relative to ADNC disease-control brains with antemortem clinical symptoms of frontotemporal dementia (n = 2), and an age-matched healthy control. We detect distinct laminar patterns of novel iron-laden glial pathology in both FTLD-Tau and FTLD-TDP brains. We find iron-positive ameboid and hypertrophic microglia and astrocytes largely in deeper GM and adjacent WM in FTLD-Tau. In contrast, FTLD-TDP presents prominent superficial cortical layer iron reactivity in astrocytic processes enveloping small blood vessels with limited involvement of adjacent WM, as well as more diffuse distribution of punctate iron-rich dystrophic microglial processes across all GM lamina. This integrated MRI/histopathology approach reveals ex vivo MRI features that are consistent with these pathological observations distinguishing FTLD-Tau and FTLD-TDP subtypes, including prominent irregular hypointense signal in deeper cortex in FTLD-Tau whereas FTLD-TDP showed upper cortical layer hypointense bands and diffuse cortical speckling. Moreover, differences in adjacent WM degeneration and iron-rich gliosis on histology between FTLD-Tau and FTLD-TDP were also readily apparent on MRI as hyperintense signal and irregular areas of hypointensity, respectively that were more prominent in FTLD-Tau compared to FTLD-TDP. These unique histopathological and radiographic features were distinct from healthy control and ADNC brains, suggesting that iron-sensitive T2*w MRI, adapted to in vivo application at sufficient resolution, may eventually offer an opportunity to improve antemortem diagnosis of FTLD proteinopathies using tissue-validated methods.
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Affiliation(s)
- M Dylan Tisdall
- Radiology, Perelman School of Medicine, University of Pennsylvania, United States.
| | - Daniel T Ohm
- Neurology, Perelman School of Medicine, University of Pennsylvania, United States
| | - Rebecca Lobrovich
- Neurology, Perelman School of Medicine, University of Pennsylvania, United States
| | - Sandhitsu R Das
- Neurology, Perelman School of Medicine, University of Pennsylvania, United States
| | - Gabor Mizsei
- Radiology, Perelman School of Medicine, University of Pennsylvania, United States
| | - Karthik Prabhakaran
- Neurology, Perelman School of Medicine, University of Pennsylvania, United States
| | - Ranjit Ittyerah
- Radiology, Perelman School of Medicine, University of Pennsylvania, United States
| | - Sydney Lim
- Radiology, Perelman School of Medicine, University of Pennsylvania, United States
| | - Corey T McMillan
- Neurology, Perelman School of Medicine, University of Pennsylvania, United States
| | - David A Wolk
- Neurology, Perelman School of Medicine, University of Pennsylvania, United States
| | - James Gee
- Radiology, Perelman School of Medicine, University of Pennsylvania, United States
| | - John Q Trojanowski
- Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, United States
| | - Edward B Lee
- Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, United States
| | - John A Detre
- Radiology, Perelman School of Medicine, University of Pennsylvania, United States; Neurology, Perelman School of Medicine, University of Pennsylvania, United States
| | - Paul Yushkevich
- Radiology, Perelman School of Medicine, University of Pennsylvania, United States
| | - Murray Grossman
- Neurology, Perelman School of Medicine, University of Pennsylvania, United States
| | - David J Irwin
- Neurology, Perelman School of Medicine, University of Pennsylvania, United States; Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, United States.
