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Dong Y, Hou T, Li Y, Liu R, Cong L, Liu K, Liu C, Han X, Ren Y, Tang S, Winblad B, Blennow K, Wang Y, Du Y, Qiu C. Plasma Amyloid-β, Total Tau, and Neurofilament Light Chain Across the Alzheimer's Disease Clinical Spectrum: A Population-Based Study. J Alzheimers Dis 2023; 96:845-858. [PMID: 37899059 PMCID: PMC10657676 DOI: 10.3233/jad-230932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/06/2023] [Indexed: 10/31/2023]
Abstract
BACKGROUND Plasma biomarkers have emerged as a promising approach for characterizing pathophysiology in mild cognitive impairment (MCI) and Alzheimer's disease (AD). OBJECTIVE We aimed to characterize plasma biomarkers for AD and neurodegeneration across the AD clinical continuum, and to assess their ability to differentiate between AD, MCI, and normal cognition. METHODS This population-based study engaged 1,446 rural-dwelling older adults (age ≥60 years, 61.0% women) derived from MIND-China; of these, 402 were defined with MCI and 142 with AD. Plasma amyloid-β (Aβ), total tau (t-tau), and neurofilament light chain (NfL) concentrations were analyzed using the Simoa platform. Data were analyzed using linear and logistic regression models, and receiver operating characteristic (ROC) analysis. RESULTS Across the AD clinical spectrum, plasma Aβ40 and NfL increased, whereas Aβ42/Aβ40 ratio decreased. Plasma t-tau was higher in people with AD dementia than those with MCI or normal cognition. Plasma NfL outperformed other biomarkers in differentiating AD from normal cognition (area under the ROC curve [AUC] = 0.75), but all plasma biomarkers performed poorly to distinguish MCI from normal cognition (AUC <0.60). Plasma NfL in combination with age, sex, education, and APOE genotype yielded the AUC of 0.87 for differentiating between AD and normal cognition, 0.79 between AD and MCI, and 0.64 between MCI and normal cognition. CONCLUSIONS In this Chinese population, AD plasma biomarkers vary by age, sex, and APOE genotype. Plasma Aβ, t-tau, and NfL differ across the AD clinical spectrum, and plasma NfL appears to be superior to plasma Aβ and t-tau for defining the clinical spectrum.
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Affiliation(s)
- Yi Dong
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, P.R. China
- Institute of Brain Science and Brain-inspired Research, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong, P.R. China
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging in Shandong First Medical University, Ministry of Education of the People’s Republic of China, Jinan, Shandong, P.R. China
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, P.R. China
| | - Tingting Hou
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, P.R. China
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging in Shandong First Medical University, Ministry of Education of the People’s Republic of China, Jinan, Shandong, P.R. China
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, P.R. China
| | - Yuanjing Li
- Aging Research Center and Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet-Stockholm University, Stockholm, Sweden
| | - Rui Liu
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, P.R. China
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging in Shandong First Medical University, Ministry of Education of the People’s Republic of China, Jinan, Shandong, P.R. China
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, P.R. China
| | - Lin Cong
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, P.R. China
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging in Shandong First Medical University, Ministry of Education of the People’s Republic of China, Jinan, Shandong, P.R. China
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, P.R. China
| | - Keke Liu
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, P.R. China
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging in Shandong First Medical University, Ministry of Education of the People’s Republic of China, Jinan, Shandong, P.R. China
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, P.R. China
| | - Cuicui Liu
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, P.R. China
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging in Shandong First Medical University, Ministry of Education of the People’s Republic of China, Jinan, Shandong, P.R. China
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, P.R. China
| | - Xiaolei Han
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, P.R. China
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging in Shandong First Medical University, Ministry of Education of the People’s Republic of China, Jinan, Shandong, P.R. China
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, P.R. China
| | - Yifei Ren
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, P.R. China
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging in Shandong First Medical University, Ministry of Education of the People’s Republic of China, Jinan, Shandong, P.R. China
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, P.R. China
| | - Shi Tang
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, P.R. China
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging in Shandong First Medical University, Ministry of Education of the People’s Republic of China, Jinan, Shandong, P.R. China
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, P.R. China
| | - Bengt Winblad
- Department of Neurobiology, Care Sciences and Society, Division of Neurogeriatrics, Center for Alzheimer Research, Karolinska Institutet, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Huddinge, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Yongxiang Wang
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, P.R. China
- Institute of Brain Science and Brain-inspired Research, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong, P.R. China
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging in Shandong First Medical University, Ministry of Education of the People’s Republic of China, Jinan, Shandong, P.R. China
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, P.R. China
- Aging Research Center and Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet-Stockholm University, Stockholm, Sweden
| | - Yifeng Du
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, P.R. China
- Institute of Brain Science and Brain-inspired Research, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong, P.R. China
- Key Laboratory of Endocrine Glucose & Lipids Metabolism and Brain Aging in Shandong First Medical University, Ministry of Education of the People’s Republic of China, Jinan, Shandong, P.R. China
- Department of Neurology, Shandong Provincial Hospital, Shandong University, Jinan, Shandong, P.R. China
| | - Chengxuan Qiu
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, P.R. China
- Institute of Brain Science and Brain-inspired Research, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, Shandong, P.R. China
- Aging Research Center and Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet-Stockholm University, Stockholm, Sweden
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Green ZD, Kueck PJ, John CS, Burns JM, Morris JK. Blood Biomarkers Discriminate Cerebral Amyloid Status and Cognitive Diagnosis when Collected with ACD-A Anticoagulant. Curr Alzheimer Res 2023; 20:557-566. [PMID: 38047367 PMCID: PMC10792989 DOI: 10.2174/0115672050271523231111192725] [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: 08/14/2023] [Revised: 10/03/2023] [Accepted: 10/05/2023] [Indexed: 12/05/2023]
Abstract
BACKGROUND The development of biomarkers that are easy to collect, process, and store is a major goal of research on current Alzheimer's Disease (AD) and underlies the growing interest in plasma biomarkers. Biomarkers with these qualities will improve diagnosis and allow for better monitoring of therapeutic interventions. However, blood collection strategies have historically differed between studies. We examined the ability of various ultrasensitive plasma biomarkers to predict cerebral amyloid status in cognitively unimpaired individuals when collected using acid citrate dextrose (ACD). We then examined the ability of these biomarkers to predict cognitive impairment independent of amyloid status. METHODS Using a cross-sectional study design, we measured amyloid beta 42/40 ratio, pTau-181, neurofilament-light, and glial fibrillary acidic protein using the Quanterix Simoa® HD-X platform. To evaluate the discriminative accuracy of these biomarkers in determining cerebral amyloid status, we used both banked plasma and 18F-AV45 PET cerebral amyloid neuroimaging data from 140 cognitively unimpaired participants. We further examined their ability to discriminate cognitive status by leveraging data from 42 cognitively impaired older adults. This study is the first, as per our knowledge, to examine these specific tests using plasma collected using acid citrate dextrose (ACD), as well as the relationship with amyloid PET status. RESULTS Plasma AB42/40 had the highest AUC (0.833, 95% C.I. 0.767-0.899) at a cut-point of 0.0706 for discriminating between the two cerebral amyloid groups (sensitivity 76%, specificity 78.5%). Plasma NFL at a cut-point of 20.58pg/mL had the highest AUC (0.908, 95% CI 0.851- 0.966) for discriminating cognitive impairment (sensitivity 84.8%, specificity 89.9%). The addition of age and apolipoprotein e4 status did not improve the discriminative accuracy of these biomarkers. CONCLUSION Our results suggest that the Aβ42/40 ratio is useful in discriminating clinician-rated elevated cerebral amyloid status and that NFL is useful for discriminating cognitive impairment status. These findings reinforce the growing body of evidence regarding the general utility of these biomarkers and extend their utility to plasma collected in a non-traditional anticoagulant.
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Affiliation(s)
- Zachary D. Green
- Alzheimer’s Disease Research Center, University of Kansas, Kansas City, KS, 66160, United States
| | - Paul J. Kueck
- Alzheimer’s Disease Research Center, University of Kansas, Kansas City, KS, 66160, United States
| | - Casey S. John
- Alzheimer’s Disease Research Center, University of Kansas, Kansas City, KS, 66160, United States
| | - Jeffrey M. Burns
- Alzheimer’s Disease Research Center, University of Kansas, Kansas City, KS, 66160, United States
- Department of Neurology, University of Kansas Medical Center, Kansas City, KS, 66160, United States
| | - Jill K. Morris
- Alzheimer’s Disease Research Center, University of Kansas, Kansas City, KS, 66160, United States
- Department of Neurology, University of Kansas Medical Center, Kansas City, KS, 66160, United States
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153
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Shir D, Mielke MM, Hofrenning EI, Lesnick TG, Knopman DS, Petersen RC, Jack CR, Algeciras-Schimnich A, Vemuri P, Graff-Radford J. Associations of Neurodegeneration Biomarkers in Cerebrospinal Fluid with Markers of Alzheimer's Disease and Vascular Pathology. J Alzheimers Dis 2023; 92:887-898. [PMID: 36806507 PMCID: PMC10193844 DOI: 10.3233/jad-221015] [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] [Indexed: 02/19/2023]
Abstract
BACKGROUND The National Institute on Aging-Alzheimer's Association Research Framework proposes defining Alzheimer's disease by grouping imaging and fluid biomarkers by their respective pathologic processes. The AT(N) structure proposes several neurodegenerative fluid biomarkers (N) including total tau (t-tau), neurogranin (Ng), and neurofilament light chain (NfL). However, pathologic drivers influencing each biomarker remain unclear. OBJECTIVE To determine whether cerebrospinal fluid (CSF)-neurodegenerative biomarkers (N) map differentially to Alzheimer's disease pathology measured by Aβ42 (an indicator of amyloidosis, [A]), p-tau (an indicator of tau deposition, [T]), and MRI vascular pathology indicators (measured by white-matter integrity, infarcts, and microbleeds [V]). METHODS Participants were from Mayo Clinic Study of Aging (MCSA) with CSF measures of NfL, Ng, t-tau, Aβ42, and p-tau and available MRI brain imaging. Linear models assessed associations between CSF neurodegeneration (N) markers, amyloid markers (A), tau (T), and vascular pathology (V). RESULTS Participants (n = 408) had a mean age of 69.2±10.7; male, 217 (53.2%); cognitively unimpaired, 359 (88%). All three neurodegeneration biomarkers correlated with age (p < 0.001 for NfL and t-tau, p = 0.018 for Ng). Men had higher CSF-NfL levels; women had higher Ng (p < 0.001). NfL and t-tau levels correlated with infarcts (p = 0.009, p = 0.034 respectively); no biomarkers correlated with white-matter integrity. N biomarkers correlated with p-tau levels (T, p < 0.001). Higher Aβ42 levels associated with higher N-biomarker levels but only among cognitively unimpaired (A, p < 0.001). CONCLUSION The influence of vascular pathology in the general population on CSF (N) biomarkers is modest, with greater influence of infarcts than white-matter disruption. Neurodegeneration markers more closely correlated with tau than amyloid markers.
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Affiliation(s)
- Dror Shir
- Department of Neurology, Mayo Clinic, Rochester, Minnesota 55905, USA
| | - Michelle M. Mielke
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota 55905, USA
- Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, North Carolina, 27101
| | | | - Timothy G. Lesnick
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota 55905, USA
| | - David S. Knopman
- Department of Neurology, Mayo Clinic, Rochester, Minnesota 55905, USA
| | - Ronald C. Petersen
- Department of Neurology, Mayo Clinic, Rochester, Minnesota 55905, USA
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota 55905, USA
| | - Clifford R. Jack
- Department of Radiology, Mayo Clinic, Rochester, Minnesota 55905, USA
| | | | - Prashanthi Vemuri
- Department of Radiology, Mayo Clinic, Rochester, Minnesota 55905, USA
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154
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Luckett PH, Chen C, Gordon BA, Wisch J, Berman SB, Chhatwal JP, Cruchaga C, Fagan AM, Farlow MR, Fox NC, Jucker M, Levin J, Masters CL, Mori H, Noble JM, Salloway S, Schofield PR, Brickman AM, Brooks WS, Cash DM, Fulham MJ, Ghetti B, Jack CR, Vöglein J, Klunk WE, Koeppe R, Su Y, Weiner M, Wang Q, Marcus D, Koudelis D, Mathurin NJ, Cash L, Hornbeck R, Xiong C, Perrin RJ, Karch CM, Hassenstab J, McDade E, Morris JC, Benzinger TL, Bateman RJ, Ances BM. Biomarker clustering in autosomal dominant Alzheimer's disease. Alzheimers Dement 2023; 19:274-284. [PMID: 35362200 PMCID: PMC9525451 DOI: 10.1002/alz.12661] [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: 11/02/2021] [Revised: 02/20/2022] [Accepted: 02/22/2022] [Indexed: 01/18/2023]
Abstract
INTRODUCTION As the number of biomarkers used to study Alzheimer's disease (AD) continues to increase, it is important to understand the utility of any given biomarker, as well as what additional information a biomarker provides when compared to others. METHODS We used hierarchical clustering to group 19 cross-sectional biomarkers in autosomal dominant AD. Feature selection identified biomarkers that were the strongest predictors of mutation status and estimated years from symptom onset (EYO). Biomarkers identified included clinical assessments, neuroimaging, cerebrospinal fluid amyloid, and tau, and emerging biomarkers of neuronal integrity and inflammation. RESULTS Three primary clusters were identified: neurodegeneration, amyloid/tau, and emerging biomarkers. Feature selection identified amyloid and tau measures as the primary predictors of mutation status and EYO. Emerging biomarkers of neuronal integrity and inflammation were relatively weak predictors. DISCUSSION These results provide novel insight into our understanding of the relationships among biomarkers and the staging of biomarkers based on disease progression.
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Affiliation(s)
| | - Charlie Chen
- Washington University in St. Louis, St. Louis, Missouri, USA
| | - Brian A. Gordon
- Washington University in St. Louis, St. Louis, Missouri, USA
| | - Julie Wisch
- Washington University in St. Louis, St. Louis, Missouri, USA
| | | | - Jasmeer P. Chhatwal
- Brigham and Women’s Hospital, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Carlos Cruchaga
- Washington University in St. Louis, St. Louis, Missouri, USA
| | - Anne M. Fagan
- Washington University in St. Louis, St. Louis, Missouri, USA
| | | | - Nick C. Fox
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Mathias Jucker
- German Center for Neurodegenerative Disease, Tübingen, Germany
- Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Johannes Levin
- Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
- German Center for Neurodegenerative Diseases, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Colin L. Masters
- Florey Institute, The University of Melbourne, Parkville, Victoria, Australia
| | - Hiroshi Mori
- Osaka City University Medical School, Nagaoka Sutoku University, Abenoku, Osaka, Japan
| | - James M. Noble
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, G.H. Sergievsky Center, and Department of Neurology, Columbia University Irving Medical Center, New York, New York, USA
| | - Stephen Salloway
- Butler Hospital and Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Peter R. Schofield
- Neuroscience Research Australia, Randwick, New South Wales, Australia
- School of Medical Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | - Adam M. Brickman
- Department of Molecular Imaging, Royal Prince Alfred Hospital, Camperdown, New South Wales, Australia
- The University of Sydney, Sydney, New South Wales, Australia
| | - William S. Brooks
- Neuroscience Research Australia, Randwick, New South Wales, Australia
- School of Medical Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | - David M. Cash
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Michael J. Fulham
- Department of Molecular Imaging, Royal Prince Alfred Hospital, Camperdown, New South Wales, Australia
- The University of Sydney, Sydney, New South Wales, Australia
| | | | | | - Jonathan Vöglein
- Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | | | | | - Yi Su
- Banner Alzheimer Institute, Phoenix, Arizona, USA
| | - Michael Weiner
- University of California San Francisco, San Francisco, California, USA
- San Francisco Veterans Affairs Medical Center, San Francisco, California, USA
| | - Qing Wang
- Washington University in St. Louis, St. Louis, Missouri, USA
| | - Daniel Marcus
- Washington University in St. Louis, St. Louis, Missouri, USA
| | | | | | - Lisa Cash
- Washington University in St. Louis, St. Louis, Missouri, USA
| | - Russ Hornbeck
- Washington University in St. Louis, St. Louis, Missouri, USA
| | - Chengjie Xiong
- Washington University in St. Louis, St. Louis, Missouri, USA
| | | | | | | | - Eric McDade
- Washington University in St. Louis, St. Louis, Missouri, USA
| | - John C. Morris
- Washington University in St. Louis, St. Louis, Missouri, USA
| | | | | | - Beau M. Ances
- Washington University in St. Louis, St. Louis, Missouri, USA
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van Engelen MPE, Heijst H, Willemse EAJ, Oudega ML, Vermunt L, Scheltens P, Vijverberg EGB, Pijnenburg YAL, Teunissen CE. Urine as matrix for analysis of neurofilament light chain is not suitable to distinguish frontotemporal dementia from psychiatric diseases. Brain Commun 2023; 5:fcad120. [PMID: 37101834 PMCID: PMC10123396 DOI: 10.1093/braincomms/fcad120] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 11/28/2022] [Accepted: 04/11/2023] [Indexed: 04/28/2023] Open
Abstract
The clinical overlap of frontotemporal dementia and primary psychiatric diseases hampers diagnostic distinction, leading to frequent misdiagnosis and diagnostic delay. Neurofilament light chain has shown great potential in CSF and blood for the distinction of frontotemporal dementia from primary psychiatric diseases. Measurement of neurofilament light chain in urine would be even more patient-friendly. We aimed to test the performance of neurofilament light chain urine measurements for diagnostics in frontotemporal dementia and to assess their correlation with serum levels. Fifty-five subjects (n = 19 frontotemporal dementia, n = 19 primary psychiatric diseases and n = 17 controls) were included with available paired urine and serum samples. All subjects underwent standardized extensive diagnostic assessment. Samples were analysed with the ultrasensitive single molecule array neurofilament light chain assay. Neurofilament light chain group comparisons were performed adjusted for age, sex and geriatric depression scale. In the majority of the cohort, neurofilament light chain concentrations were not detectable in urine (n = 6 samples above lower limit of detection (0.038 pg/ml): n = 5 frontotemporal dementia, n = 1 primary psychiatric disease). The frequency of a detectable neurofilament light chain level in urine in the frontotemporal dementia group did not differ from psychiatric disorders (Fisher Exact-test P = 0.180). In the individuals with detectable urine neurofilament light chain values, there was no correlation between the urine and serum neurofilament light chain levels. As expected, serum neurofilament light chain levels were higher in frontotemporal dementia compared to primary psychiatric diseases and controls (P < 0.001), adjusted for age, sex and geriatric depression scale. Receiver operating characteristic curve analysis of serum neurofilament light chain of frontotemporal dementia versus primary psychiatric diseases showed an area under the curve of 0.978 95% confidence interval 0.941-1.000, P < 0.001. Urine is not suitable as a matrix for neurofilament light chain analysis and serum neurofilament light chain is still the most patient-friendly matrix for differentiation between frontotemporal dementia and primary psychiatric diseases.
