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Katsumi Y, Eckbo R, Chapleau M, Wong B, McGinnis SM, Touroutoglou A, Dickerson BC, Putcha D. Greater baseline cortical atrophy in the dorsal attention network predicts faster clinical decline in Posterior Cortical Atrophy. Alzheimers Res Ther 2024; 16:262. [PMID: 39696378 DOI: 10.1186/s13195-024-01636-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2024] [Accepted: 12/02/2024] [Indexed: 12/20/2024]
Abstract
BACKGROUND Posterior Cortical Atrophy (PCA) is a clinical syndrome characterized by progressive visuospatial and visuoperceptual impairment. As the neurodegenerative disease progresses, patients lose independent functioning due to the worsening of initial symptoms and development of symptoms in other cognitive domains. The timeline of clinical progression is variable across patients, and the field currently lacks robust methods for prognostication. Here, evaluated the utility of MRI-based cortical atrophy as a predictor of longitudinal clinical decline in a sample of PCA patients. METHODS PCA patients were recruited through the Massachusetts General Hospital Frontotemporal Disorders Unit PCA Program. All patients had cortical thickness estimates from baseline MRI scans, which were used to predict longitudinal change in clinical impairment assessed by the CDR Sum-of-Boxes (CDR-SB) score. Multivariable linear regression was used to estimate the magnitude of cortical atrophy in PCA patients relative to a group of amyloid-negative cognitively unimpaired participants. Linear mixed-effects models were used to test hypotheses about the utility of baseline cortical atrophy for predicting longitudinal clinical decline. RESULTS Data acquired from 34 PCA patients (mean age = 65.41 ± 7.90, 71% females) and 24 controls (mean age = 67.34 ± 4.93, 50% females) were analyzed. 62% of the PCA patients were classified as having mild cognitive impairment (CDR 0.5) at baseline, with the rest having mild dementia (CDR 1). Each patient had at least one clinical follow-up, with the mean duration of 2.78 ± 1.62 years. Relative to controls, PCA patients showed prominent baseline atrophy in the posterior cortical regions, with the largest effect size observed in the visual network of the cerebral cortex. Cortical atrophy localized to the dorsal attention network, which supports higher-order visuospatial function, selectively predicted the rate of subsequent clinical decline. CONCLUSIONS These results demonstrate the utility of a snapshot measure of cortical atrophy of the dorsal attention network for predicting the rate of subsequent clinical decline in PCA. If replicated, this topographically-specific MRI-based biomarker could be useful as a clinical prognostication tool that facilitates personalized care planning.
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Affiliation(s)
- Yuta Katsumi
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02115, USA.
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, 02129, USA.
- Massachusetts Alzheimer's Disease Research Center, Massachusetts General Hospital, Charlestown, MA, 02129, USA.
| | - Ryan Eckbo
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Marianne Chapleau
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, 94158, USA
| | - Bonnie Wong
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02115, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Scott M McGinnis
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Alexandra Touroutoglou
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02115, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, 02129, USA
- Massachusetts Alzheimer's Disease Research Center, Massachusetts General Hospital, Charlestown, MA, 02129, USA
| | - Bradford C Dickerson
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02115, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02115, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, 02129, USA
- Massachusetts Alzheimer's Disease Research Center, Massachusetts General Hospital, Charlestown, MA, 02129, USA
| | - Deepti Putcha
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02115, USA.
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02115, USA.
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Katsumi Y, Eckbo R, Chapleau M, Wong B, McGinnis SM, Touroutoglou A, Dickerson BC, Putcha D. Greater baseline cortical atrophy in the dorsal attention network predicts faster clinical decline in Posterior Cortical Atrophy. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.10.15.24315270. [PMID: 39484250 PMCID: PMC11527058 DOI: 10.1101/2024.10.15.24315270] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/03/2024]
Abstract
Background and Objectives Posterior Cortical Atrophy (PCA) is a clinical syndrome characterized by progressive visuospatial and visuoperceptual impairment. As the neurodegenerative disease progresses, patients lose independent functioning due to the worsening of initial symptoms and development of symptoms in other cognitive domains. The timeline of clinical progression is variable across patients, and the field currently lacks robust methods for prognostication. Here, evaluated the utility of MRI-based cortical atrophy as a predictor of longitudinal clinical decline in a sample of PCA patients. Methods PCA patients were recruited through the Massachusetts General Hospital Frontotemporal Disorders Unit PCA Program. All patients had cortical thickness estimates from baseline MRI scans, which were used to predict longitudinal change in clinical impairment assessed by the CDR Sum-of-Boxes (CDR-SB) score. Multivariable linear regression was used to estimate the magnitude of cortical atrophy in PCA patients relative to a group of amyloid-negative cognitively unimpaired participants. Linear mixed-effects models were used to test hypotheses about the utility of baseline cortical atrophy for predicting longitudinal clinical decline. Results Data acquired from 34 PCA patients (mean age = 65.41 ± 7.90, 71% females) and 24 controls (mean age = 67.34 ± 4.93, 50% females) were analyzed. Sixty-two percent of the PCA patients were classified as having mild cognitive impairment (CDR 0.5) at baseline, with the rest having mild dementia (CDR 1). Each patient had at least one clinical follow-up, with the mean duration of 2.78 ± 1.62 years. Relative to controls, PCA patients showed prominent baseline atrophy in the posterior cortical regions, with the largest effect size observed in the visual network of the cerebral cortex. Cortical atrophy localized to the dorsal attention network, which supports higher-order visuospatial function, selectively predicted the rate of subsequent clinical decline. Discussion These results demonstrate the utility of a snapshot measure of cortical atrophy of the dorsal attention network for predicting the rate of subsequent clinical decline in PCA. If replicated, this topographically-specific MRI-based biomarker could be useful as a clinical prognostication tool that facilitates personalized care planning.