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50
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Farrell K, Kim S, Han N, Iida MA, Gonzalez EM, Otero-Garcia M, Walker JM, Richardson TE, Renton AE, Andrews SJ, Fulton-Howard B, Humphrey J, Vialle RA, Bowles KR, de Paiva Lopes K, Whitney K, Dangoor DK, Walsh H, Marcora E, Hefti MM, Casella A, Sissoko CT, Kapoor M, Novikova G, Udine E, Wong G, Tang W, Bhangale T, Hunkapiller J, Ayalon G, Graham RR, Cherry JD, Cortes EP, Borukov VY, McKee AC, Stein TD, Vonsattel JP, Teich AF, Gearing M, Glass J, Troncoso JC, Frosch MP, Hyman BT, Dickson DW, Murray ME, Attems J, Flanagan ME, Mao Q, Mesulam MM, Weintraub S, Woltjer RL, Pham T, Kofler J, Schneider JA, Yu L, Purohit DP, Haroutunian V, Hof PR, Gandy S, Sano M, Beach TG, Poon W, Kawas CH, Corrada MM, Rissman RA, Metcalf J, Shuldberg S, Salehi B, Nelson PT, Trojanowski JQ, Lee EB, Wolk DA, McMillan CT, Keene CD, Latimer CS, Montine TJ, Kovacs GG, Lutz MI, Fischer P, Perrin RJ, Cairns NJ, Franklin EE, Cohen HT, Raj T, Cobos I, Frost B, Goate A, White Iii CL, Crary JF. Genome-wide association study and functional validation implicates JADE1 in tauopathy. Acta Neuropathol 2022; 143:33-53. [PMID: 34719765 PMCID: PMC8786260 DOI: 10.1007/s00401-021-02379-z] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 10/13/2021] [Accepted: 10/24/2021] [Indexed: 01/07/2023]
Abstract
Primary age-related tauopathy (PART) is a neurodegenerative pathology with features distinct from but also overlapping with Alzheimer disease (AD). While both exhibit Alzheimer-type temporal lobe neurofibrillary degeneration alongside amnestic cognitive impairment, PART develops independently of amyloid-β (Aβ) plaques. The pathogenesis of PART is not known, but evidence suggests an association with genes that promote tau pathology and others that protect from Aβ toxicity. Here, we performed a genetic association study in an autopsy cohort of individuals with PART (n = 647) using Braak neurofibrillary tangle stage as a quantitative trait. We found some significant associations with candidate loci associated with AD (SLC24A4, MS4A6A, HS3ST1) and progressive supranuclear palsy (MAPT and EIF2AK3). Genome-wide association analysis revealed a novel significant association with a single nucleotide polymorphism on chromosome 4 (rs56405341) in a locus containing three genes, including JADE1 which was significantly upregulated in tangle-bearing neurons by single-soma RNA-seq. Immunohistochemical studies using antisera targeting JADE1 protein revealed localization within tau aggregates in autopsy brains with four microtubule-binding domain repeats (4R) isoforms and mixed 3R/4R, but not with 3R exclusively. Co-immunoprecipitation in post-mortem human PART brain tissue revealed a specific binding of JADE1 protein to four repeat tau lacking N-terminal inserts (0N4R). Finally, knockdown of the Drosophila JADE1 homolog rhinoceros (rno) enhanced tau-induced toxicity and apoptosis in vivo in a humanized 0N4R mutant tau knock-in model, as quantified by rough eye phenotype and terminal deoxynucleotidyl transferase dUTP nick end-labeling (TUNEL) in the fly brain. Together, these findings indicate that PART has a genetic architecture that partially overlaps with AD and other tauopathies and suggests a novel role for JADE1 as a modifier of neurofibrillary degeneration.
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Affiliation(s)
- Kurt Farrell
- Department of Pathology, Neuropathology Brain Bank and Research CoRE, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place Box 1194, New York, NY, 10029, USA
- Nash Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - SoongHo Kim
- Department of Pathology, Neuropathology Brain Bank and Research CoRE, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place Box 1194, New York, NY, 10029, USA
- Nash Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Natalia Han
- Department of Pathology, Neuropathology Brain Bank and Research CoRE, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place Box 1194, New York, NY, 10029, USA
- Nash Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Megan A Iida
- Department of Pathology, Neuropathology Brain Bank and Research CoRE, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place Box 1194, New York, NY, 10029, USA
- Nash Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Elias M Gonzalez
- Department of Cell Systems and Anatomy, Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, the Sam and Ann Barshop Institute for Longevity and Aging Studies, University of Texas Health San Antonio, San Antonio, TX, 78229, USA
| | - Marcos Otero-Garcia
- Department of Pathology and Laboratory Medicine, Division of Neuropathology, University of California, Los Angeles, CA, USA
| | - Jamie M Walker
- Department of Pathology and Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, TX, USA
| | - Timothy E Richardson
- Department of Pathology and Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, TX, USA
| | - Alan E Renton
- Nash Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Shea J Andrews
- Nash Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Brian Fulton-Howard
- Nash Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jack Humphrey