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Affiliation(s)
- Marie-Paule E van Engelen
- Correspondence to: Marie-Paule Emilie van Engelen Alzheimercentrum Amsterdam, Amsterdam UMC, Locatie VUmc, Room PK-1 Z039 De Boelelaan 1118, 1091 HZ Amsterdam, Noord-Holland, The Netherlands E-mail:
| | - Hans Heijst
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, 1081 HV, Amsterdam, The Netherlands
| | - Eline A J Willemse
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, 1081 HV, Amsterdam, The Netherlands
- Department of Neurology, University Hospital Basel and University of Basel, 4031, Basel, Switzerland
| | - Mardien L Oudega
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, Noord-Holland 1081 HZ, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, Noord-Holland 1081 HV, The Netherlands
- GGZ inGeest Specialized Mental Health Care, Location De Nieuwe Valerius, Amsterdam, Noord-Holland 1070 BB, The Netherlands
- Department of Psychiatry, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam, Noord-Holland 1081 HV, The Netherlands
- Amsterdam Neuroscience, Mood Anxiety Psychosis Sleep & Stress program, Amsterdam, Noord-Holland 1081 HV, The Netherlands
| | - Lisa Vermunt
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, Noord-Holland 1081 HV, The Netherlands
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, 1081 HV, Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, Noord-Holland 1081 HZ, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, Noord-Holland 1081 HV, The Netherlands
| | - Everard G B Vijverberg
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, Noord-Holland 1081 HZ, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, Noord-Holland 1081 HV, The Netherlands
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156
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Zetterberg H, Teunissen C, van Swieten J, Kuhle J, Boxer A, Rohrer JD, Mitic L, Nicholson AM, Pearlman R, McCaughey SM, Tatton N. The role of neurofilament light in genetic frontotemporal lobar degeneration. Brain Commun 2023; 5:fcac310. [PMID: 36694576 PMCID: PMC9866262 DOI: 10.1093/braincomms/fcac310] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 09/26/2022] [Accepted: 11/23/2022] [Indexed: 11/27/2022] Open
Abstract
Genetic frontotemporal lobar degeneration caused by autosomal dominant gene mutations provides an opportunity for targeted drug development in a highly complex and clinically heterogeneous dementia. These neurodegenerative disorders can affect adults in their middle years, progress quickly relative to other dementias, are uniformly fatal and have no approved disease-modifying treatments. Frontotemporal dementia, caused by mutations in the GRN gene which encodes the protein progranulin, is an active area of interventional drug trials that are testing multiple strategies to restore progranulin protein deficiency. These and other trials are also examining neurofilament light as a potential biomarker of disease activity and disease progression and as a therapeutic endpoint based on the assumption that cerebrospinal fluid and blood neurofilament light levels are a surrogate for neuroaxonal damage. Reports from genetic frontotemporal dementia longitudinal studies indicate that elevated concentrations of blood neurofilament light reflect disease severity and are associated with faster brain atrophy. To better inform patient stratification and treatment response in current and upcoming clinical trials, a more nuanced interpretation of neurofilament light as a biomarker of neurodegeneration is now required, one that takes into account its relationship to other pathophysiological and topographic biomarkers of disease progression from early presymptomatic to later clinically symptomatic stages.
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Affiliation(s)
- Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden.,Clinical Chemistry, Sahlgrenska University Hospital, Gothenburg, Sweden.,Dementia Research Institute, University College London, London, UK.,DRI Fluid Biomarker Laboratory, Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Charlotte Teunissen
- Department of Clinical Chemistry, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - John van Swieten
- Department of Neurology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Jens Kuhle
- Department of Clinical Research, Department of Neurology, Department of Biomedicine, Multiple Sclerosis Centre, University Hospital Basel, University of Basel, Basel, Switzerland
| | - Adam Boxer
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, CA, USA
| | - Jonathan D Rohrer
- Queen Square UCL Institute of Neurology, Dementia Research Centre, UK Dementia Research Institute, University College London, London, UK
| | - Laura Mitic
- Department of Neurology, Memory and Aging Center, University of California San Francisco, San Francisco, CA, USA.,The Bluefield Project to Cure FTD, San Francisco, CA, USA
| | - Alexandra M Nicholson
- The Bluefield Project to Cure FTD, San Francisco, CA, USA.,Department of Neuroscience, Mayo Clinic Jacksonville, Jacksonville, FL, USA
| | | | | | - Nadine Tatton
- Medical Affairs, Alector, Inc., South San Francisco, CA, USA
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Shim KH, Kang MJ, Youn YC, An SSA, Kim S. Alpha-synuclein: a pathological factor with Aβ and tau and biomarker in Alzheimer's disease. Alzheimers Res Ther 2022; 14:201. [PMID: 36587215 PMCID: PMC9805257 DOI: 10.1186/s13195-022-01150-0] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 12/20/2022] [Indexed: 01/01/2023]
Abstract
BACKGROUND Alpha-synuclein (α-syn) is considered the main pathophysiological protein component of Lewy bodies in synucleinopathies. α-Syn is an intrinsically disordered protein (IDP), and several types of structural conformations have been reported, depending on environmental factors. Since IDPs may have distinctive functions depending on their structures, α-syn can play different roles and interact with several proteins, including amyloid-beta (Aβ) and tau, in Alzheimer's disease (AD) and other neurodegenerative disorders. MAIN BODY In previous studies, α-syn aggregates in AD brains suggested a close relationship between AD and α-syn. In addition, α-syn directly interacts with Aβ and tau, promoting mutual aggregation and exacerbating the cognitive decline. The interaction of α-syn with Aβ and tau presented different consequences depending on the structural forms of the proteins. In AD, α-syn and tau levels in CSF were both elevated and revealed a high positive correlation. Especially, the CSF α-syn concentration was significantly elevated in the early stages of AD. Therefore, it could be a diagnostic marker of AD and help distinguish AD from other neurodegenerative disorders by incorporating other biomarkers. CONCLUSION The overall physiological and pathophysiological functions, structures, and genetics of α-syn in AD are reviewed and summarized. The numerous associations of α-syn with Aβ and tau suggested the significance of α-syn, as a partner of the pathophysiological roles in AD. Understanding the involvements of α-syn in the pathology of Aβ and tau could help address the unresolved issues of AD. In particular, the current status of the CSF α-syn in AD recommends it as an additional biomarker in the panel for AD diagnosis.
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Affiliation(s)
- Kyu Hwan Shim
- grid.256155.00000 0004 0647 2973Department of Bionano Technology, Gachon University, Seongnam-Si, Gyeonggi-Do Republic of Korea
| | - Min Ju Kang
- Department of Neurology, Veterans Health Service Medical Center, Veterans Medical Research Institute, Seoul, Republic of Korea
| | - Young Chul Youn
- grid.411651.60000 0004 0647 4960Department of Neurology, Chung-Ang University Hospital, Seoul, Republic of Korea
| | - Seong Soo A. An
- grid.256155.00000 0004 0647 2973Department of Bionano Technology, Gachon University, Seongnam-Si, Gyeonggi-Do Republic of Korea
| | - SangYun Kim
- grid.412480.b0000 0004 0647 3378Department of Neurology, Seoul National University Bundang Hospital and Seoul National University College of Medicine, Seongnam-Si, Gyeonggi-Do Republic of Korea
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158
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Sheng ZH, Ma LZ, Liu JY, Ou YN, Zhao B, Ma YH, Tan L. Cerebrospinal fluid neurofilament dynamic profiles predict cognitive progression in individuals with de novo Parkinson's disease. Front Aging Neurosci 2022; 14:1061096. [PMID: 36589544 PMCID: PMC9802677 DOI: 10.3389/fnagi.2022.1061096] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Accepted: 11/24/2022] [Indexed: 12/23/2022] Open
Abstract
Background Neurofilament light chain protein (NfL) in cerebrospinal fluid (CSF) reflects the severity of neurodegeneration, with its altered concentrations discovered in Parkinson's disease (PD) and Parkinson's disease dementia (PD-D). Objective To determine whether CSF NfL, a promising biomarker of neuronal/axonal damage, can be used to monitor cognitive progression in de novo Parkinson's disease and predict future cognitive decline. Methods A total of 259 people were recruited in this study, including 85 healthy controls (HC) and 174 neonatal PD patients from the Parkinson's Progression Markers Initiative (PPMI). Multiple linear regression and linear mixed effects models were used to examine the associations of baseline/longitudinal CSF NfL with cognitive decline and other CSF biomarkers. Kaplan-Meier analysis and log-rank test were used to compare the cumulative probability risk of cognition progression during the follow-up. Multivariate cox regression was used to detect cognitive progression in de novo PD. Results We found PD patients with mild cognitive impairment (PD-MCI) was higher than with normal cognition (PD-NC) in terms of CSF NfL baseline levels (p = 0.003) and longitudinal increase rate (p = 0.034). Both baseline CSF NfL and its rate of change predicted measurable cognitive decline in de novo PD (MoCA, β = -0.010, p = 0.011; β = -0.0002, p < 0.001, respectively). The predictive effects in de novo PD patients aged >65, male, ill-educated (<13 years) and without carrying Apolipoprotein E ε4 (APOE ε4) seemed to be more obvious and reflected in more domains investigated. We also observed that CSF NfL levels predicted progression in de novo PD patients with different cognitive diagnosis and amyloid status. After an average follow-up of 6.66 ± 2.54 years, higher concentration above the median of baseline CSF NfL was associated with a future high risk of PD with dementia (adjusted HR 2.82, 95% CI: 1.11-7.20, p = 0.030). Conclusion Our results indicated that CSF NfL is a promising prognostic predictor of PD, and its concentration and dynamics can monitor the severity and progression of cognitive decline in de novo PD patients.
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Cutellè C, Balducci C, Cereda D, Fusco ML, Iacobucci D, Perugini J, Pirro F, Brivio R, Bernasconi DP, Ferrarese C, Frigo M, Cavaletti G. K index utility as diagnostic and prognostic biomarker in the assessment of patients with suspected Multiple Sclerosis. J Neuroimmunol 2022; 373:577992. [PMID: 36335693 DOI: 10.1016/j.jneuroim.2022.577992] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 09/02/2022] [Accepted: 10/23/2022] [Indexed: 11/06/2022]
Abstract
The aim of the present study is to evaluate the composite role of k index in the initial assessment of Multiple Sclerosis (MS) patients and to select useful cut-offs exportable in clinical practice. We analysed CSF/serum samples of 140 patients and followed-up the CIS/MS subgroup for 7 years. Our results suggest κ index as a quantitative diagnostic and prognostic biomarker in MS, significantly associated to baseline lesion load and to successive clinical course. We propose k index ≥106 as a prognostic cut-off to select patients at major risk of relapse, potentially influencing initial therapeutic decisions.
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Affiliation(s)
- Claudia Cutellè
- Neuroimmunology Unit and Department of Neurology, San Gerardo Hospital, Monza, Italy; Experimental Neurology Unit, School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy; NeuroMI (Milan Center for Neuroscience), Milan, Italy.
| | - Claudia Balducci
- Neuroimmunology Unit and Department of Neurology, San Gerardo Hospital, Monza, Italy
| | - Diletta Cereda
- Neuroimmunology Unit and Department of Neurology, San Gerardo Hospital, Monza, Italy
| | - Maria Letizia Fusco
- Neuroimmunology Unit and Department of Neurology, San Gerardo Hospital, Monza, Italy
| | - Davide Iacobucci
- Neuroimmunology Unit and Department of Neurology, San Gerardo Hospital, Monza, Italy; Experimental Neurology Unit, School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
| | - Jacopo Perugini
- Neuroimmunology Unit and Department of Neurology, San Gerardo Hospital, Monza, Italy; Experimental Neurology Unit, School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
| | - Fiammetta Pirro
- Neuroimmunology Unit and Department of Neurology, San Gerardo Hospital, Monza, Italy; Experimental Neurology Unit, School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
| | - Rinaldo Brivio
- Biochemistry Laboratory, San Gerardo Hospital, Monza, Italy
| | - Davide Paolo Bernasconi
- Bicocca Bioinformatics Biostatistics and Bioimaging Centre - B4, School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
| | - Carlo Ferrarese
- Neuroimmunology Unit and Department of Neurology, San Gerardo Hospital, Monza, Italy; Experimental Neurology Unit, School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy; NeuroMI (Milan Center for Neuroscience), Milan, Italy
| | - Maura Frigo
- Neuroimmunology Unit and Department of Neurology, San Gerardo Hospital, Monza, Italy
| | - Guido Cavaletti
- Neuroimmunology Unit and Department of Neurology, San Gerardo Hospital, Monza, Italy; Experimental Neurology Unit, School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy; NeuroMI (Milan Center for Neuroscience), Milan, Italy
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Kosa P, Barbour C, Varosanec M, Wichman A, Sandford M, Greenwood M, Bielekova B. Molecular models of multiple sclerosis severity identify heterogeneity of pathogenic mechanisms. Nat Commun 2022; 13:7670. [PMID: 36509784 PMCID: PMC9744737 DOI: 10.1038/s41467-022-35357-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Accepted: 11/29/2022] [Indexed: 12/14/2022] Open
Abstract
While autopsy studies identify many abnormalities in the central nervous system (CNS) of subjects dying with neurological diseases, without their quantification in living subjects across the lifespan, pathogenic processes cannot be differentiated from epiphenomena. Using machine learning (ML), we searched for likely pathogenic mechanisms of multiple sclerosis (MS). We aggregated cerebrospinal fluid (CSF) biomarkers from 1305 proteins, measured blindly in the training dataset of untreated MS patients (N = 129), into models that predict past and future speed of disability accumulation across all MS phenotypes. Healthy volunteers (N = 24) data differentiated natural aging and sex effects from MS-related mechanisms. Resulting models, validated (Rho 0.40-0.51, p < 0.0001) in an independent longitudinal cohort (N = 98), uncovered intra-individual molecular heterogeneity. While candidate pathogenic processes must be validated in successful clinical trials, measuring them in living people will enable screening drugs for desired pharmacodynamic effects. This will facilitate drug development making, it hopefully more efficient and successful.
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Affiliation(s)
- Peter Kosa
- grid.94365.3d0000 0001 2297 5165Neuroimmunological Diseases Section, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD USA
| | - Christopher Barbour
- grid.94365.3d0000 0001 2297 5165Neuroimmunological Diseases Section, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD USA
| | - Mihael Varosanec
- grid.94365.3d0000 0001 2297 5165Neuroimmunological Diseases Section, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD USA
| | - Alison Wichman
- grid.94365.3d0000 0001 2297 5165Neuroimmunological Diseases Section, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD USA
| | - Mary Sandford
- grid.94365.3d0000 0001 2297 5165Neuroimmunological Diseases Section, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD USA
| | - Mark Greenwood
- grid.41891.350000 0001 2156 6108Department of Mathematical Sciences, Montana State University, Bozeman, MT USA
| | - Bibiana Bielekova
- grid.94365.3d0000 0001 2297 5165Neuroimmunological Diseases Section, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD USA
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Zjukovskaja C, Larsson A, Cherif H, Kultima K, Burman J. Biomarkers of demyelination and axonal damage are decreased after autologous hematopoietic stem cell transplantation for multiple sclerosis. Mult Scler Relat Disord 2022; 68:104210. [PMID: 36257151 DOI: 10.1016/j.msard.2022.104210] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 09/13/2022] [Accepted: 10/01/2022] [Indexed: 11/27/2022]
Abstract
BACKGROUND Autologous hematopoietic stem cell transplantation (aHSCT) has seen increased use for relapsing-remitting multiple sclerosis (RRMS) in recent years. It is considered one of the most effective treatments for RRMS and has been associated with improvement in disability and prolonged remission. This suggests that the tissue-injuring disease process may have been altered by aHSCT. To assess whether this hypothesis is correct, we performed a study of three commonly used cerebrospinal fluid biomarkers of tissue damage. METHODS In this single center study, 63 patients treated with aHSCT at Uppsala University Hospital between January 1st 2012 and January 31st 2019 were screened for participation. A control group consisting of volunteers without neurologic disease were included as a reference. Cerebrospinal fluid concentrations of neurofilament light (NFL), myelin basic protein (MBP) and glial acidic fibrillary protein (GFAp) were determined using ELISA and a multiplex proteomics platform from Meso Scale Discovery. RESULTS Forty-three patients with a mean age of 31 and a median follow-up time of 3.9 years were included. Their median baseline expanded disability status scale (EDSS) score was 3.5 and the annualized relapse rate in the year preceding aHSCT was 1.6. At baseline the proportion of patients with values above the upper limit of normal was 67% for NFL, 63% for MBP and 16% for GFAp. At 5-year follow-up, the proportion of patients with values above the upper limit of normal was 12% for NFL, 12% for MBP and 25% for GFAp. The mean concentration of NFL decreased from 920 pg/mL at baseline to 270 pg/mL at 5-year follow-up (p < 0.001); MBP decreased from 1500 to 680 pg/mL (p < 0.001); whereas the mean concentration of GFAp was unchanged. CONCLUSION In a majority of patients, biomarkers of demyelination and axonal damage reached normal values within five years from treatment with aHSCT.
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Affiliation(s)
| | - Anders Larsson
- Department of Medical Sciences, Uppsala University, Uppsala SE-751 85, Sweden
| | - Honar Cherif
- Department of Medical Sciences, Uppsala University, Uppsala SE-751 85, Sweden
| | - Kim Kultima
- Department of Medical Sciences, Uppsala University, Uppsala SE-751 85, Sweden
| | - Joachim Burman
- Department of Medical Sciences, Uppsala University, Uppsala SE-751 85, Sweden.
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Loveland PM, Watson R, Yassi N. Diagnostic challenges for dementia in Australia: are blood-based biomarkers the solution? Intern Med J 2022; 52:2181-2185. [PMID: 37133369 PMCID: PMC10946735 DOI: 10.1111/imj.15973] [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: 03/15/2022] [Accepted: 09/24/2022] [Indexed: 12/23/2022]
Abstract
The burden of dementia will increase as the Australian population ages and grows in coming decades. Early and accurate diagnosis remains challenging, and disproportionately so for particular groups, including rural communities. Recent advances in technology, however, now allow reliable measurement of blood biomarkers that could improve diagnosis in a range of settings. We discuss the most promising biomarker candidates for translation into clinical practice and research in the near future.
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Affiliation(s)
- Paula M. Loveland
- Population Health and Immunity DivisionThe Walter and Eliza Hall Institute of Medical ResearchMelbourneVictoriaAustralia
- Department of Medical BiologyThe University of MelbourneMelbourneVictoriaAustralia
- Department of Medicine, The Royal Melbourne HospitalUniversity of MelbourneMelbourneVictoriaAustralia
| | - Rosie Watson
- Population Health and Immunity DivisionThe Walter and Eliza Hall Institute of Medical ResearchMelbourneVictoriaAustralia
- Department of Medical BiologyThe University of MelbourneMelbourneVictoriaAustralia
- Department of Medicine, The Royal Melbourne HospitalUniversity of MelbourneMelbourneVictoriaAustralia
| | - Nawaf Yassi
- Population Health and Immunity DivisionThe Walter and Eliza Hall Institute of Medical ResearchMelbourneVictoriaAustralia
- Department of Medical BiologyThe University of MelbourneMelbourneVictoriaAustralia
- Department of Medicine, The Royal Melbourne HospitalUniversity of MelbourneMelbourneVictoriaAustralia
- Department of Neurology, Melbourne Brain Centre at The Royal Melbourne HospitalUniversity of MelbourneMelbourneVictoriaAustralia
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Wesenhagen KEJ, Tijms BM, Boonkamp L, Hoede PL, Goossens J, Dewit N, Scheltens P, Vanmechelen E, Visser PJ, Teunissen CE. P-tau subgroups in AD relate to distinct amyloid production and synaptic integrity profiles. Alzheimers Res Ther 2022; 14:95. [PMID: 35841015 PMCID: PMC9288016 DOI: 10.1186/s13195-022-01038-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 06/22/2022] [Indexed: 11/17/2022]
Abstract
Background We previously identified four Alzheimer’s disease (AD) subgroups with increasingly higher cerebrospinal fluid (CSF) levels of tau phosphorylated at threonine 181 (p-tau). These subgroups included individuals across the cognitive spectrum, suggesting p-tau subgroups could reflect distinct biological changes in AD, rather than disease severity. Therefore, in the current study, we further investigated which potential processes may be related with p-tau subgroups, by comparing individuals on CSF markers for presynaptic structure [vesicle-associated membrane protein 2 (VAMP2)], postsynaptic structure [neurogranin (NRGN)], axonal damage [neurofilament light (NfL)], and amyloid production [beta-secretase 1 (BACE1) and amyloid-beta 1–40 (Aβ40)]. Methods We selected 348 amyloid-positive (A+) individuals (53 preclinical, 102 prodromal, 193 AD dementia) and 112 amyloid-negative (A−) cognitively normal (CN) individuals from the Amsterdam Dementia Cohort (ADC). Individuals were labeled according to their p-tau subgroup (subgroup 1: p-tau ≤ 56 pg/ml; subgroup 2: 57–96 pg/ml; subgroup 3: 97–159 pg/ml; subgroup 4: > 159 pg/ml). CSF protein levels were measured with ELISA (NRGN, BACE1, Aβ40, NfL) or single-molecule array (Simoa) (VAMP2). We tested whether protein levels differed between the p-tau subgroups within A+ individuals with linear models corrected for age and sex and whether disease stage influenced these relationships. Results Among A+ individuals, higher p-tau subgroups showed a higher percentage of AD dementia [subgroup 1: n = 41/94 (44%); subgroup 2: n = 81/147 (55%); subgroup 3: n = 59/89 (66%); subgroup 4: n = 7/11 (64%)]. Relative to controls, subgroup 1 showed reduced CSF levels of BACE1, Aβ40, and VAMP2 and higher levels of NfL. Subgroups 2 to 4 showed gradually increased CSF levels of all measured proteins, either across the first three (NfL and Aβ40) or across all subgroups (VAMP2, NRGN, BACE1). The associations did not depend on the clinical stage (interaction p-values ranging between 0.19 and 0.87). Conclusions The results suggest that biological heterogeneity in p-tau levels in AD is related to amyloid metabolism and synaptic integrity independent of clinical stage. Biomarkers reflecting amyloid metabolism and synaptic integrity may be useful outcome measures in clinical trials targeting tau pathology.
