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Liu M, Huang Q, Huang L, Ren S, Cui L, Zhang H, Guan Y, Guo Q, Xie F, Shen D. Dysfunctions of multiscale dynamic brain functional networks in subjective cognitive decline. Brain Commun 2024; 6:fcae010. [PMID: 38304005 PMCID: PMC10833653 DOI: 10.1093/braincomms/fcae010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 11/22/2023] [Accepted: 01/15/2024] [Indexed: 02/03/2024] Open
Abstract
Subjective cognitive decline is potentially the earliest symptom of Alzheimer's disease, whose objective neurological basis remains elusive. To explore the potential biomarkers for subjective cognitive decline, we developed a novel deep learning method based on multiscale dynamical brain functional networks to identify subjective cognitive declines. We retrospectively constructed an internal data set (with 112 subjective cognitive decline and 64 healthy control subjects) to develop and internally validate the deep learning model. Conventional deep learning methods based on static and dynamic brain functional networks are compared. After the model is established, we prospectively collect an external data set (26 subjective cognitive decline and 12 healthy control subjects) for testing. Meanwhile, our method provides monitoring of the transitions between normal and abnormal (subjective cognitive decline-related) dynamical functional network states. The features of abnormal dynamical functional network states are quantified by network and variability metrics and associated with individual cognitions. Our method achieves an area under the receiver operating characteristic curve of 0.807 ± 0.046 in the internal validation data set and of 0.707 (P = 0.007) in the external testing data set, which shows improvements compared to conventional methods. The method further suggests that, at the local level, the abnormal dynamical functional network states are characterized by decreased connectivity strength and increased connectivity variability at different spatial scales. At the network level, the abnormal states are featured by scale-specifically altered modularity and all-scale decreased efficiency. Low tendencies to stay in abnormal states and high state transition variabilities are significantly associated with high general, language and executive functions. Overall, our work supports the deficits in multiscale brain dynamical functional networks detected by the deep learning method as reliable and meaningful neural alternation underpinning subjective cognitive decline.
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Affiliation(s)
- Mianxin Liu
- Shanghai Artificial Intelligence Laboratory, Shanghai 200232, China
- School of Biomedical Engineering, State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China
| | - Qi Huang
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Lin Huang
- Department of Gerontology, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai 200233, China
| | - Shuhua Ren
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Liang Cui
- Department of Gerontology, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai 200233, China
| | - Han Zhang
- School of Biomedical Engineering, State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China
| | - Yihui Guan
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Qihao Guo
- Department of Gerontology, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai 200233, China
| | - Fang Xie
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Dinggang Shen
- School of Biomedical Engineering, State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China
- Shanghai United Imaging Intelligence Co., Ltd., Shanghai 200230, China
- Shanghai Clinical Research and Trial Center, Shanghai, 201210, China
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Wu L, Arvai S, Wang SHJ, Liu AJ, Xu B. Differential diagnosis of mild cognitive impairment of Alzheimer's disease by Simoa p-tau181 measurements with matching plasma and CSF. Front Mol Neurosci 2024; 16:1288930. [PMID: 38260807 PMCID: PMC10800554 DOI: 10.3389/fnmol.2023.1288930] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 11/29/2023] [Indexed: 01/24/2024] Open
Abstract
Alzheimer's disease (AD) is characterized by a long preclinical phase. Although late-stage AD/dementia may be robustly differentiated from cognitively normal individuals by means of a clinical evaluation, PET imaging, and established biofluid biomarkers, disease differentiation between cognitively normal and various subtypes of mild cognitive impairment (MCI) remains a challenging task. Differential biomarkers for early-stage AD diagnosis with accessible biofluid samples are urgently needed. Misfolded phosphorylated tau aggregates (p-tau) are present in multiple neurodegenerative diseases known as "tauopathies", with the most common being AD. P-tau181 is a well-established p-tau biomarker to differentiate AD dementia from non-AD pathology. However, it is unclear if p-tau181 is capable of diagnosing MCI, an early AD stage, from cognitively normal subjects, or if it can discriminate MCI subtypes amnestic MCI (aMCI) from non-amnestic MCI (naMCI). Here we evaluated the capability of p-tau181 in diagnosing MCI from cognitively normal subjects and discriminating aMCI from naMCI subtypes. We collected matching plasma and CSF samples of a clinically diagnosed cohort of 35 cognitively normal, 34 aMCI, 17 naMCI, and 31 AD dementia cases (total 117 participants) with supplemental CSF Aβ42 and total tau AD biomarker levels and performed Simoa p-tau181 assays. The diagnostic capabilities of Simoa p-tau181 assays to differentiate these cohorts were evaluated. We found (i) p-tau181 can robustly differentiate MCI or aMCI from cognitively normal cohorts with matching plasma and CSF samples, but such differentiation is weaker in diagnosing naMCI from cognitively normal groups, (ii) p-tau181 is not capable of differentiating aMCI from naMCI cohorts, and (iii) either factor of Aβ or total tau burden markedly improved differentiation power to diagnose aMCI from cognitively normal group. Plasma and CSF p-tau181 levels may serve as a promising biomarker for diagnosing aMCI from normal controls in the preclinical phase. But more robust new biomarkers are needed to differentiate naMCI from cognitively normal cases or to discriminate between MCI subtypes, aMCI from naMCI.
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Affiliation(s)
- Ling Wu
- Biomanufacturing Research Institute and Technology Enterprise (BRITE), North Carolina Central University, Durham, NC, United States
- Duke-UNC Alzheimer’s Disease Research Center, Durham, NC, United States
| | - Stephanie Arvai
- Department of Neurology, Duke University Medical Center, Durham, NC, United States
| | - Shih-Hsiu J. Wang
- Duke-UNC Alzheimer’s Disease Research Center, Durham, NC, United States
- Department of Neurology, Duke University Medical Center, Durham, NC, United States
- Department of Pathology, Duke University Medical Center, Durham, NC, United States
| | - Andy J. Liu
- Duke-UNC Alzheimer’s Disease Research Center, Durham, NC, United States
- Department of Neurology, Duke University Medical Center, Durham, NC, United States
- Department of Pathology, Duke University Medical Center, Durham, NC, United States
| | - Bin Xu
- Biomanufacturing Research Institute and Technology Enterprise (BRITE), North Carolina Central University, Durham, NC, United States
- Duke-UNC Alzheimer’s Disease Research Center, Durham, NC, United States
- Department of Pharmaceutical Sciences, North Carolina Central University, Durham, NC, United States
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Pozzi FE, Remoli G, Tremolizzo L, Appollonio I, Ferrarese C, Cuffaro L. Brain Health and Cognition in Older Adults: Roadmap and Milestones towards the Implementation of Preventive Strategies. Brain Sci 2024; 14:55. [PMID: 38248270 PMCID: PMC10813413 DOI: 10.3390/brainsci14010055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 01/02/2024] [Accepted: 01/04/2024] [Indexed: 01/23/2024] Open
Abstract
In this narrative review, we delve into the evolving concept of brain health, as recognized by the WHO, focusing on its intersection with cognitive decline. We emphasize the imperative need for preventive strategies, particularly in older adults. We describe the target population that might benefit the most from risk-based approaches-namely, people with subjective cognitive decline. Additionally, we consider universal prevention in cognitively unimpaired middle-aged and older adults. Delving into multidomain personalized preventive strategies, we report on empirical evidence surrounding modifiable risk factors and interventions crucial in mitigating cognitive decline. Next, we highlight the emergence of brain health services (BHS). We explain their proposed role in risk assessment, risk communication, and tailored interventions to reduce the risk of dementia. Commenting on ongoing BHS pilot experiences, we present the inception and framework of our own BHS in Monza, Italy, outlining its operational structure and care pathways. We emphasize the need for global collaboration and intensified research efforts to address the intricate determinants of brain health and their potential impact on healthcare systems worldwide.
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Affiliation(s)
- Federico Emanuele Pozzi
- School of Medicine and Surgery, University of Milano-Bicocca, 20100 Milan, Italy; (G.R.); (L.T.); (I.A.); (C.F.); (L.C.)
- Neurology Department & Brain Health Service, Fondazione IRCCS San Gerardo dei Tintori, 20900 Monza, Italy
- Milan Center for Neuroscience (Neuro-MI), University of Milano-Bicocca, 20126 Milan, Italy
| | - Giulia Remoli
- School of Medicine and Surgery, University of Milano-Bicocca, 20100 Milan, Italy; (G.R.); (L.T.); (I.A.); (C.F.); (L.C.)
- Neurology Department & Brain Health Service, Fondazione IRCCS San Gerardo dei Tintori, 20900 Monza, Italy
| | - Lucio Tremolizzo
- School of Medicine and Surgery, University of Milano-Bicocca, 20100 Milan, Italy; (G.R.); (L.T.); (I.A.); (C.F.); (L.C.)
- Neurology Department & Brain Health Service, Fondazione IRCCS San Gerardo dei Tintori, 20900 Monza, Italy
- Milan Center for Neuroscience (Neuro-MI), University of Milano-Bicocca, 20126 Milan, Italy
| | - Ildebrando Appollonio
- School of Medicine and Surgery, University of Milano-Bicocca, 20100 Milan, Italy; (G.R.); (L.T.); (I.A.); (C.F.); (L.C.)
- Neurology Department & Brain Health Service, Fondazione IRCCS San Gerardo dei Tintori, 20900 Monza, Italy
- Milan Center for Neuroscience (Neuro-MI), University of Milano-Bicocca, 20126 Milan, Italy
| | - Carlo Ferrarese
- School of Medicine and Surgery, University of Milano-Bicocca, 20100 Milan, Italy; (G.R.); (L.T.); (I.A.); (C.F.); (L.C.)
- Neurology Department & Brain Health Service, Fondazione IRCCS San Gerardo dei Tintori, 20900 Monza, Italy
- Milan Center for Neuroscience (Neuro-MI), University of Milano-Bicocca, 20126 Milan, Italy
| | - Luca Cuffaro
- School of Medicine and Surgery, University of Milano-Bicocca, 20100 Milan, Italy; (G.R.); (L.T.); (I.A.); (C.F.); (L.C.)
- Neurology Department & Brain Health Service, Fondazione IRCCS San Gerardo dei Tintori, 20900 Monza, Italy
- Milan Center for Neuroscience (Neuro-MI), University of Milano-Bicocca, 20126 Milan, Italy
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Salimi Y, Domingo-Fernández D, Hofmann-Apitius M, Birkenbihl C. Data-Driven Thresholding Statistically Biases ATN Profiling across Cohort Datasets. J Prev Alzheimers Dis 2024; 11:185-195. [PMID: 38230732 PMCID: PMC10995057 DOI: 10.14283/jpad.2023.100] [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] [Received: 05/19/2023] [Accepted: 07/02/2023] [Indexed: 01/18/2024]
Abstract
BACKGROUND While the amyloid/tau/neurodegeneration (ATN) framework has found wide application in Alzheimer's disease research, it is unclear if thresholds obtained using distinct thresholding methods are concordant within the same dataset and interchangeable across cohorts. OBJECTIVES To investigate the robustness of data-driven thresholding methods and ATN profiling across cohort datasets. DESIGN AND SETTING We evaluated the impact of thresholding methods on ATN profiles by applying five commonly-used methodologies across cohort datasets. We assessed the generalizability of disease patterns discovered within ATN profiles by clustering individuals from different cohorts who were assigned to the same ATN profile. PARTICIPANTS AND MEASUREMENTS Participants with available CSF amyloid-β 1-42, phosphorylated tau, and total tau measurements were included from eleven AD cohort studies. RESULTS We observed high variability among obtained ATN thresholds, both across methods and datasets that impacted the resulting profile assignments of participants significantly. Clustering participants from different cohorts within the same ATN category indicated that identified disease patterns were comparable across most cohorts and biases introduced through distinct thresholding and data representations remained insignificant in most ATN profiles. CONLUSION Thresholding method selection is a decision of statistical relevance that will inevitably bias the resulting profiling and affect its sensitivity and specificity. Thresholds are likely not directly interchangeable between independent cohorts. To apply the ATN framework as an actionable and robust profiling scheme, a comprehensive understanding of the impact of used thresholding methods, their statistical implications, and a validation of results is crucial.
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Affiliation(s)
- Y. Salimi
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, 53757 Germany
- Bonn-Aachen International Center for IT, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, 53115 Germany
- Schloß Birlinghoven, Sankt Augustin, 53757 Germany
| | - D. Domingo-Fernández
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, 53757 Germany
| | - M. Hofmann-Apitius
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, 53757 Germany
- Bonn-Aachen International Center for IT, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, 53115 Germany
| | - C. Birkenbihl
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, 53757 Germany
- Bonn-Aachen International Center for IT, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, 53115 Germany
- Schloß Birlinghoven, Sankt Augustin, 53757 Germany
| | - the Alzheimer’s Disease Neuroimaging Initiative
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, 53757 Germany
- Bonn-Aachen International Center for IT, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, 53115 Germany
- Schloß Birlinghoven, Sankt Augustin, 53757 Germany
| | - the Japanese Alzheimer’s Disease Neuroimaging Initiative
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, 53757 Germany
- Bonn-Aachen International Center for IT, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, 53115 Germany
- Schloß Birlinghoven, Sankt Augustin, 53757 Germany
| | - the Alzheimer’s Disease Repository Without Borders Investigators
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, 53757 Germany
- Bonn-Aachen International Center for IT, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, 53115 Germany
- Schloß Birlinghoven, Sankt Augustin, 53757 Germany
| | - the European Prevention of Alzheimer’s Disease (EPAD) Consortium
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, 53757 Germany
- Bonn-Aachen International Center for IT, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, 53115 Germany
- Schloß Birlinghoven, Sankt Augustin, 53757 Germany
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Mazzeo S, Ingannato A, Giacomucci G, Manganelli A, Moschini V, Balestrini J, Cavaliere A, Morinelli C, Galdo G, Emiliani F, Piazzesi D, Crucitti C, Frigerio D, Polito C, Berti V, Bagnoli S, Padiglioni S, Sorbi S, Nacmias B, Bessi V. Plasma neurofilament light chain predicts Alzheimer's disease in patients with subjective cognitive decline and mild cognitive impairment: A cross-sectional and longitudinal study. Eur J Neurol 2024; 31:e16089. [PMID: 37797300 PMCID: PMC11235835 DOI: 10.1111/ene.16089] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 09/18/2023] [Accepted: 09/21/2023] [Indexed: 10/07/2023]
Abstract
BACKGROUND AND PURPOSE We aimed to evaluate the accuracy of plasma neurofilament light chain (NfL) in predicting Alzheimer's disease (AD) and the progression of cognitive decline in patients with subjective cognitive decline (SCD) and mild cognitive impairment (MCI). METHODS This longitudinal cohort study involved 140 patients (45 with SCD, 73 with MCI, and 22 with AD dementia [AD-D]) who underwent plasma NfL and AD biomarker assessments (cerebrospinal fluid, amyloid positron emission tomography [PET], and 18 F-fluorodeoxyglucose-PET) at baseline. The patients were rated according to the amyloid/tau/neurodegeneration (A/T/N) system and followed up for a mean time of 2.72 ± 0.95 years to detect progression from SCD to MCI and from MCI to AD. Forty-eight patients (19 SCD, 29 MCI) also underwent plasma NfL measurements 2 years after baseline. RESULTS At baseline, plasma NfL detected patients with biomarker profiles consistent with AD (A+/T+/N+ or A+/T+/N-) with high accuracy (area under the curve [AUC] 0.82). We identified cut-off values of 19.45 pg/mL for SCD and 20.45 pg/mL for MCI. During follow-up, nine SCD patients progressed to MCI (progressive SCD [p-SCD]), and 14 MCI patients developed AD dementia (progressive MCI [p-MCI]). The previously identified cut-off values provided good accuracy in identifying p-SCD (80% [95% confidence interval 65.69: 94.31]). The rate of NfL change was higher in p-MCI (3.52 ± 4.06 pg/mL) compared to non-progressive SCD (0.81 ± 1.25 pg/mL) and non-progressive MCI (-0.13 ± 3.24 pg/mL) patients. A rate of change lower than 1.64 pg/mL per year accurately excluded progression from MCI to AD (AUC 0.954). CONCLUSION Plasma NfL concentration and change over time may be a reliable, non-invasive tool to detect AD and the progression of cognitive decline at the earliest stages of the disease.
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Affiliation(s)
- Salvatore Mazzeo
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
- Research and Innovation Centre for Dementia‐CRIDEMAzienda Ospedaliero‐Universitaria CareggiFlorenceItaly
| | - Assunta Ingannato
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
| | - Giulia Giacomucci
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
| | - Alberto Manganelli
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
| | - Valentina Moschini
- Research and Innovation Centre for Dementia‐CRIDEMAzienda Ospedaliero‐Universitaria CareggiFlorenceItaly
| | - Juri Balestrini
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
| | - Arianna Cavaliere
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
| | - Carmen Morinelli
- Research and Innovation Centre for Dementia‐CRIDEMAzienda Ospedaliero‐Universitaria CareggiFlorenceItaly
| | - Giulia Galdo
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
| | - Filippo Emiliani
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
| | - Diletta Piazzesi
- Research and Innovation Centre for Dementia‐CRIDEMAzienda Ospedaliero‐Universitaria CareggiFlorenceItaly
| | - Chiara Crucitti
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
| | - Daniele Frigerio
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
| | | | - Valentina Berti
- Department of Biomedical, Experimental and Clinical Sciences "Mario Serio"University of FlorenceFlorenceItaly
| | - Silvia Bagnoli
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
| | - Sonia Padiglioni
- Research and Innovation Centre for Dementia‐CRIDEMAzienda Ospedaliero‐Universitaria CareggiFlorenceItaly
- Regional Referral Centre for Relational Criticalities – 50139Tuscany RegionItaly
| | - Sandro Sorbi
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
- Research and Innovation Centre for Dementia‐CRIDEMAzienda Ospedaliero‐Universitaria CareggiFlorenceItaly
- IRCCS Fondazione Don Carlo GnocchiFlorenceItaly
| | - Benedetta Nacmias
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
- IRCCS Fondazione Don Carlo GnocchiFlorenceItaly
| | - Valentina Bessi
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
- Research and Innovation Centre for Dementia‐CRIDEMAzienda Ospedaliero‐Universitaria CareggiFlorenceItaly
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Jain L, Khrestian M, Formica S, Tuason ED, Pillai JA, Rao S, Oguh O, Lippa CF, Lopez OL, Berman SB, Tsuang DW, Zabetian CP, Irwin DJ, Galasko DR, Litvan I, Marder KS, Honig LS, Fleisher JE, Galvin JE, Bozoki AC, Taylor AS, Sabbagh MN, Leverenz JB, Bekris LM. ATN cerebrospinal fluid biomarkers in dementia with Lewy bodies: Initial results from the United States Dementia with Lewy Bodies Consortium. Alzheimers Dement 2024; 20:549-562. [PMID: 37740924 PMCID: PMC10840643 DOI: 10.1002/alz.13398] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 06/09/2023] [Accepted: 06/19/2023] [Indexed: 09/25/2023]
Abstract
INTRODUCTION The National Institute on Aging - Alzheimer's Association (NIA-AA) ATN research framework proposes to use biomarkers for amyloid (A), tau (T), and neurodegeneration (N) to stage individuals with AD pathological features and track changes longitudinally. The overall aim was to utilize this framework to characterize pre-mortem ATN status longitudinally in a clinically diagnosed cohort of dementia with Lewy bodies (DLB) and to correlate it with the post mortem diagnosis. METHODS The cohort was subtyped by cerebrospinal fluid (CSF) ATN category. A subcohort had longitudinal data, and a subgroup was neuropathologically evaluated. RESULTS We observed a significant difference in Aβ42/40 after 12 months in the A+T- group. Post mortem neuropathologic analyses indicated that most of the p-Tau 181 positive (T+) cases also had a high Braak stage. DISCUSSION This suggests that DLB patients who are A+ but T- may need to be monitored to determine whether they remain A+ or ever progress to T positivity. HIGHLIGHTS Some A+T- DLB subjects transition from A+ to negative after 12-months. Clinically diagnosed DLB with LBP-AD (A+T+) maintain their positivity. Clinically diagnosed DLB with LBP-AD (A+T+) maintain their positivity. Monitoring of the A+T- sub-type of DLB may be necessary.
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Affiliation(s)
- Lavanya Jain
- Genomic Medicine InstituteCleveland ClinicClevelandOhioUSA
| | | | - Shane Formica
- Genomic Medicine InstituteCleveland ClinicClevelandOhioUSA
| | | | - Jagan A. Pillai
- Cleveland Clinic Lou Ruvo Center for Brain HealthCleveland ClinicClevelandOhioUSA
| | - Stephen Rao
- Cleveland Clinic Lou Ruvo Center for Brain HealthCleveland ClinicClevelandOhioUSA
| | - Odinachi Oguh
- Cleveland Clinic Lou Ruvo Center for Brain Health‐Las VegasCleveland ClinicLas VegasNevadaUSA
| | - Carol F. Lippa
- Cleveland Clinic Lou Ruvo Center for Brain Health‐Las VegasCleveland ClinicLas VegasNevadaUSA
| | - Oscar L. Lopez
- Cognitive Disorders & Comprehensive Alzheimer's Disease CenterThomas Jefferson UniversityPhiladelphiaPennsylvaniaUSA
| | - Sarah B. Berman
- Department of NeurologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Debby W. Tsuang
- Department of Psychiatry and Behavioral SciencesUniversity of Washington School of MedicineSeattleWashingtonUSA
- Geriatric Research, Education, and Clinical CenterVA Puget Sound Health Care SystemSeattleWashingtonUSA
| | - Cyrus P. Zabetian
- Geriatric Research, Education, and Clinical CenterVA Puget Sound Health Care SystemSeattleWashingtonUSA
- Department of NeurologyUniversity of Washington School of MedicineSeattleWashingtonUSA
| | - David J. Irwin
- Department of NeurologyUniversity of Pennsylvania Health SystemPhiladelphiaPennsylvaniaUSA
- Digital Neuropathology LaboratoryPhiladelphiaPennsylvaniaUSA
- Lewy Body Disease Research Center of ExcellencePhiladelphiaPennsylvaniaUSA
- Frontotemporal Degeneration CenterPhiladelphiaPennsylvaniaUSA
| | - Douglas R. Galasko
- Department of NeurosciencesUniversity of CaliforniaSan DiegoCaliforniaUSA
| | - Irene Litvan
- Department of NeurosciencesUniversity of CaliforniaSan DiegoCaliforniaUSA
| | - Karen S. Marder
- Columbia University Irving Medical CenterNew YorkNew YorkUSA
| | - Lawrence S. Honig
- Department of NeurosciencesUniversity of CaliforniaSan DiegoCaliforniaUSA
| | - Jori E. Fleisher
- Department of Neurological SciencesRush Medical CollegeChicagoIllinoisUSA
| | - James E. Galvin
- Department of NeurologyComprehensive Center for Brain HealthUniversity of Miami Miller School of MedicineMiamiFloridaUSA
| | - Andrea C. Bozoki
- Department of NeurologyUniversity of North CarolinaChapel HillNorth CarolinaUSA
| | | | - Marwan N. Sabbagh
- Department of NeurologyBarrow Neurological InstitutePhoenixArizonaUSA
| | - James B. Leverenz
- Cleveland Clinic Lou Ruvo Center for Brain HealthCleveland ClinicClevelandOhioUSA
| | - Lynn M. Bekris
- Genomic Medicine InstituteCleveland ClinicClevelandOhioUSA
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Høilund-Carlsen PF, Alavi A, Barrio JR. PET/CT/MRI in Clinical Trials of Alzheimer's Disease. J Alzheimers Dis 2024; 101:S579-S601. [PMID: 39422954 DOI: 10.3233/jad-240206] [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] [Indexed: 10/19/2024]
Abstract
With the advent of PET imaging in 1976, 2-deoxy-2-[18F]fluoro-D-glucose (FDG)-PET became the preferred method for in vivo investigation of cerebral processes, including regional hypometabolism in Alzheimer's disease. With the emergence of amyloid-PET tracers, [11C]Pittsburgh Compound-B in 2004 and later [18F]florbetapir, [18F]florbetaben, and [18F]flumetamol, amyloid-PET has replaced FDG-PET in Alzheimer's disease anti-amyloid clinical trial treatments to ensure "amyloid positivity" as an entry criterion, and to measure treatment-related decline in cerebral amyloid deposits. MRI has been used to rule out other brain diseases and screen for 'amyloid-related imaging abnormalities' (ARIAs) of two kinds, ARIA-E and ARIA-H, characterized by edema and micro-hemorrhage, respectively, and, to a lesser extent, to measure changes in cerebral volumes. While early immunotherapy trials of Alzheimer's disease showed no clinical effects, newer monoclonal antibody trials reported decreases of 27% to 85% in the cerebral amyloid-PET signal, interpreted by the Food and Drug Administration as amyloid removal expected to result in a reduction in clinical decline. However, due to the lack of diagnostic specificity of amyloid-PET tracers, amyloid positivity cannot prevent the inclusion of non-Alzheimer's patients and even healthy subjects in these clinical trials. Moreover, the "decreasing amyloid accumulation" assessed by amyloid-PET imaging has questionable quantitative value in the presence of treatment-related brain damage (ARIAs). Therefore, future Alzheimer's clinical trials should disregard amyloid-PET imaging and focus instead on assessment of regional brain function by FDG-PET and MRI monitoring of ARIAs and brain volume loss in all trial patients.