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Affiliation(s)
- Yuta Katsumi
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Ryan Eckbo
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Marianne Chapleau
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA 94158, USA
| | - Bonnie Wong
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02115, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Scott M McGinnis
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Alexandra Touroutoglou
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02115, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, 02129, USA
- Massachusetts Alzheimer's Disease Research Center, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
| | - Bradford C Dickerson
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02115, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02115, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, 02129, USA
- Massachusetts Alzheimer's Disease Research Center, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA 02129, USA
| | - Deepti Putcha
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02115, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02115, USA
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Stieger JR, Pinheiro-Chagas P, Fang Y, Li J, Lusk Z, Perry CM, Girn M, Contreras D, Chen Q, Huguenard JR, Spreng RN, Edlow BL, Wagner AD, Buch V, Parvizi J. Cross-regional coordination of activity in the human brain during autobiographical self-referential processing. Proc Natl Acad Sci U S A 2024; 121:e2316021121. [PMID: 39078679 PMCID: PMC11317603 DOI: 10.1073/pnas.2316021121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 06/10/2024] [Indexed: 07/31/2024] Open
Abstract
For the human brain to operate, populations of neurons across anatomical structures must coordinate their activity within milliseconds. To date, our understanding of such interactions has remained limited. We recorded directly from the hippocampus (HPC), posteromedial cortex (PMC), ventromedial/orbital prefrontal cortex (OFC), and the anterior nuclei of the thalamus (ANT) during two experiments of autobiographical memory processing that are known from decades of neuroimaging work to coactivate these regions. In 31 patients implanted with intracranial electrodes, we found that the presentation of memory retrieval cues elicited a significant increase of low frequency (LF < 6 Hz) activity followed by cross-regional phase coherence of this LF activity before select populations of neurons within each of the four regions increased high-frequency (HF > 70 Hz) activity. The power of HF activity was modulated by memory content, and its onset followed a specific temporal order of ANT→HPC/PMC→OFC. Further, we probed cross-regional causal effective interactions with repeated electrical pulses and found that HPC stimulations cause the greatest increase in LF-phase coherence across all regions, whereas the stimulation of any region caused the greatest LF-phase coherence between that particular region and ANT. These observations support the role of the ANT in gating, and the HPC in synchronizing, the activity of cortical midline structures when humans retrieve self-relevant memories of their past. Our findings offer a fresh perspective, with high temporal fidelity, about the dynamic signaling and underlying causal connections among distant regions when the brain is actively involved in retrieving self-referential memories from the past.
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Affiliation(s)
- James R. Stieger
- Laboratory of Behavioral and Cognitive Neuroscience, Human Intracranial Cognitive Electrophysiology Program, Stanford University School of Medicine, Stanford, CA94305
- Department of Neurology and Neurological Sciences, Stanford School of Medicine, Stanford, CA94305
| | - Pedro Pinheiro-Chagas
- Laboratory of Behavioral and Cognitive Neuroscience, Human Intracranial Cognitive Electrophysiology Program, Stanford University School of Medicine, Stanford, CA94305
| | - Ying Fang
- School of Psychology, South China Normal University, Guangzhou510631, China
| | - Jian Li
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA02129
| | - Zoe Lusk
- Laboratory of Behavioral and Cognitive Neuroscience, Human Intracranial Cognitive Electrophysiology Program, Stanford University School of Medicine, Stanford, CA94305
- Department of Neurology and Neurological Sciences, Stanford School of Medicine, Stanford, CA94305
| | - Claire M. Perry
- Laboratory of Behavioral and Cognitive Neuroscience, Human Intracranial Cognitive Electrophysiology Program, Stanford University School of Medicine, Stanford, CA94305
- Department of Neurology and Neurological Sciences, Stanford School of Medicine, Stanford, CA94305
| | - Manesh Girn
- Montreal Neurological Institute, Department Neurology and Neurosurgery, McGill University, Montreal, QCH3G 1A4, Canada
| | - Diego Contreras
- Department of Neuroscience, University of Pennsylvania, School of Medicine, Philadelphia, PA19104
| | - Qi Chen
- School of Psychology, South China Normal University, Guangzhou510631, China
| | - John R. Huguenard
- Department of Neurology and Neurological Sciences, Stanford School of Medicine, Stanford, CA94305
- Wu Tsai Neurosciences Institute, Stanford, CA94305
| | - R. Nathan Spreng
- Montreal Neurological Institute, Department Neurology and Neurosurgery, McGill University, Montreal, QCH3G 1A4, Canada
| | - Brian L. Edlow
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA02129
| | - Anthony D. Wagner
- Wu Tsai Neurosciences Institute, Stanford, CA94305
- Department of Psychology, Stanford University, Stanford, CA94305
| | - Vivek Buch
- Department of Neurosurgery, Stanford University, Stanford School of Medicine, Stanford, CA94305
| | - Josef Parvizi
- Laboratory of Behavioral and Cognitive Neuroscience, Human Intracranial Cognitive Electrophysiology Program, Stanford University School of Medicine, Stanford, CA94305
- Department of Neurology and Neurological Sciences, Stanford School of Medicine, Stanford, CA94305
- Wu Tsai Neurosciences Institute, Stanford, CA94305
- Department of Neurosurgery, Stanford University, Stanford School of Medicine, Stanford, CA94305
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