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Hansson O, Edelmayer RM, Boxer AL, Carrillo MC, Mielke MM, Rabinovici GD, Salloway S, Sperling R, Zetterberg H, Teunissen CE. The Alzheimer's Association appropriate use recommendations for blood biomarkers in Alzheimer's disease. Alzheimers Dement 2022; 18:2669-2686. [PMID: 35908251 PMCID: PMC10087669 DOI: 10.1002/alz.12756] [Citation(s) in RCA: 196] [Impact Index Per Article: 98.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 06/28/2022] [Accepted: 07/08/2022] [Indexed: 01/31/2023]
Abstract
Blood-based markers (BBMs) have recently shown promise to revolutionize the diagnostic and prognostic work-up of Alzheimer's disease (AD), as well as to improve the design of interventional trials. Here we discuss in detail further research needed to be performed before widespread use of BBMs. We already now recommend use of BBMs as (pre-)screeners to identify individuals likely to have AD pathological changes for inclusion in trials evaluating disease-modifying therapies, provided the AD status is confirmed with positron emission tomography (PET) or cerebrospinal fluid (CSF) testing. We also encourage studying longitudinal BBM changes in ongoing as well as future interventional trials. However, BBMs should not yet be used as primary endpoints in pivotal trials. Further, we recommend to cautiously start using BBMs in specialized memory clinics as part of the diagnostic work-up of patients with cognitive symptoms and the results should be confirmed whenever possible with CSF or PET. Additional data are needed before use of BBMs as stand-alone diagnostic AD markers, or before considering use in primary care.
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Affiliation(s)
- Oskar Hansson
- ClinicalMemory Research UnitDepartment of Clinical Sciences MalmöLund UniversityMalmöSweden
- Memory ClinicSkåne University HospitalMalmöSweden
| | | | - Adam L. Boxer
- Department of NeurologyUniversity of California San FranciscoMemory and Aging CenterSan FranciscoCaliforniaUSA
| | | | - Michelle M. Mielke
- Department of Epidemiology and PreventionWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Gil D. Rabinovici
- Department of NeurologyUniversity of California San FranciscoMemory and Aging CenterSan FranciscoCaliforniaUSA
| | - Stephen Salloway
- Departments of Neurology and PsychiatryAlpert Medical School of Brown UniversityProvidenceRhode IslandUSA
| | - Reisa Sperling
- Centerfor Alzheimer Research and TreatmentBrigham and Women's Hospital, Massachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Henrik Zetterberg
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and PhysiologyThe Sahlgrenska Academy at the University of GothenburgMölndalSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
- Department of Neurodegenerative DiseaseUCL Institute of NeurologyQueen SquareLondonUK
- UK Dementia Research Institute at UCLLondonUK
- Hong Kong Center for Neurodegenerative DiseasesClear Water BayHong KongPeople's Republic of China
| | - Charlotte E. Teunissen
- NeurochemistryLaboratoryDepartment of Clinical ChemistryAmsterdam University Medical CentersVrije UniversiteitAmsterdam NeuroscienceAmsterdamthe Netherlands
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Pagonabarraga J, Pérez-González R, Bejr-Kasem H, Marín-Lahoz J, Horta-Barba A, Martinez-Horta S, Aracil-Bolaños I, Sampedro F, Campolongo A, Rivas E, Puig-Davi A, Ruiz-Barrios I, Pérez-Pérez J, Pascual-Sedano B, Kulisevsky J. Dissociable contribution of plasma NfL and p-tau181 to cognitive impairment in Parkinson's disease. Parkinsonism Relat Disord 2022; 105:132-138. [PMID: 35752549 DOI: 10.1016/j.parkreldis.2022.05.020] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Revised: 04/13/2022] [Accepted: 05/24/2022] [Indexed: 01/09/2023]
Abstract
BACKGROUND Cognitive dysfunction is a disabling complication in Parkinson's disease (PD). Accuracy of diagnosis of mild cognitive impairment in PD (PD-MCI) depends on the tests performed, which limits results generalization. Blood-based biomarkers could provide additional objective information for PD-MCI diagnosis and progression. Blood neurofilament light chain (NfL), a marker of neuronal injury, has shown good performance for PD disease stratification and progression. While NfL is not disease-specific, phosphorylated-tau at threonine-181 (p-tau181) in blood is a highly specific marker of concomitant brain amyloid-β and tau pathology. METHODS We investigated the potential of plasma NfL and p-tau181 levels as markers of cognitive impairment in a prospective cohort of 109 PD patients with and without PD-MCI (age 68.1 ± 7 years, education 12.2± 5 years), and 40 comparable healthy controls. After a follow-up of 4 years, we evaluated their predictive value for progression to dementia. RESULTS Although NfL and p-tau181 levels were significantly increased in PD compared with healthy controls, only NfL levels were significantly higher in PD-MCI compared with PD with normal cognition (PD-NC) at baseline. After a follow-up of 4 years, only NfL predicted progression to dementia (HR 1.23, 95% CI 1.02-1.53; p = 0.038). Significant correlations between fluid biomarkers and neuropsychological examination were only found with NfL levels. CONCLUSIONS Plasma NfL levels objectively differentiates PD-MCI from PD-NC patients, and may serve as a plasma biomarker for predicting progression to dementia in PD. Plasma levels of p-tau181 does not seem to help in differentiating PD-MCI or to predict future cognitive deterioration.
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Affiliation(s)
- Javier Pagonabarraga
- Movement Disorders Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Autonomous University of Barcelona, Department of Medicine, Barcelona, Spain; Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain; Centro de Investigación en Red - Enfermedades Neurodegenerativas (CIBERNED), Spain.
| | - Rocío Pérez-González
- Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain; Centro de Investigación en Red - Enfermedades Neurodegenerativas (CIBERNED), Spain.
| | - Helena Bejr-Kasem
- Movement Disorders Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Autonomous University of Barcelona, Department of Medicine, Barcelona, Spain; Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain; Centro de Investigación en Red - Enfermedades Neurodegenerativas (CIBERNED), Spain
| | - Juan Marín-Lahoz
- Movement Disorders Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Autonomous University of Barcelona, Department of Medicine, Barcelona, Spain; Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain; Centro de Investigación en Red - Enfermedades Neurodegenerativas (CIBERNED), Spain
| | - Andrea Horta-Barba
- Movement Disorders Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Autonomous University of Barcelona, Department of Medicine, Barcelona, Spain; Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain
| | - Saul Martinez-Horta
- Movement Disorders Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Autonomous University of Barcelona, Department of Medicine, Barcelona, Spain; Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain; Centro de Investigación en Red - Enfermedades Neurodegenerativas (CIBERNED), Spain
| | - Ignacio Aracil-Bolaños
- Movement Disorders Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Autonomous University of Barcelona, Department of Medicine, Barcelona, Spain; Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain
| | - Frederic Sampedro
- Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain; Centro de Investigación en Red - Enfermedades Neurodegenerativas (CIBERNED), Spain
| | - Antonia Campolongo
- Movement Disorders Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Autonomous University of Barcelona, Department of Medicine, Barcelona, Spain; Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain; Centro de Investigación en Red - Enfermedades Neurodegenerativas (CIBERNED), Spain
| | - Elisa Rivas
- Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain; Centro de Investigación en Red - Enfermedades Neurodegenerativas (CIBERNED), Spain
| | - Arnau Puig-Davi
- Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain
| | - I Ruiz-Barrios
- Movement Disorders Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Autonomous University of Barcelona, Department of Medicine, Barcelona, Spain
| | - Jesús Pérez-Pérez
- Movement Disorders Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Autonomous University of Barcelona, Department of Medicine, Barcelona, Spain; Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain
| | - Berta Pascual-Sedano
- Movement Disorders Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Autonomous University of Barcelona, Department of Medicine, Barcelona, Spain; Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain; Centro de Investigación en Red - Enfermedades Neurodegenerativas (CIBERNED), Spain
| | - Jaime Kulisevsky
- Movement Disorders Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Autonomous University of Barcelona, Department of Medicine, Barcelona, Spain; Sant Pau Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain; Centro de Investigación en Red - Enfermedades Neurodegenerativas (CIBERNED), Spain
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Mielke MM, Aggarwal NT, Vila‐Castelar C, Agarwal P, Arenaza‐Urquijo EM, Brett B, Brugulat‐Serrat A, DuBose LE, Eikelboom WS, Flatt J, Foldi NS, Franzen S, Gilsanz P, Li W, McManus AJ, van Lent DM, Milani SA, Shaaban CE, Stites SD, Sundermann E, Suryadevara V, Trani J, Turner AD, Vonk JMJ, Quiroz YT, Babulal GM. Consideration of sex and gender in Alzheimer's disease and related disorders from a global perspective. Alzheimers Dement 2022; 18:2707-2724. [PMID: 35394117 PMCID: PMC9547039 DOI: 10.1002/alz.12662] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 02/15/2022] [Accepted: 02/20/2022] [Indexed: 01/31/2023]
Abstract
Sex or gender differences in the risk of Alzheimer's disease and related dementias (ADRD) differ by world region, suggesting that there are potentially modifiable risk factors for intervention. However, few epidemiological or clinical ADRD studies examine sex differences; even fewer evaluate gender in the context of ADRD risk. The goals of this perspective are to: (1) provide definitions of gender, biologic sex, and sexual orientation. and the limitations of examining these as binary variables; (2) provide an overview of what is known with regard to sex and gender differences in the risk, prevention, and diagnosis of ADRD; and (3) discuss these sex and gender differences from a global, worldwide perspective. Identifying drivers of sex and gender differences in ADRD throughout the world is a first step in developing interventions unique to each geographical and sociocultural area to reduce these inequities and to ultimately reduce global ADRD risk. HIGHLIGHTS: The burden of dementia is unevenly distributed geographically and by sex and gender. Scientific advances in genetics and biomarkers challenge beliefs that sex is binary. Discrimination against women and sex and gender minority (SGM) populations contributes to cognitive decline. Sociocultural factors lead to gender inequities in Alzheimer's disease and related dementias (ADRD) worldwide.
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Affiliation(s)
- Michelle M. Mielke
- Division of Epidemiology, Department of Quantitative Health SciencesMayo ClinicRochesterMinnesotaUSA
- Department of NeurologyMayo ClinicRochesterMinnesotaUSA
| | - Neelum T. Aggarwal
- Department of Neurological SciencesRush University Medical CenterChicagoIllinoisUSA
- Rush Alzheimer's Disease CenterRush University Medical CenterChicagoIllinoisUSA
| | - Clara Vila‐Castelar
- Department of Psychiatry, Harvard Medical SchoolMassachusetts General HospitalMassachusettsBostonUSA
| | - Puja Agarwal
- Rush Alzheimer's Disease CenterRush University Medical CenterChicagoIllinoisUSA
- Department of Internal MedicineRush University Medical CenterChicagoIllinoisUSA
| | - Eider M. Arenaza‐Urquijo
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain
- CIBER Fragilidad y Envejecimiento Saludable (CIBERFES)MadridSpain
| | - Benjamin Brett
- Department of NeurosurgeryMedical College of WisconsinWisconsinMilwaukeeUSA
| | - Anna Brugulat‐Serrat
- Barcelonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
- IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain
- CIBER Fragilidad y Envejecimiento Saludable (CIBERFES)MadridSpain
- Atlantic Fellow for Equity in Brain HealthThe University of California San FranciscoSan FranciscoCaliforniaUSA
| | - Lyndsey E. DuBose
- Department of Medicine, Division of GeriatricsUniversity of Colorado Anschutz Medical CampusAuroraColoradoUSA
| | - Willem S. Eikelboom
- Department of NeurologyErasmus MC University Medical CenterRotterdamThe Netherlands
| | - Jason Flatt
- Social and Behavioral Health Program, School of Public HealthUniversity of Nevada, Las VegasLas VegasNevadaUSA
| | - Nancy S. Foldi
- Department of Psychology, Queens College and The Graduate CenterCity University of New YorkNew YorkUSA
- Department of PsychiatryNew York University Long Island School of MedicineNew YorkUSA
| | - Sanne Franzen
- Department of NeurologyErasmus MC University Medical CenterRotterdamThe Netherlands
| | - Paola Gilsanz
- Kaiser Permanente Division of ResearchOaklandCaliforniaUSA
| | - Wei Li
- Department of Clinical and Diagnostic SciencesUniversity of Alabama at BirminghamBirminghamAlabamaUSA
| | - Alison J. McManus
- Department of NeurologyMassachusetts General HospitalBostonMassachusettsUSA
| | - Debora Melo van Lent
- UT Health San AntonioGlenn Biggs Institute for Alzheimer's and Neurodegenerative diseasesSan AntonioTexasUSA
- Framingham Heart StudyFraminghamMassachusettsUSA
- Department of NeurologyBoston University School of MedicineBostonMassachusettsUSA
| | - Sadaf Arefi Milani
- Division of Geriatrics & Palliative Medicine, Department of Internal MedicineUniversity of Texas Medical BranchGalvestonTexasUSA
| | - C. Elizabeth Shaaban
- Department of EpidemiologyGraduate School of Public HealthUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Shana D. Stites
- Department of PsychiatryPerlman School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Erin Sundermann
- Department of PsychiatryUniversity of CaliforniaSan DiegoCaliforniaUSA
| | - Vidyani Suryadevara
- Department of Orthopedic SurgeryRush University Medical CenterChicagoIllinoisUSA
| | - Jean‐Francoise Trani
- Department of Public HealthWashington University in St. LouisSt. LouisMissouriUSA
| | - Arlener D. Turner
- Department of Psychiatry & Behavioral SciencesUniversity of Miami Miller School of MedicineMiamiFloridaUSA
| | - Jet M. J. Vonk
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and SurgeonsColumbia UniversityNew YorkNew YorkUSA
- Julius Center for Health Sciences and Primary CareDepartment of EpidemiologyUniversity Medical Center Utrecht and Utrecht UniversityUtrechtThe Netherlands
| | - Yakeel T. Quiroz
- Department of Psychiatry, Harvard Medical SchoolMassachusetts General HospitalMassachusettsBostonUSA
- Grupo de Neurociencias de Antioquia of Universidad de AntioquiaMedellinColumbiaUSA
| | - Ganesh M. Babulal
- Department of NeurologyWashington University in St. LouisSt. LouisMississippiUSA
- Department of Clinical Research and LeadershipThe George Washington University School of Medicine and Health SciencesWashingtonDCUSA
- Department of Psychology, Faculty of HumanitiesUniversity of JohannesburgJohannesburgSouth Africa
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Fundaun J, Kolski M, Molina-Álvarez M, Baskozos G, Schmid AB. Types and Concentrations of Blood-Based Biomarkers in Adults With Peripheral Neuropathies: A Systematic Review and Meta-analysis. JAMA Netw Open 2022; 5:e2248593. [PMID: 36574244 PMCID: PMC9857490 DOI: 10.1001/jamanetworkopen.2022.48593] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 11/09/2022] [Indexed: 12/28/2022] Open
Abstract
Importance Peripheral neuropathies are common conditions and can result in numbness, paresthesia, motor deficits, and pain. There is increasing evidence for the use of biomarkers as clinical indicators of the presence, severity, and prognosis of nerve lesions; however, biomarker identification has largely been focused on disorders of the central nervous system, and less is known about their role in the peripheral nervous system. Objective To assess blood-based biomarker concentrations associated with nerve involvement in patients with peripheral neuropathy compared with control participants. Data Sources Ovid, MEDLINE, Embase, and CINAHL were searched from inception to September 23, 2021. Study Selection Observational studies reporting on blood biomarkers in patients diagnosed with peripheral neuropathy were included. This review was preregistered on PROSPERO and followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline. Data were abstracted by 1 investigator and independently reviewed by a second. Data Extraction and Synthesis Data were meta-analyzed when at least 2 studies reported the same biomarker with comparable methodology. Fixed-effects models were used when only 2 studies were included; random-effects models were used when more than 2 studies were included. Main Outcomes and Measures The outcome of interest was concentration of biomarkers. Results This review included 36 studies reporting on 4414 participants, including 2113 control participants and 2301 patients with peripheral neuropathy with 13 distinct peripheral neuropathy diagnoses. Diabetic neuropathy was the most common neuropathy diagnosis (13 studies), followed by Charcot-Marie-Tooth disease (6 studies) and Guillain-Barre syndrome (6 studies). Overall, 16 different blood-based biomarkers associated with nerve involvement were evaluated. The most used were neurofilament light chain, S100B, brain-derived neurotrophic factor, and neuron-specific enolase. Patients with peripheral neuropathy demonstrated significantly higher levels of neurofilament light chain compared with controls (standardized mean difference [SMD], 0.93 [95% CI, 0.82 to 1.05]; P < .001). There were no significant differences in levels of S100B (SMD, 1.10 [95% CI, -3.08 to 5.28]; P = .38), brain-derived neurotrophic factor (SMD, -0.52 [95% CI, -2.23 to 1.19]; P = .40), or neuron-specific enolase (SMD, -0.00 [95% CI, -1.99 to 1.98]; P = .10) in patients with peripheral neuropathy compared with control participants. Conclusions and Relevance The findings of this systematic review and meta-analysis support the use of neurofilament light chain as a blood-based measure associated with the presence of neuronal injury in patients with peripheral neuropathy.
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Affiliation(s)
- Joel Fundaun
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Melissa Kolski
- Department of Physical Therapy and Human Movement Sciences, Northwestern University, Feinberg School of Medicine, Chicago, Illinois
- Musculoskeletal Outpatient Department, Shirley Ryan AbilityLab, Chicago, Illinois
| | - Miguel Molina-Álvarez
- Area of Pharmacology, Nutrition, and Bromatology, Department of Basic Health Sciences, Universidad Rey Juan Carlos, Madrid, Spain
| | - Georgios Baskozos
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Annina B. Schmid
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
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168
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Zhou Y, Ma Y, Yu C, Chen Y, Ding J, Yu J, Zhou R, Wang X, Fan T, Shi C. Detection Analysis of Perioperative Plasma and CSF Reveals Risk Biomarkers of Postoperative Delirium of Parkinson's Disease Patients Undergoing Deep Brain Stimulation of the Subthalamic Nuclei. Clin Interv Aging 2022; 17:1739-1749. [PMID: 36474580 PMCID: PMC9719687 DOI: 10.2147/cia.s388690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Accepted: 11/22/2022] [Indexed: 12/05/2022] Open
Abstract
Objective This study aimed to explore possible biomarkers of postoperative delirium (POD) of Parkinson's disease (PD) patients received deep brain stimulation (DBS) of the subthalamic nuclei. Materials and methods This nested case control study analyzed perioperative plasma and cerebral spinal fluid (CSF) of patients (n = 40) who developed POD undergone DBS surgery (n = 10) and those who did not (n = 30). Blood sample was collected before surgery and on the first day postoperative, CSF sample was collected at the beginning of the operation. POD was assessed by the Confusion Assessment Method (CAM) twice a day between 7:00 am and 7:00 pm after the surgery until discharge. Plasma and CSF sample from the two groups were analyzed to investigate possible biomarkers for POD in PD patients. Results There was no difference between POD and Non-POD groups on the concentration of Interleukin 6 and Tumor Necrosis Factor-α in CSF, preoperative plasma and postoperative plasma. There was no difference between POD and Non-POD groups on the concentration of S100 calcium-binding protein β protein (S100β) and Neurofilament light chain (NFL) in preoperative plasma and postoperative plasma. The concentration of C-reactive protein (CRP), NFL and S100β were significant higher in POD group than non-POD group in CSF. The concentration of CRP was significantly higher in POD group than non-POD group in preoperative plasma and postoperative plasma. CSF concentration of S100β might be a potential biomarker for POD via the receiver operating characteristic curve analysis and the area under the curve value of 0.973. Conclusion For PD patients received DBS surgery, CSF S100β might be a marker for aiding detection of high-risk patients with delirium. This requires further confirmation in clinical trials.