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Affiliation(s)
- Poul F Høilund-Carlsen
- Department of Nuclear Medicine, Odense University Hospital, Odense, Denmark
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Abass Alavi
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA
| | - Jorge R Barrio
- Department of Molecular and Medical Pharmacology, David Geffen UCLA School of Medicine, Los Angeles, CA, USA
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Na S, Lee C, Ho S, Hong YJ, Jeong JH, Park KH, Kim S, Wang MJ, Choi SH, Han S, Kang SW, Kang S, Yang DW. A Longitudinal Study on Memory Enhancement in Subjective Cognitive Decline Patients: Clinical and Neuroimaging Perspectives. J Alzheimers Dis 2024; 97:193-204. [PMID: 38108349 DOI: 10.3233/jad-230667] [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] [Indexed: 12/19/2023]
Abstract
BACKGROUND Subjective cognitive decline (SCD) refers to the self-reported persistent cognitive decline despite normal objective testing, increasing the risk of dementia compared to cognitively normal individuals. OBJECTIVE This study aims to investigate the attributes of SCD patients who demonstrated memory function improvement. METHODS In this prospective study of SCD, a total of 120 subjects were enrolled as part of a multicenter cohort study aimed at identifying predictors for the clinical progression to mild cognitive impairment or dementia (CoSCo study). All subjects underwent 18F-florbetaben PET and brain MRI scans at baseline and annual neuropsychological tests. At the 24-month follow-up, we classified SCD patients based on changes in memory function, the z-score of the Seoul verbal learning test delayed recall. RESULTS Of the 120 enrolled patients, 107 successfully completed the 24-month follow-up assessment. Among these, 80 patients (74.8%) with SCD exhibited memory function improvements. SCD patients with improved memory function had a lower prevalence of coronary artery disease at baseline and performed better in the trail-making test part B compared to those without improvement. Anatomical and biomarker analysis showed a lower frequency of amyloid PET positivity and larger volumes in the left and right superior parietal lobes in subjects with improved memory function. CONCLUSIONS Our prospective study indicates that SCD patients experiencing memory improvement over a 24-month period had a lower amyloid burden, fewer cardiovascular risk factors, and superior executive cognitive function. Identifying these key factors associated with cognitive improvement may assist clinicians in predicting future memory function improvements in SCD patients.
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Affiliation(s)
- Seunghee Na
- Department of Neurology, College of Medicine, The Catholic University of Korea, Incheon St. Mary's Hospital, Incheon, South Korea
| | - Chonghwee Lee
- Department of Neurology, College of Medicine, The Catholic University of Korea, Seoul St. Mary's Hospital, Seoul, South Korea
| | - SeongHee Ho
- Department of Neurology, Hanyang University Hanmaeum Changwon Hospital, Changwon, Korea
| | - Yun Jeong Hong
- Department of Neurology, College of Medicine, The Catholic University of Korea, Uijeongbu St. Mary's Hospital, Uijeongbu, South Korea
| | - Jee Hyang Jeong
- Department of Neurology, Ewha Womans University Mokdong Hospital, Ewha Womans University School of Medicine, Seoul, South Korea
| | - Kee Hyung Park
- Department of Neurology, Gachon University Gil Hospital, Incheon, South Korea
| | - SangYun Kim
- Department of Neurology, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, South Korea
| | | | - Seong Hye Choi
- Department of Neurology, Inha University School of Medicine, Incheon, South Korea
| | | | - Seung Wan Kang
- Data Center for Korean EEG, College of Nursing, Seoul National University, Seoul, South Korea
- iMediSync Inc. Seoul, South Korea
| | - Sungmin Kang
- Research and Development, PeopleBio Inc., Seongnam-si, Gyeonggi-do, South Korea
| | - Dong Won Yang
- Department of Neurology, College of Medicine, The Catholic University of Korea, Seoul St. Mary's Hospital, Seoul, South Korea
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Zorkina YA, Morozova IO, Abramova OV, Ochneva AG, Gankina OA, Andryushenko AV, Kurmyshev MV, Kostyuk GP, Morozova AY. [Use of modern classification systems for complex diagnostics of Alzheimer's disease]. Zh Nevrol Psikhiatr Im S S Korsakova 2024; 124:121-127. [PMID: 38261294 DOI: 10.17116/jnevro2024124011121] [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] [Indexed: 01/24/2024]
Abstract
OBJECTIVE To compare the content of β-amyloid (Aβ) peptides Aβ40, Aβ42, total and threonine phosphorylated 181 tau-protein in cerebrospinal fluid (CSF) of patients with the clinical diagnosis of Alzheimer's disease (AD). MATERIAL AND METHODS The study was performed on 64 patients with a diagnosis of dementia and MMSE scores of 24 or lower. All patients underwent lumbar puncture. Aβ40, Aβ42, Aβ42/40 ratio, total tau, phosphorylated tau at threonine 181 were determined in the CSF using a multiplex assay according to the manufacturer's protocol, the concentration was determined in pkg/ml. RESULTS The preliminary diagnosis of AD was made in 3 patients (5%). As a result of the study of protein content in the CSF, signs of AD were detected in 48 (75%) people. The findings suggest that the diagnosis of AD is made 10-14 times less frequently than it should be according to the World Health Organization data. The discrepancy between clinical diagnosis and laboratory findings is confirmed by our study. CONCLUSION Differences in the therapy of dementias and the development of new drugs targeting specific links in the pathogenesis of different types of dementias require accurate and complete diagnosis of dementias, especially AD, as the most common type of dementia.
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Affiliation(s)
- Y A Zorkina
- Serbsky National Medical Research Center of Psychiatry and Narcology, Moscow, Russia
- Alexeev Mental-Health Clinic No. 1 of Moscow Healthcare Department, Moscow, Russia
| | - I O Morozova
- Alexeev Mental-Health Clinic No. 1 of Moscow Healthcare Department, Moscow, Russia
| | - O V Abramova
- Serbsky National Medical Research Center of Psychiatry and Narcology, Moscow, Russia
- Alexeev Mental-Health Clinic No. 1 of Moscow Healthcare Department, Moscow, Russia
| | - A G Ochneva
- Serbsky National Medical Research Center of Psychiatry and Narcology, Moscow, Russia
- Alexeev Mental-Health Clinic No. 1 of Moscow Healthcare Department, Moscow, Russia
| | - O A Gankina
- Alexeev Mental-Health Clinic No. 1 of Moscow Healthcare Department, Moscow, Russia
- Russian Medical Academy of Continuous Professional Education, Moscow, Russia
| | - A V Andryushenko
- Alexeev Mental-Health Clinic No. 1 of Moscow Healthcare Department, Moscow, Russia
- Lomonosov Moscow State University, Moscow, Russia
| | - M V Kurmyshev
- Alexeev Mental-Health Clinic No. 1 of Moscow Healthcare Department, Moscow, Russia
| | - G P Kostyuk
- Alexeev Mental-Health Clinic No. 1 of Moscow Healthcare Department, Moscow, Russia
| | - A Yu Morozova
- Serbsky National Medical Research Center of Psychiatry and Narcology, Moscow, Russia
- Alexeev Mental-Health Clinic No. 1 of Moscow Healthcare Department, Moscow, Russia
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Cisterna-García A, Beric A, Ali M, Pardo JA, Chen HH, Fernandez MV, Norton J, Gentsch J, Bergmann K, Budde J, Perlmutter JS, Morris JC, Cruchaga C, Botia JA, Ibanez L. Cell-free RNA signatures predict Alzheimer's disease. iScience 2023; 26:108534. [PMID: 38089583 PMCID: PMC10711471 DOI: 10.1016/j.isci.2023.108534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Revised: 11/09/2023] [Accepted: 11/20/2023] [Indexed: 02/01/2024] Open
Abstract
There is a need for affordable, scalable, and specific blood-based biomarkers for Alzheimer's disease that can be applied to a population level. We have developed and validated disease-specific cell-free transcriptomic blood-based biomarkers composed by a scalable number of transcripts that capture AD pathobiology even in the presymptomatic stages of the disease. Accuracies are in the range of the current CSF and plasma biomarkers, and specificities are high against other neurodegenerative diseases.
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Affiliation(s)
- Alejandro Cisterna-García
- Department of Psychiatry, Washington University in Saint Louis School of Medicine, Saint Louis, MO, USA
- Departamento de Ingeniería de la Información y las Comunicaciones, Universidad de Murcia, Murcia, Spain
- NeuroGenomics and Informatics Center, Washington University in Saint Louis School of Medicine, Saint Louis, MO, USA
| | - Aleksandra Beric
- Department of Psychiatry, Washington University in Saint Louis School of Medicine, Saint Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University in Saint Louis School of Medicine, Saint Louis, MO, USA
| | - Muhammad Ali
- Department of Psychiatry, Washington University in Saint Louis School of Medicine, Saint Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University in Saint Louis School of Medicine, Saint Louis, MO, USA
| | - Jose Adrian Pardo
- Departamento de Ingeniería de la Información y las Comunicaciones, Universidad de Murcia, Murcia, Spain
| | - Hsiang-Han Chen
- Department of Psychiatry, Washington University in Saint Louis School of Medicine, Saint Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University in Saint Louis School of Medicine, Saint Louis, MO, USA
| | - Maria Victoria Fernandez
- Department of Psychiatry, Washington University in Saint Louis School of Medicine, Saint Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University in Saint Louis School of Medicine, Saint Louis, MO, USA
| | - Joanne Norton
- Department of Psychiatry, Washington University in Saint Louis School of Medicine, Saint Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University in Saint Louis School of Medicine, Saint Louis, MO, USA
- The Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University in Saint Louis, Saint Louis, MO, USA
| | - Jen Gentsch
- Department of Psychiatry, Washington University in Saint Louis School of Medicine, Saint Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University in Saint Louis School of Medicine, Saint Louis, MO, USA
- The Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University in Saint Louis, Saint Louis, MO, USA
| | - Kristy Bergmann
- Department of Psychiatry, Washington University in Saint Louis School of Medicine, Saint Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University in Saint Louis School of Medicine, Saint Louis, MO, USA
| | - John Budde
- Department of Psychiatry, Washington University in Saint Louis School of Medicine, Saint Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University in Saint Louis School of Medicine, Saint Louis, MO, USA
| | - Joel S. Perlmutter
- Department of Neurology, Washington University in Saint Louis School of Medicine, Saint Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University in Saint Louis School of Medicine, Saint Louis, MO, USA
- Department of Radiology, Neuroscience, Physical Therapy, and Occupational Therapy, Washington University in Saint Louis School of Medicine, Saint Louis, MO, USA
| | - John C. Morris
- The Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University in Saint Louis, Saint Louis, MO, USA
- Department of Neurology, Washington University in Saint Louis School of Medicine, Saint Louis, MO, USA
- Department of Pathology and Immunology, Washington University in Saint Louis School of Medicine, Saint Louis, MO, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University in Saint Louis School of Medicine, Saint Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University in Saint Louis School of Medicine, Saint Louis, MO, USA
- The Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University in Saint Louis, Saint Louis, MO, USA
- Department of Neurology, Washington University in Saint Louis School of Medicine, Saint Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University in Saint Louis School of Medicine, Saint Louis, MO, USA
- Department of Genetics, Washington University in Saint Louis School of Medicine, Saint Louis, MO, USA
| | - Juan A. Botia
- Departamento de Ingeniería de la Información y las Comunicaciones, Universidad de Murcia, Murcia, Spain
| | - Laura Ibanez
- Department of Psychiatry, Washington University in Saint Louis School of Medicine, Saint Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University in Saint Louis School of Medicine, Saint Louis, MO, USA
- Department of Neurology, Washington University in Saint Louis School of Medicine, Saint Louis, MO, USA
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Liu M, Cui L, Zhao Z, Ren S, Huang L, Guan Y, Guo Q, Xie F, Huang Q, Shen D. Verifying and refining early statuses in Alzheimer's disease progression: a possibility from deep feature comparison. Cereb Cortex 2023; 33:11486-11500. [PMID: 37833708 DOI: 10.1093/cercor/bhad381] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 09/25/2023] [Accepted: 09/26/2023] [Indexed: 10/15/2023] Open
Abstract
Defining the early status of Alzheimer's disease is challenging. Theoretically, the statuses in the Alzheimer's disease continuum are expected to share common features. Here, we explore to verify and refine candidature early statuses of Alzheimer's disease with features learned from deep learning. We train models on brain functional networks to accurately classify between amnestic and non-amnestic mild cognitive impairments and between healthy controls and mild cognitive impairments. The trained models are applied to Alzheimer's disease and subjective cognitive decline groups to suggest feature similarities among the statuses and identify informative subpopulations. The amnestic mild cognitive impairment vs non-amnestic mild cognitive impairments classifier believes that 71.8% of Alzheimer's disease are amnestic mild cognitive impairment. And 73.5% of subjective cognitive declines are labeled as mild cognitive impairments, 88.8% of which are further suggested as "amnestic mild cognitive impairment." Further multimodal analyses suggest that the amnestic mild cognitive impairment-like Alzheimer's disease, mild cognitive impairment-like subjective cognitive decline, and amnestic mild cognitive impairment-like subjective cognitive decline exhibit more Alzheimer's disease -related pathological changes (elaborated β-amyloid depositions, reduced glucose metabolism, and gray matter atrophy) than non-amnestic mild cognitive impairments -like Alzheimer's disease, healthy control-like subjective cognitive decline, and non-amnestic mild cognitive impairments -like subjective cognitive decline. The test-retest reliability of the subpopulation identification is fair to good in general. The study indicates overall similarity among subjective cognitive decline, amnestic mild cognitive impairment, and Alzheimer's disease and implies their progression relationships. The results support "deep feature comparison" as a potential beneficial framework to verify and refine early Alzheimer's disease status.
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Affiliation(s)
- Mianxin Liu
- School of Biomedical Engineering, State Key Laboratory of Advanced Medical Materials and Devices, Shanghai Tech University, Shanghai 201210, China
- Shanghai Artificial Intelligence Laboratory, Shanghai 200232, China
| | - Liang Cui
- Department of Gerontology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China
| | - Zixiao Zhao
- Department of Laboratory Medicine, Center for Molecular Imaging and Translational Medicine, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen, Fujian 361102, China
| | - Shuhua Ren
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Lin Huang
- Department of Gerontology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China
| | - Yihui Guan
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai 200040, China
- National Center for Neurological Disorders, Shanghai 201112, China
| | - Qihao Guo
- Department of Gerontology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China
| | - Fang Xie
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai 200040, China
- National Center for Neurological Disorders, Shanghai 201112, China
- State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Qi Huang
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Dinggang Shen
- School of Biomedical Engineering, State Key Laboratory of Advanced Medical Materials and Devices, Shanghai Tech University, Shanghai 201210, China
- Shanghai United Imaging Intelligence Co., Ltd., Shanghai 200230, China
- Shanghai Clinical Research and Trial Center, Shanghai, 201210, China
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Allen AT, Cole WR, Walton SR, Kerr ZY, Chandran A, Mannix R, Guskiewicz KM, Meehan WP, Echemendia RJ, McCrea MA, Brett BL. Subjective and Performance-Based Cognition and Their Associations with Head Injury History in Older Former National Football League Players. Med Sci Sports Exerc 2023; 55:2170-2179. [PMID: 37443456 PMCID: PMC10787800 DOI: 10.1249/mss.0000000000003256] [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: 07/15/2023]
Abstract
PURPOSE Investigate the association between self-reported subjective and performance-based cognition among older (50-70 years) former professional American football players, as well as the relationship of cognitive measures with concussion history and years of football participation, as a proxy for repetitive head impact exposure. METHODS Among older former National Football League (NFL) players ( N = 172; mean age = 60.69 ± 5.64), associations of subjective (Patient Reported Outcome Measurement Information System Cognitive Function-Short Form) and performance-based cognitive measures (Brief Test of Adult Cognition by Telephone [BTACT] Executive Function and Episodic Memory indices) were assessed via univariable and multivariable regression models, with a priori covariates of depression and race. A similar univariate and multivariable regression approach assessed associations between concussion history and years of football participation with subjective and performance-based cognitive measures. In a sample subset ( n = 114), stability of subjective cognitive rating was assessed via partial correlation. RESULTS Subjective ratings of cognition were significantly associated with performance-based assessment, with moderate effect sizes (episodic memory ηp2 = 0.12; executive function ηp2 = 0.178). These associations were weakened, but remained significant ( P s < 0.05), with the inclusion of covariates. Greater concussion history was associated with lower subjective cognitive function ( ηp2 = 0.114, P < 0.001), but not performance-based cognition. The strength of association between concussion history and subjective cognition was substantially weakened with inclusion of covariates ( ηp2 = 0.057). Years of participation were not associated with measures of subjective or objective cognition ( P s > 0.05). CONCLUSIONS These findings reinforce the importance of comprehensive evaluation reflecting both subjective and objective measures of cognition, as well as the consideration of patient-specific factors, as part of a comprehensive neurobehavioral and health assessment of older former contact sport athletes.
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Affiliation(s)
- Andrew T. Allen
- Department of Neurosurgery, Medical College of Wisconsin, Wauwatosa, WI
| | - Wesley R. Cole
- Department of Exercise and Sport Science, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Samuel R. Walton
- Department of Physical Medicine and Rehabilitation, Virginia Commonwealth University School of Medicine, Richmond, VA
| | - Zachary Yukio Kerr
- Department of Exercise and Sport Science, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Avinash Chandran
- Department of Physical Medicine and Rehabilitation, Virginia Commonwealth University School of Medicine, Richmond, VA
- Datalys Center for Sports Injury Research and Prevention, Indianapolis, IN
| | - Rebekah Mannix
- Division of Emergency Medicine, Boston Children’s Hospital, Boston, MA
- Department of Pediatrics and Emergency Medicine, Harvard Medical School, Boston, MA
| | - Kevin M. Guskiewicz
- Department of Exercise and Sport Science, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - William P. Meehan
- Sports Medicine Division, Boston Children’s Hospital, Boston, MA
- Department of Pediatrics and Orthopedics, Harvard Medical School, Boston, MA
| | - Ruben J. Echemendia
- Psychological and Neurobehavioral Associates, Inc, State College, PA
- University Orthopedics Center Concussion Clinic, State College, PA
| | - Michael A. McCrea
- Department of Neurosurgery, Medical College of Wisconsin, Wauwatosa, WI
- Department of Neurology, Medical College of Wisconsin, Wauwatosa, WI
| | - Benjamin L. Brett
- Department of Neurosurgery, Medical College of Wisconsin, Wauwatosa, WI
- Department of Neurology, Medical College of Wisconsin, Wauwatosa, WI
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Perna L, Stocker H, Burow L, Beyer L, Trares K, Kurz C, Gürsel S, Holleczek B, Tatò M, Beyreuther K, Mons U, Gerwert K, Perneczky R, Schöttker B, Brenner H. Subjective cognitive complaints and blood biomarkers of neurodegenerative diseases: a longitudinal cohort study. Alzheimers Res Ther 2023; 15:198. [PMID: 37951931 PMCID: PMC10638700 DOI: 10.1186/s13195-023-01341-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 10/25/2023] [Indexed: 11/14/2023]
Abstract
BACKGROUND Subjective cognitive complaints (SCC) have been mostly studied in the context of Alzheimer's disease in memory clinic settings. The potential of combining SCC with genetic information and blood biomarkers of neurodegenerative diseases for risk assessment of dementia and depression in the absence of dementia among community-dwelling older adults has so far not been explored. METHODS Data were based on a population-based cohort of 6357 participants with a 17-year follow-up (ESTHER study) and a clinic-based cohort of 422 patients. Participants of both cohorts were grouped according to the diagnosis of dementia (yes/no) and the diagnosis of depression in the absence of dementia (yes/no). Participants without dementia included both cognitively unimpaired participants and cognitively impaired participants. Genetic information (APOE ε4 genotype) and blood-based biomarkers of neurodegenerative diseases (glial fibrillary acidic protein; GFAP, neurofilament light chain; NfL, phosphorylated tau181; p-tau181) were available in the ESTHER study and were determined with Simoa Technology in a nested case-control design. Logistic regression models adjusted for relevant confounders were run for the outcomes of all-cause dementia and depression in the absence of dementia. RESULTS The results showed that persistent SCC were associated both with increased risk of all-cause dementia and of depression without dementia, independently of the diagnostic setting. However, the results for the ESTHER study also showed that the combination of subjective complaints with APOE ε4 and with increased GFAP concentrations in the blood yielded a substantially increased risk of all-cause dementia (OR 5.35; 95%CI 3.25-8.81, p-value < 0.0001 and OR 7.52; 95%CI 2.79-20.29, p-value < 0.0001, respectively) but not of depression. Associations of NfL and p-tau181 with risk of all-cause dementia and depression were not statistically significant, either alone or in combination with SCC, but increased concentrations of p-tau181 seemed to be associated with an increased risk for depression. CONCLUSION In community and clinical settings, SCC predict both dementia and depression in the absence of dementia. The addition of GFAP could differentiate between the risk of all-cause dementia and the risk of depression among individuals without dementia.
