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Wessels MHJ, Van Lierop ZYGJ, Noteboom S, Strijbis EMM, Heijst JA, Van Kempen ZLE, Moraal B, Barkhof F, Uitdehaag BMJ, Schoonheim MM, Killestein J, Teunissen CE. Serum glial fibrillary acidic protein in natalizumab-treated relapsing-remitting multiple sclerosis: An alternative to neurofilament light. Mult Scler 2023; 29:1229-1239. [PMID: 37530045 PMCID: PMC10503252 DOI: 10.1177/13524585231188625] [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: 04/21/2023] [Revised: 06/12/2023] [Accepted: 06/28/2023] [Indexed: 08/03/2023]
Abstract
BACKGROUND There is a need in Relapsing-Remitting Multiple Sclerosis (RRMS) treatment for biomarkers that monitor neuroinflammation, neurodegeneration, treatment response, and disease progression despite treatment. OBJECTIVE To assess the value of serum glial fibrillary acidic protein (sGFAP) as a biomarker for clinical disease progression and brain volume measurements in natalizumab-treated RRMS patients. METHODS sGFAP and neurofilament light (sNfL) were measured in an observational cohort of natalizumab-treated RRMS patients at baseline, +3, +12, and +24 months and at the last sample follow-up (median 5.17 years). sGFAP was compared between significant clinical progressors and non-progressors and related to magnetic resonance imaging (MRI)-derived volumes of the whole brain, ventricle, thalamus, and lesion. The relationship between sGFAP and sNfL was assessed. RESULTS A total of 88 patients were included, and 47.7% progressed. sGFAP levels at baseline were higher in patients with gadolinium enhancement (1.3-fold difference, p = 0.04) and decreased in 3 months of treatment (adj. p < 0.001). No association was found between longitudinal sGFAP levels and progressor status. sGFAP at baseline and 12 months was significantly associated with normalized ventricular (positively), thalamic (negatively), and lesion volumes (positively). Baseline and 12-month sGFAP predicted annualized ventricle volume change rate after 1 year of treatment. sGFAP correlated with sNfL at baseline (p < 0.001) and last sample follow-up (p < 0.001) but stabilized earlier. DISCUSSION sGFAP levels related to MRI markers of neuroinflammation and neurodegeneration.
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Affiliation(s)
- Mark HJ Wessels
- Mark HJ Wessels Department of Neurology, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, Vrije Universiteit Amsterdam, De Boelelaan 1118, 1081 HZ Amsterdam, The Netherlands.
| | - Zoë YGJ Van Lierop
- Department of Neurology, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Samantha Noteboom
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Eva MM Strijbis
- Department of Neurology, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Johannes A Heijst
- Department of Clinical Chemistry, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Zoé LE Van Kempen
- Department of Neurology, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Bastiaan Moraal
- Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; Queen Square Institute of Neurology, Centre for Medical Image Computing, University College London, London, UK
| | - Bernard MJ Uitdehaag
- Department of Neurology, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Joep Killestein
- Department of Neurology, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Charlotte E Teunissen
- Department of Clinical Chemistry, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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Bredesen DE, Toups K, Hathaway A, Gordon D, Chung H, Raji C, Boyd A, Hill BD, Hausman-Cohen S, Attarha M, Chwa WJ, Kurakin A, Jarrett M. Precision Medicine Approach to Alzheimer's Disease: Rationale and Implications. J Alzheimers Dis 2023; 96:429-437. [PMID: 37807782 PMCID: PMC10741308 DOI: 10.3233/jad-230467] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/28/2023] [Indexed: 10/10/2023]
Abstract
The neurodegenerative disease field has enjoyed extremely limited success in the development of effective therapeutics. One potential reason is the lack of disease models that yield accurate predictions and optimal therapeutic targets. Standard clinical trials have pre-determined a single treatment modality, which may be unrelated to the primary drivers of neurodegeneration. Recent proof-of-concept clinical trials using a precision medicine approach suggest a new model of Alzheimer's disease (AD) as a chronic innate encephalitis that creates a network insufficiency. Identifying and addressing the multiple potential contributors to cognitive decline for each patient may represent a more effective strategy. Here we review the rationale for a precision medicine approach in prevention and treatment of cognitive decline associated with AD. Results and implications from recent proof-of-concept clinical trials are presented. Randomized controlled trials, with much larger patient numbers, are likely to be significant to establishing precision medicine protocols as a standard of care for prevention and treatment of cognitive decline. Furthermore, combining this approach with the pharmaceutical approach offers the potential for enhanced outcomes. However, incorporating precision medicine approaches into everyday evaluation and care, as well as future clinical trials, would require fundamental changes in trial design, IRB considerations, funding considerations, laboratory evaluation, personalized treatment plans, treatment teams, and ultimately in reimbursement guidelines. Nonetheless, precision medicine approaches to AD, based on a novel model of AD pathophysiology, offer promise that has not been realized to date with monotherapeutic approaches.