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Affiliation(s)
- Yongde Zhou
- Department of Anesthesiology, Tsinghua University Yuquan Hospital, Beijing, People’s Republic of China
| | - Yu Ma
- Department of Neurosurgery, Tsinghua University Yuquan Hospital, Beijing, People’s Republic of China
| | - Cuiping Yu
- Department of Anesthesiology, Tsinghua University Yuquan Hospital, Beijing, People’s Republic of China
| | - Yao Chen
- Department of Anesthesiology, Tsinghua University Yuquan Hospital, Beijing, People’s Republic of China
| | - Jian Ding
- Department of Anesthesiology, Tsinghua University Yuquan Hospital, Beijing, People’s Republic of China
| | - Jianfeng Yu
- Department of Anesthesiology, Tsinghua University Yuquan Hospital, Beijing, People’s Republic of China
| | - Rongsong Zhou
- Department of Neurosurgery, Tsinghua University Yuquan Hospital, Beijing, People’s Republic of China
| | - Xiaoxiao Wang
- Research Center of Clinical Epidemiology, Peking University Third Hospital, Beijing, People’s Republic of China
| | - Ting Fan
- Department of Anesthesiology, Tsinghua University Yuquan Hospital, Beijing, People’s Republic of China
| | - Chengmei Shi
- Department of Anesthesiology, Peking University Third Hospital, Beijing, People’s Republic of China,Correspondence: Chengmei Shi; Ting Fan, Email ;
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169
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A meta-analysis of the diagnostic utility of biomarkers in cerebrospinal fluid in Parkinson's disease. NPJ Parkinsons Dis 2022; 8:165. [PMID: 36446820 PMCID: PMC9709054 DOI: 10.1038/s41531-022-00431-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 11/11/2022] [Indexed: 11/30/2022] Open
Abstract
Biomarkers play important roles in the diagnosis and differential diagnosis of Parkinson's disease (PD). Thus, we carried out a systematic review and meta-analysis evaluating the diagnostic utility of cerebrospinal fluid (CSF) biomarkers to distinguish PD from atypical parkinsonian syndromes (APSs) and controls. Data for PD and APS and controls were extracted from 123 studies that reported the concentration of CSF biomarkers. Comparisons were presented using pooled Hedges' g. Sources of heterogeneity were evaluated using meta-regression, and subgroup and sensitivity analyses. We found that compared with controls, PD patients had lower levels of amyloid beta 1-42, phosphorylated tau, total tau, total α-synuclein, Zn, DJ-1, and YKL-40, and higher levels of oligomeric and phosphorylated α-synuclein. Moreover, lower CSF levels of neurofilament light chain, t-tau, YKL-40, and C-reactive protein were found in PD patients compared to those with multiple system atrophy. PD patients also had lower levels of NFL and higher levels of Aβ42 compared with patients with progressive supranuclear palsy. Reduced levels of p-tau and t-tau and higher Aβ42 levels were found in PD patients compared with patients with dementia with Lewy bodies. Finally, reduced NFL levels were found in patients with PD compared with patients with cortical basal degeneration. Therefore, we believe that the combinations of t-α-syn, Aβ42, and NFL could be promising biomarkers for the differential diagnosis of PD and APSs.
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170
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Eratne D, Keem M, Lewis C, Kang M, Walterfang M, Farrand S, Loi S, Kelso W, Cadwallader C, Berkovic SF, Li QX, Masters CL, Collins S, Santillo A, Velakoulis D. Cerebrospinal fluid neurofilament light chain differentiates behavioural variant frontotemporal dementia progressors from non-progressors. J Neurol Sci 2022; 442:120439. [PMID: 36201960 DOI: 10.1016/j.jns.2022.120439] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2022] [Revised: 09/05/2022] [Accepted: 09/25/2022] [Indexed: 11/18/2022]
Abstract
BACKGROUND Distinguishing behavioural variant frontotemporal dementia (bvFTD) from non-neurodegenerative 'non-progressor' mimics of frontal lobe dysfunction, can be one of the most challenging clinical dilemmas. A biomarker of neuronal injury, neurofilament light chain (NfL), could reduce misdiagnosis and delay. METHODS Cerebrospinal fluid (CSF) NfL, amyloid beta 1-42 (AB42), total and phosphorylated tau (T-tau, P-tau) levels were examined in patients with an initial diagnosis of bvFTD. Based on follow-up information, patients were categorised as Progressors or Non-Progressors: further subtyped into Non-Progressor Revised (non-neurological/neurodegenerative final diagnosis), and Non-Progressor Static (static deficits, not fully explained by non-neurological/neurodegenerative causes). RESULTS Forty-three patients were included: 20 Progressors, 23 Non-Progressors (15 Non-Progressor Revised, 8 Non-Progressor Static), and 20 controls. NfL concentrations were lower in Non-Progressors (Non-Progressors Mean, M = 554 pg/mL, 95%CI:[461, 675], Non-Progressor Revised M = 459 pg/mL, 95%CI:[385, 539], and Non-Progressor Static M = 730 pg/mL, 95%CI:[516, 940]), compared to Progressors (M = 2397 pg/mL, 95%CI:[1607, 3332]). NfL distinguished Progressors from Non-Progressors with the highest accuracy (area under the curve 0.92, 90%/87% sensitivity/specificity, 86%/91% positive/negative predictive value, 88% accuracy). Non-Progressor Static tended to have higher T-tau and P-tau levels compared to Non-Progressor Revised Diagnoses. CONCLUSION This study demonstrated strong diagnostic utility of CSF NfL to distinguish bvFTD from non-progressor variants, at baseline, with high accuracy, in a real-world clinical setting. This has important clinical implications, to improve outcomes for patients and clinicians facing this challenging clinical dilemma, healthcare services, and clinical trials. Further research is required to investigate heterogeneity within the non-progressor group and potential diagnostic algorithms, and prospective studies are underway assessing plasma NfL.
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Affiliation(s)
- Dhamidhu Eratne
- Neuropsychiatry, Royal Melbourne Hospital, Parkville, VIC, Australia; Melbourne Neuropsychiatry Centre & Department of Psychiatry, University of Melbourne, Parkville, VIC, Australia; National Dementia Diagnostics Laboratory, The Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia.
| | - Michael Keem
- Neuropsychiatry, Royal Melbourne Hospital, Parkville, VIC, Australia; Melbourne Neuropsychiatry Centre & Department of Psychiatry, University of Melbourne, Parkville, VIC, Australia
| | - Courtney Lewis
- Neuropsychiatry, Royal Melbourne Hospital, Parkville, VIC, Australia; Melbourne Neuropsychiatry Centre & Department of Psychiatry, University of Melbourne, Parkville, VIC, Australia
| | - Matthew Kang
- Neuropsychiatry, Royal Melbourne Hospital, Parkville, VIC, Australia; Melbourne Neuropsychiatry Centre & Department of Psychiatry, University of Melbourne, Parkville, VIC, Australia
| | - Mark Walterfang
- Neuropsychiatry, Royal Melbourne Hospital, Parkville, VIC, Australia; Melbourne Neuropsychiatry Centre & Department of Psychiatry, University of Melbourne, Parkville, VIC, Australia; National Dementia Diagnostics Laboratory, The Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia
| | - Sarah Farrand
- Neuropsychiatry, Royal Melbourne Hospital, Parkville, VIC, Australia; Melbourne Neuropsychiatry Centre & Department of Psychiatry, University of Melbourne, Parkville, VIC, Australia
| | - Samantha Loi
- Neuropsychiatry, Royal Melbourne Hospital, Parkville, VIC, Australia; Melbourne Neuropsychiatry Centre & Department of Psychiatry, University of Melbourne, Parkville, VIC, Australia
| | - Wendy Kelso
- Neuropsychiatry, Royal Melbourne Hospital, Parkville, VIC, Australia
| | | | - Samuel F Berkovic
- Epilepsy Research Centre, Department of Medicine, Austin Health, The University of Melbourne, Heidelberg, VIC, Australia
| | - Qiao-Xin Li
- National Dementia Diagnostics Laboratory, The Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia
| | - Colin L Masters
- National Dementia Diagnostics Laboratory, The Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia
| | - Steven Collins
- National Dementia Diagnostics Laboratory, The Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia
| | - Alexander Santillo
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Sölvegatan 18, Sweden
| | - Dennis Velakoulis
- Neuropsychiatry, Royal Melbourne Hospital, Parkville, VIC, Australia; Melbourne Neuropsychiatry Centre & Department of Psychiatry, University of Melbourne, Parkville, VIC, Australia
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171
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Abstract
Alzheimer's disease (AD) characterization has progressed from being indexed using clinical symptomatology followed by neuropathological examination at autopsy to in vivo signatures using cerebrospinal fluid (CSF) biomarkers and positron emission tomography. The core AD biomarkers reflect amyloid-β plaques (A), tau pathology (T) and neurodegeneration (N), following the ATN schedule, and are now being introduced into clinical routine practice. This is an important development, as disease-modifying treatments are now emerging. Further, there are now reproducible data on CSF biomarkers which reflect synaptic pathology, neuroinflammation and common co-pathologies. In addition, the development of ultrasensitive techniques has enabled the core CSF biomarkers of AD pathophysiology to be translated to blood (e.g., phosphorylated tau, amyloid-β and neurofilament light). In this chapter, we review where we stand with both core and novel CSF biomarkers, as well as the explosion of data on blood biomarkers. Also, we discuss potential applications in research aiming to better understand the disease, as well as possible use in routine clinical practice and therapeutic trials.
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Affiliation(s)
- Joel Simrén
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden.
| | - Anders Elmgren
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden; Department of Neurodegenerative Disease, Institute of Neurology, University College London, London, United Kingdom; UK Dementia Research Institute, University College London, London, United Kingdom; Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
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172
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Eratne D, Loi SM, Li QX, Stehmann C, Malpas CB, Santillo A, Janelidze S, Cadwallader C, Walia N, Ney B, Lewis V, Senesi M, Fowler C, McGlade A, Varghese S, Ravanfar P, Kelso W, Farrand S, Keem M, Kang M, Goh AMY, Dhiman K, Gupta V, Watson R, Yassi N, Kaylor-Hughes C, Kanaan R, Perucca P, Dobson H, Vivash L, Ali R, O'Brien TJ, Hansson O, Zetterberg H, Blennow K, Walterfang M, Masters CL, Berkovic SF, Collins S, Velakoulis D. Cerebrospinal fluid neurofilament light chain differentiates primary psychiatric disorders from rapidly progressive, Alzheimer's disease and frontotemporal disorders in clinical settings. Alzheimers Dement 2022; 18:2218-2233. [PMID: 35102694 DOI: 10.1002/alz.12549] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Revised: 10/26/2021] [Accepted: 11/01/2021] [Indexed: 01/31/2023]
Abstract
INTRODUCTION Many patients with cognitive and neuropsychiatric symptoms face diagnostic delay and misdiagnosis. We investigated whether cerebrospinal fluid (CSF) neurofilament light (NfL) and total-tau (t-tau) could assist in the clinical scenario of differentiating neurodegenerative (ND) from psychiatric disorders (PSY), and rapidly progressive disorders. METHODS Biomarkers were examined in patients from specialist services (ND and PSY) and a national Creutzfeldt-Jakob registry (Creutzfeldt-Jakob disease [CJD] and rapidly progressive dementias/atypically rapid variants of common ND, RapidND). RESULTS A total of 498 participants were included: 197 ND, 67 PSY, 161 CJD, 48 RapidND, and 20 controls. NfL was elevated in ND compared to PSY and controls, with highest levels in CJD and RapidND. NfL distinguished ND from PSY with 95%/78% positive/negative predictive value, 92%/87% sensitivity/specificity, 91% accuracy. NfL outperformed t-tau in most real-life clinical diagnostic dilemma scenarios, except distinguishing CJD from RapidND. DISCUSSION We demonstrated strong generalizable evidence for the diagnostic utility of CSF NfL in differentiating ND from psychiatric disorders, with high accuracy.
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Affiliation(s)
- Dhamidhu Eratne
- Neuropsychiatry, Royal Melbourne Hospital, Parkville, Victoria, Australia.,Department of Psychiatry & Melbourne Neuropsychiatry Centre, University of Melbourne, Parkville, Victoria, Australia.,National Dementia Diagnostics Laboratory, The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
| | - Samantha M Loi
- Neuropsychiatry, Royal Melbourne Hospital, Parkville, Victoria, Australia.,Department of Psychiatry & Melbourne Neuropsychiatry Centre, University of Melbourne, Parkville, Victoria, Australia.,National Dementia Diagnostics Laboratory, The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
| | - Qiao-Xin Li
- National Dementia Diagnostics Laboratory, The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
| | - Christiane Stehmann
- National Dementia Diagnostics Laboratory, The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia.,Australian National Creutzfeldt-Jakob Disease Registry, Florey Institute of Neuroscience and Mental Health and Department of Medicine, The University of Melbourne, Parkville, Victoria, Australia
| | - Charles B Malpas
- Department of Medicine, Department of Neurology, Clinical Outcomes Research Unit (CORe), Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - Alexander Santillo
- Department of Clinical Sciences Malmö, Clinical Memory Research Unit, Lund University, Lund, Sweden.,Memory Clinic, Skåne University Hospital, Malmo, Sweden
| | - Shorena Janelidze
- Department of Clinical Sciences Malmö, Clinical Memory Research Unit, Lund University, Lund, Sweden.,Memory Clinic, Skåne University Hospital, Malmo, Sweden
| | - Claire Cadwallader
- Neuropsychiatry, Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - Nirbaanjot Walia
- Neuropsychiatry, Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - Blair Ney
- The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia.,St. Vincent's Hospital Melbourne, Fitzroy, Victoria, Australia
| | - Victoria Lewis
- Australian National Creutzfeldt-Jakob Disease Registry, Florey Institute of Neuroscience and Mental Health and Department of Medicine, The University of Melbourne, Parkville, Victoria, Australia
| | - Matteo Senesi
- Australian National Creutzfeldt-Jakob Disease Registry, Florey Institute of Neuroscience and Mental Health and Department of Medicine, The University of Melbourne, Parkville, Victoria, Australia
| | - Christopher Fowler
- The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
| | - Amelia McGlade
- National Dementia Diagnostics Laboratory, The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
| | - Shiji Varghese
- National Dementia Diagnostics Laboratory, The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
| | - Parsa Ravanfar
- Neuropsychiatry, Royal Melbourne Hospital, Parkville, Victoria, Australia.,Department of Psychiatry & Melbourne Neuropsychiatry Centre, University of Melbourne, Parkville, Victoria, Australia
| | - Wendy Kelso
- Neuropsychiatry, Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - Sarah Farrand
- Neuropsychiatry, Royal Melbourne Hospital, Parkville, Victoria, Australia.,Department of Psychiatry & Melbourne Neuropsychiatry Centre, University of Melbourne, Parkville, Victoria, Australia
| | - Michael Keem
- Neuropsychiatry, Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - Matthew Kang
- Neuropsychiatry, Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - Anita M Y Goh
- Neuropsychiatry, Royal Melbourne Hospital, Parkville, Victoria, Australia.,Department of Psychiatry & Melbourne Neuropsychiatry Centre, University of Melbourne, Parkville, Victoria, Australia
| | - Kunal Dhiman
- School of Medicine, Deakin University, Geelong, Victoria, Australia.,School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, Australia
| | - Veer Gupta
- School of Medicine, Deakin University, Geelong, Victoria, Australia.,School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, Australia
| | - Rosie Watson
- Population Health and Immunity Division, the Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia
| | - Nawaf Yassi
- Population Health and Immunity Division, the Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia.,Departments of Medicine and Neurology, Melbourne Brain Centre at the Royal Melbourne Hospital, University of Melbourne, Parkville, Victoria, Australia
| | - Cath Kaylor-Hughes
- Department of General Practice, Integrated Mental Health Team, University of Melbourne, Parkville, Victoria, Australia
| | - Richard Kanaan
- Department of Psychiatry, Austin Health, University of Melbourne, Heidelberg, Victoria, Australia
| | - Piero Perucca
- Department of Medicine, Austin Health, The University of Melbourne, Heidelberg, Victoria, Australia.,Comprehensive Epilepsy Program, Austin Health, The University of Melbourne, Heidelberg, Victoria, Australia.,Department of Neuroscience, Central Clinical School, The Alfred Hospital, Monash University, Melbourne, Victoria, Australia
| | - Hannah Dobson
- Neuropsychiatry, Royal Melbourne Hospital, Parkville, Victoria, Australia.,Department of Psychiatry, Alfred Health, Melbourne, Victoria, Australia
| | - Lucy Vivash
- Department of Neuroscience, Central Clinical School, The Alfred Hospital, Monash University, Melbourne, Victoria, Australia
| | - Rashida Ali
- Department of Neuroscience, Central Clinical School, The Alfred Hospital, Monash University, Melbourne, Victoria, Australia
| | - Terence J O'Brien
- Department of Neuroscience, Central Clinical School, The Alfred Hospital, Monash University, Melbourne, Victoria, Australia
| | - Oskar Hansson
- Department of Clinical Sciences Malmö, Clinical Memory Research Unit, Lund University, Lund, Sweden.,Memory Clinic, Skåne University Hospital, Malmo, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.,Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK.,UK Dementia Research Institute at UCL, London, UK
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Mark Walterfang
- Neuropsychiatry, Royal Melbourne Hospital, Parkville, Victoria, Australia.,Department of Psychiatry & Melbourne Neuropsychiatry Centre, University of Melbourne, Parkville, Victoria, Australia.,The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
| | - Colin L Masters
- National Dementia Diagnostics Laboratory, The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
| | - Samuel F Berkovic
- Department of Medicine, Austin Health, Epilepsy Research Centre, The University of Melbourne, Heidelberg, Victoria, Australia
| | - Steven Collins
- Australian National Creutzfeldt-Jakob Disease Registry, Florey Institute of Neuroscience and Mental Health and Department of Medicine, The University of Melbourne, Parkville, Victoria, Australia
| | - Dennis Velakoulis
- Neuropsychiatry, Royal Melbourne Hospital, Parkville, Victoria, Australia.,Department of Psychiatry & Melbourne Neuropsychiatry Centre, University of Melbourne, Parkville, Victoria, Australia
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173
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del Campo M, Zetterberg H, Gandy S, Onyike CU, Oliveira F, Udeh‐Momoh C, Lleó A, Teunissen CE, Pijnenburg Y. New developments of biofluid-based biomarkers for routine diagnosis and disease trajectories in frontotemporal dementia. Alzheimers Dement 2022; 18:2292-2307. [PMID: 35235699 PMCID: PMC9790674 DOI: 10.1002/alz.12643] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Revised: 02/04/2022] [Accepted: 02/04/2022] [Indexed: 01/31/2023]
Abstract
Frontotemporal dementia (FTD) covers a spectrum of neurodegenerative disorders with different phenotypes, genetic backgrounds, and pathological states. Its clinicopathological diversity challenges the diagnostic process and the execution of clinical trials, calling for specific diagnostic biomarkers of pathologic FTD types. There is also a need for biomarkers that facilitate disease staging, quantification of severity, monitoring in clinics and observational studies, and for evaluation of target engagement and treatment response in clinical trials. This review discusses current FTD biofluid-based biomarker knowledge taking into account the differing applications. The limitations, knowledge gaps, and challenges for the development and implementation of such markers are also examined. Strategies to overcome these hurdles are proposed, including the technologies available, patient cohorts, and collaborative research initiatives. Access to robust and reliable biomarkers that define the exact underlying pathophysiological FTD process will meet the needs for specific diagnosis, disease quantitation, clinical monitoring, and treatment development.