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Affiliation(s)
- Laura Perna
- Department Genes and Environment, Max Planck Institute of Psychiatry, 80804, Munich, Germany.
- Division of Mental Health of Older Adults, Department of Psychiatry and Psychotherapy, University Hospital, LMU, Munich, Germany.
| | - Hannah Stocker
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Network Aging Research (NAR), Heidelberg University, Heidelberg, Germany
| | - Lena Burow
- Division of Mental Health of Older Adults, Department of Psychiatry and Psychotherapy, University Hospital, LMU, Munich, Germany
| | - Léon Beyer
- Faculty of Biology and Biotechnology, Department of Biophysics, Ruhr-University Bochum, 44801, Bochum, Germany
- Center for Protein Diagnostics (ProDi), Ruhr-University Bochum, 44801, Bochum, Germany
| | - Kira Trares
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Carolin Kurz
- Division of Mental Health of Older Adults, Department of Psychiatry and Psychotherapy, University Hospital, LMU, Munich, Germany
| | - Selim Gürsel
- Division of Mental Health of Older Adults, Department of Psychiatry and Psychotherapy, University Hospital, LMU, Munich, Germany
| | - Bernd Holleczek
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Saarland Cancer Registry, 66117, Saarbrücken, Germany
| | - Maia Tatò
- Division of Mental Health of Older Adults, Department of Psychiatry and Psychotherapy, University Hospital, LMU, Munich, Germany
| | - Konrad Beyreuther
- Network Aging Research (NAR), Heidelberg University, Heidelberg, Germany
| | - Ute Mons
- Department of Cardiology, Faculty of Medicine, University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Klaus Gerwert
- Faculty of Biology and Biotechnology, Department of Biophysics, Ruhr-University Bochum, 44801, Bochum, Germany
- Center for Protein Diagnostics (ProDi), Ruhr-University Bochum, 44801, Bochum, Germany
| | - Robert Perneczky
- Division of Mental Health of Older Adults, Department of Psychiatry and Psychotherapy, University Hospital, LMU, Munich, Germany
- Ageing Epidemiology (AGE) Research Unit, School of Public Health, Imperial College London, London, UK
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
- Sheffield Institute for Translational Neurology (SITraN), University of Sheffield, Sheffield, UK
| | - Ben Schöttker
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Network Aging Research (NAR), Heidelberg University, Heidelberg, Germany
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Network Aging Research (NAR), Heidelberg University, Heidelberg, Germany
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Abbatantuono C, Alfeo F, Clemente L, Lancioni G, De Caro MF, Livrea P, Taurisano P. Current Challenges in the Diagnosis of Progressive Neurocognitive Disorders: A Critical Review of the Literature and Recommendations for Primary and Secondary Care. Brain Sci 2023; 13:1443. [PMID: 37891810 PMCID: PMC10605551 DOI: 10.3390/brainsci13101443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Revised: 09/27/2023] [Accepted: 10/02/2023] [Indexed: 10/29/2023] Open
Abstract
Screening for early symptoms of cognitive impairment enables timely interventions for patients and their families. Despite the advances in dementia diagnosis, the current nosography of neurocognitive disorders (NCDs) seems to overlook some clinical manifestations and predictors that could contribute to understanding the conversion from an asymptomatic stage to a very mild one, eventually leading to obvious disease. The present review examines different diagnostic approaches in view of neurophysiological and neuropsychological evidence of NCD progression, which may be subdivided into: (1) preclinical stage; (2) transitional stage; (3) prodromal or mild stage; (4) major NCD. The absence of univocal criteria and the adoption of ambiguous or narrow labels might complicate the diagnostic process. In particular, it should be noted that: (1) only neuropathological hallmarks characterize preclinical NCD; (2) transitional NCD must be assessed through proactive neuropsychological protocols; (3) prodromal/mild NCDs are based on cognitive functional indicators; (4) major NCD requires well-established tools to evaluate its severity stage; (5) insight should be accounted for by both patient and informants. Therefore, the examination of evolving epidemiological and clinical features occurring at each NCD stage may orient primary and secondary care, allowing for more targeted prevention, diagnosis, and/or treatment of both cognitive and functional impairment.
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Affiliation(s)
- Chiara Abbatantuono
- Department of Translational Biomedicine and Neuroscience (DiBrain), University of Bari “Aldo Moro”, 70121 Bari, Italy; (C.A.); (L.C.); (G.L.); (M.F.D.C.)
| | - Federica Alfeo
- Department of Education, Communication and Psychology (For.Psi.Com), University of Bari “Aldo Moro”, 70121 Bari, Italy;
| | - Livio Clemente
- Department of Translational Biomedicine and Neuroscience (DiBrain), University of Bari “Aldo Moro”, 70121 Bari, Italy; (C.A.); (L.C.); (G.L.); (M.F.D.C.)
| | - Giulio Lancioni
- Department of Translational Biomedicine and Neuroscience (DiBrain), University of Bari “Aldo Moro”, 70121 Bari, Italy; (C.A.); (L.C.); (G.L.); (M.F.D.C.)
- Lega F D’Oro Research Center, 60027 Osimo, Italy
| | - Maria Fara De Caro
- Department of Translational Biomedicine and Neuroscience (DiBrain), University of Bari “Aldo Moro”, 70121 Bari, Italy; (C.A.); (L.C.); (G.L.); (M.F.D.C.)
| | | | - Paolo Taurisano
- Department of Translational Biomedicine and Neuroscience (DiBrain), University of Bari “Aldo Moro”, 70121 Bari, Italy; (C.A.); (L.C.); (G.L.); (M.F.D.C.)
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65
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Li H, Tan CC, Tan L, Xu W. Predictors of cognitive deterioration in subjective cognitive decline: evidence from longitudinal studies and implications for SCD-plus criteria. J Neurol Neurosurg Psychiatry 2023; 94:844-854. [PMID: 36868847 DOI: 10.1136/jnnp-2022-330246] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 01/28/2023] [Indexed: 03/05/2023]
Abstract
BACKGROUND Subjective cognitive decline (SCD) is an early manifestation of cognitive deterioration (CD) in some individuals. Therefore, it is worthwhile to conduct a systematic review and meta-analysis to summarise predictors of CD among individuals with SCD. METHOD PubMed, Embase, and Cochrane Library were searched until May 2022. Longitudinal studies that assessed factors associated with CD in SCD population were included. Multivariable-adjusted effect estimates were pooled using random-effects models. The credibility of evidence was assessed. The study protocol was registered with PROSPERO. RESULTS A total of 69 longitudinal studies were identified for systematic review, of which 37 were included for the meta-analysis. The mean conversion rate of SCD to any CD was 19.8%, including all-cause dementia (7.3%) and Alzheimer's disease (4.9%). Sixteen factors (66.67%) were found as predictors, including 5 SCD features (older age at onset, stable SCD, both self- and informant-reported SCD, worry and SCD in the memory clinic), 4 biomarkers (cerebral amyloid β-protein deposition, lower scores of Hulstaert formula, higher total tau in the cerebrospinal fluid and hippocampus atrophy), 4 modifiable factors (lower education, depression, anxiety and current smoking), 2 unmodifiable factors (apolipoprotein E4 and older age) and worse performance on Trail Making Test B. The robustness of overall evidence was impaired by risk of bias and heterogeneity. CONCLUSION This study constructed a risk factor profile for SCD to CD conversion, supporting and supplementing the existing list of features for identifying SCD populations at high risk of objective cognitive decline or dementia. These findings could promote early identification and management of high-risk populations to delay dementia onset. PROSPERO REGISTRATION NUMBER CRD42021281757.
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Affiliation(s)
- Han Li
- Neurology department, Qingdao Municipal Hospital Group, Qingdao University, Qingdao, Shandong, China
- Medical College, Qingdao University, Qingdao, China
| | - Chen-Chen Tan
- Neurology department, Qingdao Municipal Hospital Group, Qingdao University, Qingdao, Shandong, China
| | - Lan Tan
- Neurology department, Qingdao Municipal Hospital Group, Qingdao University, Qingdao, Shandong, China
| | - Wei Xu
- Neurology department, Qingdao Municipal Hospital Group, Qingdao University, Qingdao, Shandong, China
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Gouilly D, Rafiq M, Nogueira L, Salabert AS, Payoux P, Péran P, Pariente J. Beyond the amyloid cascade: An update of Alzheimer's disease pathophysiology. Rev Neurol (Paris) 2023; 179:812-830. [PMID: 36906457 DOI: 10.1016/j.neurol.2022.12.006] [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: 03/08/2022] [Revised: 10/02/2022] [Accepted: 12/02/2022] [Indexed: 03/13/2023]
Abstract
Alzheimer's disease (AD) is a multi-etiology disease. The biological system of AD is associated with multidomain genetic, molecular, cellular, and network brain dysfunctions, interacting with central and peripheral immunity. These dysfunctions have been primarily conceptualized according to the assumption that amyloid deposition in the brain, whether from a stochastic or a genetic accident, is the upstream pathological change. However, the arborescence of AD pathological changes suggests that a single amyloid pathway might be too restrictive or inconsistent with a cascading effect. In this review, we discuss the recent human studies of late-onset AD pathophysiology in an attempt to establish a general updated view focusing on the early stages. Several factors highlight heterogenous multi-cellular pathological changes in AD, which seem to work in a self-amplifying manner with amyloid and tau pathologies. Neuroinflammation has an increasing importance as a major pathological driver, and perhaps as a convergent biological basis of aging, genetic, lifestyle and environmental risk factors.
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Affiliation(s)
- D Gouilly
- Toulouse Neuroimaging Center, Toulouse, France.
| | - M Rafiq
- Toulouse Neuroimaging Center, Toulouse, France; Department of Cognitive Neurology, Epilepsy and Movement Disorders, CHU Toulouse Purpan, France
| | - L Nogueira
- Department of Cell Biology and Cytology, CHU Toulouse Purpan, France
| | - A-S Salabert
- Toulouse Neuroimaging Center, Toulouse, France; Department of Nuclear Medicine, CHU Toulouse Purpan, France
| | - P Payoux
- Toulouse Neuroimaging Center, Toulouse, France; Department of Nuclear Medicine, CHU Toulouse Purpan, France; Center of Clinical Investigation, CHU Toulouse Purpan (CIC1436), France
| | - P Péran
- Toulouse Neuroimaging Center, Toulouse, France
| | - J Pariente
- Toulouse Neuroimaging Center, Toulouse, France; Department of Cognitive Neurology, Epilepsy and Movement Disorders, CHU Toulouse Purpan, France; Center of Clinical Investigation, CHU Toulouse Purpan (CIC1436), France
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Ikonnikova A, Morozova A, Antonova O, Ochneva A, Fedoseeva E, Abramova O, Emelyanova M, Filippova M, Morozova I, Zorkina Y, Syunyakov T, Andryushchenko A, Andreuyk D, Kostyuk G, Gryadunov D. Evaluation of the Polygenic Risk Score for Alzheimer's Disease in Russian Patients with Dementia Using a Low-Density Hydrogel Oligonucleotide Microarray. Int J Mol Sci 2023; 24:14765. [PMID: 37834213 PMCID: PMC10572681 DOI: 10.3390/ijms241914765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 09/25/2023] [Accepted: 09/28/2023] [Indexed: 10/15/2023] Open
Abstract
The polygenic risk score (PRS), together with the ɛ4 allele of the APOE gene (APOE-ɛ4), has shown high potential for Alzheimer's disease (AD) risk prediction. The aim of this study was to validate the model of polygenic risk in Russian patients with dementia. A microarray-based assay was developed to identify 21 markers of polygenic risk and ɛ alleles of the APOE gene. This case-control study included 348 dementia patients and 519 cognitively normal volunteers. Cerebrospinal fluid (CSF) amyloid-β (Aβ) and tau protein levels were assessed in 57 dementia patients. PRS and APOE-ɛ4 were significant genetic risk factors for dementia. Adjusted for APOE-ɛ4, individuals with PRS corresponding to the fourth quartile had an increased risk of dementia compared to the first quartile (OR 1.85; p-value 0.002). The area under the curve (AUC) was 0.559 for the PRS model only, and the inclusion of APOE-ɛ4 improved the AUC to 0.604. PRS was positively correlated with tTau and pTau181 and inversely correlated with Aβ42/Aβ40 ratio. Carriers of APOE-ɛ4 had higher levels of tTau and pTau181 and lower levels of Aβ42 and Aβ42/Aβ40. The developed assay can be part of a strategy for assessing individuals for AD risk, with the purpose of assisting primary preventive interventions.
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Affiliation(s)
- Anna Ikonnikova
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia; (O.A.); (E.F.); (M.E.); (M.F.); (D.G.)
| | - Anna Morozova
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia; (A.M.); (A.O.); (O.A.); (I.M.); (Y.Z.); (T.S.); (A.A.); (D.A.); (G.K.)
- Department of Basic and Applied Neurobiology, V. Serbsky Federal Medical Research Centre of Psychiatry and Narcology, Kropotkinsky per. 23, 119034 Moscow, Russia
| | - Olga Antonova
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia; (O.A.); (E.F.); (M.E.); (M.F.); (D.G.)
| | - Alexandra Ochneva
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia; (A.M.); (A.O.); (O.A.); (I.M.); (Y.Z.); (T.S.); (A.A.); (D.A.); (G.K.)
| | - Elena Fedoseeva
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia; (O.A.); (E.F.); (M.E.); (M.F.); (D.G.)
| | - Olga Abramova
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia; (A.M.); (A.O.); (O.A.); (I.M.); (Y.Z.); (T.S.); (A.A.); (D.A.); (G.K.)
- Department of Basic and Applied Neurobiology, V. Serbsky Federal Medical Research Centre of Psychiatry and Narcology, Kropotkinsky per. 23, 119034 Moscow, Russia
| | - Marina Emelyanova
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia; (O.A.); (E.F.); (M.E.); (M.F.); (D.G.)
| | - Marina Filippova
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia; (O.A.); (E.F.); (M.E.); (M.F.); (D.G.)
| | - Irina Morozova
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia; (A.M.); (A.O.); (O.A.); (I.M.); (Y.Z.); (T.S.); (A.A.); (D.A.); (G.K.)
| | - Yana Zorkina
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia; (A.M.); (A.O.); (O.A.); (I.M.); (Y.Z.); (T.S.); (A.A.); (D.A.); (G.K.)
- Department of Basic and Applied Neurobiology, V. Serbsky Federal Medical Research Centre of Psychiatry and Narcology, Kropotkinsky per. 23, 119034 Moscow, Russia
| | - Timur Syunyakov
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia; (A.M.); (A.O.); (O.A.); (I.M.); (Y.Z.); (T.S.); (A.A.); (D.A.); (G.K.)
- International Centre for Education and Research in Neuropsychiatry (ICERN), Samara State Medical University, 443016 Samara, Russia
| | - Alisa Andryushchenko
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia; (A.M.); (A.O.); (O.A.); (I.M.); (Y.Z.); (T.S.); (A.A.); (D.A.); (G.K.)
| | - Denis Andreuyk
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia; (A.M.); (A.O.); (O.A.); (I.M.); (Y.Z.); (T.S.); (A.A.); (D.A.); (G.K.)
- Economy Faculty, M.V. Lomonosov Moscow State University, 119991 Moscow, Russia
| | - Georgy Kostyuk
- Mental-Health Clinic No. 1 Named after N.A. Alekseev, Zagorodnoe Highway 2, 115191 Moscow, Russia; (A.M.); (A.O.); (O.A.); (I.M.); (Y.Z.); (T.S.); (A.A.); (D.A.); (G.K.)
- Department of Psychiatry, Federal State Budgetary Educational Institution of Higher Education “Moscow State University of Food Production”, Volokolamskoye Highway 11, 125080 Moscow, Russia
| | - Dmitry Gryadunov
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia; (O.A.); (E.F.); (M.E.); (M.F.); (D.G.)
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Brunelli S, Giannella E, Bizzaglia M, De Angelis D, Sancesario GM. Secondary neurodegeneration following Stroke: what can blood biomarkers tell us? Front Neurol 2023; 14:1198216. [PMID: 37719764 PMCID: PMC10502514 DOI: 10.3389/fneur.2023.1198216] [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: 03/31/2023] [Accepted: 08/14/2023] [Indexed: 09/19/2023] Open
Abstract
Stroke is one of the leading causes of death and the primary source of disability in adults, resulting in neuronal necrosis of ischemic areas, and in possible secondary degeneration of regions surrounding or distant to the initial damaged area. Secondary neurodegeneration (SNDG) following stroke has been shown to have different pathogenetic origins including inflammation, neurovascular response and cytotoxicity, but can be associated also to regenerative processes. Aside from focal neuronal loss, ipsilateral and contralateral effects distal to the lesion site, disruptions of global functional connectivity and a transcallosal diaschisis have been reported in the chronic stages after stroke. Furthermore, SNDG can be observed in different areas not directly connected to the primary lesion, such as thalamus, hippocampus, amygdala, substantia nigra, corpus callosum, bilateral inferior fronto-occipital fasciculus and superior longitudinal fasciculus, which can be highlighted by neuroimaging techniques. Although the clinical relevance of SNDG following stroke has not been well understood, the identification of specific biomarkers that reflect the brain response to the damage, is of paramount importance to investigate in vivo the different phases of stroke. Actually, brain-derived markers, particularly neurofilament light chain, tau protein, S100b, in post-stroke patients have yielded promising results. This review focuses on cerebral morphological modifications occurring after a stroke, on associated cellular and molecular changes and on state-of-the-art of biomarkers in acute and chronic phase. Finally, we discuss new perspectives regarding the implementation of blood-based biomarkers in clinical practice to improve the rehabilitation approaches and post stroke recovery.
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Affiliation(s)
- Stefano Brunelli
- NeuroRehabilitation Unit 4, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Emilia Giannella
- Clinical Neurochemistry Unit and Biobank, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Mirko Bizzaglia
- Radiology and Diagnostic Imaging Unit, IRCCS Santa Lucia Foundation, Rome, Italy
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Hendriksen HMA, van Gils AM, van Harten AC, Hartmann T, Mangialasche F, Kamondi A, Kivipelto M, Rhodius-Meester HFM, Smets EMA, van der Flier WM, Visser LNC. Communication about diagnosis, prognosis, and prevention in the memory clinic: perspectives of European memory clinic professionals. Alzheimers Res Ther 2023; 15:131. [PMID: 37543608 PMCID: PMC10404377 DOI: 10.1186/s13195-023-01276-9] [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: 03/20/2023] [Accepted: 07/19/2023] [Indexed: 08/07/2023]
Abstract
BACKGROUND The paradigm shift towards earlier Alzheimer's disease (AD) stages and personalized medicine creates new challenges for clinician-patient communication. We conducted a survey among European memory clinic professionals to identify opinions on communication about (etiological) diagnosis, prognosis, and prevention, and inventory needs for augmenting communication skills. METHODS Memory clinic professionals (N = 160) from 21 European countries completed our online survey (59% female, 14 ± 10 years' experience, 73% working in an academic hospital). We inventoried (1) opinions on communication about (etiological) diagnosis, prognosis, and prevention using 11 statements; (2) current communication practices in response to five hypothetical cases (AD dementia, mild cognitive impairment (MCI), subjective cognitive decline (SCD), with ( +) or without ( -) abnormal AD biomarkers); and (3) needs for communication support regarding ten listed communication skills. RESULTS The majority of professionals agreed that communication on diagnosis, prognosis, and prevention should be personalized to the individual patient. In response to the hypothetical patient cases, disease stage influenced the inclination to communicate an etiological AD diagnosis: 97% would explicitly mention the presence of AD to the patient with AD dementia, 68% would do so in MCI + , and 29% in SCD + . Furthermore, 58% would explicitly rule out AD in case of MCI - when talking to patients, and 69% in case of SCD - . Almost all professionals (79-99%) indicated discussing prognosis and prevention with all patients, of which a substantial part (48-86%) would personalize their communication to patients' diagnostic test results (39-68%) or patients' anamnestic information (33-82%). The majority of clinicians (79%) would like to use online tools, training, or both to support them in communicating with patients. Topics for which professionals desired support most were: stimulating patients' understanding of information, and communicating uncertainty, dementia risk, remotely/online, and with patients not (fluently) speaking the language of the country of residence. CONCLUSIONS In a survey of European memory clinic professionals, we found a strong positive attitude towards communication with patients about (etiological) diagnosis, prognosis, and prevention, and personalization of communication to characteristics and needs of individual patients. In addition, professionals expressed a need for supporting tools and skills training to further improve their communication with patients.
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Affiliation(s)
- Heleen M A Hendriksen
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands.