- Nash Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ricardo A Vialle
- Nash Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kathryn R Bowles
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Katia de Paiva Lopes
- Nash Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kristen Whitney
- Department of Pathology, Neuropathology Brain Bank and Research CoRE, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place Box 1194, New York, NY, 10029, USA
- Nash Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Diana K Dangoor
- Department of Pathology, Neuropathology Brain Bank and Research CoRE, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place Box 1194, New York, NY, 10029, USA
- Nash Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Hadley Walsh
- Department of Pathology, Neuropathology Brain Bank and Research CoRE, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place Box 1194, New York, NY, 10029, USA
- Nash Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Edoardo Marcora
- Nash Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Marco M Hefti
- Department of Pathology, University of Iowa, Iowa City, IA, USA
| | - Alicia Casella
- Department of Pathology, Neuropathology Brain Bank and Research CoRE, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place Box 1194, New York, NY, 10029, USA
- Nash Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Cheick T Sissoko
- Department of Pathology, Neuropathology Brain Bank and Research CoRE, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place Box 1194, New York, NY, 10029, USA
- Nash Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Manav Kapoor
- Nash Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Gloriia Novikova
- Nash Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Evan Udine
- Nash Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Garrett Wong
- Nash Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Weijing Tang
- Department of Pathology, Stanford University, Palo Alto, USA
| | - Tushar Bhangale
- Department of Human Genetics, Genentech, South San Francisco, CA, USA
| | - Julie Hunkapiller
- Department of Human Genetics, Genentech, South San Francisco, CA, USA
| | - Gai Ayalon
- Neumora Therapeutics, South San Francisco, CA, USA
| | | | - Jonathan D Cherry
- Department of Pathology (Neuropathology), VA Medical Center, Boston University School of Medicine, Boston, MA, USA
| | - Etty P Cortes
- Department of Pathology, Neuropathology Brain Bank and Research CoRE, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place Box 1194, New York, NY, 10029, USA
- Nash Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Valeriy Y Borukov
- Department of Pathology, Neuropathology Brain Bank and Research CoRE, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place Box 1194, New York, NY, 10029, USA
- Nash Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ann C McKee
- Department of Pathology (Neuropathology), VA Medical Center, Boston University School of Medicine, Boston, MA, USA
| | - Thor D Stein
- Department of Pathology (Neuropathology), VA Medical Center, Boston University School of Medicine, Boston, MA, USA
| | - Jean-Paul Vonsattel
- Department of Pathology and Cell Biology, Department of Neurology, and the Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Medical Center, New York, NY, USA
| | - Andy F Teich
- Department of Pathology and Cell Biology, Department of Neurology, and the Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Medical Center, New York, NY, USA
| | - Marla Gearing
- Department of Pathology and Laboratory Medicine (Neuropathology) and Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Jonathan Glass
- Department of Pathology and Laboratory Medicine (Neuropathology) and Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Juan C Troncoso
- Department of Pathology, Division of Neuropathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Matthew P Frosch
- Department of Neurology and Pathology, Harvard Medical School and Massachusetts General Hospital, Charlestown, MA, USA
| | - Bradley T Hyman
- Department of Neurology and Pathology, Harvard Medical School and Massachusetts General Hospital, Charlestown, MA, USA
| | | | | | - Johannes Attems
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Margaret E Flanagan
- Department of Pathology (Neuropathology), Northwestern Cognitive Neurology and Alzheimer Disease Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Qinwen Mao
- Department of Pathology (Neuropathology), Northwestern Cognitive Neurology and Alzheimer Disease Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - M-Marsel Mesulam
- Department of Pathology (Neuropathology), Northwestern Cognitive Neurology and Alzheimer Disease Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Sandra Weintraub
- Department of Pathology (Neuropathology), Northwestern Cognitive Neurology and Alzheimer Disease Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Randy L Woltjer
- Department of Pathology, Oregon Health Sciences University, Portland, OR, USA
| | - Thao Pham
- Department of Pathology, Oregon Health Sciences University, Portland, OR, USA
| | - Julia Kofler
- Department of Pathology (Neuropathology), University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Julie A Schneider
