1
|
Ye N, Deng B, Hu H, Ai Y, Liu X, Zhou S, Li Y. The association between oral health and mild cognitive impairment in community-dwelling older adults. Front Public Health 2024; 12:1464439. [PMID: 39484361 PMCID: PMC11524816 DOI: 10.3389/fpubh.2024.1464439] [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: 07/14/2024] [Accepted: 09/30/2024] [Indexed: 11/03/2024] Open
Abstract
Background Older adults with cognitive impairment can experience poor oral health due to reduced self-care ability, yet the impact of various oral health indicators on the cognitive ability remains unclear. We investigated the relationship between oral health indicators and mild cognitive impairment (MCI) in older adults. Methods A cross-sectional study of 234 older adults aged 65 years or over was performed form January to March 2023 at health screening departments of hospitals. This study used the Mini-mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Activities of Daily Living (ADL), Clinical Dementia Rating (CDR), and Hachinski Ischemic Score (HIS) to measure MCI. Two qualified dentists performed clinical oral examinations (number of teeth lost, dental caries, removable dentures, periodontitis). The other oral health status was measured by subjective assessment questionnaires, and the oral health-related quality of life (OHRQoL) was assessed by Geriatric Oral Health Assessment Index (GOHAI). Results Of the 234 older adults, 166 had MCI and 68 had normal cognitive ability. The univariate analyses revealed that older adults with poor oral health indicators of dental caries, mastication ability, oral and maxillofacial pain, self-perceived oral health status and OHRQoL had lower cognitive levels. The stepwise logistic regression analysis observed that higher education level (OR = 0.06, 95%CI = 0.007, 0.567) and OHRQoL score (OR = 0.92, 95%CI = 0.878, 0.963) were negatively associated with the presence of MCI. The area under the ROC curve (AUC) of MCI was 0.675 (95% CI: 0.600, 0.749) with a low sensitivity of 41.6% and a moderate specificity of 86.8%. Conclusion OHRQoL was found to be associated with MCI, implying that OHRQoL may be important in cognitive decline. The GOHAI scale can be used to more easily assess the oral health of older adults, which is important for the timely detection of poor oral status to delay cognitive decline.
Collapse
Affiliation(s)
- Niansi Ye
- School of Nursing, Hubei University of Chinese Medicine, Wuhan, China
- Nursing Department, Wuhan No.1 Hospital, Wuhan, China
| | - Bei Deng
- School of Nursing, Hubei University of Chinese Medicine, Wuhan, China
| | - Hui Hu
- School of Nursing, Hubei University of Chinese Medicine, Wuhan, China
- Engineering Research Center of TCM Protection Technology and New Product Development for the Elderly Brain Health, Ministry of Education, Wuhan, China
- Hubei Shizhen Laboratory, Wuhan, China
| | - Yating Ai
- School of Nursing, Hubei University of Chinese Medicine, Wuhan, China
- Engineering Research Center of TCM Protection Technology and New Product Development for the Elderly Brain Health, Ministry of Education, Wuhan, China
- Hubei Shizhen Laboratory, Wuhan, China
| | - Xueting Liu
- School of Nursing, Hubei University of Chinese Medicine, Wuhan, China
| | - Shi Zhou
- School of Nursing, Hubei University of Chinese Medicine, Wuhan, China
| | - Yucan Li
- School of Nursing, Hubei University of Chinese Medicine, Wuhan, China
| |
Collapse
|
2
|
Karlawish J, Grill JD. Alzheimer's disease biomarkers and the tyranny of treatment. EBioMedicine 2024; 108:105291. [PMID: 39366841 DOI: 10.1016/j.ebiom.2024.105291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Revised: 08/02/2024] [Accepted: 08/04/2024] [Indexed: 10/06/2024] Open
Abstract
Advances in treatment are changing not only the therapeutic options for patients with Alzheimer's disease; they're also changing their diagnostic options. Technologies to detect amyloid such as PET imaging and blood or CSF testing now have a central role in Alzheimer's disease care. Notably, this role has been made possible by regulatory approval and coverage by payers of therapies. Access to treatments and the diagnostic tests needed to prescribe them is encourageing but it reveals a problem. These tests are tailored to the needs of the therapies, not to the needs of patients. Patients and families need to understand the causes of their impairments and their prognosis. This requires access to the best available diagnostic tests and this access should not depend on the availability of treatments. These tests should be used to their fullest capacity to inform patients of the causes of their cognitive impairments and their prognosis. Unfortunately, compared to diagnostic testing, treatment options are overvalued. We call this problem the tyranny of treatment.
Collapse
Affiliation(s)
- Jason Karlawish
- Departments of Medicine, Medical Ethics and Health Policy, and Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Joshua D Grill
- Departments of Psychiatry & Human Behavior and Neurobiology & Behavior, Institute for Memory Impairments and Neurological Disorders, University of California Irvine, Irvine CA, USA.
| |
Collapse
|
3
|
Liu Y, Qing Z, Qin R, Chen H, Ye Q, Li M, Luo C, Liu R, Xu Y, Zhao H, Zhang B. Module-level structural and functional alternations in amnestic mild cognitive impairment. CHINESE JOURNAL OF ACADEMIC RADIOLOGY 2024; 7:264-276. [DOI: 10.1007/s42058-024-00160-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 06/02/2024] [Accepted: 06/21/2024] [Indexed: 11/07/2024]
|
4
|
Liu K, Tao Y, Zhao Q, Xia W, Li X, Zhang S, Yao Y, Xiang H, Han C, Tan L, Sun B, Li D, Li A, Liu C. Binding adaptability of chemical ligands to polymorphic α-synuclein amyloid fibrils. Proc Natl Acad Sci U S A 2024; 121:e2321633121. [PMID: 39172784 PMCID: PMC11363296 DOI: 10.1073/pnas.2321633121] [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: 12/08/2023] [Accepted: 07/17/2024] [Indexed: 08/24/2024] Open
Abstract
α-synuclein (α-syn) assembles into structurally distinct fibril polymorphs seen in different synucleinopathies, such as Parkinson's disease and multiple system atrophy. Targeting these unique fibril structures using chemical ligands holds diagnostic significance for different disease subtypes. However, the molecular mechanisms governing small molecules interacting with different fibril polymorphs remain unclear. Here, we investigated the interactions of small molecules belonging to four distinct scaffolds, with different α-syn fibril polymorphs. Using cryo-electron microscopy, we determined the structures of these molecules when bound to the fibrils formed by E46K mutant α-syn and compared them to those bound with wild-type α-syn fibrils. Notably, we observed that these ligands exhibit remarkable binding adaptability, as they engage distinct binding sites across different fibril polymorphs. While the molecular scaffold primarily steered the binding locations and geometries on specific sites, the conjugated functional groups further refined this adaptable binding by fine-tuning the geometries and binding sites. Overall, our finding elucidates the adaptability of small molecules binding to different fibril structures, which sheds light on the diagnostic tracer and drug developments tailored to specific pathological fibril polymorphs.