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands.
| | - Aniek M van Gils
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Argonde C van Harten
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Tobias Hartmann
- Experimental Neurology, Saarland University, 66424, Homburg, Germany
- Deutsches Institut Für DemenzPrävention, Saarland University, 66424, Homburg, Germany
| | - Francesca Mangialasche
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Karolinska University Hospital, Medical Unit Aging, Theme Inflammation and Aging, Stockholm, Sweden
| | - Anita Kamondi
- Department of Neurology, Neurology and Neurosurgery, National Institute of Mental Health, Budapest, Hungary
- Department of Neurology, Semmelweis University, Budapest, Hungary
| | - Miia Kivipelto
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Karolinska University Hospital, Medical Unit Aging, Theme Inflammation and Aging, Stockholm, Sweden
- Ageing and Epidemiology (AGE) Research Unit, School of Public Health, Imperial College London, London, UK
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Helsinki, Finland
| | - Hanneke F M Rhodius-Meester
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Department of Geriatric Medicine, The Memory Clinic, Oslo University Hospital, Oslo, Norway
- Internal Medicine, Geriatric Medicine Section, Amsterdam Cardiovascular Sciences Institute, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
| | - Ellen M A Smets
- Medical Psychology, Amsterdam UMC Location AMC, University of Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health, Quality of Care, Personalized Medicine, , Amsterdam, The Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Epidemiology and Biostatistics, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Leonie N C Visser
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Medical Psychology, Amsterdam UMC Location AMC, University of Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health, Quality of Care, Personalized Medicine, , Amsterdam, The Netherlands
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Erickson P, Simrén J, Brum WS, Ennis GE, Kollmorgen G, Suridjan I, Langhough R, Jonaitis EM, Van Hulle CA, Betthauser TJ, Carlsson CM, Asthana S, Ashton NJ, Johnson SC, Shaw LM, Blennow K, Andreasson U, Bendlin BB, Zetterberg H. Prevalence and Clinical Implications of a β-Amyloid-Negative, Tau-Positive Cerebrospinal Fluid Biomarker Profile in Alzheimer Disease. JAMA Neurol 2023; 80:2807607. [PMID: 37523162 PMCID: PMC10391361 DOI: 10.1001/jamaneurol.2023.2338] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Accepted: 05/05/2023] [Indexed: 08/01/2023]
Abstract
Importance Knowledge is lacking on the prevalence and prognosis of individuals with a β-amyloid-negative, tau-positive (A-T+) cerebrospinal fluid (CSF) biomarker profile. Objective To estimate the prevalence of a CSF A-T+ biomarker profile and investigate its clinical implications. Design, Setting, and Participants This was a retrospective cohort study of the cross-sectional multicenter University of Gothenburg (UGOT) cohort (November 2019-January 2021), the longitudinal multicenter Alzheimer Disease Neuroimaging Initiative (ADNI) cohort (individuals with mild cognitive impairment [MCI] and no cognitive impairment; September 2005-May 2022), and 2 Wisconsin cohorts, Wisconsin Alzheimer Disease Research Center and Wisconsin Registry for Alzheimer Prevention (WISC; individuals without cognitive impairment; February 2007-November 2020). This was a multicenter study, with data collected from referral centers in clinical routine (UGOT) and research settings (ADNI and WISC). Eligible individuals had 1 lumbar puncture (all cohorts), 2 or more cognitive assessments (ADNI and WISC), and imaging (ADNI only) performed on 2 separate occasions. Data were analyzed on August 2022 to April 2023. Exposures Baseline CSF Aβ42/40 and phosphorylated tau (p-tau)181; cognitive tests (ADNI: modified preclinical Alzheimer cognitive composite [mPACC]; WISC: modified 3-test PACC [PACC-3]). Exposures in the ADNI cohort included [18F]-florbetapir amyloid positron emission tomography (PET), magnetic resonance imaging (MRI), [18F]-fluorodeoxyglucose PET (FDG-PET), and cross-sectional tau-PET (ADNI: [18F]-flortaucipir, WISC: [18F]-MK6240). Main Outcomes and Measures Primary outcomes were the prevalence of CSF AT biomarker profiles and continuous longitudinal global cognitive outcome and imaging biomarker trajectories in A-T+ vs A-T- groups. Secondary outcomes included cross-sectional tau-PET. Results A total of 7679 individuals (mean [SD] age, 71.0 [8.4] years; 4101 male [53%]) were included in the UGOT cohort, 970 individuals (mean [SD] age, 73 [7.0] years; 526 male [54%]) were included in the ADNI cohort, and 519 individuals (mean [SD] age, 60 [7.3] years; 346 female [67%]) were included in the WISC cohort. The prevalence of an A-T+ profile in the UGOT cohort was 4.1% (95% CI, 3.7%-4.6%), being less common than the other patterns. Longitudinally, no significant differences in rates of worsening were observed between A-T+ and A-T- profiles for cognition or imaging biomarkers. Cross-sectionally, A-T+ had similar tau-PET uptake to individuals with an A-T- biomarker profile. Conclusion and Relevance Results suggest that the CSF A-T+ biomarker profile was found in approximately 5% of lumbar punctures and was not associated with a higher rate of cognitive decline or biomarker signs of disease progression compared with biomarker-negative individuals.
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Affiliation(s)
- Pontus Erickson
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Joel Simrén
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Wagner S. Brum
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Gilda E. Ennis
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison
| | | | | | - Rebecca Langhough
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison
| | - Erin M. Jonaitis
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison
| | - Carol A. Van Hulle
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison
| | - Tobey J. Betthauser
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison
| | - Cynthia M. Carlsson
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison
- Division of Geriatrics and Gerontology, Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison
- Geriatric Research Education and Clinical Center of the Wm. S. Middleton Memorial Veterans Hospital, Madison, Wisconsin
| | - Sanjay Asthana
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison
- Division of Geriatrics and Gerontology, Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison
- Geriatric Research Education and Clinical Center of the Wm. S. Middleton Memorial Veterans Hospital, Madison, Wisconsin
| | - Nicholas J. Ashton
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute Clinical Neuroscience Institute, King’s College London, London, England
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, England
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | - Sterling C. Johnson
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison
| | - Leslie M. Shaw
- Department of Pathology and Laboratory Medicine, University of Pennsylvania School of Medicine, Philadelphia
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Ulf Andreasson
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Barbara B. Bendlin
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison
| | - Henrik Zetterberg
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison
- Institute of Neurology, Department of Neurodegenerative Disease, University College London, London, England
- UK Dementia Research Institute, University College London, London, England
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
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Peretti DE, Ribaldi F, Scheffler M, Mu L, Treyer V, Gietl AF, Hock C, Frisoni GB, Garibotto V. ATN profile classification across two independent prospective cohorts. Front Med (Lausanne) 2023; 10:1168470. [PMID: 37559930 PMCID: PMC10407659 DOI: 10.3389/fmed.2023.1168470] [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: 02/17/2023] [Accepted: 07/10/2023] [Indexed: 08/11/2023] Open
Abstract
Background The ATN model represents a research framework used to describe in subjects the presence or absence of Alzheimer's disease (AD) pathology through biomarkers. The aim of this study was to describe the prevalence of different ATN profiles using quantitative imaging biomarkers in two independent cohorts, and to evaluate the pertinence of ATN biomarkers to identify comparable populations across independent cohorts. Methods A total of 172 subjects from the Geneva Memory Clinic and 113 volunteers from a study on healthy aging at the University Hospital of Zurich underwent amyloid (A) and tau (T) PET, as well as T1-weigthed MRI scans using site-specific protocols. Subjects were classified by cognition (cognitively unimpaired, CU, or impaired, CI) based on clinical assessment by experts. Amyloid data converted into the standardized centiloid scale, tau PET data normalized to cerebellar uptake, and hippocampal volume expressed as a ratio over total intracranial volume ratio were considered as biomarkers for A, T, and neurodegeneration (N), respectively. Positivity for each biomarker was defined based on previously published thresholds. Subjects were then classified according to the ATN model. Differences among profiles were tested using Kruskal-Wallis ANOVA, and between cohorts using Wilcoxon tests. Results Twenty-nine percent of subjects from the Geneva cohorts were classified with a normal (A-T-N-) profile, while the Zurich cohort included 64% of subjects in the same category. Meanwhile, 63% of the Geneva and 16% of the Zurich cohort were classified within the AD continuum (being A+ regardless of other biomarkers' statuses). Within cohorts, ATN profiles were significantly different for age and mini-mental state examination scores, but not for years of education. Age was not significantly different between cohorts. In general, imaging A and T biomarkers were significantly different between cohorts, but they were no longer significantly different when stratifying the cohorts by ATN profile. N was not significantly different between cohorts. Conclusion Stratifying subjects into ATN profiles provides comparable groups of subjects even when individual recruitment followed different criteria.
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Affiliation(s)
- Débora E. Peretti
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Faculty of Medicine, Geneva University Neurocenter, University of Geneva, Geneva, Switzerland
| | - Federica Ribaldi
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
| | - Max Scheffler
- Division of Radiology, Geneva University Hospitals, Geneva, Switzerland
| | - Linjing Mu
- Department of Nuclear Medicine, University Hospital of Zurich, University of Zurich, Zurich, Switzerland
- Institute of Pharmaceutical Sciences, Zurich, Switzerland
| | - Valerie Treyer
- Department of Nuclear Medicine, University Hospital of Zurich, University of Zurich, Zurich, Switzerland
| | - Anton F. Gietl
- Department of Nuclear Medicine, University Hospital of Zurich, University of Zurich, Zurich, Switzerland
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
| | - Christoph Hock
- Department of Nuclear Medicine, University Hospital of Zurich, University of Zurich, Zurich, Switzerland
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
| | - Giovanni B. Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Memory Clinic, Geneva University Hospitals, Geneva, Switzerland
| | - Valentina Garibotto
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Faculty of Medicine, Geneva University Neurocenter, University of Geneva, Geneva, Switzerland
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals, Geneva, Switzerland
- Center for Biomedical Imaging, University of Geneva, Geneva, Switzerland
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Giangrande C, Delatour V, Andreasson U, Blennow K, Gobom J, Zetterberg H. Harmonization and standardization of biofluid-based biomarker measurements for AT(N) classification in Alzheimer's disease. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12465. [PMID: 37600860 PMCID: PMC10432775 DOI: 10.1002/dad2.12465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 05/31/2023] [Accepted: 07/05/2023] [Indexed: 08/22/2023]
Abstract
Fluid biomarkers are currently measured in cerebrospinal fluid and blood for Alzheimer's disease diagnosis and are promising targets for drug development and for patients' follow-up in clinical trials. These biomarkers have been grouped in an unbiased research framework, the amyloid (Aβ), tau, and neurodegeneration (AT[N]) biomarker system to aid patients' early diagnosis and stratification. Metrological approaches relying on mass spectrometry have been used for the development of reference materials and reference measurement procedures. Despite their excellent performances as clinical tools, fluid biomarkers often present an important between-laboratory variation. Standardization efforts were carried out on the biomarkers currently included in the AT(N) classification system, involving the collaboration of national metrology institutes, clinicians, researchers, and in vitro diagnostic providers. This article provides an overview of current activities towards standardization. These reference methods and reference materials may be used for recalibration of immunoassays and the establishment of standardized cutoff values allowing a better stratification of Alzheimer's disease patients. Highlights The AT(N) biomarker system allows stratifying AD patients on the basis of biomarker profiles.Fluid biomarker measurements often present an important between-laboratory variation preventing the establishment of standardized cutoff values.Overview on the standardization initiatives involving the fluid biomarkers currently included in the AT(N) framework.
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Affiliation(s)
- Chiara Giangrande
- Laboratoire National de Métrologie et d'Essais (LNE)Department of BioanalysesParis, Cedex 15France
| | - Vincent Delatour
- Laboratoire National de Métrologie et d'Essais (LNE)Department of BioanalysesParis, Cedex 15France
| | - Ulf Andreasson
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and Physiologythe Sahlgrenska Academy at the University of Gothenburg, MölndalGothenburgSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
| | - Kaj Blennow
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and Physiologythe Sahlgrenska Academy at the University of Gothenburg, MölndalGothenburgSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
| | - Johan Gobom
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and Physiologythe Sahlgrenska Academy at the University of Gothenburg, MölndalGothenburgSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
| | - Henrik Zetterberg
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and Physiologythe Sahlgrenska Academy at the University of Gothenburg, MölndalGothenburgSweden
- 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 KongChina
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public HealthUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
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73
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César-Freitas KG, Berardis ACP, Pretto TVM, Viagi AM, Lourençon V, Zanini LYK, Barbosa ICC, Machado RP, Cunha NGM, Watanabe MJL, Cecchini MA, Brucki SMD, Nitrini R. Follow-up of participants with subjective cognitive decline from Tremembé epidemiologic study, Brazil. Dement Neuropsychol 2023; 17:e20220064. [PMID: 37261255 PMCID: PMC10229081 DOI: 10.1590/1980-5764-dn-2022-0064] [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: 08/17/2022] [Revised: 02/07/2023] [Accepted: 03/09/2023] [Indexed: 06/02/2023] Open
Abstract
Subjective cognitive decline is defined as a self-perceived cognitive decline but with normal performance in neuropsychological assessments. Objective To verify the evolution of patients diagnosed with subjective cognitive decline compared to the cognitively normal group without any concern. Methods This is a follow-up study based on data analysis from the Tremembé epidemiologic study, in Brazil. The 211 individuals classified as cognitively normal and 174 diagnosed as having subjective cognitive decline at baseline were invited to participate. Results After a median follow-up time of five years, 108 subjective cognitive decline participants (62.0%) were reassessed. Of these, 58 (53.7%) kept this diagnosis, whereas 14 individuals (12.9%) progressed to mild cognitive impairment and 5 (4.6%) to dementia. In the cognitively normal group, 107 (50.7%) were reassessed, of which 51 (47.7%) were still classified likewise, 6 (5.6%) evolved to mild cognitive impairment and 9 (8.4%) to dementia. The presence of cognitive decline had a significant association with increasing age and depression symptoms. Considering the total number of baseline participants in each group: the subjective cognitive decline group showed higher percentage of mild cognitive impairment (p=0.022) and no difference was found in progression to dementia (p=0.468) between the groups after follow-up assessment. Conclusion Most subjective cognitive decline participants at baseline kept their cognitive complaint at follow-up and this group progressed more to mild cognitive impairment than the other group. No difference in the progression to dementia was found, despite the higher incidence of dementia in the cognitively normal group.
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Affiliation(s)
- Karolina Gouveia César-Freitas
- Universidade de São Paulo, Faculdade de Medicina, Unidade de Neurologia Cognitiva e Comportamental, Departamento de Neurologia, São Paulo SP, Brazil
- Universidade de Taubaté, Departamento de Medicina, Taubaté SP, Brazil
| | | | | | | | - Vitorio Lourençon
- Universidade de Taubaté, Departamento de Medicina, Taubaté SP, Brazil
| | | | | | | | | | | | - Mario Amore Cecchini
- Universidade de São Paulo, Faculdade de Medicina, Unidade de Neurologia Cognitiva e Comportamental, Departamento de Neurologia, São Paulo SP, Brazil
| | - Sonia Maria Dozzi Brucki
- Universidade de São Paulo, Faculdade de Medicina, Unidade de Neurologia Cognitiva e Comportamental, Departamento de Neurologia, São Paulo SP, Brazil
| | - Ricardo Nitrini
- Universidade de São Paulo, Faculdade de Medicina, Unidade de Neurologia Cognitiva e Comportamental, Departamento de Neurologia, São Paulo SP, Brazil
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Khosroazad S, Gilbert CF, Aronis JB, Daigle KM, Esfahani M, Almaghasilah A, Ahmed FS, Elias MF, Meuser TM, Kaye LW, Singer CM, Abedi A, Hayes MJ. Sleep movements and respiratory coupling as a biobehavioral metric for early Alzheimer's disease in independently dwelling adults. BMC Geriatr 2023; 23:252. [PMID: 37106470 PMCID: PMC10141904 DOI: 10.1186/s12877-023-03983-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 04/19/2023] [Indexed: 04/29/2023] Open
Abstract
INTRODUCTION Sleep disorder is often the first symptom of age-related cognitive decline associated with Alzheimer's disease (AD) observed in primary care. The relationship between sleep and early AD was examined using a patented sleep mattress designed to record respiration and high frequency movement arousals. A machine learning algorithm was developed to classify sleep features associated with early AD. METHOD Community-dwelling older adults (N = 95; 62-90 years) were recruited in a 3-h catchment area. Study participants were tested on the mattress device in the home bed for 2 days, wore a wrist actigraph for 7 days, and provided sleep diary and sleep disorder self-reports during the 1-week study period. Neurocognitive testing was completed in the home within 30-days of the sleep study. Participant performance on executive and memory tasks, health history and demographics were reviewed by a geriatric clinical team yielding Normal Cognition (n = 45) and amnestic MCI-Consensus (n = 33) groups. A diagnosed MCI group (n = 17) was recruited from a hospital memory clinic following diagnostic series of neuroimaging biomarker assessment and cognitive criteria for AD. RESULTS In cohort analyses, sleep fragmentation and wake after sleep onset duration predicted poorer executive function, particularly memory performance. Group analyses showed increased sleep fragmentation and total sleep time in the diagnosed MCI group compared to the Normal Cognition group. Machine learning algorithm showed that the time latency between movement arousals and coupled respiratory upregulation could be used as a classifier of diagnosed MCI vs. Normal Cognition cases. ROC diagnostics identified MCI with 87% sensitivity; 89% specificity; and 88% positive predictive value. DISCUSSION AD sleep phenotype was detected with a novel sleep biometric, time latency, associated with the tight gap between sleep movements and respiratory coupling, which is proposed as a corollary of sleep quality/loss that affects the autonomic regulation of respiration during sleep. Diagnosed MCI was associated with sleep fragmentation and arousal intrusion.
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Affiliation(s)
- Somayeh Khosroazad
- Electrical and Computer Engineering, University of Maine, 5708 Barrows Hall, Orono, ME, 04469, USA
- Activas Diagnostics, LLC, 20 Godfrey Dr., Orono, ME, 04473, USA
| | - Christopher F Gilbert
- Activas Diagnostics, LLC, 20 Godfrey Dr., Orono, ME, 04473, USA
- Psychology Department, University of Maine, 5740 Beryl Warner Williams Hall, Orono, ME, 5740-04469, USA
| | - Jessica B Aronis
- Activas Diagnostics, LLC, 20 Godfrey Dr., Orono, ME, 04473, USA
- Psychology Department, University of Maine, 5740 Beryl Warner Williams Hall, Orono, ME, 5740-04469, USA
| | - Katrina M Daigle
- Psychology Department, Suffolk University, 73 Tremont St., Boston, MA, 02108, USA
| | | | - Ahmed Almaghasilah
- Electrical and Computer Engineering, University of Maine, 5708 Barrows Hall, Orono, ME, 04469, USA
- Graduate School of Biomedical Science & Engineering, University of Maine, 5775 Stodder Hall, Orono, ME, 04469, USA
| | - Fayeza S Ahmed
- Psychology Department, University of Maine, 5740 Beryl Warner Williams Hall, Orono, ME, 5740-04469, USA
| | - Merrill F Elias
- Psychology Department, University of Maine, 5740 Beryl Warner Williams Hall, Orono, ME, 5740-04469, USA
| | - Thomas M Meuser
- Center for Excellence On Aging, University of New England, 11 Hills Beach Rd., Biddeford, ME, 04005, USA
| | - Leonard W Kaye
- Center On Aging, University of Maine, 327 Camden Hall, Orono, ME, 04469, USA
| | - Clifford M Singer
- Psychology Department, University of Maine, 5740 Beryl Warner Williams Hall, Orono, ME, 5740-04469, USA
- Mood and Memory Clinic, Northern Light Health, 269 Stillwater Ave., Bangor, ME, 04402, USA
| | - Ali Abedi
- Electrical and Computer Engineering, University of Maine, 5708 Barrows Hall, Orono, ME, 04469, USA
- Activas Diagnostics, LLC, 20 Godfrey Dr., Orono, ME, 04473, USA
| | - Marie J Hayes
- Activas Diagnostics, LLC, 20 Godfrey Dr., Orono, ME, 04473, USA.
- Psychology Department, University of Maine, 5740 Beryl Warner Williams Hall, Orono, ME, 5740-04469, USA.
- Graduate School of Biomedical Science & Engineering, University of Maine, 5775 Stodder Hall, Orono, ME, 04469, USA.
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Lassi M, Fabbiani C, Mazzeo S, Burali R, Vergani AA, Giacomucci G, Moschini V, Morinelli C, Emiliani F, Scarpino M, Bagnoli S, Ingannato A, Nacmias B, Padiglioni S, Micera S, Sorbi S, Grippo A, Bessi V, Mazzoni A. Degradation of EEG microstates patterns in subjective cognitive decline and mild cognitive impairment: Early biomarkers along the Alzheimer's Disease continuum? Neuroimage Clin 2023; 38:103407. [PMID: 37094437 PMCID: PMC10149415 DOI: 10.1016/j.nicl.2023.103407] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Revised: 03/29/2023] [Accepted: 04/14/2023] [Indexed: 04/26/2023]
Abstract
Alzheimer's disease (AD) pathological changes may begin up to decades earlier than the appearance of the first symptoms of cognitive decline. Subjective cognitive decline (SCD) could be the first pre-clinical sign of possible AD, which might be followed by mild cognitive impairment (MCI), the initial stage of clinical cognitive decline. However, the neural correlates of these prodromic stages are not completely clear yet. Recent studies suggest that EEG analysis tools characterizing the cortical activity as a whole, such as microstates and cortical regions connectivity, might support a characterization of SCD and MCI conditions. Here we test this approach by performing a broad set of analyses to identify the prominent EEG markers differentiating SCD (n = 57), MCI (n = 46) and healthy control subjects (HC, n = 19). We found that the salient differences were in the temporal structure of the microstates patterns, with MCI being associated with less complex sequences due to the altered transition probability, frequency and duration of canonic microstate C. Spectral content of EEG, network connectivity, and spatial arrangement of microstates were instead largely similar in the three groups. Interestingly, comparing properties of EEG microstates in different cerebrospinal fluid (CSF) biomarkers profiles, we found that canonic microstate C displayed significant differences in topography in AD-like profile. These results show that the progression of dementia might be associated with a degradation of the cortical organization captured by microstates analysis, and that this leads to altered transitions between cortical states. Overall, our approach paves the way for the use of non-invasive EEG recordings in the identification of possible biomarkers of progression to AD from its prodromal states.
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Affiliation(s)
- Michael Lassi
- The BioRobotics Institute and Department of Excellence in Robotics and AI, Sant'Anna School of Advanced Studies, viale Rinaldo Piaggio 34, 56025 Pisa, Italy
| | - Carlo Fabbiani
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci, 269, 50143 Florence, Italy
| | - Salvatore Mazzeo
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci, 269, 50143 Florence, Italy; Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Rachele Burali
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci, 269, 50143 Florence, Italy
| | - Alberto Arturo Vergani
- The BioRobotics Institute and Department of Excellence in Robotics and AI, Sant'Anna School of Advanced Studies, viale Rinaldo Piaggio 34, 56025 Pisa, Italy
| | - Giulia Giacomucci
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Valentina Moschini
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Carmen Morinelli
- Dipartimento Neuromuscolo-scheletrico e degli organi di senso, Careggi University Hospital, 50134 Florence, Italy
| | - Filippo Emiliani
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Maenia Scarpino
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci, 269, 50143 Florence, Italy
| | - Silvia Bagnoli
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Assunta Ingannato
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Benedetta Nacmias
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci, 269, 50143 Florence, Italy; Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Sonia Padiglioni
- Regional Referral Centre for Relational Criticalities - Tuscany Region, 50139 Florence, Italy
| | - Silvestro Micera
- The BioRobotics Institute and Department of Excellence in Robotics and AI, Sant'Anna School of Advanced Studies, viale Rinaldo Piaggio 34, 56025 Pisa, Italy; Bertarelli Foundation Chair in Translational Neuroengineering, Centre for Neuroprosthetics and Institute of Bioengineering, School of Engineering, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
| | - Sandro Sorbi
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci, 269, 50143 Florence, Italy; Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Antonello Grippo
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci, 269, 50143 Florence, Italy
| | - Valentina Bessi
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Alberto Mazzoni
- The BioRobotics Institute and Department of Excellence in Robotics and AI, Sant'Anna School of Advanced Studies, viale Rinaldo Piaggio 34, 56025 Pisa, Italy.