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Affiliation(s)
- Dale E. Bredesen
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
| | - Kat Toups
- Bay Area Wellness, Walnut Creek, CA, USA
| | | | | | | | - Cyrus Raji
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Alan Boyd
- CNS Vital Signs, Morrisville, NC, USA
| | - Benjamin D. Hill
- Department of Psychology, University of South Alabama, Mobile, AL, USA
| | | | | | - Won Jong Chwa
- Department of Radiology, St. Louis University, St. Louis, MO, USA
| | - Alexei Kurakin
- Department of Neurology, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
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van Lierop ZY, Noteboom S, Steenwijk MD, van Dam M, Toorop AA, van Kempen ZLE, Moraal B, Barkhof F, Uitdehaag BM, Schoonheim MM, Teunissen CE, Killestein J. Neurofilament-light and contactin-1 association with long-term brain atrophy in natalizumab-treated relapsing-remitting multiple sclerosis. Mult Scler 2022; 28:2231-2242. [PMID: 36062492 DOI: 10.1177/13524585221118676] [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] [Indexed: 11/16/2022]
Abstract
BACKGROUND Despite highly effective treatment strategies for patients with relapsing-remitting multiple sclerosis (RRMS), long-term neurodegeneration and disease progression are often considerable. Accurate blood-based biomarkers that predict long-term neurodegeneration are lacking. OBJECTIVE To assess the predictive value of serum neurofilament-light (sNfL) and serum contactin-1 (sCNTN1) for long-term magnetic resonance imaging (MRI)-derived neurodegeneration in natalizumab-treated patients with RRMS. METHODS sNfL and sCNTN1 were measured in an observational cohort of natalizumab-treated patients with RRMS at baseline (first dose) and at 3 months, Year 1, Year 2, and last follow-up (median = 5.2 years) of treatment. Disability progression was quantified using "EDSS-plus" criteria. Neurodegeneration was measured by calculating annualized percentage brain, ventricular, and thalamic volume change (PBVC, VVC, and TVC, respectively). Linear regression analysis was performed to identify longitudinal predictors of neurodegeneration. RESULTS In total, 88 patients (age = 37 ± 9 years, 75% female) were included, of whom 48% progressed. Year 1 sNfL level (not baseline or 3 months) was associated with PBVC (standardized (std.) β = -0.26, p = 0.013), VVC (standardized β = 0.36, p < 0.001), and TVC (standardized β = -0.24, p = 0.02). For sCNTN1, only 3-month level was associated with VVC (standardized β = -0.31, p = 0.002). CONCLUSION Year 1 (but not baseline) sNfL level was predictive for long-term brain atrophy in patients treated with natalizumab. sCNTN1 level did not show a clear predictive value.