Collapse
Affiliation(s)
- Kaien Liu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai201210, China
| | - Youqi Tao
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai200030, China
- Zhangjiang Institute for Advanced Study, Shanghai Jiao Tong University, Shanghai200240, China
| | - Qinyue Zhao
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai200030, China
- Zhangjiang Institute for Advanced Study, Shanghai Jiao Tong University, Shanghai200240, China
| | - Wencheng Xia
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai201210, China
| | - Xiang Li
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai200030, China
- Zhangjiang Institute for Advanced Study, Shanghai Jiao Tong University, Shanghai200240, China
| | - Shenqing Zhang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai200030, China
- Zhangjiang Institute for Advanced Study, Shanghai Jiao Tong University, Shanghai200240, China
| | - Yuxuan Yao
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai200030, China
- Zhangjiang Institute for Advanced Study, Shanghai Jiao Tong University, Shanghai200240, China
| | - Huaijiang Xiang
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai201210, China
| | - Chao Han
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai201210, China
| | - Li Tan
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai201210, China
| | - Bo Sun
- School of Life Science and Technology, ShanghaiTech University, Shanghai201210, China
| | - Dan Li
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders (Ministry of Education), Shanghai Jiao Tong University, Shanghai200030, China
- Zhangjiang Institute for Advanced Study, Shanghai Jiao Tong University, Shanghai200240, China
| | - Ang Li
- State Key Laboratory of Chemical Biology, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai200032, China
| | - Cong Liu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai201210, China
- State Key Laboratory of Chemical Biology, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, Shanghai200032, China
| |
Collapse
|
5
|
Cotta Ramusino M, Massa F, Festari C, Gandolfo F, Nicolosi V, Orini S, Nobili F, Frisoni GB, Morbelli S, Garibotto V. Diagnostic performance of molecular imaging methods in predicting the progression from mild cognitive impairment to dementia: an updated systematic review. Eur J Nucl Med Mol Imaging 2024; 51:1876-1890. [PMID: 38355740 DOI: 10.1007/s00259-024-06631-y] [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: 11/13/2023] [Accepted: 01/27/2024] [Indexed: 02/16/2024]
Abstract
PURPOSE Epidemiological and logistical reasons are slowing the clinical validation of the molecular imaging biomarkers in the initial stages of neurocognitive disorders. We provide an updated systematic review of the recent advances (2017-2022), highlighting methodological shortcomings. METHODS Studies reporting the diagnostic accuracy values of the molecular imaging techniques (i.e., amyloid-, tau-, [18F]FDG-PETs, DaT-SPECT, and cardiac [123I]-MIBG scintigraphy) in predicting progression from mild cognitive impairment (MCI) to dementia were selected according to the Preferred Reporting Items for a Systematic Review and Meta-Analysis (PRISMA) method and evaluated with the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Main eligibility criteria were as follows: (1) ≥ 50 subjects with MCI, (2) follow-up ≥ 3 years, (3) gold standard: progression to dementia or diagnosis on pathology, and (4) measures of prospective accuracy. RESULTS Sensitivity (SE) and specificity (SP) in predicting progression to dementia, mainly to Alzheimer's dementia were 43-100% and 63-94% for [18F]FDG-PET and 64-94% and 48-93% for amyloid-PET. Longitudinal studies were lacking for less common disorders (Dementia with Lewy bodies-DLB and Frontotemporal lobe degeneration-FTLD) and for tau-PET, DaT-SPECT, and [123I]-MIBG scintigraphy. Therefore, the accuracy values from cross-sectional studies in a smaller sample of subjects (n > 20, also including mild dementia stage) were chosen as surrogate outcomes. DaT-SPECT showed 47-100% SE and 71-100% SP in differentiating Lewy body disease (LBD) from non-LBD conditions; tau-PET: 88% SE and 100% SP in differentiating DLB from Posterior Cortical Atrophy. [123I]-MIBG scintigraphy differentiated LBD from non-LBD conditions with 47-100% SE and 71-100% SP. CONCLUSION Molecular imaging has a moderate-to-good accuracy in predicting the progression of MCI to Alzheimer's dementia. Longitudinal studies are sparse in non-AD conditions, requiring additional efforts in these settings.
Collapse
Affiliation(s)
- Matteo Cotta Ramusino
- Unit of Behavior Neurology and Dementia Research Center, IRCCS Mondino Foundation, via Mondino 2, 27100, Pavia, Italy.
| | - Federico Massa
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, Genoa, Italy
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Cristina Festari
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni Di Dio Fatebenefratelli, Brescia, Italy
| | - Federica Gandolfo
- Department of Geriatric Care, Orthogeriatrics and Rehabilitation, E.O. Galliera Hospital, Genoa, Italy
| | - Valentina Nicolosi
- UOC Neurologia Ospedale Magalini Di Villafranca Di Verona (VR) ULSS 9, Verona, Italy
| | - Stefania Orini
- Alzheimer's Unit-Memory Clinic, IRCCS Istituto Centro San Giovanni Di Dio Fatebenefratelli, Brescia, Italy
- Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Flavio Nobili
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Giovanni B Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Department of Rehabilitation and Geriatrics, Geneva University and University Hospitals, Geneva, Switzerland
| | - Silvia Morbelli
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
- Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy
| | - Valentina Garibotto
- Division of Nuclear Medicine and Molecular Imaging, Diagnostic Department, University Hospitals of Geneva, Geneva, Switzerland
- NIMTLab, Department of Radiology and Medical Informatics, Faculty of Medicine, University of Geneva, Geneva, Switzerland
- CIBM Center for Biomedical Imaging, Geneva, Switzerland
| |
Collapse
|
6
|
Plassman BL, Ford CB, Smith VA, DePasquale N, Burke JR, Korthauer L, Ott BR, Belanger E, Shepherd-Banigan ME, Couch E, Jutkowitz E, O’Brien EC, Sorenson C, Wetle TT, Van Houtven CH. Elevated Amyloid-β PET Scan and Cognitive and Functional Decline in Mild Cognitive Impairment and Dementia of Uncertain Etiology. J Alzheimers Dis 2024; 97:1161-1171. [PMID: 38306055 PMCID: PMC11034799 DOI: 10.3233/jad-230950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2024]
Abstract
BACKGROUND Elevated amyloid-β (Aβ) on positron emission tomography (PET) scan is used to aid diagnosis of Alzheimer's disease (AD), but many prior studies have focused on patients with a typical AD phenotype such as amnestic mild cognitive impairment (MCI). Little is known about whether elevated Aβ on PET scan predicts rate of cognitive and functional decline among those with MCI or dementia that is clinically less typical of early AD, thus leading to etiologic uncertainty. OBJECTIVE We aimed to investigate whether elevated Aβ on PET scan predicts cognitive and functional decline over an 18-month period in those with MCI or dementia of uncertain etiology. METHODS In 1,028 individuals with MCI or dementia of uncertain etiology, we evaluated the association between elevated Aβ on PET scan and change on a telephone cognitive status measure administered to the participant and change in everyday function as reported by their care partner. RESULTS Individuals with either MCI or dementia and elevated Aβ (66.6% of the sample) showed greater cognitive decline compared to those without elevated Aβ on PET scan, whose cognition was relatively stable over 18 months. Those with either MCI or dementia and elevated Aβ were also reported to have greater functional decline compared to those without elevated Aβ, even though the latter group showed significant care partner-reported functional decline over time. CONCLUSIONS Elevated Aβ on PET scan can be helpful in predicting rates of both cognitive and functional decline, even among cognitively impaired individuals with atypical presentations of AD.