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Affiliation(s)
- Marta del Campo
- Departamento de Ciencias Farmacéuticas y de la SaludFacultad de FarmaciaUniversidad San Pablo‐CEUCEU UniversitiesMadridSpain
| | - Henrik Zetterberg
- Institute of Neuroscience and PhysiologyThe Sahlgrenska Academy at the University of GothenburgGothenburgSweden,Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden,UK Dementia Research Institute at UCLLondonUK,Department of Neurodegenerative DiseaseUCL Institute of NeurologyLondonUK,Hong Kong Center for Neurodegenerative DiseasesHong KongChina
| | - Sam Gandy
- Department of NeurologyIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Chiadi U Onyike
- Division of Geriatric Psychiatry and NeuropsychiatryThe Johns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Fabricio Oliveira
- Department of Neurology and NeurosurgeryEscola Paulista de MedicinaFederal University of São Paulo (UNIFESP)São PauloSão PauloBrazil
| | - Chi Udeh‐Momoh
- Ageing Epidemiology Research UnitSchool of Public HealthFaculty of MedicineImperial College LondonLondonUK,Translational Health SciencesFaculty of MedicineUniversity of BristolBristolUK
| | - Alberto Lleó
- Neurology DepartmentHospital de la Santa Creu I Sant PauBarcelonaSpain
| | - Charlotte E. Teunissen
- Neurochemistry LaboratoryDepartment of Clinical ChemistryAmsterdam NeuroscienceAmsterdam University Medical CentersVrije UniversiteitAmsterdamthe Netherlands
| | - Yolande Pijnenburg
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceVrije Universiteit AmsterdamAmsterdam UMCAmsterdamthe Netherlands
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174
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Delaby C, Bousiges O, Bouvier D, Fillée C, Fourier A, Mondésert E, Nezry N, Omar S, Quadrio I, Rucheton B, Schraen-Maschke S, van Pesch V, Vicca S, Lehmann S, Bedel A. Neurofilaments contribution in clinic: state of the art. Front Aging Neurosci 2022; 14:1034684. [PMID: 36389064 PMCID: PMC9664201 DOI: 10.3389/fnagi.2022.1034684] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 10/10/2022] [Indexed: 07/26/2023] Open
Abstract
Neurological biomarkers are particularly valuable to clinicians as they can be used for diagnosis, prognosis, or response to treatment. This field of neurology has evolved considerably in recent years with the improvement of analytical methods, allowing the detection of biomarkers not only in cerebrospinal fluid (CSF) but also in less invasive fluids like blood. These advances greatly facilitate the repeated quantification of biomarkers, including at asymptomatic stages of the disease. Among the various informative biomarkers of neurological disorders, neurofilaments (NfL) have proven to be of particular interest in many contexts, such as neurodegenerative diseases, traumatic brain injury, multiple sclerosis, stroke, and cancer. Here we discuss these different pathologies and the potential value of NfL assay in the management of these patients, both for diagnosis and prognosis. We also describe the added value of NfL compared to other biomarkers currently used to monitor the diseases described in this review.
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Affiliation(s)
- Constance Delaby
- Université de Montpellier, IRMB, INM, INSERM, CHU de Montpellier, Laboratoire Biochimie-Protéomique clinique, Montpellier, France
- Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau—Biomedical Research Institute Sant Pau—Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Olivier Bousiges
- Laboratoire de biochimie et biologie moléculaire (LBBM)—Pôle de biologie Hôpital de Hautepierre—CHU de Strasbourg, CNRS, laboratoire ICube UMR 7357 et FMTS (Fédération de Médecine Translationnelle de Strasbourg), équipe IMIS, Strasbourg, France
| | - Damien Bouvier
- Service de Biochimie et Génétique Moléculaire, CHU de Clermont-Ferrand, Clermont-Ferrand, France
| | - Catherine Fillée
- Cliniques universitaires Saint-Luc UCLouvain, Service de Biochimie Médicale, Brussels, Belgium
| | - Anthony Fourier
- Biochimie et Biologie Moléculaire—LBMMS, Unité de diagnostic des pathologies dégénératives, Centre de Biologie et Pathologie Est, Groupement Hospitalier Est, Lyon, France
| | - Etienne Mondésert
- Université de Montpellier, IRMB, INM, INSERM, CHU de Montpellier, Laboratoire Biochimie-Protéomique clinique, Montpellier, France
| | - Nicolas Nezry
- Univ. Lille, Inserm, CHU Lille, UMR-S-U1172, LiCEND, Lille Neuroscience & Cognition, LabEx DISTALZ, Lille, France
| | - Souheil Omar
- Laboratoire de biologie médicale de l’Institut de Neurologie de Tunis, Tunis, Tunisia
| | - Isabelle Quadrio
- Biochimie et Biologie Moléculaire—LBMMS, Unité de diagnostic des pathologies dégénératives, Centre de Biologie et Pathologie Est, Groupement Hospitalier Est, Lyon, France
| | - Benoit Rucheton
- Laboratoire de Biologie, Institut Bergonié, Bordeaux, France
| | - Susanna Schraen-Maschke
- Univ. Lille, Inserm, CHU Lille, UMR-S-U1172, LiCEND, Lille Neuroscience & Cognition, LabEx DISTALZ, Lille, France
| | - Vincent van Pesch
- Cliniques universitaires Saint-Luc UCLouvain, Service de Neurologie, Brussels, Belgium
| | - Stéphanie Vicca
- Hôpital Necker-Enfants malades, Paris, Laboratoire de Biochimie générale, DMU BioPhyGen, AP-HP.Centre—Université de Paris, Paris, France
| | - Sylvain Lehmann
- Université de Montpellier, IRMB, INM, INSERM, CHU de Montpellier, Laboratoire Biochimie-Protéomique clinique, Montpellier, France
| | - Aurelie Bedel
- Service de Biochimie, CHU Pellegrin, Bordeaux, France
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175
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Vermunt L, Otte M, Verberk IMW, Killestein J, Lemstra AW, van der Flier WM, Pijnenburg YAL, Vijverberg EGB, Bouwman FH, Gravesteijn G, van de Berg WDJ, Scheltens P, van Harten AC, Willemse EAJ, Teunissen CE. Age- and disease-specific reference values for neurofilament light presented in an online interactive support interface. Ann Clin Transl Neurol 2022; 9:1832-1837. [PMID: 36196979 DOI: 10.1002/acn3.51676] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 09/12/2022] [Accepted: 09/26/2022] [Indexed: 11/07/2022] Open
Abstract
Interpretation of axonal damage biomarker Neurofilament Light chain (NfL) concentrations is difficult due to the lack of age-specific and disease-specific reference values. We here developed an interactive interface to support interpretation of NfL results in human body fluids. We used NfL values of 1698 individuals without a neurological disorder, aged 19-85 years, and patients with MS and dementias. Percentile regression estimates per diagnosis populate interactive graphs, alongside NfL background information (available on: https://mybiomarkers.shinyapps.io/Neurofilament). This accessible interface provides reference for interpretation of the individual patient results for clinicians. It showcases an adaptable method to support interpretation of age-dependent biomarkers in neurology.
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Affiliation(s)
- Lisa Vermunt
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Marco Otte
- Network Institute Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Inge M W Verberk
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Joep Killestein
- MS Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Afina W Lemstra
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,Department of Epidemiology and Data Science, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Yolande A L Pijnenburg
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Everard G B Vijverberg
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Femke H Bouwman
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Gido Gravesteijn
- Department of Clinical Genetics and Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Wilma D J van de Berg
- Clinical Neuroanatomy and Biobanking, department of Anatomy and Neurosciences, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,Life Science Partners (LSP), Amsterdam, The Netherlands
| | - Argonde C van Harten
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Eline A J Willemse
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Charlotte E Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
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176
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Svenningsson AL, Stomrud E, Palmqvist S, Hansson O, Ossenkoppele R. Axonal degeneration and amyloid pathology predict cognitive decline beyond cortical atrophy. Alzheimers Res Ther 2022; 14:144. [PMID: 36192766 PMCID: PMC9531524 DOI: 10.1186/s13195-022-01081-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Accepted: 09/11/2022] [Indexed: 12/02/2022]
Abstract
BACKGROUND Cortical atrophy is associated with cognitive decline, but the association is not perfect. We aimed to identify factors explaining the discrepancy between the degree of cortical atrophy and cognitive decline in cognitively unimpaired elderly. METHODS The discrepancy between atrophy and cognitive decline was measured using the residuals from a linear regression analysis between change in whole brain cortical thickness over time and change in a cognitive composite measure over time in 395 cognitively unimpaired participants from the Swedish BioFINDER study. We tested for bivariate associations of this residual measure with demographic, imaging, and fluid biomarker variables using Pearson correlations and independent-samples t-tests, and for multivariate associations using linear regression models. Mediation analyses were performed to explore possible paths between the included variables. RESULTS In bivariate analyses, older age (r = -0.11, p = 0.029), male sex (t = -3.00, p = 0.003), larger intracranial volume (r = -0.17, p < 0.001), carrying an APOEe4 allele (t = -2.71, p = 0.007), larger white matter lesion volume (r = -0.16, p = 0.002), lower cerebrospinal fluid (CSF) β-amyloid (Aβ) 42/40 ratio (t = -4.05, p < 0.001), and higher CSF levels of phosphorylated tau (p-tau) 181 (r = -0.22, p < 0.001), glial fibrillary acidic protein (GFAP; r = -0.15, p = 0.003), and neurofilament light (NfL; r = -0.34, p < 0.001) were negatively associated with the residual measure, i.e., associated with worse than expected cognitive trajectory given the level of atrophy. In a multivariate analysis, only lower CSF Aβ42/40 ratio and higher CSF NfL levels explained cognition beyond brain atrophy. Mediation analyses showed that associations between the residual measure and APOEe4 allele, CSF Aβ42/40 ratio, and CSF GFAP and p-tau181 levels were mediated by levels of CSF NfL, as were the associations with the residual measure for age, sex, and WML volume. CONCLUSIONS Our results suggest that axonal degeneration and amyloid pathology independently affect the rate of cognitive decline beyond the degree of cortical atrophy. Furthermore, axonal degeneration mediated the negative effects of old age, male sex, and white matter lesions, and in part also amyloid and tau pathology, on cognition over time when accounting for cortical atrophy.
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Affiliation(s)
- Anna Linnéa Svenningsson
- grid.4514.40000 0001 0930 2361Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, SE 205 02 Malmö, Sweden ,grid.411843.b0000 0004 0623 9987Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Erik Stomrud
- grid.4514.40000 0001 0930 2361Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, SE 205 02 Malmö, Sweden ,grid.411843.b0000 0004 0623 9987Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Sebastian Palmqvist
- grid.4514.40000 0001 0930 2361Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, SE 205 02 Malmö, Sweden ,grid.411843.b0000 0004 0623 9987Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Oskar Hansson
- grid.4514.40000 0001 0930 2361Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, SE 205 02 Malmö, Sweden ,grid.411843.b0000 0004 0623 9987Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Rik Ossenkoppele
- grid.4514.40000 0001 0930 2361Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, SE 205 02 Malmö, Sweden ,grid.484519.5Alzheimer Center Amsterdam, Department of Neurology, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, Netherlands
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177
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Eratne D, Janelidze S, Malpas CB, Loi S, Walterfang M, Merritt A, Diouf I, Blennow K, Zetterberg H, Cilia B, Wannan C, Bousman C, Everall I, Zalesky A, Jayaram M, Thomas N, Berkovic SF, Hansson O, Velakoulis D, Pantelis C, Santillo A, Stehmann C, Cadwallader C, Fowler C, Ravanfar P, Farrand S, Keem M, Kang M, Watson R, Yassi N, Kaylor-Hughes C, Kanaan R, Perucca P, Vivash L, Ali R, O’Brien TJ, Masters CL, Collins S, Kelso W, Evans A, King A, Kwan P, Gunn J, Goranitis I, Pan T, Lewis C, Kalincik T. Plasma neurofilament light chain protein is not increased in treatment-resistant schizophrenia and first-degree relatives. Aust N Z J Psychiatry 2022; 56:1295-1305. [PMID: 35179048 DOI: 10.1177/00048674211058684] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
OBJECTIVE Schizophrenia, a complex psychiatric disorder, is often associated with cognitive, neurological and neuroimaging abnormalities. The processes underlying these abnormalities, and whether a subset of people with schizophrenia have a neuroprogressive or neurodegenerative component to schizophrenia, remain largely unknown. Examining fluid biomarkers of diverse types of neuronal damage could increase our understanding of these processes, as well as potentially provide clinically useful biomarkers, for example with assisting with differentiation from progressive neurodegenerative disorders such as Alzheimer and frontotemporal dementias. METHODS This study measured plasma neurofilament light chain protein (NfL) using ultrasensitive Simoa technology, to investigate the degree of neuronal injury in a well-characterised cohort of people with treatment-resistant schizophrenia on clozapine (n = 82), compared to first-degree relatives (an at-risk group, n = 37), people with schizophrenia not treated with clozapine (n = 13), and age- and sex-matched controls (n = 59). RESULTS We found no differences in NfL levels between treatment-resistant schizophrenia (mean NfL, M = 6.3 pg/mL, 95% confidence interval: [5.5, 7.2]), first-degree relatives (siblings, M = 6.7 pg/mL, 95% confidence interval: [5.2, 8.2]; parents, M after adjusting for age = 6.7 pg/mL, 95% confidence interval: [4.7, 8.8]), controls (M = 5.8 pg/mL, 95% confidence interval: [5.3, 6.3]) and not treated with clozapine (M = 4.9 pg/mL, 95% confidence interval: [4.0, 5.8]). Exploratory, hypothesis-generating analyses found weak correlations in treatment-resistant schizophrenia, between NfL and clozapine levels (Spearman's r = 0.258, 95% confidence interval: [0.034, 0.457]), dyslipidaemia (r = 0.280, 95% confidence interval: [0.064, 0.470]) and a negative correlation with weight (r = -0.305, 95% confidence interval: [-0.504, -0.076]). CONCLUSION Treatment-resistant schizophrenia does not appear to be associated with neuronal, particularly axonal degeneration. Further studies are warranted to investigate the utility of NfL to differentiate treatment-resistant schizophrenia from neurodegenerative disorders such as behavioural variant frontotemporal dementia, and to explore NfL in other stages of schizophrenia such as the prodome and first episode.
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Affiliation(s)
- Dhamidhu Eratne
- Neuropsychiatry, The Royal Melbourne Hospital, Parkville, VIC, Australia.,Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden
| | - Charles B Malpas
- Clinical Outcomes Research Unit (CORe), Department of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Melbourne, VIC, Australia.,Department of Neurology, The Royal Melbourne Hospital, Melbourne, VIC, Australia.,Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, VIC, Australia
| | - Samantha Loi
- Neuropsychiatry, The Royal Melbourne Hospital, Parkville, VIC, Australia.,Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia
| | - Mark Walterfang
- Neuropsychiatry, The Royal Melbourne Hospital, Parkville, VIC, Australia.,Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia
| | - Antonia Merritt
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia
| | - Ibrahima Diouf
- Clinical Outcomes Research Unit (CORe), Department of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Melbourne, VIC, Australia.,Department of Neurology, The Royal Melbourne Hospital, Melbourne, VIC, Australia
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, Sahlgrenska University Hospital, University of Gothenburg, Mölndal, Sweden
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, Sahlgrenska University Hospital, University of Gothenburg, Mölndal, Sweden.,Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden.,Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK.,UK Dementia Research Institute, University College London (UCL), London, UK.,Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Brandon Cilia
- The University of Melbourne, Parkville, VIC, Australia
| | - Cassandra Wannan
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia
| | - Chad Bousman
- Departments of Medical Genetics, Psychiatry, and Physiology & Pharmacology, University of Calgary, Calgary, AB, Canada
| | - Ian Everall
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Andrew Zalesky
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia
| | - Mahesh Jayaram
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia.,Mid West Area Mental Health Service, Melbourne Health, Sunshine, VIC, Australia
| | - Naveen Thomas
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia.,Mid West Area Mental Health Service, Melbourne Health, Sunshine, VIC, Australia
| | - Samuel F Berkovic
- Epilepsy Research Centre, Department of Medicine, Austin Health, The University of Melbourne, Heidelberg, VIC, Australia
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden
| | - Dennis Velakoulis
- Neuropsychiatry, The Royal Melbourne Hospital, Parkville, VIC, Australia.,Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, VIC, Australia.,Mid West Area Mental Health Service, Melbourne Health, Sunshine, VIC, Australia
| | - Alexander Santillo
- Clinical Memory Research Unit, Department of Clinical Sciences, Faculty of Medicine, Lund University, Lund, Sweden
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178
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Morris HR. Blood based biomarkers for movement disorders. Acta Neurol Scand 2022; 146:353-361. [PMID: 36156206 PMCID: PMC9828103 DOI: 10.1111/ane.13700] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 08/12/2022] [Accepted: 08/19/2022] [Indexed: 01/12/2023]
Abstract
Movement disorders have been carefully clinically defined, based on clinico-pathological series; however there is often diagnostic and prognostic uncertainty, especially in early stage disease. Blood-based biomarkers for Alzheimer's disease (AD), particularly p-tau181 and p-tau217, may be useful in the movement disorder clinic, especially in identifying corticobasal syndrome due to AD pathology and in identifying Parkinson's disease (PD) patients at high risk for the future development of dementia. Serum or plasma neurofilament light (NfL) may be useful in separating Parkinson's plus syndromes (progressive supranuclear palsy-PSP, multiple system atrophy - MSA, and corticobasal syndrome-CBS) from PD. NfL is also a prognostic biomarker, in that the level of baseline or cross-sectional plasma/serum NfL is associated with a worse prognosis in PD and PSP. The development of protein aggregation assays in cerebrospinal fluid and multiplex assays which can measure 100 s-1000s of proteins in blood will provide new tools and insights for movement disorders for clinicians and researchers. The challenge is in efficiently integrating these tools into clinical practice and multi-modal approaches, where biomarkers are combined with clinical, genetic, and imaging data may guide the future use of these technologies.
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Affiliation(s)
- Huw R. Morris
- Department of Clinical and Movement Neurosciences, Queen Square Institute of NeurologyUniversity College LondonLondonUK
- UCL Movement Disorders CentreUniversity College LondonLondonUK
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179
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Fitzgerald KC, Sotirchos ES, Smith MD, Lord HN, DuVal A, Mowry EM, Calabresi PA. Contributors to Serum NfL Levels in People without Neurologic Disease. Ann Neurol 2022; 92:688-698. [PMID: 35730070 PMCID: PMC9489658 DOI: 10.1002/ana.26446] [Citation(s) in RCA: 39] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 06/13/2022] [Accepted: 06/16/2022] [Indexed: 11/11/2022]
Abstract
OBJECTIVE To assess the effects of demographics, lifestyle factors, and comorbidities on serum neurofilament light chain (sNfL) levels in people without neurologic disease and establish demographic-specific reference ranges of sNfL. METHODS The National Health and Nutrition Examination Survey (NHANES) is a representative sample of the US population in which detailed information on demographic, lifestyle, routine laboratory tests, and overall health status are systematically collected. From stored serum samples, we measured sNfL levels using a novel high-throughput immunoassay (Siemens Healthineers). We evaluated the predictive capacity of 52 demographic, lifestyle, comorbidity, anthropometric, or laboratory characteristics in explaining variability in sNfL levels. Predictive performance was assessed using cross-validated R2 (R2 cv ) and forward selection was used to obtain a set of best predictors of sNfL levels. Adjusted reference ranges were derived incorporating characteristics using generalized additive models for location, scale, and shape. RESULTS We included 1,706 NHANES participants (average age: 43.6 ± 14.8 y; 50.6% male, 35% non-white) without neurological disorders. In univariate models, age explained the most variability in sNfL (R2 cv = 26.8%). Multivariable prediction models for sNfL contained three covariates (in order of their selection): age, creatinine, and glycosylated hemoglobin (HbA1c) (standardized β-age: 0.46, 95% confidence interval [CI]: 0.43, 0.50; creatinine: 0.18, 95% CI: 0.13, 0.22; HbA1c: 0.09, 95% CI: 0.06, 0.11). Adjusted centile curves were derived incorporating identified predictors. We provide an interactive R Shiny application to translate our findings and allow other investigators to use the derived centile curves. INTERPRETATION Results will help to guide interpretation of sNfL levels as they relate to neurologic conditions. ANN NEUROL 2022;92:688-698.