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Mirkin S, Albensi BC. Should artificial intelligence be used in conjunction with Neuroimaging in the diagnosis of Alzheimer's disease? Front Aging Neurosci 2023; 15:1094233. [PMID: 37187577 PMCID: PMC10177660 DOI: 10.3389/fnagi.2023.1094233] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 03/27/2023] [Indexed: 05/17/2023] Open
Abstract
Alzheimer's disease (AD) is a progressive, neurodegenerative disorder that affects memory, thinking, behavior, and other cognitive functions. Although there is no cure, detecting AD early is important for the development of a therapeutic plan and a care plan that may preserve cognitive function and prevent irreversible damage. Neuroimaging, such as magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomography (PET), has served as a critical tool in establishing diagnostic indicators of AD during the preclinical stage. However, as neuroimaging technology quickly advances, there is a challenge in analyzing and interpreting vast amounts of brain imaging data. Given these limitations, there is great interest in using artificial Intelligence (AI) to assist in this process. AI introduces limitless possibilities in the future diagnosis of AD, yet there is still resistance from the healthcare community to incorporate AI in the clinical setting. The goal of this review is to answer the question of whether AI should be used in conjunction with neuroimaging in the diagnosis of AD. To answer the question, the possible benefits and disadvantages of AI are discussed. The main advantages of AI are its potential to improve diagnostic accuracy, improve the efficiency in analyzing radiographic data, reduce physician burnout, and advance precision medicine. The disadvantages include generalization and data shortage, lack of in vivo gold standard, skepticism in the medical community, potential for physician bias, and concerns over patient information, privacy, and safety. Although the challenges present fundamental concerns and must be addressed when the time comes, it would be unethical not to use AI if it can improve patient health and outcome.
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Affiliation(s)
- Sophia Mirkin
- Dr. Kiran C. Patel College of Osteopathic Medicine, Nova Southeastern University, Fort Lauderdale, FL, United States
| | - Benedict C. Albensi
- Barry and Judy Silverman College of Pharmacy, Nova Southeastern University, Fort Lauderdale, FL, United States
- St. Boniface Hospital Research, Winnipeg, MB, Canada
- University of Manitoba, Winnipeg, MB, Canada
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Bryant AM, Kerr ZY, Walton SR, Barr WB, Guskiewicz KM, McCrea MA, Brett BL. Investigating the association between subjective and objective performance-based cognitive function among former collegiate football players. Clin Neuropsychol 2023; 37:595-616. [PMID: 35670306 PMCID: PMC9726994 DOI: 10.1080/13854046.2022.2083021] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Accepted: 05/22/2022] [Indexed: 11/03/2022]
Abstract
OBJECTIVE Studies have observed variable associations of prior contact sport participation with subjective and objective measures of cognitive function. This study directly investigated the association between subjective self-report and objective performance-based cognition among former collegiate football players, as well as its relationship to self-reported concussion history. METHODS Former collegiate football players (N = 57; mean age = 37.9 years [SD = 1.49]) retired from sport 15-years prior were enrolled. Linear regression models examined associations between subjective cognition (Quality of Life in Neurological Disorders Cognitive Functioning-Short Form), and performance on a neuropsychological battery. Domain specific (executive function) metrics of subjective (Behavior Rating Inventory of Executive Function-Adult) and objective cognition were also exclusively examined. Associations between self-reported concussion history with subjective and objective measures were tested. Potential influential factors (sleep quality and distress) were included as covariates. RESULTS Subjective cognition was not significantly associated with any objective measures of cognitive functioning (p's > .05). Greater self-reported concussion history was inversely associated with subjective cognition (B = -2.49, p = .004), but not objective performance-based cognition (p's > .05). Distress was significantly related to all metrics of subjective cognition (p's < .001) as well as performance on delayed recall and verbal fluency (p's < .05). Sleep quality was only significantly related to timed visuospatial sequencing (p = .033). CONCLUSIONS Reliance on self-reported measures of cognitive functioning alone is insufficient when assessing cognition in former contact sport athletes. Assessment of other factors known to influence subjective cognitive complaints should also be examined in determining the presence of cognitive deficits.
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Affiliation(s)
- Andrew M. Bryant
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, Wisconsin
- Department of Neurology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Zachary Y. Kerr
- Department of Exercise and Sport Science, University of North Carolina at Chapel Hill
| | - Samuel R. Walton
- Department of Exercise and Sport Science, University of North Carolina at Chapel Hill
| | | | - Kevin M. Guskiewicz
- Department of Exercise and Sport Science, University of North Carolina at Chapel Hill
| | - Michael A. McCrea
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, Wisconsin
- Department of Neurology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Benjamin L. Brett
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, Wisconsin
- Department of Neurology, Medical College of Wisconsin, Milwaukee, Wisconsin
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Reynolds G, Buckley R, Papp K, Schultz SA, Rentz D, Sperling R, Amariglio R. Relation of modifiable lifestyle and mood factors to cognitive concerns among participants and their study partners in the A4 screen data. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12435. [PMID: 37304049 PMCID: PMC10248212 DOI: 10.1002/dad2.12435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 03/16/2023] [Accepted: 04/10/2023] [Indexed: 06/13/2023]
Abstract
Introduction Subjective cognitive decline (SCD) has been associated with elevated amyloid levels and increased risk of future cognitive decline, as well as modifiable variables, including depression, anxiety, and physical inactivity. Participants generally endorse greater and earlier concerns than their close family and friends (study partners [SPs]), which may reflect subtle changes at the earliest stages of disease among participants with underlying neurodegenerative processes. However, many individuals with subjective concerns are not at risk of Alzheimer's disease (AD) pathology, suggesting that additional factors, such as lifestyle habits, may be contributory. Methods We examined the relation between SCD, amyloid status, lifestyle habits (exercise, sleep), mood/anxiety, and demographic variables among 4481 cognitively unimpaired older adults who are being screened for a multi-site secondary prevention trial (A4 screen data; mean ±SD: age = 71.3 ±4.7, education = 16.6 ±2.8, 59% women, 96% non-Hispanic or Latino, 92% White]. Results On the Cognitive Function Index (CFI) participants endorsed higher concerns compared to SPs. Participant concerns were associated with older age, positive amyloid status, worse mood/anxiety, lower education, and lower exercise, whereas SP concerns were associated with older participant age, male gender of participant, positive amyloid status of participant, and worse participant-reported mood/anxiety. Discussion Findings suggest that modifiable/lifestyle factors (e.g., exercise, education) may be associated with participant concerns among cognitively unimpaired individuals and highlight the importance of further examining how modifiable factors impact participant- and SP-reported concerns, which may inform trial recruitment and clinical interventions.
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Affiliation(s)
- Gretchen Reynolds
- Department of NeurologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Rachel Buckley
- Department of NeurologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Melbourne School of Psychological SciencesUniversity of MelbourneParkvilleVictoriaAustralia
| | - Kathryn Papp
- Department of NeurologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Stephanie A. Schultz
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Dorene Rentz
- Department of NeurologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Reisa Sperling
- Department of NeurologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Rebecca Amariglio
- Department of NeurologyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
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79
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Arnoldy L, Gauci S, Young LM, Marx W, Macpherson H, Pipingas A, Civier O, White DJ. The association of dietary and nutrient patterns on neurocognitive decline: A systematic review of MRI and PET studies. Ageing Res Rev 2023; 87:101892. [PMID: 36878405 DOI: 10.1016/j.arr.2023.101892] [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: 05/11/2021] [Revised: 02/14/2023] [Accepted: 02/27/2023] [Indexed: 03/08/2023]
Abstract
BACKGROUND As the global population ages, there has been a growing incidence of neurodegenerative diseases such as Alzheimer's. More recently, studies exploring the relationship between dietary patterns and neuroimaging outcomes have received particular attention. This systematic literature review provides a structured overview of the association between dietary and nutrient patterns on neuroimaging outcomes and cognitive markers in middle-aged to older adults. A comprehensive literature search was conducted to find relevant articles published from 1999 to date using the following databases Ovid MEDLINE, Embase, PubMed, Scopus and Web of Science. The inclusion criteria for the articles comprised studies reporting on the association between dietary patterns and neuroimaging outcomes, which includes both specific pathological hallmarks of neurodegenerative diseases such as Aβ and tau and nonspecific markers such as structural MRI and glucose metabolism. The risk of bias was evaluated using the Quality Assessment tool from the National Heart, Lung, and Blood Institute of the National Institutes of Health. The results were then organized into a summary of results table, collated based on synthesis without meta-analysis. After conducting the search, 6050 records were extracted and screened for eligibility, with 107 eligible for full-text screening and 42 articles ultimately being included in this review. The results of the systematic review indicate that there is some evidence suggesting that healthy dietary and nutrient patterns were associated with neuroimaging measures, indicative of a protective influence on neurodegeneration and brain ageing. Conversely, unhealthy dietary and nutrient patterns showed evidence pointing to decreased brain volumes, poorer cognition and increased Aβ deposition. Future research should focus on sensitive neuroimaging acquisition and analysis methods, to study early neurodegenerative changes and identify critical periods for interventions and prevention. SYSTEMATIC REVIEW REGISTRATION PROSPERO registration no, CRD42020194444).
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Affiliation(s)
- Lizanne Arnoldy
- Centre of Human Psychopharmacology, Centre for Mental Health and Brain Sciences, Swinburne University, Melbourne Australia.
| | - Sarah Gauci
- Centre of Human Psychopharmacology, Centre for Mental Health and Brain Sciences, Swinburne University, Melbourne Australia; IMPACT - the Institute for Mental and Physical Health and Clinical Translation, Food & Mood Centre, School of Medicine, Deakin University, Geelong, Australia
| | - Lauren M Young
- Centre of Human Psychopharmacology, Centre for Mental Health and Brain Sciences, Swinburne University, Melbourne Australia; IMPACT - the Institute for Mental and Physical Health and Clinical Translation, Food & Mood Centre, School of Medicine, Deakin University, Geelong, Australia
| | - Wolfgang Marx
- IMPACT - the Institute for Mental and Physical Health and Clinical Translation, Food & Mood Centre, School of Medicine, Deakin University, Geelong, Australia
| | - Helen Macpherson
- Institute for Physical Activity and Nutrition (IPAN), School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC, Australia
| | - Andrew Pipingas
- Centre of Human Psychopharmacology, Centre for Mental Health and Brain Sciences, Swinburne University, Melbourne Australia
| | - Oren Civier
- Swinburne Neuroimaging, Swinburne University, Melbourne, Australia
| | - David J White
- Centre of Human Psychopharmacology, Centre for Mental Health and Brain Sciences, Swinburne University, Melbourne Australia; Swinburne Neuroimaging, Swinburne University, Melbourne, Australia
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80
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Zhao YL, Ou YN, Ma YH, Tan L, Yu JT. Characteristics of Subjective Cognitive Decline Associated with Alzheimer's Disease Amyloid Pathology: Findings from The CABLE Study. J Alzheimers Dis 2023; 92:581-590. [PMID: 36776070 DOI: 10.3233/jad-221154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/10/2023]
Abstract
BACKGROUND Subjective cognitive decline (SCD) is considered as a preclinical hallmark of Alzheimer's disease (AD). However, the characteristics of SCD associated with amyloid pathology remain unclear. OBJECTIVE We aimed to explore the associations between SCD characteristics with amyloid pathology. METHODS Using logistic regression analyses, we analyzed the associations between cerebrospinal fluid (CSF) amyloid pathology with AD risk factors, SCD-specific characteristics (onset of SCD within the last five years, age at onset ≥60 years, feelings of worse performance, informant confirmation of complaints, worries, other domains of cognition complaints), as well as subthreshold depressive and anxiety symptoms among individuals with SCD. RESULTS A total of 535 SCD individuals with available CSF Aβ 42 information from the Chinese Alzheimer's Biomarker and LifestylE (CABLE) study (mean age of 63.5 years, range 40 to 88 years; 47.10% female) were enrolled. The characteristics of informant confirmation of complaints (OR, 95% CI = 2.00, 1.19-3.36), subthreshold depressive symptoms (OR, 95% CI = 2.31, 1.05-5.09), and subthreshold anxiety symptoms (OR, 95% CI = 2.22, 1.09-4.51) were found to be significantly associated with pathological amyloid in multivariate analyses when adjusting for age, sex, education, and APOE ɛ4. Besides, age and females were observed risks for amyloid pathology in subscale analyses. Nonetheless, we did not find any associations of other SCD-specific characteristics with amyloid pathology in this study. CONCLUSION Our study suggested that informant confirmed complaints and subthreshold psychiatric symptoms might be critical for discriminating AD-related SCD from non-AD related SCD.
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Affiliation(s)
- Yong-Li Zhao
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Ya-Nan Ou
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Ya-Hui Ma
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Jin-Tai Yu
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontier Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
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81
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Medina-Vera D, Enache D, Tambaro S, Abuhashish E, Rosell-Valle C, Winblad B, Rodríguez de Fonseca F, Bereczki E, Nilsson P. Translational potential of synaptic alterations in Alzheimer's disease patients and amyloid precursor protein knock-in mice. Brain Commun 2023; 5:fcad001. [PMID: 36687391 PMCID: PMC9851419 DOI: 10.1093/braincomms/fcad001] [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: 02/21/2022] [Revised: 09/19/2022] [Accepted: 01/03/2023] [Indexed: 01/09/2023] Open
Abstract
Synaptic dysfunction is an early event in Alzheimer's disease. Post-mortem studies suggest that alterations in synaptic proteins are associated with cognitive decline in Alzheimer's disease. We measured the concentration of three synaptic proteins, zinc transporter protein 3, dynamin1 and AMPA glutamate receptor 3 in cerebrospinal fluid of subjects with mild cognitive impairment (n = 18) and Alzheimer's disease (n = 18) and compared the levels to cognitively and neurologically healthy controls (n = 18) by using ELISA assay. In addition, we aimed to assess the translational potential of these synaptic proteins in two established amyloid precursor protein knock-in Alzheimer's disease mouse models by assessing the cerebrospinal fluid, hippocampal and cortical synaptic protein concentrations. Using ELISA, we measured in parallel these three proteins in cerebrospinal fluid and/or brain of 12- and 24-month-old AppNL-F and AppNL-G-F knock-in mice and AppWt control mice. The regional distribution and expression of these proteins were explored upon aging of the App knock-in models by quantitative immunofluorescence microscopy. Notably, we found a significant increase in concentrations of zinc transporter protein 3 and AMPA glutamate receptor 3 in cerebrospinal fluid of both patient groups compared with cognitively healthy controls. Dynamin1 concentration was significantly higher in Alzheimer's disease patients. Remarkably, patients with mild cognitive impairment who converted to Alzheimer's disease (n = 7) within 2 years exhibited elevated baseline cerebrospinal fluid zinc transporter protein 3 concentrations compared with mild cognitive impairment patients who did not convert (n = 11). Interestingly, similar to the alterations in Alzheimer's disease subjects, cerebrospinal fluid AMPA glutamate receptor 3 concentration was significantly higher in AppNL-G-F knock-in mice when compared with wild-type controls. Furthermore, we have detected age and brain regional specific changes of the three synaptic proteins in the hippocampus and prefrontal cortex of both AppNL-F and AppNL-G-F knock-in mice. Notably, all the three cerebrospinal fluid synaptic protein concentrations correlated negatively with concentrations in hippocampal lysates. The elevated zinc transporter protein 3 concentrations in the cerebrospinal fluid of converter versus non-converter mild cognitive impairment patients suggests a prospective role of zinc transporter 3 in differentiating dementia patients of the biological continuum of Alzheimer's disease. The increased cerebrospinal fluid concentrations of synaptic proteins in both patient groups, potentially reflecting synaptic alterations in the brain, were similarly observed in the amyloid precursor protein knock-in mouse models highlighting the translational potential of these proteins as markers for synaptic alterations. These synaptic markers could potentially help reduce the current disparities between human and animal model-based studies aiding the translation of preclinical discoveries of pathophysiological changes into clinical research.
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Affiliation(s)
- Dina Medina-Vera
- Instituto de Investigación Biomédica de Málaga-IBIMA, Unidad de Gestión Clínica de Salud Mental, Hospital Regional Universitario de Málaga, Málaga 29010, Spain,Facultad de Ciencias, Universidad de Málaga, Málaga 29010, Spain,Facultad de Medicina, Universidad de Málaga, Málaga 29010, Spain
| | - Daniela Enache
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Division of Neurogeriatrics, Karolinska Institutet, 17164 Solna, Sweden
| | - Simone Tambaro
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Division of Neurogeriatrics, Karolinska Institutet, 17164 Solna, Sweden
| | - Ethar Abuhashish
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Division of Neurogeriatrics, Karolinska Institutet, 17164 Solna, Sweden
| | - Cristina Rosell-Valle
- Instituto de Investigación Biomédica de Málaga-IBIMA, Unidad de Gestión Clínica de Salud Mental, Hospital Regional Universitario de Málaga, Málaga 29010, Spain
| | - Bengt Winblad
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Division of Neurogeriatrics, Karolinska Institutet, 17164 Solna, Sweden,Theme Inflammation and Aging, Karolinska University Hospital, 17164 Solna, Sweden
| | - Fernando Rodríguez de Fonseca
- Instituto de Investigación Biomédica de Málaga-IBIMA, Unidad de Gestión Clínica de Salud Mental, Hospital Regional Universitario de Málaga, Málaga 29010, Spain
| | - Erika Bereczki
- Correspondence to: Erika Bereczki Department of NVS, Center for Alzheimer Research Division of Neurogeriatrics, Karolinska Institutet BioClinicum J10:30, 17 164, Stockholm, Sweden E-mail:
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82
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Caprioglio C, Ribaldi F, Visser LNC, Minguillon C, Collij LE, Grau-Rivera O, Zeyen P, Molinuevo JL, Gispert JD, Garibotto V, Moro C, Walker Z, Edison P, Demonet JF, Barkhof F, Scheltens P, Alves IL, Gismondi R, Farrar G, Stephens AW, Jessen F, Frisoni GB, Altomare D. Analysis of Psychological Symptoms Following Disclosure of Amyloid-Positron Emission Tomography Imaging Results to Adults With Subjective Cognitive Decline. JAMA Netw Open 2023; 6:e2250921. [PMID: 36637820 PMCID: PMC9857261 DOI: 10.1001/jamanetworkopen.2022.50921] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/14/2023] Open
Abstract
IMPORTANCE Individuals who are amyloid-positive with subjective cognitive decline and clinical features increasing the likelihood of preclinical Alzheimer disease (SCD+) are at higher risk of developing dementia. Some individuals with SCD+ undergo amyloid-positron emission tomography (PET) as part of research studies and frequently wish to know their amyloid status; however, the disclosure of a positive amyloid-PET result might have psychological risks. OBJECTIVE To assess the psychological outcomes of the amyloid-PET result disclosure in individuals with SCD+ and explore which variables are associated with a safer disclosure in individuals who are amyloid positive. DESIGN, SETTING, AND PARTICIPANTS This prospective, multicenter study was conducted as part of The Amyloid Imaging to Prevent Alzheimer Disease Diagnostic and Patient Management Study (AMYPAD-DPMS) (recruitment period: from April 2018 to October 2020). The setting was 5 European memory clinics, and participants included patients with SCD+ who underwent amyloid-PET. Statistical analysis was performed from July to October 2022. EXPOSURES Disclosure of amyloid-PET result. MAIN OUTCOMES AND MEASURES Psychological outcomes were defined as (1) disclosure related distress, assessed using the Impact of Event Scale-Revised (IES-R; scores of at least 33 indicate probable presence of posttraumatic stress disorder [PTSD]); and (2) anxiety and depression, assessed using the Hospital Anxiety and Depression scale (HADS; scores of at least 15 indicate probable presence of severe mood disorder symptoms). RESULTS After disclosure, 27 patients with amyloid-positive SCD+ (median [IQR] age, 70 [66-74] years; gender: 14 men [52%]; median [IQR] education: 15 [13 to 17] years, median [IQR] Mini-Mental State Examination [MMSE] score, 29 [28 to 30]) had higher median (IQR) IES-R total score (10 [2 to 14] vs 0 [0 to 2]; P < .001), IES-R avoidance (0.00 [0.00 to 0.69] vs 0.00 [0.00 to 0.00]; P < .001), IES-R intrusions (0.50 [0.13 to 0.75] vs 0.00 [0.00 to 0.25]; P < .001), and IES-R hyperarousal (0.33 [0.00 to 0.67] vs 0.00 [0.00 to 0.00]; P < .001) scores than the 78 patients who were amyloid-negative (median [IQR], age, 67 [64 to 74] years, 45 men [58%], median [IQR] education: 15 [12 to 17] years, median [IQR] MMSE score: 29 [28 to 30]). There were no observed differences between amyloid-positive and amyloid-negative patients in the median (IQR) HADS Anxiety (-1.0 [-3.0 to 1.8] vs -2.0 [-4.8 to 1.0]; P = .06) and Depression (-1.0 [-2.0 to 0.0] vs -1.0 [-3.0 to 0.0]; P = .46) deltas (score after disclosure - scores at baseline). In patients with amyloid-positive SCD+, despite the small sample size, higher education was associated with lower disclosure-related distress (ρ = -0.43; P = .02) whereas the presence of study partner was associated with higher disclosure-related distress (W = 7.5; P = .03). No participants with amyloid-positive SCD+ showed probable presence of PTSD or severe anxiety or depression symptoms at follow-up. CONCLUSIONS AND RELEVANCE The disclosure of a positive amyloid-PET result to patients with SCD+ was associated with a bigger psychological change, yet such change did not reach the threshold for clinical concern.