Collapse
Affiliation(s)
- Brenda L. Plassman
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Duke University, Durham, NC, USA
- Department of Neurology, School of Medicine, Duke University, NC, USA
| | - Cassie B. Ford
- Department of Population Health Sciences, Duke University, Durham, NC, USA
| | - Valerie A. Smith
- Department of Population Health Sciences, Duke University, Durham, NC, USA
- Department of Medicine, Division of General Internal Medicine, Duke University, Durham, NC, USA
- Durham ADAPT, Durham Veterans Affairs Medical Center, Durham, NC, USA
| | - Nicole DePasquale
- Department of Medicine, Division of General Internal Medicine, Duke University, Durham, NC, USA
| | - James R. Burke
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Duke University, Durham, NC, USA
- Department of Neurology, School of Medicine, Duke University, NC, USA
| | - Laura Korthauer
- Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, RI, USA
| | - Brian R. Ott
- Department of Neurology, Alpert Medical School of Brown University, Providence, RI, USA
| | - Emmanuelle Belanger
- Department of Health Services Policy and Practice, School of Public Health, Brown University, Providence, RI, USA
| | - Megan E. Shepherd-Banigan
- Department of Population Health Sciences, Duke University, Durham, NC, USA
- Durham ADAPT, Durham Veterans Affairs Medical Center, Durham, NC, USA
- Duke-Margolis Center for Health Policy, Durham, NC, USA
| | - Elyse Couch
- Department of Health Services Policy and Practice, School of Public Health, Brown University, Providence, RI, USA
| | - Eric Jutkowitz
- Department of Health Services Policy and Practice, School of Public Health, Brown University, Providence, RI, USA
| | - Emily C. O’Brien
- Department of Population Health Sciences, Duke University, Durham, NC, USA
| | - Corinna Sorenson
- Department of Population Health Sciences, Duke University, Durham, NC, USA
- Duke-Margolis Center for Health Policy, Durham, NC, USA
- Sanford School of Public Policy, Duke University, Durham, NC, USA
| | - Terrie T. Wetle
- Department of Health Services Policy and Practice, School of Public Health, Brown University, Providence, RI, USA
- Center for Gerontology and Healthcare Research, Brown University School of Public Health, Providence, RI, USA
| | - Courtney H. Van Houtven
- Department of Population Health Sciences, Duke University, Durham, NC, USA
- Durham ADAPT, Durham Veterans Affairs Medical Center, Durham, NC, USA
- Duke-Margolis Center for Health Policy, Durham, NC, USA
| |
Collapse
|
7
|
Kwon HS, Kim JY, Koh SH, Choi SH, Lee EH, Jeong JH, Jang JW, Park KW, Kim EJ, Hong JY, Yoon SJ, Yoon B, Park HH, Han MH. Predicting cognitive stage transition using p-tau181, Centiloid, and other measures. Alzheimers Dement 2023; 19:4641-4650. [PMID: 36988152 DOI: 10.1002/alz.13054] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 02/03/2023] [Accepted: 02/21/2023] [Indexed: 03/30/2023]
Abstract
BACKGROUND A combination of plasma phospho-tau (p-tau), amyloid beta (Aβ)-positron emission tomography (PET), brain magnetic resonance imaging, cognitive function tests, and other biomarkers might predict future cognitive decline. This study aimed to investigate the efficacy of combining these biomarkers in predicting future cognitive stage transitions within 3 years. METHODS Among the participants in the Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer's Disease (KBASE-V) study, 49 mild cognitive impairment (MCI) and 113 cognitively unimpaired (CU) participants with Aβ-PET and brain imaging data were analyzed. RESULTS Older age, increased plasma p-tau181, Aβ-PET positivity, and decreased semantic fluency were independently associated with cognitive stage transitions. Combining age, p-tau181, the Centiloid scale, semantic fluency, and hippocampal volume produced high predictive value in predicting future cognitive stage transition (area under the curve = 0.879). CONCLUSIONS Plasma p-tau181 and Centiloid scale alone or in combination with other biomarkers, might predict future cognitive stage transition in non-dementia patients. HIGHLIGHTS -Plasma p-tau181 and Centiloid scale might predict future cognitive stage transition. -Combining them or adding other biomarkers increased the predictive value. -Factors that independently associated with cognitive stage transition were demonstrated.
Collapse
Affiliation(s)
- Hyuk Sung Kwon
- Department of Neurology, Hanyang University Guri Hospital, Hanyang University College of Medicine, Guri, Republic of Korea
| | - Ji Young Kim
- Department of Nuclear Medicine, Hanyang University Guri Hospital, Hanyang University College of Medicine, Guri, Republic of Korea
| | - Seong-Ho Koh
- Department of Neurology, Hanyang University Guri Hospital, Hanyang University College of Medicine, Guri, Republic of Korea
| | - Seong Hye Choi
- Department of Neurology, Inha University College of Medicine, Incheon, Republic of Korea
| | - Eun-Hye Lee
- Department of Neurology, Hanyang University Guri Hospital, Hanyang University College of Medicine, Guri, Republic of Korea
| | - Jee Hyang Jeong
- Department of Neurology, Ewha Womans University School of Medicine, Seoul, Republic of Korea
| | - Jae-Won Jang
- Department of Neurology, Kangwon National University School of Medicine, Chuncheon, Republic of Korea
| | - Kyung Won Park
- Department of Neurology, Dong-A Medical Center, Dong-A University College of Medicine, Busan, Republic of Korea
| | - Eun-Joo Kim
- Department of Neurology, Pusan National University Hospital, Pusan National University School of Medicine and Medical Research Institute, Busan, Republic of Korea
| | - Jin Yong Hong
- Department of Neurology, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea
| | - Soo Jin Yoon
- Department of Neurology, Eulji University Hospital, Eulji University School of Medicine, Daejeon, Republic of Korea
| | - Bora Yoon
- Department of Neurology, Konyang University College of Medicine, Daejeon, Republic of Korea
| | - Hyun-Hee Park
- Department of Neurology, Hanyang University Guri Hospital, Hanyang University College of Medicine, Guri, Republic of Korea
| | - Myung Hoon Han
- Department of Neurosurgery, Hanyang University Guri Hospital, Hanyang University College of Medicine, Guri, Republic of Korea
| |
Collapse
|
8
|
Wang ZB, Tan L, Wang HF, Chen SD, Fu Y, Gao PY, Ma YH, Guo Y, Hou JH, Zhang DD, Yu JT. Differences between ante mortem Alzheimer's disease biomarkers in predicting neuropathology at autopsy. Alzheimers Dement 2023; 19:3613-3624. [PMID: 36840620 DOI: 10.1002/alz.12997] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 01/18/2023] [Accepted: 01/19/2023] [Indexed: 02/26/2023]
Abstract
INTRODUCTION This study aimed to assess whether biomarkers related to amyloid, tau, and neurodegeneration can accurately predict Alzheimer's disease (AD) neuropathology at autopsy in early and late clinical stages. METHODS We included 100 participants who had ante mortem biomarker measurements and underwent post mortem neuropathological examination. Based on ante mortem clinical diagnosis, participants were divided into non-dementia and dementia, as early or late clinical stages. RESULTS Amyloid positron emission tomography (PET) and cerebrospinal fluid (CSF) amyloid beta (Aβ)42/phosphorylated tau (p-tau)181 showed excellent performance in differentiating autopsy-confirmed AD and predicting the risk of neuropathological changes in early and late clinical stages. However, CSF Aβ42 performed better in the early clinical stage, while CSF p-tau181, CSF t-tau, and plasma p-tau181 performed better in the late clinical stage. DISCUSSION Our findings provide important clinical information that, if using PET, CSF, and plasma biomarkers to detect AD pathology, researchers must consider their differential performances at different clinical stages of AD. HIGHLIGHTS Amyloid PET and CSF Aβ42/p-tau181 were the most promising candidate biomarkers for predicting AD pathology. CSF Aβ42 can serve as a candidate predictive biomarker in the early clinical stage of AD. CSF p-tau181, CSF t-tau, and plasma p-tau181 can serve as candidate predictive biomarkers in the late clinical stage of AD. Combining APOE ε4 genotypes can significantly improve the predictive accuracy of AD-related biomarkers for AD pathology.