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Affiliation(s)
- Kathryn C Fitzgerald
- Division of Neuroimmunology and Neurological Infections, Department of Neurology, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Elias S Sotirchos
- Division of Neuroimmunology and Neurological Infections, Department of Neurology, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Matthew D Smith
- Division of Neuroimmunology and Neurological Infections, Department of Neurology, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Hannah-Noelle Lord
- Division of Neuroimmunology and Neurological Infections, Department of Neurology, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Anna DuVal
- Division of Neuroimmunology and Neurological Infections, Department of Neurology, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Ellen M Mowry
- Division of Neuroimmunology and Neurological Infections, Department of Neurology, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Peter A Calabresi
- Division of Neuroimmunology and Neurological Infections, Department of Neurology, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
- Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
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180
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Kaisey M, Lashgari G, Fert-Bober J, Ontaneda D, Solomon AJ, Sicotte NL. An Update on Diagnostic Laboratory Biomarkers for Multiple Sclerosis. Curr Neurol Neurosci Rep 2022; 22:675-688. [PMID: 36269540 DOI: 10.1007/s11910-022-01227-1] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/12/2022] [Indexed: 01/27/2023]
Abstract
PURPOSE For many patients, the multiple sclerosis (MS) diagnostic process can be lengthy, costly, and fraught with error. Recent research aims to address the unmet need for an accurate and simple diagnostic process through discovery of novel diagnostic biomarkers. This review summarizes recent studies on MS diagnostic fluid biomarkers, with a focus on blood biomarkers, and includes discussion of technical limitations and practical applicability. RECENT FINDINGS This line of research is in its early days. Accurate and easily obtainable biomarkers for MS have not yet been identified and validated, but several approaches to uncover them are underway. Continue efforts to define laboratory diagnostic biomarkers are likely to play an increasingly important role in defining MS at the earliest stages, leading to better long-term clinical outcomes.
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Affiliation(s)
- Marwa Kaisey
- Cedars-Sinai Medical Center Department of Neurology, 127 S. San Vicente Blvd, A6600, Los Angeles, CA, 90048, USA.
| | - Ghazal Lashgari
- Cedars-Sinai Medical Center Department of Neurology, 127 S. San Vicente Blvd, A6600, Los Angeles, CA, 90048, USA
| | - Justyna Fert-Bober
- Cedars-Sinai Medical Center Department of Neurology, 127 S. San Vicente Blvd, A6600, Los Angeles, CA, 90048, USA
| | - Daniel Ontaneda
- Mellen Center for Multiple Sclerosis, Neurological Institute, Cleveland Clinic, 9500 Euclid Ave. U10 Mellen Center, Cleveland, OH, 44106, USA
| | - Andrew J Solomon
- Department of Neurological Sciences, Larner College of Medicine at the University of Vermont University Health Center, Arnold 2, 1 South Prospect Street, Burlington, VT, 05401, USA
| | - Nancy L Sicotte
- Cedars-Sinai Medical Center Department of Neurology, 127 S. San Vicente Blvd, A6600, Los Angeles, CA, 90048, USA
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181
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Staffaroni AM, Quintana M, Wendelberger B, Heuer HW, Russell LL, Cobigo Y, Wolf A, Goh SYM, Petrucelli L, Gendron TF, Heller C, Clark AL, Taylor JC, Wise A, Ong E, Forsberg L, Brushaber D, Rojas JC, VandeVrede L, Ljubenkov P, Kramer J, Casaletto KB, Appleby B, Bordelon Y, Botha H, Dickerson BC, Domoto-Reilly K, Fields JA, Foroud T, Gavrilova R, Geschwind D, Ghoshal N, Goldman J, Graff-Radford J, Graff-Radford N, Grossman M, Hall MGH, Hsiung GY, Huey ED, Irwin D, Jones DT, Kantarci K, Kaufer D, Knopman D, Kremers W, Lago AL, Lapid MI, Litvan I, Lucente D, Mackenzie IR, Mendez MF, Mester C, Miller BL, Onyike CU, Rademakers R, Ramanan VK, Ramos EM, Rao M, Rascovsky K, Rankin KP, Roberson ED, Savica R, Tartaglia MC, Weintraub S, Wong B, Cash DM, Bouzigues A, Swift IJ, Peakman G, Bocchetta M, Todd EG, Convery RS, Rowe JB, Borroni B, Galimberti D, Tiraboschi P, Masellis M, Finger E, van Swieten JC, Seelaar H, Jiskoot LC, Sorbi S, Butler CR, Graff C, Gerhard A, Langheinrich T, Laforce R, Sanchez-Valle R, de Mendonça A, Moreno F, Synofzik M, Vandenberghe R, Ducharme S, Le Ber I, Levin J, Danek A, Otto M, Pasquier F, Santana I, Kornak J, Boeve BF, Rosen HJ, Rohrer JD, Boxer AL. Temporal order of clinical and biomarker changes in familial frontotemporal dementia. Nat Med 2022; 28:2194-2206. [PMID: 36138153 PMCID: PMC9951811 DOI: 10.1038/s41591-022-01942-9] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2021] [Accepted: 07/08/2022] [Indexed: 01/17/2023]
Abstract
Unlike familial Alzheimer's disease, we have been unable to accurately predict symptom onset in presymptomatic familial frontotemporal dementia (f-FTD) mutation carriers, which is a major hurdle to designing disease prevention trials. We developed multimodal models for f-FTD disease progression and estimated clinical trial sample sizes in C9orf72, GRN and MAPT mutation carriers. Models included longitudinal clinical and neuropsychological scores, regional brain volumes and plasma neurofilament light chain (NfL) in 796 carriers and 412 noncarrier controls. We found that the temporal ordering of clinical and biomarker progression differed by genotype. In prevention-trial simulations using model-based patient selection, atrophy and NfL were the best endpoints, whereas clinical measures were potential endpoints in early symptomatic trials. f-FTD prevention trials are feasible but will likely require global recruitment efforts. These disease progression models will facilitate the planning of f-FTD clinical trials, including the selection of optimal endpoints and enrollment criteria to maximize power to detect treatment effects.
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Affiliation(s)
- Adam M Staffaroni
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.
| | | | | | - Hilary W Heuer
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Lucy L Russell
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square London, London, UK
| | - Yann Cobigo
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Amy Wolf
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Sheng-Yang Matt Goh
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | | | - Tania F Gendron
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - Carolin Heller
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square London, London, UK
| | - Annie L Clark
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Jack Carson Taylor
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Amy Wise
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Elise Ong
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Leah Forsberg
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Danielle Brushaber
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Julio C Rojas
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Lawren VandeVrede
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Peter Ljubenkov
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Joel Kramer
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Kaitlin B Casaletto
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Brian Appleby
- Department of Neurology, Case Western Reserve University, Cleveland, OH, USA
| | - Yvette Bordelon
- Department of Neurology, University of California, Los Angeles, Los Angeles, USA
| | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Bradford C Dickerson
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Julie A Fields
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Tatiana Foroud
- Indiana University School of Medicine, National Centralized Repository for Alzheimer's, Indianapolis, IN, USA
| | | | - Daniel Geschwind
- Department of Neurology, University of California, Los Angeles, Los Angeles, USA
- Institute for Precision Health, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Nupur Ghoshal
- Departments of Neurology and Psychiatry, Washington University School of Medicine, Washington University, St. Louis, MO, USA
| | - Jill Goldman
- Department of Neurology, Columbia University, New York, NY, USA
| | | | | | - Murray Grossman
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Matthew G H Hall
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Ging-Yuek Hsiung
- Division of Neurology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Edward D Huey
- Department of Neurology, Columbia University, New York, NY, USA
| | - David Irwin
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - David T Jones
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Kejal Kantarci
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Daniel Kaufer
- Department of Neurology, University of North Carolina, Chapel Hill, NC, USA
| | - David Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Walter Kremers
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Argentina Lario Lago
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Maria I Lapid
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Irene Litvan
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Diane Lucente
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Ian R Mackenzie
- Department of Pathology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Mario F Mendez
- Department of Neurology, University of California, Los Angeles, Los Angeles, USA
| | - Carly Mester
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Bruce L Miller
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Chiadi U Onyike
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University, Baltimore, MD, USA
| | - Rosa Rademakers
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
- Applied and Translational Neurogenomics Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | | | - Eliana Marisa Ramos
- Department of Neurology, University of California, Los Angeles, Los Angeles, USA
| | - Meghana Rao
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Katya Rascovsky
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Katherine P Rankin
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Erik D Roberson
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Rodolfo Savica
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - M Carmela Tartaglia
- Tanz Centre for Research in Neurodegenerative Diseases, Division of Neurology, University of Toronto, Toronto, Ontario, Canada
| | - Sandra Weintraub
- Department of Neurology, Northwestern University, Chicago, IL, USA
| | - Bonnie Wong
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - David M Cash
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square London, London, UK
| | - Arabella Bouzigues
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square London, London, UK
| | - Imogen J Swift
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square London, London, UK
| | - Georgia Peakman
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square London, London, UK
| | - Martina Bocchetta
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square London, London, UK
| | - Emily G Todd
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square London, London, UK
| | - Rhian S Convery
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square London, London, UK
| | - James B Rowe
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust and Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Barbara Borroni
- Centre for Neurodegenerative Disorders, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Daniela Galimberti
- Department of Biomedical, Surgical and Dental Sciences, University of Milan, Milan, Italy
- Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Milan, Italy
| | | | - Mario Masellis
- Division of Neurology, Department of Medicine, Sunnybrook Health Sciences Centre; Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Elizabeth Finger
- Department of Clinical Neurological Sciences, University of Western Ontario, London, Ontario, Canada
| | | | - Harro Seelaar
- Department of Neurology, Erasmus Medical Centre, Rotterdam, Netherlands
| | - Lize C Jiskoot
- Department of Neurology, Erasmus Medical Centre, Rotterdam, Netherlands
| | - Sandro Sorbi
- Department of Neurofarba, University of Florence, Florence, Italy
- IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy
| | - Chris R Butler
- Nuffield Department of Clinical Neurosciences, Medical Sciences Division, University of Oxford, Oxford, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Caroline Graff
- Center for Alzheimer Research, Division of Neurogeriatrics, Department of Neurobiology, Care Sciences and Society, Bioclinicum, Karolinska Institutet, Solna, Sweden
- Unit for Hereditary Dementias, Theme Aging, Karolinska University Hospital, Solna, Sweden
| | - Alexander Gerhard
- Division of Neuroscience and Experimental Psychology, Wolfson Molecular Imaging Centre, University of Manchester, Manchester, UK
- Departments of Geriatric Medicine and Nuclear Medicine, Center for Translational Neuro- and Behavioral Sciences, University Medicine Essen, Essen, Germany
| | - Tobias Langheinrich
- Division of Neuroscience and Experimental Psychology, Wolfson Molecular Imaging Centre, University of Manchester, Manchester, UK
- Cerebral Function Unit, Manchester Centre for Clinical Neurosciences, Salford Royal NHS Foundation Trust, Salford, UK
| | - Robert Laforce
- Clinique Interdisciplinaire de Mémoire, Département des Sciences Neurologiques, CHU de Québec, and Faculté de Médecine, Université Laval, Québec City, Québec, Canada
| | - Raquel Sanchez-Valle
- Alzheimer's disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic, Institut d'Investigacións Biomèdiques August Pi I Sunyer, University of Barcelona, Barcelona, Spain
| | | | - Fermin Moreno
- Cognitive Disorders Unit, Department of Neurology, Donostia University Hospital, San Sebastian, Gipuzkoa, Spain
- Neuroscience Area, Biodonostia Health Research Institute, San Sebastian, Gipuzkoa, Spain
| | - Matthis Synofzik
- Department of Neurodegenerative Diseases, Hertie-Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, Tübingen, Germany
- Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Rik Vandenberghe
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
- Neurology Service, University Hospitals Leuven, Leuven, Belgium
- Leuven Brain Institute, KU Leuven, Leuven, Belgium
| | - Simon Ducharme
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, Department of Neurology & Neurosurgery, McGill University, Montreal, Québec, Canada
| | - Isabelle Le Ber
- Sorbonne Université, Paris Brain Institute - Institut du Cerveau - ICM, Inserm U1127, CNRS UMR 7225, AP-HP - Hôpital Pitié-Salpêtrière, Paris, France
- Centre de référence des démences rares ou précoces, IM2A, Département de Neurologie, AP-HP - Hôpital Pitié-Salpêtrière, Paris, France
- Département de Neurologie, AP-HP - Hôpital Pitié-Salpêtrière, Paris, France
| | - Johannes Levin
- Neurologische Klinik und Poliklinik, Ludwig-Maximilians-Universität, Munich, Germany
- Center for Neurodegenerative Diseases (DZNE), Munich, Germany
- Munich Cluster of Systems Neurology, Munich, Germany
| | - Adrian Danek
- Neurologische Klinik und Poliklinik, Ludwig-Maximilians-Universität, Munich, Germany
| | - Markus Otto
- Department of Neurology, University of Ulm, Ulm, Germany
| | - Florence Pasquier
- University of Lille, Lille, France
- Inserm, Lille, France
- CHU, CNR-MAJ, Labex Distalz, LiCEND Lille, Lille, France
| | - Isabel Santana
- Neurology Service, Faculty of Medicine, University Hospital of Coimbra (HUC), University of Coimbra, Coimbra, Portugal
- Center for Neuroscience and Cell Biology, Faculty of Medicine, University of Coimbra, Coimbra, Portugal
| | - John Kornak
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | | | - Howard J Rosen
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Jonathan D Rohrer
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square London, London, UK
| | - Adam L Boxer
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.
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Burgess BL, Cho E, Honigberg L. Neurofilament light as a predictive biomarker of unresolved chemotherapy-induced peripheral neuropathy in subjects receiving paclitaxel and carboplatin. Sci Rep 2022; 12:15593. [PMID: 36114333 PMCID: PMC9481642 DOI: 10.1038/s41598-022-18716-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 08/18/2022] [Indexed: 11/09/2022] Open
Abstract
AbstractManagement of chemotherapy-induced peripheral neuropathy (CIPN) remains a significant challenge in the treatment of cancer. Risk mitigation for CIPN involves preemptive reduction of cumulative dose or reduction of dose intensity upon emergence of symptoms, despite the risk of reduced tumor efficacy. A predictive biomarker for dose-limiting CIPN could improve treatment outcomes by allowing providers to make informed decisions that balance both safety and efficacy. To identify a predictive biomarker of CIPN, markers of neurodegeneration neurofilament-light (NfL), glial fibrillary acidic protein (GFAP), tau and ubiquitin c-terminal hydrolase L1 (UCHL1) were assessed in serum of up to 88 subjects drawn 21 days following the first of 6 treatments with chemotherapeutics paclitaxel and carboplatin. Serum NfL and GFAP were increased with chemotherapy. Further, NfL change predicted subsequent onset of grade 2–3 CIPN during the remainder of the trial (mean treatment duration = 200 days) and trended toward stronger prediction of CIPN that remained unresolved at the end of the study. These results confirm previous reports that serum NfL is increased in CIPN and provide the first evidence that NfL can be used to identify subjects susceptible to dose-limiting paclitaxel and carboplatin induced CIPN prior to onset of symptoms.
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183
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Arslan B, Ayhan Arslan G, Tuncer A, Karabudak R, Sepici Dinçel A. Evaluation of cerebrospinal fluid neurofilament light chain levels in multiple sclerosis and non-demyelinating diseases of the central nervous system: clinical and biochemical perspective. Bosn J Basic Med Sci 2022; 22:699-706. [PMID: 35490364 PMCID: PMC9519158 DOI: 10.17305/bjbms.2021.7326] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 04/25/2022] [Indexed: 11/16/2022] Open
Abstract
The neurofilament light chain (NfL) is a promising biomarker in the diagnosis, prognosis, and treatment response evaluation of neurological diseases. The aims of this study were to compare the cerebrospinal fluid (CSF) NfL levels in multiple sclerosis (MS) and certain non-demyelinating diseases of the central nervous system (NDCNS); to determine the relationship between clinical and radiological features and CSF NfL levels in patients with MS; and to compare the enzyme-linked immunosorbent assay (ELISA) and single molecule array (SIMOA) methods for NfL measurement using paired CSF and serum samples. We retrospectively analyzed the clinical data and performed NfL measurements in CSF and serum samples of newly diagnosed and treatment-naive patients with CNS diseases evaluated between 1 January 2019 and 1 January 2020. Eligible patients were divided into three groups: MS (n=23), differential diagnosis of MS (n=19), and NDCNS (n=42). First, we compared the CSF NfL levels among the three groups using the previously validated CSF ELISA assay. Next, we evaluated the relationship between CSF NfL levels and the clinical and radiological findings in MS group. Finally, we compared CSF and serum samples from patients of the MS groups (paired serum and CSF samples, n=19) using two different methods (ELISA and SIMOA). The CSF NfL level was the highest in the NDCNS group (1169.64 [535.92-5120.11] pg/mL, p=0.025). There was a strong positive correlation between the number of T2 lesions and CSF NfL level (r=0.786, p<0.001) in the MS group. There was excellent consistency between ELISA and SIMOA for CSF samples, but not for serum samples. Our results indicated that CSF NfL levels may also be used in the management of NDCNS and that SIMOA is the most reliable method for serum NfL determination.
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Affiliation(s)
- Burak Arslan
- Department of Medical Biochemistry, Gazi University Faculty of Medicine, Ankara, Turkey; Department of Medical Biochemistry, Erciş State Hospital, Van, Turkey
| | | | - Aslı Tuncer
- Department of Neurology, Hacettepe University Faculty of Medicine, Ankara, Turkey
| | - Rana Karabudak
- Department of Neurology, Hacettepe University Faculty of Medicine, Ankara, Turkey
| | - Aylin Sepici Dinçel
- Department of Medical Biochemistry, Gazi University Faculty of Medicine, Ankara, Turkey
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Bolsewig K, Hok-A-Hin Y, Sepe F, Boonkamp L, Jacobs D, Bellomo G, Paoletti FP, Vanmechelen E, Teunissen C, Parnetti L, Willemse E. A Combination of Neurofilament Light, Glial Fibrillary Acidic Protein, and Neuronal Pentraxin-2 Discriminates Between Frontotemporal Dementia and Other Dementias. J Alzheimers Dis 2022; 90:363-380. [DOI: 10.3233/jad-220318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background: The differential diagnosis of frontotemporal dementia (FTD) is still a challenging task due to its symptomatic overlap with other neurological diseases and the lack of biofluid-based biomarkers. Objective: To investigate the diagnostic potential of a combination of novel biomarkers in cerebrospinal fluid (CSF) and blood. Methods: We included 135 patients from the Centre for Memory Disturbances, University of Perugia, with the diagnoses FTD (n = 37), mild cognitive impairment due to Alzheimer’s disease (MCI-AD, n = 47), Lewy body dementia (PDD/DLB, n = 22), and cognitively unimpaired patients as controls (OND, n = 29). Biomarker levels of neuronal pentraxin-2 (NPTX2), neuronal pentraxin receptor, neurofilament light (NfL) and glial fibrillary acidic protein (GFAP) were measured in CSF, as well as NfL and GFAP in serum. We assessed biomarker differences by analysis of covariance and generalized linear models (GLM). We performed receiver operating characteristics analyses and Spearman correlation to determine biomarker associations. Results: CSF NPTX2 and serum GFAP levels varied most between diagnostic groups. The combination of CSF NPTX2, serum NfL and serum GFAP differentiated FTD from the other groups with good accuracy FTD versus MCI-AD: area under the curve (AUC [95% CI] = 0.89 [0.81–0.96]; FTD versus PDD/DLB: AUC = 0.82 [0.71–0.93]; FTD versus OND: AUC = 0.80 [0.70–0.91]). CSF NPTX2 and serum GFAP correlated positively only in PDD/DLB (ρ= 0.56, p < 0.05). NPTX2 and serum NfL did not correlate in any of the diagnostic groups. Serum GFAP and serum NfL correlated positively in all groups (ρ= 0.47–0.74, p < 0.05). Conclusion: We show the combined potential of CSF NPTX2, serum NfL, and serum GFAP to differentiate FTD from other neurodegenerative disorders.