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Affiliation(s)
- Zoë Ygj van Lierop
- Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Samantha Noteboom
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Martijn D Steenwijk
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Maureen van Dam
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Alyssa A Toorop
- Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Zoé LE van Kempen
- Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Bastiaan Moraal
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, the Netherlands/Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, UK
| | - Bernard Mj Uitdehaag
- Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Charlotte E Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Joep Killestein
- Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, MS Center Amsterdam, Amsterdam Neuroscience, Amsterdam, the Netherlands
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Bigler ED, Skiles M, Wade BSC, Abildskov TJ, Tustison NJ, Scheibel RS, Newsome MR, Mayer AR, Stone JR, Taylor BA, Tate DF, Walker WC, Levin HS, Wilde EA. FreeSurfer 5.3 versus 6.0: are volumes comparable? A Chronic Effects of Neurotrauma Consortium study. Brain Imaging Behav 2021; 14:1318-1327. [PMID: 30511116 DOI: 10.1007/s11682-018-9994-x] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
Automated neuroimaging methods like FreeSurfer ( https://surfer.nmr.mgh.harvard.edu/ ) have revolutionized quantitative neuroimaging analyses. Such analyses provide a variety of metrics used for image quantification, including magnetic resonance imaging (MRI) volumetrics. With the release of FreeSurfer version 6.0, it is important to assess its comparability to the widely-used previous version 5.3. The current study used data from the initial 249 participants in the ongoing Chronic Effects of Neurotrauma Consortium (CENC) multicenter observational study to compare the volumetric output of versions 5.3 and 6.0 across various regions of interest (ROI). In the current investigation, the following ROIs were examined: total intracranial volume, total white matter volume, total ventricular volume, total gray matter volume, and right and left volumes for the thalamus, pallidum, putamen, caudate, amygdala and hippocampus. Absolute ROI volumes derived from FreeSurfer 6.0 differed significantly from those obtained using version 5.3. We also employed a clinically-based evaluation strategy to compare both versions in their prediction of age-mediated volume reductions (or ventricular increase) in the aforementioned structures. Statistical comparison involved both general linear modeling (GLM) and random forest (RF) methods, where cross-validation error was significantly higher using segmentations from FreeSurfer version 5.3 versus version 6.0 (GLM: t = 4.97, df = 99, p value = 2.706e-06; RF: t = 4.85, df = 99, p value = 4.424e-06). Additionally, the relative importance of ROIs used to predict age using RFs differed between FreeSurfer versions, indicating substantial differences in the two versions. However, from the perspective of correlational analyses, fitted regression lines and their slopes were similar between the two versions, regardless of version used. While absolute volumes are not interchangeable between version 5.3 and 6.0, ROI correlational analyses appear to yield similar results, suggesting the interchangeability of ROI volume for correlational studies.
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Affiliation(s)
- Erin D Bigler
- Psychology Department and Neuroscience Center, Brigham Young University, Provo, UT, 84602, USA.
| | - Marc Skiles
- Psychology Department and Neuroscience Center, Brigham Young University, Provo, UT, 84602, USA
| | - Benjamin S C Wade
- Missouri Institute of Mental Health, University of Missouri-St. Louis, St. Louis, MO, USA.,Imaging Genetics Center, University of Southern California, Marina del Rey, CA, USA.,Ahmanson-Lovelace Brain Mapping Center, Department of Neurology, UCLA, Los Angeles, CA, USA
| | - Tracy J Abildskov
- Psychology Department and Neuroscience Center, Brigham Young University, Provo, UT, 84602, USA
| | - Nick J Tustison
- Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, VA, USA
| | - Randall S Scheibel
- Michael DeBakey VA Medical Center and Baylor College of Medicine, Houston, TX, USA
| | - Mary R Newsome
- Michael DeBakey VA Medical Center and Baylor College of Medicine, Houston, TX, USA
| | | | - James R Stone
- Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, VA, USA
| | | | - David F Tate
- Missouri Institute of Mental Health, University of Missouri-St. Louis, St. Louis, MO, USA
| | | | - Harvey S Levin
- Michael DeBakey VA Medical Center and Baylor College of Medicine, Houston, TX, USA
| | - Elisabeth A Wilde
- Michael DeBakey VA Medical Center and Baylor College of Medicine, Houston, TX, USA.,University of Utah, Salt Lake City, UT, USA