Collapse
Affiliation(s)
- Zhi-Bo Wang
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Hui-Fu Wang
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Shi-Dong Chen
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yan Fu
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Pei-Yang Gao
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Ya-Hui Ma
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Yu Guo
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jia-Hui Hou
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Dan-Dan Zhang
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Jin-Tai Yu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| |
Collapse
|
9
|
Pemberton HG, Buckley C, Battle M, Bollack A, Patel V, Tomova P, Cooke D, Balhorn W, Hegedorn K, Lilja J, Brand C, Farrar G. Software compatibility analysis for quantitative measures of [ 18F]flutemetamol amyloid PET burden in mild cognitive impairment. EJNMMI Res 2023; 13:48. [PMID: 37225974 DOI: 10.1186/s13550-023-00994-3] [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: 09/26/2022] [Accepted: 05/05/2023] [Indexed: 05/26/2023] Open
Abstract
RATIONALE Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer's disease pathogenesis. In clinical practice, trained readers will visually categorise positron emission tomography (PET) scans as either Aβ positive or negative. However, adjunct quantitative analysis is becoming more widely available, where regulatory approved software can currently generate metrics such as standardised uptake value ratios (SUVr) and individual Z-scores. Therefore, it is of direct value to the imaging community to assess the compatibility of commercially available software packages. In this collaborative project, the compatibility of amyloid PET quantification was investigated across four regulatory approved software packages. In doing so, the intention is to increase visibility and understanding of clinically relevant quantitative methods. METHODS Composite SUVr using the pons as the reference region was generated from [18F]flutemetamol (GE Healthcare) PET in a retrospective cohort of 80 amnestic mild cognitive impairment (aMCI) patients (40 each male/female; mean age = 73 years, SD = 8.52). Based on previous autopsy validation work, an Aβ positivity threshold of ≥ 0.6 SUVrpons was applied. Quantitative results from MIM Software's MIMneuro, Syntermed's NeuroQ, Hermes Medical Solutions' BRASS and GE Healthcare's CortexID were analysed using intraclass correlation coefficient (ICC), percentage agreement around the Aβ positivity threshold and kappa scores. RESULTS Using an Aβ positivity threshold of ≥ 0.6 SUVrpons, 95% agreement was achieved across the four software packages. Two patients were narrowly classed as Aβ negative by one software package but positive by the others, and two patients vice versa. All kappa scores around the same Aβ positivity threshold, both combined (Fleiss') and individual software pairings (Cohen's), were ≥ 0.9 signifying "almost perfect" inter-rater reliability. Excellent reliability was found between composite SUVr measurements for all four software packages, with an average measure ICC of 0.97 and 95% confidence interval of 0.957-0.979. Correlation coefficient analysis between the two software packages reporting composite z-scores was strong (r2 = 0.98). CONCLUSION Using an optimised cortical mask, regulatory approved software packages provided highly correlated and reliable quantification of [18F]flutemetamol amyloid PET with a ≥ 0.6 SUVrpons positivity threshold. In particular, this work could be of interest to physicians performing routine clinical imaging rather than researchers performing more bespoke image analysis. Similar analysis is encouraged using other reference regions as well as the Centiloid scale, when it has been implemented by more software packages.
Collapse
Affiliation(s)
- Hugh G Pemberton
- GE Healthcare, Pollards Wood, Chalfont St Giles, Amersham, HP8 4SP, UK.
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK.
- UCL Queen Square Institute of Neurology, University College London, London, UK.
| | | | - Mark Battle
- GE Healthcare, Pollards Wood, Chalfont St Giles, Amersham, HP8 4SP, UK
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Ariane Bollack
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK
| | - Vrajesh Patel
- GE Healthcare, Pollards Wood, Chalfont St Giles, Amersham, HP8 4SP, UK
| | - Petya Tomova
- GE Healthcare, Pollards Wood, Chalfont St Giles, Amersham, HP8 4SP, UK
| | | | | | | | | | - Christine Brand
- GE Healthcare, Pollards Wood, Chalfont St Giles, Amersham, HP8 4SP, UK
| | - Gill Farrar
- GE Healthcare, Pollards Wood, Chalfont St Giles, Amersham, HP8 4SP, UK
| |
Collapse
|
10
|
Kim BS, Jun S, Kim H. Cognitive Trajectories and Associated Biomarkers in Patients with Mild Cognitive Impairment. J Alzheimers Dis 2023; 92:803-814. [PMID: 36806501 DOI: 10.3233/jad-220326] [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: 02/19/2023]
Abstract
BACKGROUND To diagnose mild cognitive impairment (MCI) patients at risk of progression to dementia is clinically important but challenging. OBJECTIVE We classified MCI patients based on cognitive trajectories and compared biomarkers among groups. METHODS This study analyzed amnestic MCI patients with at least three Clinical Dementia Rating (CDR) scores available over a minimum of 36 months from the Alzheimer's Disease Neuroimaging Initiative database. Patients were classified based on their progression using trajectory modeling with the CDR-sum of box scores. We compared clinical and neuroimaging biomarkers across groups. RESULTS Of 569 eligible MCI patients (age 72.7±7.4 years, women n = 223), three trajectory groups were identified: stable (58.2%), slow decliners (24.6%), and fast decliners (17.2%). In the fifth year after diagnosis, the CDR-sum of box scores increased by 1.2, 5.4, and 11.8 points for the stable, slow, and fast decliners, respectively. Biomarkers associated with cognitive decline were amyloid-β 42, total tau, and phosphorylated tau protein in cerebrospinal fluid, hippocampal volume, cortical metabolism, and amount of cortical and subcortical amyloid deposits. Cortical metabolism and the amount of amyloid deposits were associated with the rate of cognitive decline. CONCLUSION Data-driven trajectory analysis provides new insights into the various cognitive trajectories of MCI. Baseline brain metabolism, and the amount of cortical and subcortical amyloid burden can provide additional information on the rate of cognitive decline.
Collapse
Affiliation(s)
- Bum Soo Kim
- Department of Nuclear Medicine, Kosin University Gospel Hospital, University of Kosin College of Medicine, Busan, Republic of Korea
| | - Sungmin Jun
- Department of Nuclear Medicine, Kosin University Gospel Hospital, University of Kosin College of Medicine, Busan, Republic of Korea
| | - Heeyoung Kim
- Department of Nuclear Medicine, Kosin University Gospel Hospital, University of Kosin College of Medicine, Busan, Republic of Korea
| | | |
Collapse
|
11
|
Sur C, Adamczuk K, Scott D, Kost J, Sampat M, Buckley C, Farrar G, Newton B, Suhy J, Bennacef I, Egan MF. Evaluation of 18F-flutemetamol amyloid PET image analysis parameters on the effect of verubecestat on brain amlyoid load in Alzheimer's disease. Mol Imaging Biol 2022; 24:862-873. [PMID: 35794343 DOI: 10.1007/s11307-022-01735-z] [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: 12/13/2021] [Revised: 03/17/2022] [Accepted: 04/21/2022] [Indexed: 12/29/2022]
Abstract
PURPOSE The BACE inhibitor verubecestat was previously found to reduce amyloid load as assessed by 18F-flutemetamol positron emission tomography (PET) composite cortical standard uptake value ratio (SUVr) in patients with mild-to-moderate Alzheimer's disease (AD) in a substudy of the EPOCH trial. Here, we report on additional analyses relevant to the EPOCH PET data, to help inform on the use of PET for assessing amlyloid load in AD clinical trials. PROCEDURES The analyses addressed (1) identification of an optimal 18F-flutemetamol reference region, (2) determination of the threshold to characterize the magnitude of the longitudinal change, and (3) the impact of partial volume correction (PVC). Pons and subcortical white matter were evaluated as reference regions. The SUVr cutoffs and final reference region choice were determined using 162 18F-flutemetamol PET scans from the AIBL dataset. 18F-flutemetamol SUVrs were computed at baseline and at Week 78 in EPOCH participants who received verubecestat 12 mg (n = 14), 40 mg (n = 20), or placebo (n = 20). Drug effects on amyloid load were computed using either Meltzer (MZ), or symmetric geometric transfer matrix (SGTM) PVC and compared to uncorrected data. RESULTS The optimal subcortical white matter and pons SUVr cutoffs were determined to be 0.69 and 0.62, respectively. The effect size to detect longitudinal change was higher for subcortical white matter (1.20) than pons (0.45). Hence, subcortical white matter was used as the reference region for the EPOCH PET substudy. In EPOCH, uncorrected baseline SUVr values correlated strongly with MZ PVC (r2 = 0.94) and SGTM PVC (r2 = 0.92) baseline SUVr values, and PVC did not provide improvement for evaluating treatment effects on amyloid load at Week 78. No change from baseline was observed in the placebo group at Week 78, whereas a 0.02 and a 0.04 decrease in SUVr were observed in the 12 mg and 40 mg arms, with the latter representing a 22% reduction in the amyloid load above the detection threshold. CONCLUSIONS Treatment-related 18F-flutemetamol longitudinal changes in AD clinical trials can be quantified using a subcortical white matter reference region without PVC. CLINICAL TRIAL REGISTRATION clinicaltrials.gov NCT01739348.