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Affiliation(s)
- Katharina Bolsewig
- Department of Clinical Chemistry, Neuro chemistry Laboratory and Biobank, Amsterdam Neuroscience, Amsterdam UMC, VU University, The Netherlands
| | - Yanaika Hok-A-Hin
- Department of Clinical Chemistry, Neuro chemistry Laboratory and Biobank, Amsterdam Neuroscience, Amsterdam UMC, VU University, The Netherlands
| | - Federica Sepe
- Department of Clinical Chemistry, Neuro chemistry Laboratory and Biobank, Amsterdam Neuroscience, Amsterdam UMC, VU University, The Netherlands
- Department of Medicine and Surgery, Laboratory of Clinical Neuro chemistry, University of Perugia, Perugia, Italy
| | - Lynn Boonkamp
- Department of Clinical Chemistry, Neuro chemistry Laboratory and Biobank, Amsterdam Neuroscience, Amsterdam UMC, VU University, The Netherlands
| | | | - Giovanni Bellomo
- Department of Medicine and Surgery, Laboratory of Clinical Neuro chemistry, University of Perugia, Perugia, Italy
| | - Federico Paolini Paoletti
- Department of Medicine and Surgery, Laboratory of Clinical Neuro chemistry, University of Perugia, Perugia, Italy
| | | | - Charlotte Teunissen
- Department of Clinical Chemistry, Neuro chemistry Laboratory and Biobank, Amsterdam Neuroscience, Amsterdam UMC, VU University, The Netherlands
| | - Lucilla Parnetti
- Department of Medicine and Surgery, Laboratory of Clinical Neuro chemistry, University of Perugia, Perugia, Italy
| | - Eline Willemse
- Department of Clinical Chemistry, Neuro chemistry Laboratory and Biobank, Amsterdam Neuroscience, Amsterdam UMC, VU University, The Netherlands
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185
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Ning L, Wang B. Neurofilament light chain in blood as a diagnostic and predictive biomarker for multiple sclerosis: A systematic review and meta-analysis. PLoS One 2022; 17:e0274565. [PMID: 36103562 PMCID: PMC9473405 DOI: 10.1371/journal.pone.0274565] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Accepted: 08/30/2022] [Indexed: 11/18/2022] Open
Abstract
Background
Neurofilament light chain (NfL) in cerebrospinal fluid (CSF) is a biomarker of multiple sclerosis (MS). However, CSF sampling is invasive and has limited the clinical application. With the development of highly sensitive single-molecule assay, the accurate quantification of the very low NfL levels in blood become feasible. As evidence being accumulated, we performed a meta-analysis to evaluate the diagnostic and predictive value of blood NfL in MS patients.
Methods
We performed literature search on PubMed, EMBASE, Web of Science and Cochrane Library from inception to May 31, 2022. The blood NfL differences between MS vs. controls, MS vs. clinically isolated syndrome (CIS), progressive MS (PMS) vs. relapsing-remitting MS (RRMS), and MS in relapse vs. MS in remission were estimated by standard mean difference (SMD) and corresponding 95% confidence interval (CI). Pooled hazard ratio (HR) and 95%CI were calculated to predict time to reach Expanded Disability Status Scale (EDSS) score≥4.0 and to relapse.
Results
A total of 28 studies comprising 6545 MS patients and 2477 controls were eligible for meta-analysis of diagnosis value, and 5 studies with 4444 patients were synthesized in analysis of predictive value. Blood NfL levels were significantly higher in MS patients vs. age-matched controls (SMD = 0.64, 95%CI 0.44–0.85, P<0.001), vs. non-matched controls (SMD = 0.76, 95%CI 0.56–0.96, P<0.001) and vs. CIS patients (SMD = 0.30, 95%CI 0.18–0.42, P<0.001), in PMS vs. RRMS (SMD = 0.56, 95%CI 0.27–0.85, P<0.001), and in relapsed patients vs. remitted patients (SMD = 0.54, 95%CI 0.16–0.92, P = 0.005). Patients with high blood NfL levels had shorter time to reach EDSS score≥4.0 (HR = 2.36, 95%CI 1.32–4.21, P = 0.004) but similar time to relapse (HR = 1.32, 95%CI 0.90–1.93, P = 0.155) compared to those with low NfL levels.
Conclusion
As far as we know, this is the first meta-analysis evaluating the diagnosis and predictive value of blood NfL in MS. The present study indicates blood NfL may be a useful biomarker in diagnosing MS, distinguishing MS subtypes and predicting disease worsening in the future.
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Affiliation(s)
- Liangxia Ning
- Department of Neurology, Yuncheng Central Hospital, The Eighth Shanxi Medical University, Yuncheng, China
| | - Bin Wang
- Department of Neurology, Yuncheng Central Hospital, The Eighth Shanxi Medical University, Yuncheng, China
- * E-mail:
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186
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Serum neurofilament levels in patients with multiple sclerosis: A comparison of SIMOA and high sensitivity ELISA assays and contributing factors to ELISA levels. Mult Scler Relat Disord 2022; 67:104177. [PMID: 36130459 DOI: 10.1016/j.msard.2022.104177] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 09/09/2022] [Indexed: 11/22/2022]
Abstract
BACKGROUND Serum neurofilaments (sNfs), especially the most investigated serum neurofilament light chain (sNfL), are promising biomarkers in multiple sclerosis (MS). However, their clinical utility is still limited, given the availability and costs of accessible analytical methods. The gold standard for the detection of sNfs is represented by the single molecule arrays (SIMOA). Recently, a high sensitivity enzyme-linked immunosorbent assay (hsELISA) has also been introduced. The objective of the study was to compare both assays for the determination of sNfL and neurofilament heavy chain (sNfH) concentrations in a defined MS cohort. The second objective was to identify contributing factors to sNfs concentrations determined by hsELISA. METHODS Serum samples were collected from MS patients attending the MS Centre, University Hospital Ostrava, Czech Republic. The levels of sNfs were detected using SIMOA and hsELISA assays. RESULTS The Spearman's rank correlation coefficient between the sNfL SIMOA and sNfL hsELISA and between the sNfH SIMOA and sNfH hsELISA was moderate rs= 0.543 (p = 0.001) and rs= 0.583 (p = 0.001), respectively. The Passing-Bablok regression analysis demonstrated bias between both methods. Equally significant bias between the methods was confirmed by the Bland-Altman plots. Furthermore, confounding factors affecting the sNfL levels were glomerular filtration rate (eGFR; 95% CI -2.34 to -0.04) and sex (95% CI -2.38 to -0.10). The sNfH levels were affected by age (95% CI 0.01 to 0.07), eGFR (95% CI -2.45 to -0.02), body mass index (BMI; 95% CI -0.31 to -0.05), and blood volume (95% CI 0.69 to 3.35). CONCLUSION This analytical study showed significant differences between hsELISA and SIMOA methods, especially for the sNfH concentrations. We identified confounding factors for sNfs levels determined by hsELISA. The sNfs levels were influenced by renal function and sex, whilst sNfH levels were affected by age, BMI, and total blood volume.
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187
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De Schaepdryver M, Masrori P, Van Damme P, Poesen K. Effect of neurofilament analysis on the diagnostic delay in amyotrophic lateral sclerosis. CNS Neurosci Ther 2022; 29:70-77. [PMID: 36047371 PMCID: PMC9804063 DOI: 10.1111/cns.13960] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Revised: 08/14/2022] [Accepted: 08/18/2022] [Indexed: 02/06/2023] Open
Abstract
AIMS The aim of this study was to investigate whether neurofilament light (NfL) and phosphorylated neurofilament heavy (pNfH) in cerebrospinal fluid (CSF), sampled prior to referral to a neuromuscular reference center (NMRC), shorten the diagnostic delay in patients with amyotrophic lateral sclerosis. METHODS In this retrospective study, patients with ALS were included with (i) determination of neurofilaments (Nfs) before referral to the NMRC (preC-Nfs ALS, n = 58), (ii) determination of Nfs at the NMRC (C-Nfs, n = 54) or (iii) with no determination of Nfs (C-No Nfs, n = 180). Fifty-six disease controls were included. RESULTS The preC-Nfs cohort had CSF sampled 2.2 months (range: 0.6-12.0 months) before referral to the NMRC. In this cohort, the diagnostic delay was significantly shorter [median (range): 8.24 (2.37-49.7) months] than in the C-Nfs cases [median (range): 11.4 (2.93-86.5) months; p < 0.05], but not in the C-No Nfs cases. When including the disease progression rate and the presence of a genetic mutation as covariates, the difference ceased to exist (p = 0.14). pNfH and NfL levels in the preC-Nfs cohort were significantly higher than in disease controls (p < 0.0001). Both Nfs showed a similar discriminating performance. CONCLUSIONS CSF Nfs assessed before the diagnosis of ALS at a NMRC decreased the diagnostic delay in specific cases by 3 months and only when other covariates were not taken into account.
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Affiliation(s)
- Maxim De Schaepdryver
- Laboratory for Molecular Neurobiomarker Research, Department of NeurosciencesLeuven Brain Institute, KU LeuvenLeuvenBelgium
| | - Pegah Masrori
- Laboratory of NeurobiologyCenter for Brain & Disease Research, VIBLeuvenBelgium,Department of NeurologyUniversity Hospitals LeuvenLeuvenBelgium,Experimental Neurology, Department of NeurosciencesLeuven Brain Institute, KU LeuvenLeuvenBelgium
| | - Philip Van Damme
- Laboratory of NeurobiologyCenter for Brain & Disease Research, VIBLeuvenBelgium,Department of NeurologyUniversity Hospitals LeuvenLeuvenBelgium,Experimental Neurology, Department of NeurosciencesLeuven Brain Institute, KU LeuvenLeuvenBelgium
| | - Koen Poesen
- Laboratory for Molecular Neurobiomarker Research, Department of NeurosciencesLeuven Brain Institute, KU LeuvenLeuvenBelgium,Laboratory MedicineUniversity Hospitals LeuvenLeuvenBelgium
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188
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Exploring the brain metabolic correlates of process-specific CSF biomarkers in patients with MCI due to Alzheimer's disease: preliminary data. Neurobiol Aging 2022; 117:212-221. [DOI: 10.1016/j.neurobiolaging.2022.03.019] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2021] [Revised: 03/08/2022] [Accepted: 03/15/2022] [Indexed: 12/30/2022]
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189
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Zetterberg H. Biofluid-based biomarkers for Alzheimer's disease-related pathologies: An update and synthesis of the literature. Alzheimers Dement 2022; 18:1687-1693. [PMID: 35213777 PMCID: PMC9514308 DOI: 10.1002/alz.12618] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Revised: 12/05/2021] [Accepted: 01/10/2022] [Indexed: 01/24/2023]
Abstract
The past few years have seen an explosion in sensitive and specific assays for cerebrospinal fluid (CSF) and blood biomarkers for Alzheimer's disease (AD) and related disorders, as well as some novel assays based on pathological seed-induced protein misfolding in patient samples. Here, I review this exciting field that promises to transform dementia diagnostics and disease monitoring. I discuss data on biomarkers for amyloid beta (Aβ) and tau pathology, neurodegeneration, and glial activation, mention the most promising biomarkers for α-synuclein and TDP-43 pathology, and highlight the need for further research into common co-pathologies. Finally, I consider practical aspects of blood-based biomarker-supported AD diagnostics and emphasize the importance of biomarker interpretation in a full clinical context.
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Affiliation(s)
- Henrik Zetterberg
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and Physiologythe Sahlgrenska Academy at the University of GothenburgMölndalSweden,Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden,Department of Neurodegenerative DiseaseUCL Institute of NeurologyLondonUK,UK Dementia Research Institute at UCLLondonUK,Hong Kong Center for Neurodegenerative DiseasesHong KongChina
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190
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Contador J, Pérez-Millan A, Guillen N, Sarto J, Tort-Merino A, Balasa M, Falgàs N, Castellví M, Borrego-Écija S, Juncà-Parella J, Bosch B, Fernández-Villullas G, Ramos-Campoy O, Antonell A, Bargalló N, Sanchez-Valle R, Sala Llonch R, Lladó A. Sex differences in early-onset Alzheimer's disease. Eur J Neurol 2022; 29:3623-3632. [PMID: 36005384 DOI: 10.1111/ene.15531] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2022] [Revised: 08/10/2022] [Accepted: 08/13/2022] [Indexed: 11/29/2022]
Abstract
INTRODUCTION Sex is believed to drive heterogeneity in Alzheimer's disease (AD), although evidence in early-onset AD (<65 years, EOAD) is scarce. METHODS We included 62 EOAD patients and 44 healthy controls (HC) with cerebrospinal fluid (CSF) AD's core biomarkers and neurofilament light chain levels, neuropsychological assessment, and 3T-MRI. We measured cortical thickness (CTh) and hippocampal subfield volumes (HpS) using Freesurfer. Adjusted linear models were used to analyze sex-differences and the relationship between atrophy and cognition. RESULTS Compared to same-sex HC, female-EOAD showed greater cognitive impairment and broader atrophy burden than male-EOAD. In a direct female-EOAD and male-EOAD comparison, there were slight differences in temporal CTh, with no differences in cognition or HpS. CSF tau levels were higher in female-EOAD than in male-EOAD. Greater atrophy was associated with worse cognition in female-EOAD. CONCLUSIONS At diagnosis, there are sex-differences in the pattern of cognitive impairment, atrophy burden and CSF tau in EOAD, suggesting there is an influence of sex on pathology spreading and susceptibility to the disease in EOAD.
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Affiliation(s)
- José Contador
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
| | - Agnès Pérez-Millan
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain.,Institute of Neurosciences. Department of Biomedicine, Faculty of Medicine, University of Barcelona, Barcelona, Spain
| | - Nuria Guillen
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
| | - Jordi Sarto
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
| | - Adrià Tort-Merino
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
| | - Mircea Balasa
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain.,Atlantic Fellow for Equity in Brain Health, Global Brain Heath Institute
| | - Neus Falgàs
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain.,Atlantic Fellow for Equity in Brain Health, Global Brain Heath Institute
| | - Magdalena Castellví
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
| | - Sergi Borrego-Écija
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
| | - Jordi Juncà-Parella
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
| | - Beatriz Bosch
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
| | - Guadalupe Fernández-Villullas
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
| | - Oscar Ramos-Campoy
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
| | - Anna Antonell
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
| | - Nuria Bargalló
- Image Diagnostic Centre Radiology Department, Hospital Clínic de Barcelona, Magnetic Resonance Image Core facility Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain.,Centro de Investigación Biomédica en Red de Salud Mental. CIBERSAM., Spain
| | - Raquel Sanchez-Valle
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
| | - Roser Sala Llonch
- Institute of Neurosciences. Department of Biomedicine, Faculty of Medicine, University of Barcelona, Barcelona, Spain.,Biomedical Imaging Group, Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Barcelona, Spain
| | - Albert Lladó
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain
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Parvizi T, König T, Wurm R, Silvaieh S, Altmann P, Klotz S, Rommer PS, Furtner J, Regelsberger G, Lehrner J, Traub-Weidinger T, Gelpi E, Stögmann E. Real-world applicability of glial fibrillary acidic protein and neurofilament light chain in Alzheimer’s disease. Front Aging Neurosci 2022; 14:887498. [PMID: 36072480 PMCID: PMC9441692 DOI: 10.3389/fnagi.2022.887498] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 07/04/2022] [Indexed: 11/13/2022] Open
Abstract
Background: Blood-based biomarkers may add a great benefit in detecting the earliest neuropathological changes in patients with Alzheimer’s disease (AD). We examined the utility of neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) regarding clinical diagnosis and differentiation between amyloid positive and negative patients. To evaluate the practical application of these biomarkers in a routine clinical setting, we conducted this study in a heterogeneous memory-clinic population.Methods: We included 167 patients in this retrospective cross-sectional study, 123 patients with an objective cognitive decline [mild cognitive impairment (MCI) due to AD, n = 63, and AD-dementia, n = 60] and 44 age-matched healthy controls (HC). Cerebrospinal fluid (CSF) and plasma concentrations of NfL and GFAP were measured with single molecule array (SIMOA®) technology using the Neurology 2-Plex B kit from Quanterix. To assess the discriminatory potential of different biomarkers, age- and sex-adjusted receiver operating characteristic (ROC) curves were calculated and the area under the curve (AUC) of each model was compared.Results: We constructed a panel combining plasma NfL and GFAP with known AD risk factors (Combination panel: age+sex+APOE4+GFAP+NfL). With an AUC of 91.6% (95%CI = 0.85–0.98) for HC vs. AD and 81.7% (95%CI = 0.73–0.90) for HC vs. MCI as well as an AUC of 87.5% (95%CI = 0.73–0.96) in terms of predicting amyloid positivity, this panel showed a promising discriminatory power to differentiate these populations.Conclusion: The combination of plasma GFAP and NfL with well-established risk factors discerns amyloid positive from negative patients and could potentially be applied to identify patients who would benefit from a more invasive assessment of amyloid pathology. In the future, improved prediction of amyloid positivity with a noninvasive test may decrease the number and costs of a more invasive or expensive diagnostic approach.
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Affiliation(s)
- Tandis Parvizi
- Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Theresa König
- Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Raphael Wurm
- Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Sara Silvaieh
- Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Patrick Altmann
- Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Sigrid Klotz
- Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, Vienna, Austria
| | | | - Julia Furtner
- Division of Neuroradiology and Musculoskeletal Radiology, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Günther Regelsberger
- Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Johann Lehrner
- Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Tatjana Traub-Weidinger
- Division of Nuclear Medicine, Department of Biomedical Imaging and Image-Guided Therapy, University of Vienna, Vienna, Austria
| | - Ellen Gelpi
- Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Elisabeth Stögmann
- Department of Neurology, Medical University of Vienna, Vienna, Austria
- *Correspondence: Elisabeth Stögmann
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192
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van Zeggeren IE, ter Horst L, Heijst H, Teunissen CE, van de Beek D, Brouwer MC. Neurofilament light chain in central nervous system infections: a prospective study of diagnostic accuracy. Sci Rep 2022; 12:14140. [PMID: 35986031 PMCID: PMC9391449 DOI: 10.1038/s41598-022-17643-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 07/28/2022] [Indexed: 11/30/2022] Open
Abstract
Diagnosing central nervous system (CNS) infections quickly is often difficult. Neurofilament light chain (NfL) is a component of the axonal cytoskeleton and identified as marker of neuronal damage in several CNS diseases. We evaluated the diagnostic accuracy of NfL for diagnosing CNS infections. We included patients from a prospective cohort of consecutive patients in whom a lumbar puncture was performed for suspected CNS infection in an academic hospital in The Netherlands. The index test was NfL in cerebrospinal fluid (CSF) and reference standard the final clinical diagnosis. Diagnostic accuracy was determined using the area-under-the-curve (AUC) with 95% confidence intervals (CI). The association of CSF NfL with clinical characteristics, diagnosis and outcome was evaluated. Between 2012 and 2015, 273 episodes in adults of which sufficient CSF was available were included. CNS infection was diagnosed in 26%(n = 70), CNS inflammatory disease in 7%(n = 20), systemic infection in 32%(n = 87), and other neurological disorders in 33%(n = 90). Median CSF NfL level was 593 pg/ml (IQR 249–1569) and did not discriminate between diagnostic categories or CNS infection subcategories. AUC for diagnosing any CNS infection compared to patients without CNS infections was 0.50 (95% CI 0.42–0.59). Patients presenting with an altered mental status had higher NfL levels compared to other patients. We concluded that NfL cannot discriminate between causes in patients suspected of CNS infections. High concentrations of NfL are associated with severe neurological disease and the prognostic value of NfL in patients with CNS infections should be investigated in future research.
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Abdelnour C, Agosta F, Bozzali M, Fougère B, Iwata A, Nilforooshan R, Takada LT, Viñuela F, Traber M. Perspectives and challenges in patient stratification in Alzheimer’s disease. Alzheimers Res Ther 2022; 14:112. [PMID: 35964143 PMCID: PMC9375274 DOI: 10.1186/s13195-022-01055-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Accepted: 07/27/2022] [Indexed: 12/14/2022]
Abstract
Background Patient stratification is the division of a patient population into distinct subgroups based on the presence or absence of particular disease characteristics. As patient stratification can be used to account for the underlying pathology of a disease, it can help physicians to tailor therapeutic interventions to individuals and optimize their care management and treatment regime. Alzheimer’s disease, the most common form of dementia, is a heterogeneous disease and its management benefits from patient stratification in clinical trials, and the development of personalized care and treatment strategies for people living with the disease. Main body In this review, we discuss the importance of the stratification of people living with Alzheimer’s disease, the challenges associated with early diagnosis and patient stratification, and the evolution of patient stratification once disease-modifying therapies become widely available. Conclusion Patient stratification plays an important role in drug development in clinical trials and may play an even larger role in clinical practice. A timely diagnosis and stratification of people living with Alzheimer’s disease is paramount in determining people who are at risk of progressing from mild cognitive impairment to Alzheimer’s dementia. There are key issues associated with stratifying patients which include the heterogeneity and complex neurobiology behind Alzheimer’s disease, our inadequately prepared healthcare systems, and the cultural perceptions of Alzheimer’s disease. Stratifying people living with Alzheimer’s disease may be the key in establishing precision and personalized medicine in the field, optimizing disease prevention and pharmaceutical treatment to slow or stop cognitive decline, while minimizing adverse effects.