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Affiliation(s)
- Camilla Caprioglio
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Geneva University Hospitals, Geneva, Switzerland
| | - Federica Ribaldi
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Geneva University Hospitals, Geneva, Switzerland
| | - Leonie N. C. Visser
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Karolinska Institutet, Stockholm/Solna, Sweden
- Department of Medical Psychology, Amsterdam Public Health Research Institute, Amsterdam University Medical Centers (UMC)–Location VUmc, Amsterdam, the Netherlands
| | - Carolina Minguillon
- Barcelonaßeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Lyduine E. Collij
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers (UMC)–Location VUmc, Amsterdam, the Netherlands
| | - Oriol Grau-Rivera
- Barcelonaßeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Philip Zeyen
- Department of Psychiatry, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - José Luis Molinuevo
- Barcelonaßeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- H. Lundbeck A/S, Denmark
| | - Juan Domingo Gispert
- Barcelonaßeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Barcelona, Spain
| | - Valentina Garibotto
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals, Geneva, Switzerland
- Center for Biomedical Imaging (CIBM), Geneva, Switzerland
| | - Christian Moro
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Geneva University Hospitals, Geneva, Switzerland
| | - Zuzana Walker
- Division of Psychiatry, University College London, London, United Kingdom
- Margaret’s Hospital, Essex Partnership University NHS Foundation Trust, Essex, United Kingdom
| | - Paul Edison
- Division of Neurology, Department of Brain Sciences, Imperial College London, United Kingdom
| | | | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers (UMC)–Location VUmc, Amsterdam, the Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, United Kingdom
| | - Philip Scheltens
- Alzheimer Center, Department of Neurology, Amsterdam University Medical Centers (UMC)–Location VUmc, Amsterdam, the Netherlands
| | - Isadora Lopes Alves
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers (UMC)–Location VUmc, Amsterdam, the Netherlands
| | | | | | | | - Frank Jessen
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of Medicine, University of Geneva, Geneva, Switzerland
- German Center for Neurodegenerative Diseases (DZNE), Bonn-Cologne, Germany
- Excellence Cluster Cellular Stress Responses in Aging-Related Diseases (CECAD), Medical Faculty, University of Cologne, Germany
| | - Giovanni B. Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Geneva University Hospitals, Geneva, Switzerland
| | - Daniele Altomare
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Geneva University Hospitals, Geneva, Switzerland
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83
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Frölich L, van der Flier WM, Gustavsson A, Rossini PM, Holzapfel D. Response to the letter titled "The conundrum of the AD continuum". Alzheimers Dement 2023; 19:373-374. [PMID: 36074640 DOI: 10.1002/alz.12784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 07/07/2022] [Indexed: 01/18/2023]
Affiliation(s)
- Lutz Frölich
- Department of Geriatric Psychiatry, Central Institute of Mental Health Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Department of Neurology, Department of Epidemiology and Data Science, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands
| | - Anders Gustavsson
- Quantify Research, Stockholm, Sweden.,Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden
| | - Paolo M Rossini
- Faculty of Medicine of the Catholic University of the Sacred Heart, Milano, Italy.,Department of Neurosci & Neurorehab IRCCS San Raffaele-Rome, Roma, Italy
| | - Drew Holzapfel
- CEO Initiative on Alzheimer's Disease, Washington DC, US
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84
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Hammers DB, Lin JH, Polsinelli AJ, Logan PE, Risacher SL, Schwarz AJ, Apostolova LG. Criterion Validation of Tau PET Staging Schemes in Relation to Cognitive Outcomes. J Alzheimers Dis 2023; 96:197-214. [PMID: 37742649 PMCID: PMC10825758 DOI: 10.3233/jad-230512] [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] [Accepted: 08/14/2023] [Indexed: 09/26/2023]
Abstract
BACKGROUND Utilization of NIA-AA Research Framework requires dichotomization of tau pathology. However, due to the novelty of tau-PET imaging, there is no consensus on methods to categorize scans into "positive" or "negative" (T+ or T-). In response, some tau topographical pathologic staging schemes have been developed. OBJECTIVE The aim of the current study is to establish criterion validity to support these recently-developed staging schemes. METHODS Tau-PET data from 465 participants from the Alzheimer's Disease Neuroimaging Initiative (aged 55 to 90) were classified as T+ or T- using decision rules for the Temporal-Occipital Classification (TOC), Simplified TOC (STOC), and Lobar Classification (LC) tau pathologic schemes of Schwarz, and Chen staging scheme. Subsequent dichotomization was analyzed in comparison to memory and learning slope performances, and diagnostic accuracy using actuarial diagnostic methods. RESULTS Tau positivity was associated with worse cognitive performance across all staging schemes. Cognitive measures were nearly all categorized as having "fair" sensitivity at classifying tau status using TOC, STOC, and LC schemes. Results were comparable between Schwarz schemes, though ease of use and better data fit preferred the STOC and LC schemes. While some evidence was supportive for Chen's scheme, validity lagged behind others-likely due to elevated false positive rates. CONCLUSIONS Tau-PET staging schemes appear to be valuable for Alzheimer's disease diagnosis, tracking, and screening for clinical trials. Their validation provides support as options for tau pathologic dichotomization, as necessary for use of NIA-AA Research Framework. Future research should consider other staging schemes and validation with other outcome benchmarks.
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Affiliation(s)
- Dustin B. Hammers
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Joshua H. Lin
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | | | - Paige E. Logan
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Shannon L. Risacher
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Adam J. Schwarz
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Takeda Pharmaceuticals Ltd., Cambridge, MA, USA
| | - Liana G. Apostolova
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
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85
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Liu Z, Guan R, Bu F, Pan L. Treatment of Alzheimer's disease by combination of acupuncture and Chinese medicine based on pathophysiological mechanism: A review. Medicine (Baltimore) 2022; 101:e32218. [PMID: 36626477 PMCID: PMC9750551 DOI: 10.1097/md.0000000000032218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 11/16/2022] [Indexed: 01/11/2023] Open
Abstract
Alzheimer's disease (AD) is a neurodegenerative disorder characterized by neurodegeneration, nerve loss, neurofibrillary tangles, and Aβ plaques. In modern medical science, there has been a serious obstacle to the effective treatment of AD. At present, there is no clinically proven and effective western medicine treatment for AD. The reason is that the etiology of AD is not yet fully understood. In 2018, the international community put forward a purely biological definition of AD, but soon this view of biomarkers was widely questioned, because the so-called AD biomarkers are shared with other neurological diseases, the diagnostic accuracy is low, and they face various challenges in the process of clinical diagnosis and treatment. Nowadays, scholars increasingly regard AD as the result of multimechanism and multicenter interaction. Because there is no exact Western medicine treatment for AD, the times call for the comprehensive treatment of AD in traditional Chinese medicine (TCM). AD belongs to the category of "dull disease" in TCM. For thousands of years, TCM has accumulated a lot of relevant treatment experience in the process of diagnosis and treatment. TCM, acupuncture, and the combination of acupuncture and medicine all play an important role in the treatment of AD. Based on the research progress of modern medicine on the pathophysiology of AD, this paper discusses the treatment of this disease with the combination of acupuncture and medicine.
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Affiliation(s)
- Zhao Liu
- Heilongjiang University of Traditional Chinese Medicine, Harbin, Heilongjiang Province, China
| | - Ruiqian Guan
- Heilongjiang University of Traditional Chinese Medicine, Harbin, Heilongjiang Province, China
- Second Affiliated Hospital of Heilongjiang University of Traditional Chinese Medicine, Harbin, Heilongjiang Province, China
| | - Fan Bu
- Heilongjiang University of Traditional Chinese Medicine, Harbin, Heilongjiang Province, China
| | - Limin Pan
- Heilongjiang University of Traditional Chinese Medicine, Harbin, Heilongjiang Province, China
- Second Affiliated Hospital of Heilongjiang University of Traditional Chinese Medicine, Harbin, Heilongjiang Province, China
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86
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Lan G, Cai Y, Li A, Liu Z, Ma S, Guo T. Association of Presynaptic Loss with Alzheimer's Disease and Cognitive Decline. Ann Neurol 2022; 92:1001-1015. [PMID: 36056679 DOI: 10.1002/ana.26492] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 08/22/2022] [Accepted: 08/24/2022] [Indexed: 12/29/2022]
Abstract
OBJECTIVE Increased presynaptic dysfunction measured by cerebrospinal fluid (CSF) growth-associated protein-43 (GAP43) may be observed in Alzheimer's disease (AD), but how CSF GAP43 increases relate to AD-core pathologies, neurodegeneration, and cognitive decline in AD requires further investigation. METHODS We analyzed 731 older adults with baseline β-amyloid (Aβ) positron emission tomography (PET), CSF GAP43, CSF phosphorylated tau181 (p-Tau181 ), and 18 F-fluorodeoxyglucose PET, and longitudinal residual hippocampal volume and cognitive assessments. Among them, 377 individuals had longitudinal 18 F-fluorodeoxyglucose PET, and 326 individuals had simultaneous longitudinal CSF GAP43, Aβ PET, and CSF p-Tau181 data. We compared baseline and slopes of CSF GAP43 among different stages of AD, as well as their associations with Aβ PET, CSF p-Tau181 , residual hippocampal volume, 18 F-fluorodeoxyglucose PET, and cognition cross-sectionally and longitudinally. RESULTS Regardless of Aβ positivity and clinical diagnosis, CSF p-Tau181 -positive individuals showed higher CSF GAP43 concentrations (p < 0.001) and faster rates of CSF GAP43 increases (p < 0.001) compared with the CSF p-Tau181 -negative individuals. Moreover, higher CSF GAP43 concentrations and faster rates of CSF GAP43 increases were strongly related to CSF p-Tau181 independent of Aβ PET. They were related to more rapid hippocampal atrophy, hypometabolism, and cognitive decline (p < 0.001), and predicted the progression from MCI to dementia (area under the curve for baseline 0.704; area under the curve for slope 0.717) over a median 4 years of follow up. INTERPRETATION Tau aggregations rather than Aβ plaques primarily drive presynaptic dysfunction measured by CSF GAP43, which may lead to sequential neurodegeneration and cognitive impairment in AD or neurodegenerative diseases. ANN NEUROL 2022;92:1001-1015.
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Affiliation(s)
- Guoyu Lan
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen, China.,Tsinghua Shenzhen International Graduate School (SIGS), Tsinghua University, Shenzhen, China
| | - Yue Cai
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen, China.,Tsinghua Shenzhen International Graduate School (SIGS), Tsinghua University, Shenzhen, China
| | - Anqi Li
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen, China
| | - Zhen Liu
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen, China
| | - Shaohua Ma
- Tsinghua Shenzhen International Graduate School (SIGS), Tsinghua University, Shenzhen, China
| | - Tengfei Guo
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen, China.,Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, Shenzhen, China
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87
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Spence H, McNeil CJ, Waiter GD. Cognition and brain iron deposition in whole grey matter regions and hippocampal subfields. Eur J Neurosci 2022; 56:6039-6054. [PMID: 36215153 PMCID: PMC10092357 DOI: 10.1111/ejn.15838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 09/26/2022] [Accepted: 10/03/2022] [Indexed: 12/29/2022]
Abstract
Regional brain iron accumulation is observed in many neurodegenerative diseases, including Alzheimer's disease and Parkinson's disease, and is associated with cognitive decline. We explored associations between age, cognition and iron content in grey matter regions and hippocampal subfields in 380 participants of the Aberdeen children of the 1950s cohort and their first-generation relatives (aged 26-72 years). Participants underwent cognitive assessment at the time of MRI scanning. Quantitative susceptibility mapping of these MRI data was used to assess iron content in grey matter regions and in hippocampal subfields. Principle component analysis was performed on cognitive test scores to create a general cognition score. Spline analysis was used with the Akaike information criterion to determine if order 1, 2 or 3 natural splines were optimal for assessing non-linear relationships between regional iron and age. Multivariate linear models were used to assess associations between regional iron and cognition. Higher iron correlated with older age in the left putamen across all ages and in the right putamen of only participants over 58. Whereas a decrease in iron with older age was observed in the right thalamus and left pallidum across all ages. Right amygdala iron levels were associated with poorer general cognition scores and poorer immediate recall scores. Iron was not associated with any measures of cognitive performance in other regions of interest. Our results suggest that, whilst iron in some regions was associated with cognitive performance, there is an overall lack of association between regional iron content and cognitive ability in cognitively healthy individuals.
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Affiliation(s)
- Holly Spence
- Aberdeen Biomedical Imaging Centre, Institute of Medical Sciences, University of Aberdeen, Aberdeen, UK
| | - Chris J McNeil
- Aberdeen Biomedical Imaging Centre, Institute of Medical Sciences, University of Aberdeen, Aberdeen, UK
| | - Gordon D Waiter
- Aberdeen Biomedical Imaging Centre, Institute of Medical Sciences, University of Aberdeen, Aberdeen, UK
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88
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Chiu PY, Yang FC, Chiu MJ, Lin WC, Lu CH, Yang SY. Relevance of plasma biomarkers to pathologies in Alzheimer's disease, Parkinson's disease and frontotemporal dementia. Sci Rep 2022; 12:17919. [PMID: 36289355 PMCID: PMC9605966 DOI: 10.1038/s41598-022-22647-6] [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: 08/08/2022] [Accepted: 10/18/2022] [Indexed: 01/20/2023] Open
Abstract
Amyloid plaques and tau tangles are pathological hallmarks of Alzheimer's disease (AD). Parkinson's disease (PD) results from the accumulation of α-synuclein. TAR DNA-binding protein (TDP-43) and total tau protein (T-Tau) play roles in FTD pathology. All of the pathological evidence was found in the biopsy. However, it is impossible to perform stein examinations in clinical practice. Assays of biomarkers in plasma would be convenient. It would be better to investigate the combinations of various biomarkers in AD, PD and FTD. Ninety-one subjects without neurodegenerative diseases, 76 patients with amnesic mild cognitive impairment (aMCI) or AD dementia, combined as AD family, were enrolled. One hundred and nine PD patients with normal cognition (PD-NC) or dementia (PDD), combined as PD family, were enrolled. Twenty-five FTD patients were enrolled for assays of plasma amyloid β 1-40 (Aβ1-40), Aβ1-42, T-Tau, α-synuclein and TDP-43 using immunomagnetic reduction (IMR). The results show that Aβs and T-Tau are major domains in AD family. α-synuclein is highly dominant in PD family. FTD is closely associated with TDP-43 and T-Tau. The dominant plasma biomarkers in AD family, PD family and FTD are consistent with pathology. This implies that plasma biomarkers are promising for precise and differential assessments of AD, PD and FTD in clinical practice.
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Affiliation(s)
- Pai-Yi Chiu
- grid.452796.b0000 0004 0634 3637Department of Neurology, Show Chwan Memorial Hospital, Chunghwa, 500 Taiwan ,MR-Guided Focus Ultrasound Center, Chang Bin Shaw Chwan Memorial Hospital, Changhwa, 505 Taiwan
| | - Fu-Chi Yang
- grid.278244.f0000 0004 0638 9360Department of Neurology, Tri-Service General Hospital, National Defense Medical Center, Taipei, 114 Taiwan
| | - Ming-Jang Chiu
- grid.19188.390000 0004 0546 0241Department of Neurology, National Taiwan University Hospital, College of Medicine, National Taiwan University, Taipei, 100 Taiwan ,grid.19188.390000 0004 0546 0241Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, 100 Taiwan ,grid.19188.390000 0004 0546 0241Department of Psychology, National Taiwan University, Taipei, 106 Taiwan ,grid.19188.390000 0004 0546 0241Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, 106 Taiwan
| | - Wei-Che Lin
- grid.145695.a0000 0004 1798 0922Department of Diagnostic Radiology, Kaohsiung Chang Gung Memorial Hospital, College of Medicine, Chang Gung University, Kaohsiung, 833 Taiwan
| | - Cheng-Hsien Lu
- grid.145695.a0000 0004 1798 0922Department of Neurology, Kaohsiung Chang Gung Memorial Hospital, College of Medicine, Chang Gung University, Kaohsiung, 833 Taiwan
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89
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Deatsch A, Perovnik M, Namías M, Trošt M, Jeraj R. Development of a deep learning network for Alzheimer’s disease classification with evaluation of imaging modality and longitudinal data. Phys Med Biol 2022; 67. [PMID: 36055243 DOI: 10.1088/1361-6560/ac8f10] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 09/02/2022] [Indexed: 11/11/2022]
Abstract
Abstract
Objective. Neuroimaging uncovers important information about disease in the brain. Yet in Alzheimer’s disease (AD), there remains a clear clinical need for reliable tools to extract diagnoses from neuroimages. Significant work has been done to develop deep learning (DL) networks using neuroimaging for AD diagnosis. However, no particular model has emerged as optimal. Due to a lack of direct comparisons and evaluations on independent data, there is no consensus on which modality is best for diagnostic models or whether longitudinal information enhances performance. The purpose of this work was (1) to develop a generalizable DL model to distinguish neuroimaging scans of AD patients from controls and (2) to evaluate the influence of imaging modality and longitudinal data on performance. Approach. We trained a 2-class convolutional neural network (CNN) with and without a cascaded recurrent neural network (RNN). We used datasets of 772 (N
AD = 364, N
control = 408) 3D 18F-FDG PET scans and 780 (N
AD = 280, N
control = 500) T1-weighted volumetric-3D MR images (containing 131 and 144 patients with multiple timepoints) from the Alzheimer’s Disease Neuroimaging Initiative, plus an independent set of 104 (N
AD = 63, N
NC = 41) 18F-FDG PET scans (one per patient) for validation. Main Results. ROC analysis showed that PET-trained models outperformed MRI-trained, achieving maximum AUC with the CNN + RNN model of 0.93 ± 0.08, with accuracy 82.5 ± 8.9%. Adding longitudinal information offered significant improvement to performance on 18F-FDG PET, but not on T1-MRI. CNN model validation with an independent 18F-FDG PET dataset achieved AUC of 0.99. Layer-wise relevance propagation heatmaps added CNN interpretability. Significance. The development of a high-performing tool for AD diagnosis, with the direct evaluation of key influences, reveals the advantage of using 18F-FDG PET and longitudinal data over MRI and single timepoint analysis. This has significant implications for the potential of neuroimaging for future research on AD diagnosis and clinical management of suspected AD patients.
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90
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Nosheny RL, Amariglio R, Sikkes SA, Van Hulle C, Bicalho MAC, Dowling NM, Brucki SMD, Ismail Z, Kasuga K, Kuhn E, Numbers K, Aaronson A, Moretti DV, Pereiro AX, Sánchez‐Benavides G, Sellek Rodríguez AF, Urwyler P, Zawaly K. The role of dyadic cognitive report and subjective cognitive decline in early ADRD clinical research and trials: Current knowledge, gaps, and recommendations. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2022; 8:e12357. [PMID: 36226046 PMCID: PMC9530696 DOI: 10.1002/trc2.12357] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 08/05/2022] [Accepted: 08/22/2022] [Indexed: 11/05/2022]
Abstract
Efficient identification of cognitive decline and Alzheimer's disease (AD) risk in early stages of the AD disease continuum is a critical unmet need. Subjective cognitive decline is increasingly recognized as an early symptomatic stage of AD. Dyadic cognitive report, including subjective cognitive complaints (SCC) from a participant and an informant/study partner who knows the participant well, represents an accurate, reliable, and efficient source of data for assessing risk. However, the separate and combined contributions of self- and study partner report, and the dynamic relationship between the two, remains unclear. The Subjective Cognitive Decline Professional Interest Area within the Alzheimer's Association International Society to Advance Alzheimer's Research and Treatment convened a working group focused on dyadic patterns of subjective report. Group members identified aspects of dyadic-report information important to the AD research field, gaps in knowledge, and recommendations. By reviewing existing data on this topic, we found evidence that dyadic measures are associated with objective measures of cognition and provide unique information in preclinical and prodromal AD about disease stage and progression and AD biomarker status. External factors including dyad (participant-study partner pair) relationship and sociocultural factors contribute to these associations. We recommend greater dyad report use in research settings to identify AD risk. Priority areas for future research include (1) elucidation of the contributions of demographic and sociocultural factors, dyad type, and dyad relationship to dyad report; (2) exploration of agreement and discordance between self- and study partner report across the AD syndromic and disease continuum; (3) identification of domains (e.g., memory, executive function, neuropsychiatric) that predict AD risk outcomes and differentiate cognitive impairment due to AD from other impairment; (4) development of best practices for study partner engagement; (5) exploration of study partner report as AD clinical trial endpoints; (6) continued development, validation, and optimization, of study partner report instruments tailored to the goals of the research and population.
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Affiliation(s)
- Rachel L. Nosheny
- University of California San FranciscoDepartment of PsychiatrySan FranciscoCaliforniaUSA
- Veteran's Administration Advanced Research CenterSan FranciscoCaliforniaUSA
| | - Rebecca Amariglio
- Center for Alzheimer Research and TreatmentDepartment of NeurologyBrigham and Women's HospitalDepartment of Neurology Massachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Sietske A.M. Sikkes
- Amsterdam University Medical CentersDepartment of NeurologyAlzheimer Center AmsterdamNorth Hollandthe Netherlands/VU UniversityDepartment of ClinicalNeuro & Development PsychologyNorth Hollandthe Netherlands
| | - Carol Van Hulle
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Maria Aparecida Camargos Bicalho
- UFMG: Federal University of Minas GeraisDepartment of Clinical MedicineJenny de Andrade Faria – Center for Geriatrics and Gerontology of UFMGBelo HorizonteBrazil
| | - N. Maritza Dowling
- George Washington UniversityDepartment of Acute & Chronic CareSchool of NursingDepartment of Epidemiology & BiostatisticsMilken Institute School of Public HealthWashingtonDistrict of ColumbiaUSA
| | | | - Zahinoor Ismail
- Hotchkiss Brain Institute and O'Brien Institute for Public HealthCumming School of MedicineUniversity of CalgaryCalgaryAlbertaCanada
| | - Kensaku Kasuga
- Department of Molecular GeneticsBrain Research InstituteNiigata UniversityNiigataJapan
| | - Elizabeth Kuhn
- UNICAEN, INSERM, PhIND “Physiopathology and Imaging of Neurological Disorders,”Institut Blood and Brain @ Caen‐NormandieNormandie UniversityCaenFrance
| | - Katya Numbers
- Centre for Healthy Brain Ageing (CHeBA)Department of PsychiatryUniversity of New South WalesSydneyNew South WalesAustralia
| | - Anna Aaronson
- Veteran's Administration Advanced Research CenterSan FranciscoCaliforniaUSA
| | - Davide Vito Moretti
- IRCCS Istituto Centro San Giovanni di Dio FatebenefratelliAlzheimer Rehabilitation Operative UnitBresciaItaly
| | - Arturo X. Pereiro
- Faculty of PsychologyDepartment of Developmental PsychologyUniversity of Santiago de CompostelaGaliciaSpain
| | | | - Allis F. Sellek Rodríguez
- Costa Rican Foundation for the Care of Older Adults with Alzheimer's and Other Dementias (FundAlzheimer Costa Rica)CartagoCosta Rica
| | - Prabitha Urwyler
- ARTORG Center for Biomedical EngineeringUniversity of BernUniversity Neurorehabilitation UnitDepartment of NeurologyInselspitalBernSwitzerland
| | - Kristina Zawaly
- University of AucklandDepartment of General Practice and Primary Health CareSchool of Population HealthFaculty of Medical and Health SciencesAucklandNew Zealand
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91
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Janssen O, Jansen WJ, Vos SJ, Boada M, Parnetti L, Gabryelewicz T, Fladby T, Molinuevo JL, Villeneuve S, Hort J, Epelbaum S, Lleó A, Engelborghs S, van der Flier WM, Landau S, Popp J, Wallin A, Scheltens P, Rikkert MO, Snyder PJ, Rowe C, Chételat G, Ruíz A, Marquié M, Chipi E, Wolfsgruber S, Heneka M, Boecker H, Peters O, Jarholm J, Rami L, Tort‐Merino A, Binette AP, Poirier J, Rosa‐Neto P, Cerman J, Dubois B, Teichmann M, Alcolea D, Fortea J, Sánchez‐Saudinós MB, Ebenau J, Pocnet C, Eckerström M, Thompson L, Villemagne V, Buckley R, Burnham S, Delarue M, Freund‐Levi Y, Wallin ÅK, Ramakers I, Tsolaki M, Soininen H, Hampel H, Spiru L, Tijms B, Ossenkoppele R, Verhey FRJ, Jessen F, Visser PJ. Characteristics of subjective cognitive decline associated with amyloid positivity. Alzheimers Dement 2022; 18:1832-1845. [PMID: 34877782 PMCID: PMC9786747 DOI: 10.1002/alz.12512] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 07/21/2021] [Accepted: 09/22/2021] [Indexed: 01/28/2023]
Abstract
INTRODUCTION The evidence for characteristics of persons with subjective cognitive decline (SCD) associated with amyloid positivity is limited. METHODS In 1640 persons with SCD from 20 Amyloid Biomarker Study cohort, we investigated the associations of SCD-specific characteristics (informant confirmation, domain-specific complaints, concerns, feelings of worse performance) demographics, setting, apolipoprotein E gene (APOE) ε4 carriership, and neuropsychiatric symptoms with amyloid positivity. RESULTS Between cohorts, amyloid positivity in 70-year-olds varied from 10% to 76%. Only older age, clinical setting, and APOE ε4 carriership showed univariate associations with increased amyloid positivity. After adjusting for these, lower education was also associated with increased amyloid positivity. Only within a research setting, informant-confirmed complaints, memory complaints, attention/concentration complaints, and no depressive symptoms were associated with increased amyloid positivity. Feelings of worse performance were associated with less amyloid positivity at younger ages and more at older ages. DISCUSSION Next to age, setting, and APOE ε4 carriership, SCD-specific characteristics may facilitate the identification of amyloid-positive individuals.