Collapse
|
12
|
Rauhala E, Johansson J, Karrasch M, Eskola O, Tolvanen T, Parkkola R, Virtanen KA, Rinne JO. Change in brain amyloid load and cognition in patients with amnestic mild cognitive impairment: a 3-year follow-up study. EJNMMI Res 2022; 12:55. [PMID: 36065070 PMCID: PMC9445147 DOI: 10.1186/s13550-022-00928-5] [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: 05/18/2022] [Accepted: 08/22/2022] [Indexed: 11/10/2022] Open
Abstract
Background Our aim was to investigate the discriminative value of 18F-Flutemetamol PET in longitudinal assessment of amyloid beta accumulation in amnestic mild cognitive impairment (aMCI) patients, in relation to longitudinal cognitive changes.
Methods We investigated the change in 18F-Flutemetamol uptake and cognitive impairment in aMCI patients over time up to 3 years which enabled us to investigate possible association between changes in brain amyloid load and cognition over time. Thirty-four patients with aMCI (mean age 73.4 years, SD 6.6) were examined with 18F-Flutemetamol PET scan, brain MRI and cognitive tests at baseline and after 3-year follow-up or earlier if the patient had converted to Alzheimer´s disease (AD). 18F-Flutemetamol data were analyzed both with automated region-of-interest analysis and voxel-based statistical parametric mapping. Results 18F-flutemetamol uptake increased during the follow-up, and the increase was significantly higher in patients who were amyloid positive at baseline as compared to the amyloid-negative ones. At follow-up, there was a significant association between 18F-Flutemetamol uptake and MMSE, logical memory I (immediate recall), logical memory II (delayed recall) and verbal fluency. An association was seen between the increase in 18F-Flutemetamol uptake and decline in MMSE and logical memory I scores. Conclusions In the early phase of aMCI, presence of amyloid pathology at baseline strongly predicted amyloid accumulation during follow-up, which was further paralleled by cognitive declines. Inversely, some of our patients remained amyloid negative also at the end of the study without significant change in 18F-Flutemetamol uptake or cognition. Future studies with longer follow-up are needed to distinguish whether the underlying pathophysiology of aMCI in such patients is other than AD.
Collapse
Affiliation(s)
- Elina Rauhala
- Clinical Neurosciences, Faculty of Medicine, Turku University Hospital, University of Turku and Neurocenter, Turku, Finland
| | - Jarkko Johansson
- Turku PET Centre, Turku University Hospital, Turku, Finland.,Department of Radiation Sciences, Umeå University, Umeå, Sweden
| | - Mira Karrasch
- Department of Psychology, Åbo Akademi University, Turku, Finland
| | - Olli Eskola
- Turku PET Centre, University of Turku, Turku, Finland
| | - Tuula Tolvanen
- Turku PET Centre, University of Turku, Turku, Finland.,Department of Medical Physics, Turku University Hospital, Turku, Finland
| | - Riitta Parkkola
- Department of Radiology, University of Turku and Turku University Hospital, Turku, Finland
| | | | - Juha O Rinne
- Turku PET Centre, Turku University Hospital, Turku, Finland. .,InFLAMES Research Flagship Center, University of Turku, Turku, Finland.
| |
Collapse
|
13
|
Chapleau M, Iaccarino L, Soleimani-Meigooni D, Rabinovici GD. The Role of Amyloid PET in Imaging Neurodegenerative Disorders: A Review. J Nucl Med 2022; 63:13S-19S. [PMID: 35649652 DOI: 10.2967/jnumed.121.263195] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 03/22/2022] [Indexed: 12/17/2022] Open
Abstract
Imaging of amyloid deposition using PET has been available in research studies for 2 decades and has been approved for clinical use by the U.S. Food and Drug Administration, the European Medicines Agency, and other regulatory agencies around the world. Amyloid PET is a crucial tool for the diagnosis of Alzheimer disease, as it allows the noninvasive detection of amyloid plaques, a core neuropathologic feature that defines the disease. The clinical use of amyloid PET is expected to increase with recent accelerated approval in the United States of aducanumab, an antiamyloid monoclonal antibody, for the treatment of mild cognitive impairment and mild dementia due to Alzheimer disease. However, amyloid pathology can also be found in cognitively unimpaired older adults and in patients with other neurodegenerative disorders. The aim of this review is to provide an up-to-date overview of the application of amyloid PET in neurodegenerative diseases. We provide an in-depth analysis of the clinical, pathologic, and imaging correlates; a comparison with other available biomarkers; and a review of the application of amyloid PET in clinical trials and clinical utility studies.
Collapse
Affiliation(s)
- Marianne Chapleau
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California;
| | - Leonardo Iaccarino
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
| | - David Soleimani-Meigooni
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California.,Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California; and.,Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California
| |
Collapse
|
14
|
Crișan G, Moldovean-Cioroianu NS, Timaru DG, Andrieș G, Căinap C, Chiș V. Radiopharmaceuticals for PET and SPECT Imaging: A Literature Review over the Last Decade. Int J Mol Sci 2022; 23:5023. [PMID: 35563414 PMCID: PMC9103893 DOI: 10.3390/ijms23095023] [Citation(s) in RCA: 82] [Impact Index Per Article: 41.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2022] [Revised: 04/23/2022] [Accepted: 04/28/2022] [Indexed: 02/04/2023] Open
Abstract
Positron emission tomography (PET) uses radioactive tracers and enables the functional imaging of several metabolic processes, blood flow measurements, regional chemical composition, and/or chemical absorption. Depending on the targeted processes within the living organism, different tracers are used for various medical conditions, such as cancer, particular brain pathologies, cardiac events, and bone lesions, where the most commonly used tracers are radiolabeled with 18F (e.g., [18F]-FDG and NA [18F]). Oxygen-15 isotope is mostly involved in blood flow measurements, whereas a wide array of 11C-based compounds have also been developed for neuronal disorders according to the affected neuroreceptors, prostate cancer, and lung carcinomas. In contrast, the single-photon emission computed tomography (SPECT) technique uses gamma-emitting radioisotopes and can be used to diagnose strokes, seizures, bone illnesses, and infections by gauging the blood flow and radio distribution within tissues and organs. The radioisotopes typically used in SPECT imaging are iodine-123, technetium-99m, xenon-133, thallium-201, and indium-111. This systematic review article aims to clarify and disseminate the available scientific literature focused on PET/SPECT radiotracers and to provide an overview of the conducted research within the past decade, with an additional focus on the novel radiopharmaceuticals developed for medical imaging.
Collapse
Affiliation(s)
- George Crișan
- Faculty of Physics, Babeş-Bolyai University, Str. M. Kogălniceanu 1, 400084 Cluj-Napoca, Romania; (G.C.); (N.S.M.-C.); (D.-G.T.)