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194
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Mak G, Menon S, Lu JQ. Neurofilaments in neurologic disorders and beyond. J Neurol Sci 2022; 441:120380. [PMID: 36027641 DOI: 10.1016/j.jns.2022.120380] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 08/07/2022] [Accepted: 08/10/2022] [Indexed: 11/17/2022]
Abstract
Many neurologic diseases can initially present as a diagnostic challenge and even when a diagnosis is made, monitoring of disease activity, progression and response to therapy may be limited with existing clinical and paraclinical assessments. As such, the identification of disease specific biomarkers provides a promising avenue by which diseases can be effectively diagnosed, monitored and used as a prognostic indicator for long-term outcomes. Neurofilaments are an integral component of the neuronal cytoskeleton, where assessment of neurofilaments in the blood, cerebrospinal fluid (CSF) and diseased tissue has been shown to have value in providing diagnostic clarity, monitoring disease activity, tracking progression and treatment efficacy, as well as lending prognostic insight into long-term outcomes. As such, this review attempts to provide a glimpse into the structure and function of neurofilaments, their role in various neurologic and non-neurologic disorders, including uncommon conditions with recent knowledge of neurofilament-related pathology, as well as their applicability in future clinical practice.
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Affiliation(s)
- Gloria Mak
- McMaster University, Department of Medicine, Hamilton, Ontario, Canada
| | - Suresh Menon
- McMaster University, Department of Medicine, Hamilton, Ontario, Canada
| | - Jian-Qiang Lu
- McMaster University, Department of Pathology and Molecular Medicine, Hamilton, Ontario, Canada.
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195
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Andrews EJ, Martini AC, Head E. Exploring the role of sex differences in Alzheimer's disease pathogenesis in Down syndrome. Front Neurosci 2022; 16:954999. [PMID: 36033603 PMCID: PMC9411995 DOI: 10.3389/fnins.2022.954999] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 07/25/2022] [Indexed: 11/14/2022] Open
Abstract
Women are disproportionately affected by Alzheimer's disease (AD), yet little is known about sex-specific effects on the development of AD in the Down syndrome (DS) population. DS is caused by a full or partial triplication of chromosome 21, which harbors the amyloid precursor protein (APP) gene, among others. The majority of people with DS in their early- to mid-40s will accumulate sufficient amyloid-beta (Aβ) in their brains along with neurofibrillary tangles (NFT) for a neuropathological diagnosis of AD, and the triplication of the APP gene is regarded as the main cause. Studies addressing sex differences with age and impact on dementia in people with DS are inconsistent. However, women with DS experience earlier age of onset of menopause, marked by a drop in estrogen, than women without DS. This review focuses on key sex differences observed with age and AD in people with DS and a discussion of possible underlying mechanisms that could be driving or protecting from AD development in DS. Understanding how biological sex influences the brain will lead to development of dedicated therapeutics and interventions to improve the quality of life for people with DS and AD.
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Affiliation(s)
- Elizabeth J. Andrews
- Department of Pathology and Laboratory Medicine, University of California, Irvine, Irvine, CA, United States
| | - Alessandra C. Martini
- Department of Pathology and Laboratory Medicine, University of California, Irvine, Irvine, CA, United States
| | - Elizabeth Head
- Department of Pathology and Laboratory Medicine, University of California, Irvine, Irvine, CA, United States
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, Irvine, CA, United States
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Gleason CE, Zuelsdorff M, Gooding DC, Kind AJH, Johnson AL, James TT, Lambrou NH, Wyman MF, Ketchum FB, Gee A, Johnson SC, Bendlin BB, Zetterberg H. Alzheimer's disease biomarkers in Black and non-Hispanic White cohorts: A contextualized review of the evidence. Alzheimers Dement 2022; 18:1545-1564. [PMID: 34870885 PMCID: PMC9543531 DOI: 10.1002/alz.12511] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Revised: 09/10/2021] [Accepted: 09/15/2021] [Indexed: 02/06/2023]
Abstract
Black Americans are disproportionately affected by dementia. To expand our understanding of mechanisms of this disparity, we look to Alzheimer's disease (AD) biomarkers. In this review, we summarize current data, comparing the few studies presenting these findings. Further, we contextualize the data using two influential frameworks: the National Institute on Aging-Alzheimer's Association (NIA-AA) Research Framework and NIA's Health Disparities Research Framework. The NIA-AA Research Framework provides a biological definition of AD that can be measured in vivo. However, current cut-points for determining pathological versus non-pathological status were developed using predominantly White cohorts-a serious limitation. The NIA's Health Disparities Research Framework is used to contextualize findings from studies identifying racial differences in biomarker levels, because studying biomakers in isolation cannot explain or reduce inequities. We offer recommendations to expand study beyond initial reports of racial differences. Specifically, life course experiences associated with racialization and commonly used study enrollment practices may better account for observations than exclusively biological explanations.
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Affiliation(s)
- Carey E. Gleason
- Division of Geriatrics and GerontologyDepartment of MedicineUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
- Wisconsin Alzheimer's Disease Research CenterMadisonWisconsinUSA
- Geriatric ResearchEducation and Clinical Center (11G)William S. Middleton Memorial Veterans HospitalMadisonWisconsinUSA
| | - Megan Zuelsdorff
- Wisconsin Alzheimer's Disease Research CenterMadisonWisconsinUSA
- University of Wisconsin School of NursingMadisonWisconsinUSA
| | - Diane C. Gooding
- Department of PsychologyUniversity of Wisconsin, MadisonMadisonWisconsinUSA
- Department of PsychiatryUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Amy J. H. Kind
- Division of Geriatrics and GerontologyDepartment of MedicineUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
- Wisconsin Alzheimer's Disease Research CenterMadisonWisconsinUSA
- Geriatric ResearchEducation and Clinical Center (11G)William S. Middleton Memorial Veterans HospitalMadisonWisconsinUSA
- Center for Health Disparities ResearchDepartment of MedicineUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Adrienne L. Johnson
- Center for Tobacco Research and InterventionUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Taryn T. James
- Division of Geriatrics and GerontologyDepartment of MedicineUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
- Wisconsin Alzheimer's Disease Research CenterMadisonWisconsinUSA
| | - Nickolas H. Lambrou
- Geriatric ResearchEducation and Clinical Center (11G)William S. Middleton Memorial Veterans HospitalMadisonWisconsinUSA
| | - Mary F. Wyman
- Geriatric ResearchEducation and Clinical Center (11G)William S. Middleton Memorial Veterans HospitalMadisonWisconsinUSA
- Department of PsychologyUniversity of Wisconsin, MadisonMadisonWisconsinUSA
| | - Fred B. Ketchum
- Department of NeurologyUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Alexander Gee
- Nehemiah Center for Urban Leadership DevelopmentMadisonWisconsinUSA
| | - Sterling C. Johnson
- Division of Geriatrics and GerontologyDepartment of MedicineUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
- Wisconsin Alzheimer's Disease Research CenterMadisonWisconsinUSA
- Geriatric ResearchEducation and Clinical Center (11G)William S. Middleton Memorial Veterans HospitalMadisonWisconsinUSA
| | - Barbara B. Bendlin
- Division of Geriatrics and GerontologyDepartment of MedicineUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
- Wisconsin Alzheimer's Disease Research CenterMadisonWisconsinUSA
| | - Henrik Zetterberg
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and Physiologythe Sahlgrenska Academy at the University of GothenburgMölndalSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
- Department of Neurodegenerative DiseaseUCL Institute of Neurology, Queen SquareLondonUK
- UK Dementia Research Institute at UCLLondonUK
- Hong Kong Center for NeurodegenerationHong KongChina
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197
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Keshavan A, O'Shea F, Chapman MD, Hart MS, Lunn MP, Paterson RW, Rohrer JD, Mummery CJ, Fox NC, Zetterberg H, Schott JM. CSF biomarkers for dementia. Pract Neurol 2022; 22:285-294. [PMID: 35301255 DOI: 10.1136/practneurol-2021-003310] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/18/2022] [Indexed: 11/03/2022]
Abstract
Although cerebrospinal fluid (CSF) biomarker testing is incorporated into some current guidelines for the diagnosis of dementia (such as England's National Institute for Health and Care Excellence (NICE)), it is not widely accessible for most patients for whom biomarkers could potentially change management. Here we share our experience of running a clinical cognitive CSF service and discuss recent developments in laboratory testing including the use of the CSF amyloid-β 42/40 ratio and automated assay platforms. We highlight the importance of collaborative working between clinicians and laboratory staff, of preanalytical sample handling, and discuss the various factors influencing interpretation of the results in appropriate clinical contexts. We advocate for broadening access to CSF biomarkers by sharing clinical expertise, protocols and interpretation with colleagues working in psychiatry and elderly care, especially when access to CSF may be part of a pathway to disease-modifying treatments for Alzheimer's disease and other forms of dementia.
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Affiliation(s)
- Ashvini Keshavan
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Frankie O'Shea
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Miles D Chapman
- Neuroimmunology and CSF Laboratory, National Hospital for Neurology and Neurosurgery, London, UK.,Department of Neuroinflammation, UCL Queen Square Institute of Neurology, London, UK
| | - Melanie S Hart
- Neuroimmunology and CSF Laboratory, National Hospital for Neurology and Neurosurgery, London, UK.,Department of Neuroinflammation, UCL Queen Square Institute of Neurology, London, UK
| | - Michael Pt Lunn
- Neuroimmunology and CSF Laboratory, National Hospital for Neurology and Neurosurgery, London, UK.,MRC Centre for Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London, UK
| | - Ross W Paterson
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Jonathan D Rohrer
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London Institute of Neurology, London, UK
| | - Catherine J Mummery
- Dementia Research Centre, Department of Neurodegenerative Disease, National Hospital for Neurology and Neurosurgery, London, UK
| | - Nick C Fox
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Henrik Zetterberg
- Fluid Biomarkers Laboratory, UK DRI at University College London, UK Dementia Research Institute, London, UK.,Clinical Neurochemistry Laboratory, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg Sahlgrenska Academy, Goteborg, Sweden
| | - Jonathan M Schott
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
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198
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Nguyen AD, Malmstrom TK, Aggarwal G, Miller DK, Vellas B, Morley JE. Serum neurofilament light levels are predictive of all-cause mortality in late middle-aged individuals. EBioMedicine 2022; 82:104146. [PMID: 35830835 PMCID: PMC9284367 DOI: 10.1016/j.ebiom.2022.104146] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 06/13/2022] [Accepted: 06/22/2022] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND Blood biomarkers can offer valuable and easily accessible indicators of normal biological processes, pathogenic conditions, and responses to therapeutic interventions. Recent studies found that levels of neurofilament light chain (NfL) in the blood are associated with mortality in three European cohorts of older adults (median ages 73, 93, and 100 years). Whether similar associations exist in younger adults and in other ethnic groups is currently not known. METHODS We utilized a cohort study that included 294 African Americans (baseline ages 49-65). Serum NfL levels were measured using a Meso Scale Discovery-based assay. Vital status was determined by matching through the National Death Index. FINDINGS Seventy-two participants (24.5%) died during the 14-15 years of follow up (2000-2014). Baseline serum NfL levels were significantly higher in the decedent group (86.1±65.7 pg/ml vs. 50.1±28.0 pg/ml, p < 0·001). In binomial logistic regression models adjusted for age, gender, education, baseline smoking status, BMI, and total comorbidities (0-11), serum NfL levels remained a strong predictor of all-cause mortality, and sensitivity analyses employing multiple additional covariates did not substantively change the relationship. Further, Kaplan-Meier curves based on serum NfL quartiles showed reduced survival in groups with higher serum NfL levels. INTERPRETATION This study found a positive association between serum NfL levels and mortality in late middle-aged and older individuals. While our findings support that serum NfL levels may be a useful biomarker for all-cause mortality, further studies are needed to understand the biological mechanisms underlying this association. FUNDING National Institute on Aging, Saint Louis University.
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Affiliation(s)
- Andrew D Nguyen
- Division of Geriatric Medicine, Department of Internal Medicine, Saint Louis University School of Medicine, St. Louis, MO, USA; Department of Pharmacology and Physiology, Saint Louis University School of Medicine, St. Louis, MO, USA; Henry and Amelia Nasrallah Center for Neuroscience, Saint Louis University, St. Louis, MO, USA.
| | - Theodore K Malmstrom
- Henry and Amelia Nasrallah Center for Neuroscience, Saint Louis University, St. Louis, MO, USA; Department of Psychiatry and Behavioral Neuroscience, Saint Louis University School of Medicine, St. Louis, MO, USA
| | - Geetika Aggarwal
- Division of Geriatric Medicine, Department of Internal Medicine, Saint Louis University School of Medicine, St. Louis, MO, USA; Department of Pharmacology and Physiology, Saint Louis University School of Medicine, St. Louis, MO, USA; Henry and Amelia Nasrallah Center for Neuroscience, Saint Louis University, St. Louis, MO, USA
| | | | - Bruno Vellas
- Gérontopôle de Toulouse, Institut du Vieillissement, Centre Hospitalo-Universitaire de Toulouse, Toulouse, France; UMR 1295 INSERM, University of Toulouse III, Toulouse, France
| | - John E Morley
- Division of Geriatric Medicine, Department of Internal Medicine, Saint Louis University School of Medicine, St. Louis, MO, USA
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199
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Kölliker Frers RA, Otero-Losada M, Kobiec T, Udovin LD, Aon Bertolino ML, Herrera MI, Capani F. Multidimensional overview of neurofilament light chain contribution to comprehensively understanding multiple sclerosis. Front Immunol 2022; 13:912005. [PMID: 35967312 PMCID: PMC9368191 DOI: 10.3389/fimmu.2022.912005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2022] [Accepted: 06/27/2022] [Indexed: 11/13/2022] Open
Abstract
Multiple sclerosis (MS) is an inflammatory neurodegenerative disease characterized by demyelination, progressive axonal loss, and varying clinical presentations. Axonal damage associated with the inflammatory process causes neurofilaments, the major neuron structural proteins, to be released into the extracellular space, reaching the cerebrospinal fluid (CSF) and the peripheral blood. Methodological advances in neurofilaments’ serological detection and imaging technology, along with many clinical and therapeutic studies in the last years, have deepened our understanding of MS immunopathogenesis. This review examines the use of light chain neurofilaments (NFLs) as peripheral MS biomarkers in light of the current clinical and therapeutic evidence, MS immunopathology, and technological advances in diagnostic tools. It aims to highlight NFL multidimensional value as a reliable MS biomarker with a diagnostic-prognostic profile while improving our comprehension of inflammatory neurodegenerative processes, mainly RRMS, the most frequent clinical presentation of MS.
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Affiliation(s)
- Rodolfo A. Kölliker Frers
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Centro de Altos Estudios en Ciencias Humanas y de la Salud, Universidad Abierta Interamericana, Consejo Nacional de Investigaciones Científicas y Técnicas (CAECIHS. UAI-CONICET), Buenos Aires, Argentina
- Unidad de Parasitología, Hospital J. M. Ramos Mejía, Buenos Aires, Argentina
| | - Matilde Otero-Losada
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Centro de Altos Estudios en Ciencias Humanas y de la Salud, Universidad Abierta Interamericana, Consejo Nacional de Investigaciones Científicas y Técnicas (CAECIHS. UAI-CONICET), Buenos Aires, Argentina
- *Correspondence: Matilde Otero-Losada,
| | - Tamara Kobiec
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Centro de Altos Estudios en Ciencias Humanas y de la Salud, Universidad Abierta Interamericana, Consejo Nacional de Investigaciones Científicas y Técnicas (CAECIHS. UAI-CONICET), Buenos Aires, Argentina
- Centro de Investigaciones en Psicología y Psicopedagogía (CIPP), Facultad de Psicología y Psicopedagogía, Pontificia Universidad Católica Argentina (UCA), Buenos Aires, Argentina
| | - Lucas D. Udovin
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Centro de Altos Estudios en Ciencias Humanas y de la Salud, Universidad Abierta Interamericana, Consejo Nacional de Investigaciones Científicas y Técnicas (CAECIHS. UAI-CONICET), Buenos Aires, Argentina
| | - María Laura Aon Bertolino
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Centro de Altos Estudios en Ciencias Humanas y de la Salud, Universidad Abierta Interamericana, Consejo Nacional de Investigaciones Científicas y Técnicas (CAECIHS. UAI-CONICET), Buenos Aires, Argentina
| | - María I. Herrera
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Centro de Altos Estudios en Ciencias Humanas y de la Salud, Universidad Abierta Interamericana, Consejo Nacional de Investigaciones Científicas y Técnicas (CAECIHS. UAI-CONICET), Buenos Aires, Argentina
- Centro de Investigaciones en Psicología y Psicopedagogía (CIPP), Facultad de Psicología y Psicopedagogía, Pontificia Universidad Católica Argentina (UCA), Buenos Aires, Argentina
| | - Francisco Capani
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Centro de Altos Estudios en Ciencias Humanas y de la Salud, Universidad Abierta Interamericana, Consejo Nacional de Investigaciones Científicas y Técnicas (CAECIHS. UAI-CONICET), Buenos Aires, Argentina
- Departamento de Biología, Universidad Argentina John Kennedy (UAJK), Buenos Aires, Argentina
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200
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Yao W, Zhang X, Zhao H, Xu Y, Bai F. Inflammation Disrupts Cognitive Integrity via Plasma Neurofilament Light Chain Coupling Brain Networks in Alzheimer’s Disease. J Alzheimers Dis 2022; 89:505-518. [PMID: 35871350 DOI: 10.3233/jad-220475] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Objective: Background: Plasma neurofilament light chain (NFL) is a recognized biomarker for Alzheimer’s disease (AD) and inflammation. Intrinsically organized default mode network core subsystem and frontoparietal network (FPN) and their interactions support complex cognitive function. The present study investigated the inflammatory effect on cognitive integrity via plasma NFL coupling internetwork interactions in AD. Objective: Objective: This study investigates the hypothesis that inflammation-related plasma NFL could affect the interactions of the core subsystem and FPN, which leads to the aggravation of the clinical symptoms of AD-spectrum patients. Objective: Methods: A total of 112 AD-spectrum participants underwent complete resting-state fMRI, neuropsychological tests, and plasma NFL at baseline (n = 112) and after approximately 17 months of follow-up (n = 112). The specific intersystem changes in the core subsystem and FPN were calculated and compared across groups. Then, the classifications of different AD-spectrum groups were analyzed using the association of plasma NFL and the changed intersystem interacting regions. Finally, mediation analysis was applied to investigate the significance of plasma NFL coupling networks on cognitive impairments in these subjects. Objective: Results: Discrimination of disease-related interactions of the core subsystem and FPN was found in AD-spectrum patients, which was the neural circuit fundamental to plasma NFL disrupting cognitive integrity. Furthermore, the clinical significance of plasma NFL coupling networks on AD identification and monitoring cognitive impairments were revealed in these subjects. Conclusion: The characteristic change in inflammation-related plasma NFL coupled with brain internetwork interactions could be used as a potential observation indicator in the progression of AD patients.
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Affiliation(s)
- Weina Yao
- Department of Neurology, Nanjing Drum Tower Hospital Clinical College of Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China
| | - Xiao Zhang
- Department of Neurology, Nanjing Drum Tower Hospital Clinical College of Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China
| | - Hui Zhao
- Department of Neurology, Nanjing Drum Tower Hospital of The Affiliated Hospital of Nanjing University Medical School, and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China
- Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China
- Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Yun Xu
- Department of Neurology, Nanjing Drum Tower Hospital of The Affiliated Hospital of Nanjing University Medical School, and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China
- Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China
- Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Feng Bai
- Department of Neurology, Nanjing Drum Tower Hospital of The Affiliated Hospital of Nanjing University Medical School, and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China
- Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China
- Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
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