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Ezzati A, Katz MJ, Lipton ML, Zimmerman ME, Lipton RB. Hippocampal volume and cingulum bundle fractional anisotropy are independently associated with verbal memory in older adults. Brain Imaging Behav 2016; 10:652-9. [PMID: 26424564 DOI: 10.1007/s11682-015-9452-y] [Citation(s) in RCA: 54] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
The objective of this study was to investigate the relationship of medial temporal lobe and posterior cingulate cortex (PCC) volumetrics as well as fractional anisotropy of the cingulum angular bundle (CAB) and the cingulum cingulate gyrus (CCG) bundle to performance on measures of verbal memory in non-demented older adults. The participants were 100 non-demented adults over the age of 70 years from the Einstein Aging Study. Volumetric data were estimated from T1-weighted images. The entire cingulum was reconstructed using diffusion tensor MRI and probabilistic tractography. Association between verbal episodic memory and MRI measures including volume of hippocampus (HIP), entorhinal cortex (ERC), PCC and fractional anisotropy of CAB and CCG bundle were modeled using linear regression. Relationships between atrophy of these structures and regional cingulum fractional anisotropy were also explored. Decreased HIP volume on the left and decreased fractional anisotropy of left CAB were associated with lower memory performance. Volume changes in ERC, PCC and CCG disruption were not associated with memory performance. In regression models, left HIP volume and left CAB-FA were each independently associated with episodic memory. The results suggest that microstructural changes in the left CAB and decreased left HIP volume independently influence episodic memory performance in older adults without dementia. The importance of these findings in age and illness-related memory decline require additional exploration.
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Zelko FA, Pardoe HR, Blackstone SR, Jackson GD, Berg AT. Regional brain volumes and cognition in childhood epilepsy: does size really matter? Epilepsy Res 2014; 108:692-700. [PMID: 24630049 DOI: 10.1016/j.eplepsyres.2014.02.003] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [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: 07/22/2013] [Revised: 01/13/2014] [Accepted: 02/02/2014] [Indexed: 11/26/2022]
Abstract
PURPOSE Recent studies have correlated neurocognitive function and regional brain volumes in children with epilepsy. We tested whether brain volume differences between children with and without epilepsy explained differences in neurocognitive function. METHODS The study sample included 108 individuals with uncomplicated non-syndromic epilepsy (NSE) and 36 healthy age- and gender-matched controls. Participants received a standardized cognitive battery. Whole brain T1-weighted MRI was obtained and volumes analyzed with FreeSurfer (TM). KEY FINDINGS Total brain volume (TBV) was significantly smaller in cases. After adjustment for TBV, cases had significantly larger regional grey matter volumes for total, frontal, parietal, and precentral cortex. Cases had poorer performance on neurocognitive indices of intelligence and variability of sustained attention. In cases, TBV showed small associations with intellectual indices of verbal and perceptual ability, working memory, and overall IQ. In controls, TBV showed medium associations with working memory and variability of sustained attention. In both groups, small associations were seen between some TBV-adjusted regional brain volumes and neurocognitive indices, but not in a consistent pattern. Brain volume differences did not account for cognitive differences between the groups. SIGNIFICANCE Patients with uncomplicated NSE have smaller brains than controls but areas of relative grey matter enlargement. That this relative regional enlargement occurs in the context of poorer overall neurocognitive functioning suggests that it is not adaptive. However, the lack of consistent associations between case-control differences in brain volumes and cognitive functioning suggests that brain volumes have limited explanatory value for cognitive functioning in childhood epilepsy.
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Affiliation(s)
- Frank A Zelko
- Department of Child and Adolescent Psychiatry, Ann and Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, United States; Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL, United States.
| | - Heath R Pardoe
- Florey Institute of Neuroscience and Mental Health, Melbourne, Australia; New York University School of Medicine, New York, NY, United States
| | - Sarah R Blackstone
- Department of Public Health, Northern Illinois University, DeKalb, IL, United States
| | - Graeme D Jackson
- Florey Institute of Neuroscience and Mental Health, Melbourne, Australia; Department of Medicine, University of Melbourne, Parkville, Victoria, Australia
| | - Anne T Berg
- Epilepsy Center, Ann and Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, United States; Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, IL, United States
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