- Department of Nuclear Medicine, County Clinical Hospital, Clinicilor 3-5, 400006 Cluj-Napoca, Romania;
| | | | - Diana-Gabriela Timaru
- Faculty of Physics, Babeş-Bolyai University, Str. M. Kogălniceanu 1, 400084 Cluj-Napoca, Romania; (G.C.); (N.S.M.-C.); (D.-G.T.)
| | - Gabriel Andrieș
- Department of Nuclear Medicine, County Clinical Hospital, Clinicilor 3-5, 400006 Cluj-Napoca, Romania;
| | - Călin Căinap
- The Oncology Institute “Prof. Dr. Ion Chiricuţă”, Republicii 34-36, 400015 Cluj-Napoca, Romania;
| | - Vasile Chiș
- Faculty of Physics, Babeş-Bolyai University, Str. M. Kogălniceanu 1, 400084 Cluj-Napoca, Romania; (G.C.); (N.S.M.-C.); (D.-G.T.)
- Institute for Research, Development and Innovation in Applied Natural Sciences, Babeș-Bolyai University, Str. Fântânele 30, 400327 Cluj-Napoca, Romania
| |
Collapse
|
15
|
Pichet Binette A, Palmqvist S, Bali D, Farrar G, Buckley CJ, Wolk DA, Zetterberg H, Blennow K, Janelidze S, Hansson O. Combining plasma phospho-tau and accessible measures to evaluate progression to Alzheimer's dementia in mild cognitive impairment patients. Alzheimers Res Ther 2022; 14:46. [PMID: 35351181 PMCID: PMC8966264 DOI: 10.1186/s13195-022-00990-0] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Accepted: 03/16/2022] [Indexed: 02/06/2023]
Abstract
BACKGROUND Up to now, there are no clinically available minimally invasive biomarkers to accurately identify mild cognitive impairment (MCI) patients who are at greater risk to progress to Alzheimer's disease (AD) dementia. The recent advent of blood-based markers opens the door for more accessible biomarkers. We aimed to identify which combinations of AD related plasma biomarkers and other easily accessible assessments best predict progression to AD dementia in patients with mild cognitive impairment (MCI). METHODS We included patients with amnestic MCI (n = 110) followed prospectively over 3 years to assess clinical status. Baseline plasma biomarkers (amyloid-β 42/40, phosphorylated tau217 [p-tau217], neurofilament light and glial fibrillary acidic protein), hippocampal volume, APOE genotype, and cognitive tests were available. Logistic regressions with conversion to amyloid-positive AD dementia within 3 years as outcome was used to evaluate the performance of different biomarkers measured at baseline, used alone or in combination. The first analyses included only the plasma biomarkers to determine the ones most related to AD dementia conversion. Second, hippocampal volume, APOE genotype and a brief cognitive composite score (mPACC) were combined with the best plasma biomarker. RESULTS Of all plasma biomarker combinations, p-tau217 alone had the best performance for discriminating progression to AD dementia vs all other combinations (AUC 0.84, 95% CI 0.75-0.93). Next, combining p-tau217 with hippocampal volume, cognition, and APOE genotype provided the best discrimination between MCI progressors vs. non-progressors (AUC 0.89, 0.82-0.95). Across the few best models combining different markers, p-tau217 and cognition were consistently the main contributors. The most parsimonious model including p-tau217 and cognition had a similar model fit, but a slightly lower AUC (0.87, 0.79-0.95, p = 0.07). CONCLUSION We identified that combining plasma p-tau217 and a brief cognitive composite score was strongly related to greater risk of progression to AD dementia in MCI patients, suggesting that these measures could be key components of future prognostic algorithms for early AD. TRIAL REGISTRATION NCT01028053 , registered December 9, 2009.
Collapse
Affiliation(s)
- Alexa Pichet Binette
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden.
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, SE-20502, Malmö, Sweden
| | - Divya Bali
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
| | | | | | - David A Wolk
- Department of Neurology, Penn Memory Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden.
- Memory Clinic, Skåne University Hospital, SE-20502, Malmö, Sweden.
| |
Collapse
|
16
|
Jack CR, Therneau TM, Lundt ES, Wiste HJ, Mielke MM, Knopman DS, Graff-Radford J, Lowe VJ, Vemuri P, Schwarz CG, Senjem ML, Gunter JL, Petersen RC. Long-term associations between amyloid positron emission tomography, sex, apolipoprotein E and incident dementia and mortality among individuals without dementia: hazard ratios and absolute risk. Brain Commun 2022; 4:fcac017. [PMID: 35310829 PMCID: PMC8924651 DOI: 10.1093/braincomms/fcac017] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 11/08/2021] [Accepted: 01/31/2022] [Indexed: 11/14/2022] Open
Abstract
Dementia and mortality rates rise inexorably with age and consequently interact. However, because of the major logistical difficulties in accounting for both outcomes in a defined population, very little work has examined how risk factors and biomarkers for incident dementia are influenced by competing mortality. The objective of this study was to examine long-term associations between amyloid PET, APOE ɛ4, sex, education and cardiovascular/metabolic conditions, and hazard and absolute risk of dementia and mortality in individuals without dementia at enrolment. Participants were enrolled in the Mayo Clinic Study of Aging, a population-based study of cognitive ageing in Olmsted County, MN, USA. All were without dementia and were age 55-92 years at enrolment and were followed longitudinally. Predictor variables were amyloid PET, APOE ɛ4 status, sex, education, cardiovascular/metabolic conditions and age. The main outcomes were incident dementia and mortality. Multivariable, multi-state models were used to estimate mortality and incident dementia rates and absolute risk of dementia and mortality by predictor variable group. Of the 4984 participants in the study, 4336 (87%) were cognitively unimpaired and 648 (13%) had mild cognitive impairment at enrolment. The median age at enrolment was 75 years; 2463 (49%) were women. The median follow-up time was 9.4 years (7.5 years after PET). High versus normal amyloid (hazard ratio 2.11, 95% confidence interval 1.43-2.79), APOE ɛ4 (women: hazard ratio 2.24, 95% confidence interval 1.80-2.77; men: hazard ratio 1.37, 95% confidence interval 1.09-1.71), older age and two additional cardiovascular/metabolic conditions (hazard ratio 1.37, 95% confidence interval 1.22-1.53) were associated with the increased hazard of dementia (all P < 0.001). Among APOE ɛ4 carriers with elevated amyloid, remaining lifetime risk of dementia at age 65 years was greater in women [74% (95% confidence interval 65-84%) high and 58% (95% confidence interval 52-65%) moderate amyloid], than men [62% (95% confidence interval 52-73%) high and 44% (95% confidence interval 35-53%) moderate amyloid]. Overall, the hazard and absolute risk of dementia varied considerably by predictor group. The absolute risk of dementia associated with predictors characteristic of Alzheimer's disease was greater in women than men while at the same time the combination of APOE ɛ4 non-carrier with normal amyloid was more protective in women than men. This set of findings may be attributed in part to different biological effects and in part to lower mortality rates in women.