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Affiliation(s)
- Olin Janssen
- Alzheimer Centre LimburgDepartment of Psychiatry and NeuropsychologySchool for Mental Health and NeuroscienceMaastricht UniversityMaastrichtThe Netherlands
| | - Willemijn J. Jansen
- Alzheimer Centre LimburgDepartment of Psychiatry and NeuropsychologySchool for Mental Health and NeuroscienceMaastricht UniversityMaastrichtThe Netherlands
| | - Stephanie J.B. Vos
- Alzheimer Centre LimburgDepartment of Psychiatry and NeuropsychologySchool for Mental Health and NeuroscienceMaastricht UniversityMaastrichtThe Netherlands
| | - Merce Boada
- Fundació ACEInstitut Català de Neurociències AplicadesFacultat de MedicinaUniversitat International de Catalunya‐BarcelonaBarcelonaSpain,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED)Instituto de Salud Carlos IIIMadridSpain
| | - Lucilla Parnetti
- Section of NeurologyCenter for Memory Disturbances – Lab. of Clinical NeurochemistryDepartment of Medicine and SurgeryUniversity of PerugiaPerugiaItaly
| | - Tomasz Gabryelewicz
- Department of Neurodegenerative DisordersMossakowski Medical Research CentrePolish Academy of SciencesWarsawPoland
| | - Tormod Fladby
- Department of NeurologyAkershus University HospitalLorenskogNorway
| | - José Luis Molinuevo
- Alzheimer's Disease and Other Cognitive Disorders UnitNeurology Service, Hospital Clínic of BarcelonaAugust Pi i Sunyer Biomedical Research Institute (IDIBAPS)BarcelonaSpain
| | - Sylvia Villeneuve
- Centre for Studies on Prevention of Alzheimer's Disease (StOP‐AD) CentreMontrealQuebecCanada
| | - Jakub Hort
- Department of NeurologySecond Faculty of MedicineCharles University and Motol University HospitalPragueCzech Republic,International Clinical Research CenterSt. Anne's University HospitalBrnoCzech Republic
| | - Stéphane Epelbaum
- AP‐HPHôpital de la Pitié SalpêtrièreInstitute of Memory and Alzheimer's Disease (IM2A)Centre of excellence of neurodegenerative disease (CoEN)Department of NeurologyParisFrance,Inserm Sorbonne UniversitéInriaAramis project‐teamParis Brain Institute – Institut du Cerveau (ICM)ParisFrance
| | - Alberto Lleó
- Neurology DepartmentHospital de Sant PauBarcelonaSpain
| | | | - Wiesje M. van der Flier
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceAmsterdam UMCVrije Universiteit AmsterdamAmsterdamThe Netherlands
| | - Susan Landau
- Helen Wills Neuroscience InstituteUniversity of CaliforniaBerkeley, CaliforniaUSA
| | - Julius Popp
- Department of Geriatric PsychiatryPsychiatric University Hospital, ZürichSwitzerland,Old Age PsychiatryUniversity Hospital of LausanneLausanneSwitzerland
| | - Anders Wallin
- CSIRO Health & BiosecurityParkvilleVictoriaAustralia,Institute of Neuroscience and PhysiologySahlgrenska Academy at University of GothenburgMölndalSweden
| | - Philip Scheltens
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceAmsterdam UMCVrije Universiteit AmsterdamAmsterdamThe Netherlands
| | - Marcel Olde Rikkert
- Department of Geriatric MedicineRadboud Alzheimer CenterRadboud University Medical CenterNijmegenThe Netherlands
| | - Peter J. Snyder
- Institute of Clinical MedicineUniversity of OsloOsloNorway,KingstonThe University of Rhode IslandRhode IslandUSA
| | - Chris Rowe
- Department of Molecular Imaging & TherapyAustin HealthMelbourneAustralia
| | - Gaël Chételat
- Institut National de la Sant. et de la Recherche M.dicale (Inserm)CaenFrance
| | - Agustin Ruíz
- Fundació ACEInstitut Català de Neurociències AplicadesFacultat de MedicinaUniversitat International de Catalunya‐BarcelonaBarcelonaSpain,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED)Instituto de Salud Carlos IIIMadridSpain
| | - Marta Marquié
- Fundació ACEInstitut Català de Neurociències AplicadesFacultat de MedicinaUniversitat International de Catalunya‐BarcelonaBarcelonaSpain,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED)Instituto de Salud Carlos IIIMadridSpain
| | - Elena Chipi
- Section of NeurologyCenter for Memory Disturbances – Lab. of Clinical NeurochemistryDepartment of Medicine and SurgeryUniversity of PerugiaPerugiaItaly
| | - Steffen Wolfsgruber
- German Center For Neurodegenerative Diseases/Clinical ResearchDeutsches Zentrum für Neurodegenerative Erkrankungen e.V. (DZNE)Zentrum für klinische Forschung/AGCologneGermany,Department of Neurodegenerative Diseases and PsychiatryUniversity Hospital BonnBonnGermany
| | - Michael Heneka
- Department of Neurodegenerative Diseases and PsychiatryUniversity Hospital BonnBonnGermany
| | - Henning Boecker
- Functional Neuroimaging GroupDepartment of RadiologyUniversity Hospital BonnBonnGermany
| | - Oliver Peters
- Klinik für Psychiatrie und PsychotherapieCharité Universitätsmedizin Berlin ‐ CBFBerlinDeutschland
| | - Jonas Jarholm
- Department of NeurologyAkershus University HospitalLorenskogNorway
| | - Lorena Rami
- Alzheimer's Disease and Other Cognitive Disorders UnitNeurology Service, Hospital Clínic of BarcelonaAugust Pi i Sunyer Biomedical Research Institute (IDIBAPS)BarcelonaSpain
| | - Adrià Tort‐Merino
- Alzheimer's Disease and Other Cognitive Disorders UnitNeurology Service, Hospital Clínic of BarcelonaAugust Pi i Sunyer Biomedical Research Institute (IDIBAPS)BarcelonaSpain
| | - Alexa Pichet Binette
- Centre for Studies on Prevention of Alzheimer's Disease (StOP‐AD) CentreMontrealQuebecCanada
| | - Judes Poirier
- Centre for Studies on Prevention of Alzheimer's Disease (StOP‐AD) CentreMontrealQuebecCanada
| | - Pedro Rosa‐Neto
- Centre for Studies on Prevention of Alzheimer's Disease (StOP‐AD) CentreMontrealQuebecCanada
| | - Jiri Cerman
- Department of NeurologySecond Faculty of MedicineCharles University and Motol University HospitalPragueCzech Republic,International Clinical Research CenterSt. Anne's University HospitalBrnoCzech Republic
| | - Bruno Dubois
- AP‐HPHôpital de la Pitié SalpêtrièreInstitute of Memory and Alzheimer's Disease (IM2A)Centre of excellence of neurodegenerative disease (CoEN)Department of NeurologyParisFrance
| | - Marc Teichmann
- AP‐HPHôpital de la Pitié SalpêtrièreInstitute of Memory and Alzheimer's Disease (IM2A)Centre of excellence of neurodegenerative disease (CoEN)Department of NeurologyParisFrance
| | | | - Juan Fortea
- Neurology DepartmentHospital de Sant PauBarcelonaSpain
| | | | - Jarith Ebenau
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceAmsterdam UMCVrije Universiteit AmsterdamAmsterdamThe Netherlands
| | - Cornelia Pocnet
- Old Age PsychiatryUniversity Hospital of LausanneLausanneSwitzerland
| | - Marie Eckerström
- Institute of Neuroscience and PhysiologySahlgrenska Academy at University of GothenburgMölndalSweden
| | - Louisa Thompson
- Institute of Clinical MedicineUniversity of OsloOsloNorway,KingstonThe University of Rhode IslandRhode IslandUSA
| | - Victor Villemagne
- Department of Molecular Imaging & TherapyAustin HealthMelbourneAustralia,Department of PsychiatryUniversity of PittsburghPittsburghUSA
| | - Rachel Buckley
- Brigham and Women's Hospital and Department of Neurology Massachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Samantha Burnham
- Section of NeurologyCenter for Memory Disturbances – Lab. of Clinical NeurochemistryDepartment of Medicine and SurgeryUniversity of PerugiaPerugiaItaly
| | - Marion Delarue
- Institut National de la Sant. et de la Recherche M.dicale (Inserm)CaenFrance
| | - Yvonne Freund‐Levi
- Department of NeurobiologyCare Sciences and SocietyKarolinska InstitutetStockholmSweden
| | - Åsa K. Wallin
- Department of Clinical Sciences MalmöClinical Memory Research UnitLund UniversityLundSweden
| | - Inez Ramakers
- Alzheimer Centre LimburgDepartment of Psychiatry and NeuropsychologySchool for Mental Health and NeuroscienceMaastricht UniversityMaastrichtThe Netherlands
| | - Magda Tsolaki
- Memory and Dementia Center3rd Department of Neurology“G Papanicolau” General HospitalAristotle University of ThessalonikiThessalonikiGreece
| | - Hilkka Soininen
- Institute of Clinical MedicineNeurologyUniversity of Eastern FinlandKuopioFinland
| | - Harald Hampel
- GRC no 21, Alzheimer Precision Medicine (AMP)AP‐HPPitié‐Salpêtrière HospitalSorbonne UniversityParisFrance
| | - Luiza Spiru
- Carol DAVILA University of Medicine and PharmacyBucharestRomania,Geriatrics‐ Gerontology and Old Age PsychiatryAlzheimer UnitAna Aslan International Foundation – Memory Center and Longevity MedicineBucharestRomania
| | | | | | | | - Betty Tijms
- Alzheimer Centre LimburgDepartment of Psychiatry and NeuropsychologySchool for Mental Health and NeuroscienceMaastricht UniversityMaastrichtThe Netherlands
| | - Rik Ossenkoppele
- Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceAmsterdam UMCVrije Universiteit AmsterdamAmsterdamThe Netherlands,Clinical Memory Research UnitDepartment of Clinical SciencesMalmöLund UniversityLundSweden,Alzheimer's Disease and Other Cognitive Disorders UnitNeurology Service, Hospital Clínic of BarcelonaAugust Pi i Sunyer Biomedical Research Institute (IDIBAPS)BarcelonaSpain
| | - Frans R. J. Verhey
- Alzheimer Centre LimburgDepartment of Psychiatry and NeuropsychologySchool for Mental Health and NeuroscienceMaastricht UniversityMaastrichtThe Netherlands
| | - Frank Jessen
- Department of PsychiatryUniversity of CologneCologneGermany,German Center For Neurodegenerative Diseases/Clinical ResearchDeutsches Zentrum für Neurodegenerative Erkrankungen e.V. (DZNE)Zentrum für klinische Forschung/AGCologneGermany
| | - Pieter Jelle Visser
- Alzheimer Centre LimburgDepartment of Psychiatry and NeuropsychologySchool for Mental Health and NeuroscienceMaastricht UniversityMaastrichtThe Netherlands,Alzheimer Center AmsterdamDepartment of NeurologyAmsterdam NeuroscienceAmsterdam UMCVrije Universiteit AmsterdamAmsterdamThe Netherlands,Department of NeurobiologyCare Sciences and SocietyKarolinska InstitutetStockholmSweden
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92
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van der Flier WM, Scheltens P. The ATN Framework—Moving Preclinical Alzheimer Disease to Clinical Relevance. JAMA Neurol 2022; 79:968-970. [DOI: 10.1001/jamaneurol.2022.2967] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Wiesje M. van der Flier
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Epidemiology and Data Science, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- EQT Life Sciences, Amsterdam, the Netherlands
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93
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Baldeiras I, Silva-Spínola A, Lima M, Leitão MJ, Durães J, Vieira D, Tbuas-Pereira M, Cruz VT, Rocha R, Alves L, Machado Á, Milheiro M, Santiago B, Santana I. Alzheimer’s Disease Diagnosis Based on the Amyloid, Tau, and Neurodegeneration Scheme (ATN) in a Real-Life Multicenter Cohort of General Neurological Centers. J Alzheimers Dis 2022; 90:419-432. [DOI: 10.3233/jad-220587] [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 ATN scheme was proposed as an unbiased biological characterization of the Alzheimer’s disease (AD) spectrum, grouping biomarkers into three categories: brain Amyloidosis-A, Tauopathy-T, Neurodegeneration-N. Although this scheme was mainly recommended for research, it is relevant for diagnosis. Objective: To evaluate the ATN scheme performance in real-life cohorts reflecting the inflow of patients with cognitive complaints and different underlying disorders in general neurological centers. Methods: We included patients (n = 1,128) from six centers with their core cerebrospinal fluid-AD biomarkers analyzed centrally. A was assessed through Aβ 42/Aβ 40, T through pTau-181, and N through tTau. Association between demographic features, clinical diagnosis at baseline/follow-up and ATN profiles was assessed. Results: The prevalence of ATN categories was: A-T-N-: 28.3% ; AD continuum (A + T-/+N-/+): 47.8% ; non-AD (A- plus T or/and N+): 23.9% . ATN profiles prevalence was strongly influenced by age, showing differences according to gender, APOE genotype, and cognitive status. At baseline, 74.6% of patients classified as AD fell in the AD continuum, decreasing to 47.4% in mild cognitive impairment and 42.3% in other neurodegenerative conditions. At follow-up, 41% of patients changed diagnosis, and 92% of patients that changed to AD were classified within the AD continuum. A + was the best individual marker for predicting a final AD diagnosis, and the combinations A + T+(irrespective of N) and A + T+N+had the highest overall accuracy (83%). Conclusion: The ATN scheme is useful to guide AD diagnosis real-life neurological centers settings. However, it shows a lack of accuracy for patients with other types of dementia. In such cases, the inclusion of other markers specific for non-AD proteinopathies could be an important aid to the differential diagnosis.
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Affiliation(s)
- Inês Baldeiras
- Neurology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
- Faculdade de Medicina, Universidade de Coimbra, Coimbra, Portugal
- Center for Neuroscience and Cell Biology; Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal
| | - Anuschka Silva-Spínola
- Center for Neuroscience and Cell Biology; Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal
| | - Marisa Lima
- Neurology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
- Center for Neuroscience and Cell Biology; Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal
- Center for Research in Neuropsychology and Cognitive Behavioral Intervention, Faculty of Psychology and Educational Sciences, University of Coimbra, Coimbra, Portugal
| | - Maria João Leitão
- Center for Neuroscience and Cell Biology; Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal
| | - João Durães
- Neurology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
- Faculdade de Medicina, Universidade de Coimbra, Coimbra, Portugal
- Center for Neuroscience and Cell Biology; Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal
| | - Daniela Vieira
- Neurology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Miguel Tbuas-Pereira
- Neurology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
- Faculdade de Medicina, Universidade de Coimbra, Coimbra, Portugal
- Center for Neuroscience and Cell Biology; Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal
| | | | - Raquel Rocha
- ULSM Unidade Local de Sáude de Matosinhos, Matosinhos, Portugal
| | - Luisa Alves
- Hospital Egas Moniz, Centro Hospitalar de Lisboa Ocidental, Lisboa, Portugal
| | | | | | | | - Isabel Santana
- Neurology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
- Faculdade de Medicina, Universidade de Coimbra, Coimbra, Portugal
- Center for Neuroscience and Cell Biology; Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal
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94
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Ebenau JL, Visser D, Kroeze LA, van Leeuwenstijn MSSA, van Harten AC, Windhorst AD, Golla SVS, Boellaard R, Scheltens P, Barkhof F, van Berckel BNM, van der Flier WM. Longitudinal change in ATN biomarkers in cognitively normal individuals. Alzheimers Res Ther 2022; 14:124. [PMID: 36057616 PMCID: PMC9440493 DOI: 10.1186/s13195-022-01069-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 08/23/2022] [Indexed: 04/14/2023]
Abstract
BACKGROUND Biomarkers for amyloid, tau, and neurodegeneration (ATN) have predictive value for clinical progression, but it is not clear how individuals move through these stages. We examined changes in ATN profiles over time, and investigated determinants of change in A status, in a sample of cognitively normal individuals presenting with subjective cognitive decline (SCD). METHODS We included 92 individuals with SCD from the SCIENCe project with [18F]florbetapir PET (A) available at two time points (65 ± 8y, 42% female, MMSE 29 ± 1, follow-up 2.5 ± 0.7y). We additionally used [18F]flortaucipir PET for T and medial temporal atrophy score on MRI for N. Thirty-nine individuals had complete biomarker data at baseline and follow-up, enabling the construction of ATN profiles at two time points. All underwent extensive neuropsychological assessments (follow-up time 4.9 ± 2.8y, median number of visits n = 4). We investigated changes in biomarker status and ATN profiles over time. We assessed which factors predisposed for a change from A- to A+ using logistic regression. We additionally used linear mixed models to assess change from A- to A+, compared to the group that remained A- at follow-up, as predictor for cognitive decline. RESULTS At baseline, 62% had normal AD biomarkers (A-T-N- n = 24), 5% had non-AD pathologic change (A-T-N+ n = 2,) and 33% fell within the Alzheimer's continuum (A+T-N- n = 9, A+T+N- n = 3, A+T+N+ n = 1). Seventeen subjects (44%) changed to another ATN profile over time. Only 6/17 followed the Alzheimer's disease sequence of A → T → N, while 11/17 followed a different order (e.g., reverted back to negative biomarker status). APOE ε4 carriership inferred an increased risk of changing from A- to A+ (OR 5.2 (95% CI 1.2-22.8)). Individuals who changed from A- to A+, showed subtly steeper decline on Stroop I (β - 0.03 (SE 0.01)) and Stroop III (- 0.03 (0.01)), compared to individuals who remained A-. CONCLUSION We observed considerable variability in the order of ATN biomarkers becoming abnormal. Individuals who became A+ at follow-up showed subtle decline on tests for attention and executive functioning, confirming clinical relevance of amyloid positivity.
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Affiliation(s)
- Jarith L Ebenau
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands.
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands.
| | - Denise Visser
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Radiology & Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
| | - Lior A Kroeze
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Mardou S S A van Leeuwenstijn
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Argonde C van Harten
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Albert D Windhorst
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Radiology & Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
| | - Sandeep V S Golla
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Radiology & Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
| | - Ronald Boellaard
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Radiology & Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Radiology & Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- UCL Institutes of Neurology and Healthcare Engineering, London, UK
| | - Bart N M van Berckel
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Radiology & Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Epidemiology & Data Science, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
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95
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A dominance analysis of subjective cognitive complaint comorbidities in former professional football players with and without mild cognitive impairment. J Int Neuropsychol Soc 2022:1-12. [PMID: 36039970 PMCID: PMC9971325 DOI: 10.1017/s135561772200056x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
OBJECTIVES Subjective cognitive difficulties (SCDs) are associated with factors commonly reported in older adults and former contact sport athletes, regardless of objective cognitive decline. We investigated the relative contribution of these factors to SCD in former National Football League (NFL)-players with and without a diagnosis of mild cognitive impairment (MCI). METHODS Former NFL players (n = 907) aged ≥ 50 years (mean = 64.7 ± 8.9), with (n = 165) and without (n = 742) a diagnosis of MCI completed health questionnaires. Multivariable regression and dominance analyses determined the relative importance of SCD factors on SCD: 1) depression, 2) anxiety, 3) sleep disturbance, 4) pain interference, 5) ability to participate in social roles and activities, 6) stress-related events, 7) fatigue, 8) concussion history, and 9) education. SCD outcomes included Neuro-QoL Emotional-Behavioral Dyscontrol and the PROMIS Cognitive Function. Fisher's z-transformation compared comorbid contributing factors to SCD across MCI and non-MCI groups. RESULTS Complete dominance of anxiety was established over most comorbid factors across the MCI and non-MCI groups. Fatigue also exhibited complete dominance over most comorbid factors, though its influence in the MCI group was less robust (general dominance). Average contributions to variance accounted for by comorbid factors to ratings of SCD across MCI and non-MCI groups did not statistically differ (Z-statistics <1.96, ps>.05). CONCLUSIONS Anxiety and fatigue are the most robust factors associated with SCD in former professional football players across various combinations of clinical presentations (different combinations of comorbid factors), regardless of documented cognitive impairment. Self-reported deficits may be less reliable in detecting objective impairment in the presence of these factors, with multidimensional assessment being ideal.
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96
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Kumar V, Kim SH, Bishayee K. Dysfunctional Glucose Metabolism in Alzheimer’s Disease Onset and Potential Pharmacological Interventions. Int J Mol Sci 2022; 23:ijms23179540. [PMID: 36076944 PMCID: PMC9455726 DOI: 10.3390/ijms23179540] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 08/05/2022] [Accepted: 08/21/2022] [Indexed: 12/04/2022] Open
Abstract
Alzheimer’s disease (AD) is the most common age-related dementia. The alteration in metabolic characteristics determines the prognosis. Patients at risk show reduced glucose uptake in the brain. Additionally, type 2 diabetes mellitus increases the risk of AD with increasing age. Therefore, changes in glucose uptake in the cerebral cortex may predict the histopathological diagnosis of AD. The shifts in glucose uptake and metabolism, insulin resistance, oxidative stress, and abnormal autophagy advance the pathogenesis of AD syndrome. Here, we summarize the role of altered glucose metabolism in type 2 diabetes for AD prognosis. Additionally, we discuss diagnosis and potential pharmacological interventions for glucose metabolism defects in AD to encourage the development of novel therapeutic methods.