- Departments of Pathology (Neuropathology) and Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Lei Yu
- Departments of Pathology (Neuropathology) and Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Dushyant P Purohit
- Department of Pathology, Neuropathology Brain Bank and Research CoRE, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place Box 1194, New York, NY, 10029, USA
- Department of Psychiatry, Alzheimer's Disease Research Center, James J. Peters VA Medical Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Vahram Haroutunian
- Nash Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Alzheimer's Disease Research Center, James J. Peters VA Medical Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Patrick R Hof
- Nash Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sam Gandy
- Department of Psychiatry, Alzheimer's Disease Research Center, James J. Peters VA Medical Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Neurology, Center for Cognitive Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Mary Sano
- Department of Psychiatry, Alzheimer's Disease Research Center, James J. Peters VA Medical Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Thomas G Beach
- Department of Neuropathology, Banner Sun Health Research Institute, Sun City, AZ, USA
| | - Wayne Poon
- Department of Neurology, Department of Epidemiology, Institute for Memory Impairments and Neurological Disorders, UC Irvine, Irvine, CA, USA
| | - Claudia H Kawas
- Department of Neurology, Department of Neurobiology and Behavior, Institute for Memory Impairments and Neurological Disorders, UC Irvine, Irvine, CA, USA
| | - María M Corrada
- Department of Neurology, Department of Epidemiology, Institute for Memory Impairments and Neurological Disorders, UC Irvine, Irvine, CA, USA
| | - Robert A Rissman
- Department of Neurosciences University of California and the Veterans Affairs San Diego Healthcare System, La Jolla, San Diego, California, USA
| | - Jeff Metcalf
- Department of Neurosciences University of California and the Veterans Affairs San Diego Healthcare System, La Jolla, San Diego, California, USA
| | - Sara Shuldberg
- Department of Neurosciences University of California and the Veterans Affairs San Diego Healthcare System, La Jolla, San Diego, California, USA
| | - Bahar Salehi
- Department of Neurosciences University of California and the Veterans Affairs San Diego Healthcare System, La Jolla, San Diego, California, USA
| | - Peter T Nelson
- Department of Pathology (Neuropathology) and Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY, USA
| | - John Q Trojanowski
- Center for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Edward B Lee
- Center for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - David A Wolk
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Corey T McMillan
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - C Dirk Keene
- Department of Laboratory Medicine and Pathology, University of f Medicine, Seattle, WA, USA
| | - Caitlin S Latimer
- Department of Laboratory Medicine and Pathology, University of f Medicine, Seattle, WA, USA
| | - Thomas J Montine
- Department of Laboratory Medicine and Pathology, University of f Medicine, Seattle, WA, USA
- Department of Pathology, Stanford University, Palo Alto, USA
| | - Gabor G Kovacs
- Laboratory Medicine Program, Krembil Brain Institute, University Health Network, Toronto, ON, Canada
- Tanz Centre for Research in Neurodegenerative Disease and Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
- Institute of Neurology, Medical University of Vienna, Vienna, Austria
| | - Mirjam I Lutz
- Institute of Neurology, Medical University of Vienna, Vienna, Austria
| | - Peter Fischer
- Department of Psychiatry, Danube Hospital, Vienna, Austria
| | - Richard J Perrin
- Department of Pathology and Immunology, Department of Neurology, Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Nigel J Cairns
- College of Medicine and Health, University of Exeter, Exeter, UK
| | - Erin E Franklin
- Department of Pathology and Immunology, Department of Neurology, Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Herbert T Cohen
- Departments of Medicine, Pathology, and Pharmacology, Boston University School of Medicine and Boston Medical Center, Boston, MA, USA
| | - Towfique Raj
- Nash Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Inma Cobos
- Department of Pathology, Stanford University, Palo Alto, USA
| | - Bess Frost
- Department of Cell Systems and Anatomy, Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, the Sam and Ann Barshop Institute for Longevity and Aging Studies, University of Texas Health San Antonio, San Antonio, TX, 78229, USA
| | - Alison Goate
- Nash Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Charles L White Iii
- Department of Pathology (Neuropathology), University of Texas Southwestern Medical School, Dallas, TX, USA
| | - John F Crary
- Department of Pathology, Neuropathology Brain Bank and Research CoRE, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Place Box 1194, New York, NY, 10029, USA.
- Nash Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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