Collapse
Affiliation(s)
| | - Terry M. Therneau
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Emily S. Lundt
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Heather J. Wiste
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Michelle M. Mielke
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | | | | | - Val J. Lowe
- Department of Nuclear Medicine, Mayo Clinic, Rochester, MN, USA
| | | | | | | | | | | |
Collapse
|
17
|
Ni R, Nitsch RM. Recent Developments in Positron Emission Tomography Tracers for Proteinopathies Imaging in Dementia. Front Aging Neurosci 2022; 13:751897. [PMID: 35046791 PMCID: PMC8761855 DOI: 10.3389/fnagi.2021.751897] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Accepted: 11/17/2021] [Indexed: 12/15/2022] Open
Abstract
An early detection and intervention for dementia represent tremendous unmet clinical needs and priorities in society. A shared feature of neurodegenerative diseases causing dementia is the abnormal accumulation and spreading of pathological protein aggregates, which affect the selective vulnerable circuit in a disease-specific pattern. The advancement in positron emission tomography (PET) biomarkers has accelerated the understanding of the disease mechanism and development of therapeutics for Alzheimer's disease and Parkinson's disease. The clinical utility of amyloid-β PET and the clinical validity of tau PET as diagnostic biomarker for Alzheimer's disease continuum have been demonstrated. The inclusion of biomarkers in the diagnostic criteria has introduced a paradigm shift that facilitated the early and differential disease diagnosis and impacted on the clinical management. Application of disease-modifying therapy likely requires screening of patients with molecular evidence of pathological accumulation and monitoring of treatment effect assisted with biomarkers. There is currently still a gap in specific 4-repeat tau imaging probes for 4-repeat tauopathies and α-synuclein imaging probes for Parkinson's disease and dementia with Lewy body. In this review, we focused on recent development in molecular imaging biomarkers for assisting the early diagnosis of proteinopathies (i.e., amyloid-β, tau, and α-synuclein) in dementia and discussed future perspectives.
Collapse
Affiliation(s)
- Ruiqing Ni
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
- Institute for Biomedical Engineering, ETH & University of Zurich, Zurich, Switzerland
| | - Roger M. Nitsch
- Institute for Regenerative Medicine, University of Zurich, Zurich, Switzerland
| |
Collapse
|
18
|
Müller EG, Edwin TH, Strand BH, Stokke C, Revheim ME, Knapskog AB. Is Amyloid Burden Measured by 18F-Flutemetamol PET Associated with Progression in Clinical Alzheimer's Disease? J Alzheimers Dis 2021; 85:197-205. [PMID: 34776444 PMCID: PMC8842772 DOI: 10.3233/jad-215046] [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] [Indexed: 11/15/2022]
Abstract
Background: Patients with Alzheimer’s disease (AD) show heterogeneity in clinical progression rate, and we have limited tools to predict prognosis. Amyloid burden from 18F-Flutemetamol positron emission tomography (PET), as measured by standardized uptake value ratios (SUVR), might provide prognostic information. Objective: We investigate whether 18F-Flutemetamol PET composite or regional SUVRs are associated with trajectories of clinical progression. Methods: This observational longitudinal study included 94 patients with clinical AD. PET images were semi-quantified with normalization to pons. Group-based trajectory modeling was applied to identify trajectory groups according to change in the Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) over time. Multinomial logistic regression models assessed the association of SUVRs with trajectory group membership. Results: Three trajectory groups were identified. In the regression models, neither composite nor regional SUVRs were associated with trajectory group membership. Conclusion: There were no associations between CDR progression and 18F-Flutemetamol PET-derived composite SUVRs or regional SUVRs in clinical AD.
Collapse
Affiliation(s)
- Ebba Gløersen Müller
- Division of Radiology and Nuclear Medicine, Department of Nuclear Medicine, Oslo University Hospital, Oslo, Norway.,Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Trine Holt Edwin
- Institute of Health and Society, Faculty of Medicine, University of Oslo, Oslo, Norway.,Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway.,Norwegian National Advisory Unit on Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway
| | - Bjørn Heine Strand
- Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway.,Norwegian National Advisory Unit on Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway.,Department of Chronic Diseases and Ageing, Norwegian Institute of Public Health, Oslo, Norway
| | - Caroline Stokke
- Division of Radiology and Nuclear Medicine, Department of Nuclear Medicine, Oslo University Hospital, Oslo, Norway.,Department of Physics, University of Oslo, Oslo, Norway
| | - Mona Elisabeth Revheim
- Division of Radiology and Nuclear Medicine, Department of Nuclear Medicine, Oslo University Hospital, Oslo, Norway.,Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | | |
Collapse
|
19
|
McCollum LE, Das SR, Xie L, de Flores R, Wang J, Xie SX, Wisse LEM, Yushkevich PA, Wolk DA. Oh brother, where art tau? Amyloid, neurodegeneration, and cognitive decline without elevated tau. Neuroimage Clin 2021; 31:102717. [PMID: 34119903 PMCID: PMC8207301 DOI: 10.1016/j.nicl.2021.102717] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Revised: 05/21/2021] [Accepted: 06/02/2021] [Indexed: 12/24/2022]
Abstract
Mild cognitive impairment (MCI) can be an early manifestation of Alzheimer's disease (AD) pathology, other pathologic entities [e.g., cerebrovascular disease, Lewy body disease, LATE (limbic-predominant age-related TDP-43 encephalopathy)], or mixed pathologies, with concomitant AD- and non-AD pathology being particularly common, albeit difficult to identify, in living MCI patients. The National Institute on Aging and Alzheimer's Association (NIA-AA) A/T/(N) [β-Amyloid/Tau/(Neurodegeneration)] AD research framework, which classifies research participants according to three binary biomarkers [β-amyloid (A+/A-), tau (T+/T-), and neurodegeneration (N+/N-)], provides an indirect means of identifying such cases. Individuals with A+T-(N+) MCI are thought to have both AD pathologic change, given the presence of β-amyloid, and non-AD pathophysiology, given neurodegeneration without tau, because in typical AD it is tau accumulation that is most tightly linked to neuronal injury and cognitive decline. Thus, in A+T-(N+) MCI (hereafter referred to as "mismatch MCI" for the tau-neurodegeneration mismatch), non-AD pathology is hypothesized to drive neurodegeneration and symptoms, because β-amyloid, in the absence of tau, likely reflects a preclinical stage of AD. We compared a group of individuals with mismatch MCI to groups with A+T+(N+) MCI (or "prodromal AD") and A-T-(N+) MCI (or "neurodegeneration-only MCI") on cross-sectional and longitudinal cognition and neuroimaging characteristics. β-amyloid and tau status were determined by CSF assays, while neurodegeneration status was based on hippocampal volume on MRI. Overall, mismatch MCI was less "AD-like" than prodromal AD and generally, with some exceptions, more closely resembled the neurodegeneration-only group. At baseline, mismatch MCI had less episodic memory loss compared to prodromal AD. Longitudinally, mismatch MCI declined more slowly than prodromal AD across all included cognitive domains, while mismatch MCI and neurodegeneration-only MCI declined at comparable rates. Prodromal AD had smaller baseline posterior hippocampal volume than mismatch MCI, and whole brain analyses demonstrated cortical thinning that was widespread in prodromal AD but largely restricted to the medial temporal lobes (MTLs) for the mismatch and neurodegeneration-only MCI groups. Longitudinally, mismatch MCI had slower rates of volume loss than prodromal AD throughout the MTLs. Differences in cross-sectional and longitudinal cognitive and neuroimaging measures between mismatch MCI and prodromal AD may reflect disparate underlying pathologic processes, with the mismatch group potentially being driven by non-AD pathologies on a background of largely preclinical AD. These findings suggest that β-amyloid status alone in MCI may not reveal the underlying driver of symptoms with important implications for enrollment in clinical trials and prognosis.