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Affiliation(s)
- Vijay Kumar
- Department of Biochemistry, Institute of Cell Differentiation and Aging, College of Medicine, Hallym University, Chuncheon 24252, Korea
| | - So-Hyeon Kim
- Biomedical Science Core-Facility, Soonchunhyang Institute of Medi-Bio Science, Soonchunhyang University, Cheonan 31151, Korea
| | - Kausik Bishayee
- Biomedical Science Core-Facility, Soonchunhyang Institute of Medi-Bio Science, Soonchunhyang University, Cheonan 31151, Korea
- Correspondence: or
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97
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Oberstein TJ, Schmidt MA, Florvaag A, Haas AL, Siegmann EM, Olm P, Utz J, Spitzer P, Doerfler A, Lewczuk P, Kornhuber J, Maler JM. Amyloid-β levels and cognitive trajectories in non-demented pTau181-positive subjects without amyloidopathy. Brain 2022; 145:4032-4041. [PMID: 35973034 DOI: 10.1093/brain/awac297] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 07/11/2022] [Accepted: 07/24/2022] [Indexed: 11/13/2022] Open
Abstract
Phosphorylated Tau181 (pTau181) in cerebrospinal fluid (CSF) and recently in plasma has been associated with Alzheimer's disease. In the absence of amyloidopathy, individuals with increased total Tau levels and/or temporal lobe atrophy experience no or only mild cognitive decline compared with biomarker-negative controls, leading to the proposal to categorize this constellation as Suspected non-Alzheimer disease pathophysiology (SNAP). We investigated whether the characteristics of SNAP also applied to individuals with increased CSF-pTau181 without amyloidopathy. In this long-term observational study, 285 non-demented individuals, including 76 individuals with subjective cognitive impairment and 209 individuals with mild cognitive impairment, were classified based on their CSF-levels of pTau181 (T), total Tau (N), Amyloid-beta-(Aβ)-42 and Aβ42/Aβ40 ratio (A) into A + T+N±, A + T-N±, A-T + N±, and A-T-N-. The longitudinal analysis included 154 subjects with a follow-up of more than 12 months who were followed to a median of 4.6 years (interquartile range = 4.3 years). We employed linear mixed models on psychometric tests and region of interest analysis of structural MRI data. Cognitive decline and hippocampal atrophy rate were significantly higher in A + T+N ± compared to A-T + N±, whereas there was no difference between A-T + N ± and A-T-N-. Furthermore, there was no significant difference between A-T + N ± and controls in dementia risk (Hazard ratio 0.3, 95% confidence interval [0.1, 1.9]). However, A-T + N ± and A-T-N- could be distinguished based on their Aβ42 and Aβ40 levels. Both Aβ40 and Aβ42 levels were significantly increased in A-T + N ± compared to controls. Long term follow-up of A-T + N ± individuals revealed no evidence that this biomarker constellation was associated with dementia or more severe hippocampal atrophy rates compared to controls. However, because of the positive association of pTau181 with Aβ in the A-T + N ± group, a link to the pathophysiology of Alzheimer´s disease cannot be excluded in this case. We propose to refer to these individuals in the SNAP group as "pTau and Aβ surge with subtle deterioration" (PASSED). The investigation of the circumstances of simultaneous elevation of pTau and Aβ might provide a deeper insight into the process under which Aβ becomes pathological.
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Affiliation(s)
- Timo Jan Oberstein
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Manuel Alexander Schmidt
- Institute of Neuroradiology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Anna Florvaag
- Department of Radiology and Nuclear Medicine, Klinikum Nuremberg, Nuremberg, Germany
| | - Anna Lena Haas
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Eva Maria Siegmann
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Pauline Olm
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Janine Utz
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Philipp Spitzer
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Arnd Doerfler
- Institute of Neuroradiology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Piotr Lewczuk
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.,Department of Neurodegeneration Diagnostics, Medical University of Bialystok, University Hospital of Bialystok, Bialystok, Poland.,Department of Biochemical Diagnostics, University Hospital of Bialystok, Bialystok, Poland
| | - Johannes Kornhuber
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Juan Manuel Maler
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
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Dulewicz M, Kulczyńska-Przybik A, Mroczko P, Kornhuber J, Lewczuk P, Mroczko B. Biomarkers for the Diagnosis of Alzheimer’s Disease in Clinical Practice: The Role of CSF Biomarkers during the Evolution of Diagnostic Criteria. Int J Mol Sci 2022; 23:ijms23158598. [PMID: 35955728 PMCID: PMC9369334 DOI: 10.3390/ijms23158598] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 07/30/2022] [Accepted: 07/30/2022] [Indexed: 11/16/2022] Open
Abstract
Alzheimer’s disease (AD) is a progressive condition and the most common cause of dementia worldwide. The neuropathological changes characteristic of the disorder can be successfully detected before the development of full-blown AD. Early diagnosis of the disease constitutes a formidable challenge for clinicians. CSF biomarkers are the in vivo evidence of neuropathological changes developing in the brain of dementia patients. Therefore, measurement of their concentrations allows for improved accuracy of clinical diagnosis. Moreover, AD biomarkers may provide an indication of disease stage. Importantly, the CSF biomarkers of AD play a pivotal role in the new diagnostic criteria for the disease, and in the recent biological definition of AD by the National Institute on Aging, NIH and Alzheimer’s Association. Due to the necessity of collecting CSF by lumbar puncture, the procedure seems to be an important issue not only from a medical, but also a legal, viewpoint. Furthermore, recent technological advances may contribute to the automation of AD biomarkers measurement and may result in the establishment of unified cut-off values and reference limits. Moreover, a group of international experts in the field of AD biomarkers have developed a consensus and guidelines on the interpretation of CSF biomarkers in the context of AD diagnosis. Thus, technological advancement and expert recommendations may contribute to a more widespread use of these diagnostic tests in clinical practice to support a diagnosis of mild cognitive impairment (MCI) or dementia due to AD. This review article presents up-to-date data regarding the usefulness of CSF biomarkers in routine clinical practice and in biomarkers research.
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Affiliation(s)
- Maciej Dulewicz
- Department of Neurodegeneration Diagnostics, Medical University of Bialystok, 15-269 Bialystok, Poland; (A.K.-P.); (P.L.); (B.M.)
- Correspondence:
| | - Agnieszka Kulczyńska-Przybik
- Department of Neurodegeneration Diagnostics, Medical University of Bialystok, 15-269 Bialystok, Poland; (A.K.-P.); (P.L.); (B.M.)
| | - Piotr Mroczko
- Department of Criminal Law and Criminology, Faculty of Law, University of Bialystok, 15-213 Bialystok, Poland;
| | - Johannes Kornhuber
- Department of Psychiatry and Psychotherapy, Universitätsklinikum Erlangen and Friedrich-Alexander Universität Erlangen-Nürnberg, 91054 Erlangen, Germany;
| | - Piotr Lewczuk
- Department of Neurodegeneration Diagnostics, Medical University of Bialystok, 15-269 Bialystok, Poland; (A.K.-P.); (P.L.); (B.M.)
- Department of Psychiatry and Psychotherapy, Universitätsklinikum Erlangen and Friedrich-Alexander Universität Erlangen-Nürnberg, 91054 Erlangen, Germany;
| | - Barbara Mroczko
- Department of Neurodegeneration Diagnostics, Medical University of Bialystok, 15-269 Bialystok, Poland; (A.K.-P.); (P.L.); (B.M.)
- Department of Biochemical Diagnostics, Medical University of Bialystok, 15-269 Bialystok, Poland
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Kikuchi M, Kobayashi K, Itoh S, Kasuga K, Miyashita A, Ikeuchi T, Yumoto E, Kosaka Y, Fushimi Y, Takeda T, Manabe S, Hattori S, Disease Neuroimaging Initiative A, Nakaya A, Kamijo K, Matsumura Y. Identification of mild cognitive impairment subtypes predicting conversion to Alzheimer’s disease using multimodal data. Comput Struct Biotechnol J 2022; 20:5296-5308. [PMID: 36212530 PMCID: PMC9513733 DOI: 10.1016/j.csbj.2022.08.007] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 08/03/2022] [Accepted: 08/03/2022] [Indexed: 11/27/2022] Open
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100
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Tondo G, Boccalini C, Vanoli EG, Presotto L, Muscio C, Ciullo V, Banaj N, Piras F, Filippini G, Tiraboschi P, Tagliavini F, Frisoni GB, Cappa SF, Spalletta G, Perani D. Brain Metabolism and Amyloid Load in Individuals With Subjective Cognitive Decline or Pre-Mild Cognitive Impairment. Neurology 2022; 99:e258-e269. [PMID: 35487700 PMCID: PMC9302934 DOI: 10.1212/wnl.0000000000200351] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2021] [Accepted: 02/21/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVE This was a multicenter study aimed at investigating the characteristics of cognitive decline, neuropsychiatric symptoms, and brain imaging in individuals with subjective cognitive decline (SCD) and subtle cognitive decline (pre-mild cognitive impairment [pre-MCI]). METHODS Data were obtained from the Network-AD project (NET-2011-02346784). The included participants underwent baseline cognitive and neurobehavioral evaluation, FDG-PET, and amyloid PET. We used principal component analysis (PCA) to identify independent neuropsychological and neuropsychiatric dimensions and their association with brain metabolism. RESULTS A total of 105 participants (SCD = 49, pre-MCI = 56) were included. FDG-PET was normal in 45% of participants and revealed brain hypometabolism in 55%, with a frontal-like pattern as the most frequent finding (28%). Neuropsychiatric symptoms emerging from the Neuropsychiatric Inventory and the Starkstein Apathy Scale were highly prevalent in the whole sample (78%). An abnormal amyloid load was detected in the 18% of the participants who underwent amyloid PET (n = 60). PCA resulted in 3 neuropsychological factors: (1) executive/visuomotor, correlating with hypometabolism in frontal and occipital cortices and basal ganglia; (2) memory, correlating with hypometabolism in temporoparietal regions; and (3) visuospatial/constructional, correlating with hypometabolism in frontoparietal cortices. Two factors emerged from the neuropsychiatric PCA: (1) affective, correlating with hypometabolism in orbitofrontal and cingulate cortex and insula; (2) hyperactive/psychotic, correlating with hypometabolism in frontal, temporal, and parietal regions. DISCUSSION FDG-PET evidence suggests either normal brain function or different patterns of brain hypometabolism in SCD and pre-MCI. These results indicate that SCD and pre-MCI represent heterogeneous populations. Different neuropsychological and neuropsychiatric profiles emerged, which correlated with neuronal dysfunction in specific brain regions. Long-term follow-up studies are needed to assess the risk of progression to dementia in these conditions.
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Affiliation(s)
- Giacomo Tondo
- From Vita-Salute San Raffaele University (G.T., C.B., D.P.); In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience (G.T., C.B., L.P., D.P.), IRCCS San Raffaele Scientific Institute; Nuclear Medicine Unit (E.G.V., L.P., D.P.), San Raffaele Hospital; Unit of Neurology and Neuropathology (P.T.), Fondazione IRCCS Istituto Neurologico Carlo Besta (C.M., G.F., F.T.), Milan; Laboratory of Neuropsychiatry (V.C., N.B., F.P., G.S.), IRCCS Santa Lucia Foundation, Rome; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (G.B.F.), Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging (G.B.F.), University Hospitals and University of Geneva, Switzerland; ICoN (S.F.C.), Scuola Universitaria Superiore IUSS Pavia; and IRCCS Mondino Foundation (S.F.C.), Pavia, Italy
| | - Cecilia Boccalini
- From Vita-Salute San Raffaele University (G.T., C.B., D.P.); In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience (G.T., C.B., L.P., D.P.), IRCCS San Raffaele Scientific Institute; Nuclear Medicine Unit (E.G.V., L.P., D.P.), San Raffaele Hospital; Unit of Neurology and Neuropathology (P.T.), Fondazione IRCCS Istituto Neurologico Carlo Besta (C.M., G.F., F.T.), Milan; Laboratory of Neuropsychiatry (V.C., N.B., F.P., G.S.), IRCCS Santa Lucia Foundation, Rome; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (G.B.F.), Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging (G.B.F.), University Hospitals and University of Geneva, Switzerland; ICoN (S.F.C.), Scuola Universitaria Superiore IUSS Pavia; and IRCCS Mondino Foundation (S.F.C.), Pavia, Italy
| | - Emilia Giovanna Vanoli
- From Vita-Salute San Raffaele University (G.T., C.B., D.P.); In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience (G.T., C.B., L.P., D.P.), IRCCS San Raffaele Scientific Institute; Nuclear Medicine Unit (E.G.V., L.P., D.P.), San Raffaele Hospital; Unit of Neurology and Neuropathology (P.T.), Fondazione IRCCS Istituto Neurologico Carlo Besta (C.M., G.F., F.T.), Milan; Laboratory of Neuropsychiatry (V.C., N.B., F.P., G.S.), IRCCS Santa Lucia Foundation, Rome; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (G.B.F.), Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging (G.B.F.), University Hospitals and University of Geneva, Switzerland; ICoN (S.F.C.), Scuola Universitaria Superiore IUSS Pavia; and IRCCS Mondino Foundation (S.F.C.), Pavia, Italy
| | - Luca Presotto
- From Vita-Salute San Raffaele University (G.T., C.B., D.P.); In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience (G.T., C.B., L.P., D.P.), IRCCS San Raffaele Scientific Institute; Nuclear Medicine Unit (E.G.V., L.P., D.P.), San Raffaele Hospital; Unit of Neurology and Neuropathology (P.T.), Fondazione IRCCS Istituto Neurologico Carlo Besta (C.M., G.F., F.T.), Milan; Laboratory of Neuropsychiatry (V.C., N.B., F.P., G.S.), IRCCS Santa Lucia Foundation, Rome; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (G.B.F.), Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging (G.B.F.), University Hospitals and University of Geneva, Switzerland; ICoN (S.F.C.), Scuola Universitaria Superiore IUSS Pavia; and IRCCS Mondino Foundation (S.F.C.), Pavia, Italy
| | - Cristina Muscio
- From Vita-Salute San Raffaele University (G.T., C.B., D.P.); In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience (G.T., C.B., L.P., D.P.), IRCCS San Raffaele Scientific Institute; Nuclear Medicine Unit (E.G.V., L.P., D.P.), San Raffaele Hospital; Unit of Neurology and Neuropathology (P.T.), Fondazione IRCCS Istituto Neurologico Carlo Besta (C.M., G.F., F.T.), Milan; Laboratory of Neuropsychiatry (V.C., N.B., F.P., G.S.), IRCCS Santa Lucia Foundation, Rome; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (G.B.F.), Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging (G.B.F.), University Hospitals and University of Geneva, Switzerland; ICoN (S.F.C.), Scuola Universitaria Superiore IUSS Pavia; and IRCCS Mondino Foundation (S.F.C.), Pavia, Italy
| | - Valentina Ciullo
- From Vita-Salute San Raffaele University (G.T., C.B., D.P.); In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience (G.T., C.B., L.P., D.P.), IRCCS San Raffaele Scientific Institute; Nuclear Medicine Unit (E.G.V., L.P., D.P.), San Raffaele Hospital; Unit of Neurology and Neuropathology (P.T.), Fondazione IRCCS Istituto Neurologico Carlo Besta (C.M., G.F., F.T.), Milan; Laboratory of Neuropsychiatry (V.C., N.B., F.P., G.S.), IRCCS Santa Lucia Foundation, Rome; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (G.B.F.), Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging (G.B.F.), University Hospitals and University of Geneva, Switzerland; ICoN (S.F.C.), Scuola Universitaria Superiore IUSS Pavia; and IRCCS Mondino Foundation (S.F.C.), Pavia, Italy
| | - Nerisa Banaj
- From Vita-Salute San Raffaele University (G.T., C.B., D.P.); In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience (G.T., C.B., L.P., D.P.), IRCCS San Raffaele Scientific Institute; Nuclear Medicine Unit (E.G.V., L.P., D.P.), San Raffaele Hospital; Unit of Neurology and Neuropathology (P.T.), Fondazione IRCCS Istituto Neurologico Carlo Besta (C.M., G.F., F.T.), Milan; Laboratory of Neuropsychiatry (V.C., N.B., F.P., G.S.), IRCCS Santa Lucia Foundation, Rome; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (G.B.F.), Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging (G.B.F.), University Hospitals and University of Geneva, Switzerland; ICoN (S.F.C.), Scuola Universitaria Superiore IUSS Pavia; and IRCCS Mondino Foundation (S.F.C.), Pavia, Italy
| | - Federica Piras
- From Vita-Salute San Raffaele University (G.T., C.B., D.P.); In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience (G.T., C.B., L.P., D.P.), IRCCS San Raffaele Scientific Institute; Nuclear Medicine Unit (E.G.V., L.P., D.P.), San Raffaele Hospital; Unit of Neurology and Neuropathology (P.T.), Fondazione IRCCS Istituto Neurologico Carlo Besta (C.M., G.F., F.T.), Milan; Laboratory of Neuropsychiatry (V.C., N.B., F.P., G.S.), IRCCS Santa Lucia Foundation, Rome; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (G.B.F.), Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging (G.B.F.), University Hospitals and University of Geneva, Switzerland; ICoN (S.F.C.), Scuola Universitaria Superiore IUSS Pavia; and IRCCS Mondino Foundation (S.F.C.), Pavia, Italy
| | - Graziella Filippini
- From Vita-Salute San Raffaele University (G.T., C.B., D.P.); In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience (G.T., C.B., L.P., D.P.), IRCCS San Raffaele Scientific Institute; Nuclear Medicine Unit (E.G.V., L.P., D.P.), San Raffaele Hospital; Unit of Neurology and Neuropathology (P.T.), Fondazione IRCCS Istituto Neurologico Carlo Besta (C.M., G.F., F.T.), Milan; Laboratory of Neuropsychiatry (V.C., N.B., F.P., G.S.), IRCCS Santa Lucia Foundation, Rome; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (G.B.F.), Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging (G.B.F.), University Hospitals and University of Geneva, Switzerland; ICoN (S.F.C.), Scuola Universitaria Superiore IUSS Pavia; and IRCCS Mondino Foundation (S.F.C.), Pavia, Italy
| | - Pietro Tiraboschi
- From Vita-Salute San Raffaele University (G.T., C.B., D.P.); In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience (G.T., C.B., L.P., D.P.), IRCCS San Raffaele Scientific Institute; Nuclear Medicine Unit (E.G.V., L.P., D.P.), San Raffaele Hospital; Unit of Neurology and Neuropathology (P.T.), Fondazione IRCCS Istituto Neurologico Carlo Besta (C.M., G.F., F.T.), Milan; Laboratory of Neuropsychiatry (V.C., N.B., F.P., G.S.), IRCCS Santa Lucia Foundation, Rome; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (G.B.F.), Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging (G.B.F.), University Hospitals and University of Geneva, Switzerland; ICoN (S.F.C.), Scuola Universitaria Superiore IUSS Pavia; and IRCCS Mondino Foundation (S.F.C.), Pavia, Italy
| | - Fabrizio Tagliavini
- From Vita-Salute San Raffaele University (G.T., C.B., D.P.); In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience (G.T., C.B., L.P., D.P.), IRCCS San Raffaele Scientific Institute; Nuclear Medicine Unit (E.G.V., L.P., D.P.), San Raffaele Hospital; Unit of Neurology and Neuropathology (P.T.), Fondazione IRCCS Istituto Neurologico Carlo Besta (C.M., G.F., F.T.), Milan; Laboratory of Neuropsychiatry (V.C., N.B., F.P., G.S.), IRCCS Santa Lucia Foundation, Rome; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (G.B.F.), Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging (G.B.F.), University Hospitals and University of Geneva, Switzerland; ICoN (S.F.C.), Scuola Universitaria Superiore IUSS Pavia; and IRCCS Mondino Foundation (S.F.C.), Pavia, Italy
| | - Giovanni Battista Frisoni
- From Vita-Salute San Raffaele University (G.T., C.B., D.P.); In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience (G.T., C.B., L.P., D.P.), IRCCS San Raffaele Scientific Institute; Nuclear Medicine Unit (E.G.V., L.P., D.P.), San Raffaele Hospital; Unit of Neurology and Neuropathology (P.T.), Fondazione IRCCS Istituto Neurologico Carlo Besta (C.M., G.F., F.T.), Milan; Laboratory of Neuropsychiatry (V.C., N.B., F.P., G.S.), IRCCS Santa Lucia Foundation, Rome; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (G.B.F.), Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging (G.B.F.), University Hospitals and University of Geneva, Switzerland; ICoN (S.F.C.), Scuola Universitaria Superiore IUSS Pavia; and IRCCS Mondino Foundation (S.F.C.), Pavia, Italy
| | - Stefano F Cappa
- From Vita-Salute San Raffaele University (G.T., C.B., D.P.); In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience (G.T., C.B., L.P., D.P.), IRCCS San Raffaele Scientific Institute; Nuclear Medicine Unit (E.G.V., L.P., D.P.), San Raffaele Hospital; Unit of Neurology and Neuropathology (P.T.), Fondazione IRCCS Istituto Neurologico Carlo Besta (C.M., G.F., F.T.), Milan; Laboratory of Neuropsychiatry (V.C., N.B., F.P., G.S.), IRCCS Santa Lucia Foundation, Rome; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (G.B.F.), Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging (G.B.F.), University Hospitals and University of Geneva, Switzerland; ICoN (S.F.C.), Scuola Universitaria Superiore IUSS Pavia; and IRCCS Mondino Foundation (S.F.C.), Pavia, Italy
| | - Gianfranco Spalletta
- From Vita-Salute San Raffaele University (G.T., C.B., D.P.); In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience (G.T., C.B., L.P., D.P.), IRCCS San Raffaele Scientific Institute; Nuclear Medicine Unit (E.G.V., L.P., D.P.), San Raffaele Hospital; Unit of Neurology and Neuropathology (P.T.), Fondazione IRCCS Istituto Neurologico Carlo Besta (C.M., G.F., F.T.), Milan; Laboratory of Neuropsychiatry (V.C., N.B., F.P., G.S.), IRCCS Santa Lucia Foundation, Rome; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (G.B.F.), Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging (G.B.F.), University Hospitals and University of Geneva, Switzerland; ICoN (S.F.C.), Scuola Universitaria Superiore IUSS Pavia; and IRCCS Mondino Foundation (S.F.C.), Pavia, Italy
| | - Daniela Perani
- From Vita-Salute San Raffaele University (G.T., C.B., D.P.); In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience (G.T., C.B., L.P., D.P.), IRCCS San Raffaele Scientific Institute; Nuclear Medicine Unit (E.G.V., L.P., D.P.), San Raffaele Hospital; Unit of Neurology and Neuropathology (P.T.), Fondazione IRCCS Istituto Neurologico Carlo Besta (C.M., G.F., F.T.), Milan; Laboratory of Neuropsychiatry (V.C., N.B., F.P., G.S.), IRCCS Santa Lucia Foundation, Rome; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (G.B.F.), Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging (G.B.F.), University Hospitals and University of Geneva, Switzerland; ICoN (S.F.C.), Scuola Universitaria Superiore IUSS Pavia; and IRCCS Mondino Foundation (S.F.C.), Pavia, Italy.
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