Collapse
Affiliation(s)
- Lauren E McCollum
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA; Department of Medicine, University of Tennessee Graduate School of Medicine, Knoxville, TN, USA.
| | - Sandhitsu R Das
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA; Department of Radiology, Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, PA, USA
| | - Long Xie
- Department of Radiology, Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, PA, USA
| | - Robin de Flores
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA; Department of Radiology, Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, PA, USA; INSERM UMR-S U1237, Université de Caen Normandie, Caen, Normandy, USA
| | - Jieqiong Wang
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Sharon X Xie
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
| | - Laura E M Wisse
- Department of Radiology, Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, PA, USA; Department of Diagnostic Radiology, Lund University, Lund, Sweden
| | - Paul A Yushkevich
- Department of Radiology, Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania, Philadelphia, PA, USA
| | - David A Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| |
Collapse
|
20
|
Hansson O. Biomarkers for neurodegenerative diseases. Nat Med 2021; 27:954-963. [PMID: 34083813 DOI: 10.1038/s41591-021-01382-x] [Citation(s) in RCA: 432] [Impact Index Per Article: 144.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 05/03/2021] [Indexed: 12/14/2022]
Abstract
Biomarkers for neurodegenerative diseases are needed to improve the diagnostic workup in the clinic but also to facilitate the development and monitoring of effective disease-modifying therapies. Positron emission tomography methods detecting amyloid-β and tau pathology in Alzheimer's disease have been increasingly used to improve the design of clinical trials and observational studies. In recent years, easily accessible and cost-effective blood-based biomarkers detecting the same Alzheimer's disease pathologies have been developed, which might revolutionize the diagnostic workup of Alzheimer's disease globally. Relevant biomarkers for α-synuclein pathology in Parkinson's disease are also emerging, as well as blood-based markers of general neurodegeneration and glial activation. This review presents an overview of the latest advances in the field of biomarkers for neurodegenerative diseases. Future directions are discussed regarding implementation of novel biomarkers in clinical practice and trials.
Collapse
Affiliation(s)
- Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden. .,Memory Clinic, Skåne University Hospital, Malmö, Sweden.
| |
Collapse
|
21
|
Bucci M, Savitcheva I, Farrar G, Salvadó G, Collij L, Doré V, Gispert JD, Gunn R, Hanseeuw B, Hansson O, Shekari M, Lhommel R, Molinuevo JL, Rowe C, Sur C, Whittington A, Buckley C, Nordberg A. A multisite analysis of the concordance between visual image interpretation and quantitative analysis of [ 18F]flutemetamol amyloid PET images. Eur J Nucl Med Mol Imaging 2021; 48:2183-2199. [PMID: 33844055 PMCID: PMC8175298 DOI: 10.1007/s00259-021-05311-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Accepted: 03/09/2021] [Indexed: 12/18/2022]
Abstract
BACKGROUND [18F]flutemetamol PET scanning provides information on brain amyloid load and has been approved for routine clinical use based upon visual interpretation as either negative (equating to none or sparse amyloid plaques) or amyloid positive (equating to moderate or frequent plaques). Quantitation is however fundamental to the practice of nuclear medicine and hence can be used to supplement amyloid reading methodology especially in unclear cases. METHODS A total of 2770 [18F]flutemetamol images were collected from 3 clinical studies and 6 research cohorts with available visual reading of [18F]flutemetamol and quantitative analysis of images. These were assessed further to examine both the discordance and concordance between visual and quantitative imaging primarily using thresholds robustly established using pathology as the standard of truth. Scans covered a wide range of cases (i.e. from cognitively unimpaired subjects to patients attending the memory clinics). Methods of quantifying amyloid ranged from using CE/510K cleared marked software (e.g. CortexID, Brass), to other research-based methods (e.g. PMOD, CapAIBL). Additionally, the clinical follow-up of two types of discordance between visual and quantitation (V+Q- and V-Q+) was examined with competing risk regression analysis to assess possible differences in prediction for progression to Alzheimer's disease (AD) and other diagnoses (OD). RESULTS Weighted mean concordance between visual and quantitation using the autopsy-derived threshold was 94% using pons as the reference region. Concordance from a sensitivity analysis which assessed the maximum agreement for each cohort using a range of cut-off values was also estimated at approximately 96% (weighted mean). Agreement was generally higher in clinical cases compared to research cases. V-Q+ discordant cases were 11% more likely to progress to AD than V+Q- for the SUVr with pons as reference region. CONCLUSIONS Quantitation of amyloid PET shows a high agreement vs binary visual reading and also allows for a continuous measure that, in conjunction with possible discordant analysis, could be used in the future to identify possible earlier pathological deposition as well as monitor disease progression and treatment effectiveness.
Collapse
Affiliation(s)
- Marco Bucci
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
| | - Irina Savitcheva
- Medical Radiation Physics and Nuclear Medicine, Section for Nuclear Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Gill Farrar
- Pharmaceutical Diagnostics, GE Healthcare, Amersham, UK
| | - Gemma Salvadó
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Lyduine Collij
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan, 1117, Amsterdam, Netherlands
| | - Vincent Doré
- Austin Health, University of Melbourne, Melbourne, Australia.,Health and Biosecurity, CSIRO, Parkville, Australia
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Universitat Pompeu Fabra, Barcelona, Spain.,Centro de Investigación Biomédica en Red Bioingenieriá, Biomateriales y Nanomedicina, (CIBER-BBN), Barcelona, Spain
| | - Roger Gunn
- Invicro, London, UK.,Division of Brain Sciences, Department of Medicine, Imperial College, London, UK
| | - Bernard Hanseeuw
- Neurology and Nuclear Medicine Departments, Saint-Luc University Hospital, Av. Hippocrate, 10, 1200, Brussels, Belgium.,Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmo, Lund University, Lund, Sweden
| | - Mahnaz Shekari
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Universitat Pompeu Fabra, Barcelona, Spain
| | - Renaud Lhommel
- Neurology and Nuclear Medicine Departments, Saint-Luc University Hospital, Av. Hippocrate, 10, 1200, Brussels, Belgium
| | - José Luis Molinuevo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain.,IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.,Universitat Pompeu Fabra, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Christopher Rowe
- Austin Health, University of Melbourne, Melbourne, Australia.,Department of Medicine, The University of Melbourne, Melbourne, Australia
| | | | | | | | - Agneta Nordberg
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden. .,Department of Aging, Karolinska University Hospital, Stockholm, Sweden.
| |
Collapse
|
22
|
Bao YW, Chau ACM, Chiu PKC, Shea YF, Kwan JSK, Chan FHW, Mak HKF. Heterogeneity of Amyloid Binding in Cognitively Impaired Patients Consecutively Recruited from a Memory Clinic: Evaluating the Utility of Quantitative 18F-Flutemetamol PET-CT in Discrimination of Mild Cognitive Impairment from Alzheimer's Disease and Other Dementias. J Alzheimers Dis 2021; 79:819-832. [PMID: 33361593 PMCID: PMC7902948 DOI: 10.3233/jad-200890] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND With the more widespread use of 18F-radioligand-based amyloid-β (Aβ) PET-CT imaging, we evaluated Aβ binding and the utility of neocortical 18F-Flutemetamol standardized uptake value ratio (SUVR) as a biomarker. OBJECTIVE 18F-Flutemetamol SUVR was used to differentiate 1) mild cognitive impairment (MCI) from Alzheimer's disease (AD), and 2) MCI from other non-AD dementias (OD). METHODS 109 patients consecutively recruited from a University memory clinic underwent clinical evaluation, neuropsychological test, MRI and 18F-Flutemetamol PET-CT. The diagnosis was made by consensus of a panel consisting of 1 neuroradiologist and 2 geriatricians. The final cohort included 13 subjective cognitive decline (SCD), 22 AD, 39 MCI, and 35 OD. Quantitative analysis of 16 region-of-interests made by Cortex ID software (GE Healthcare). RESULTS The global mean 18F-Flutemetamol SUVR in SCD, MCI, AD, and OD were 0.50 (SD-0.08), 0.53 (SD-0.16), 0.76 (SD-0.10), and 0.56 (SD-0.16), respectively, with SUVR in SCD and MCI and OD being significantly lower than AD. Aβ binding in SCD, MCI, and OD was heterogeneous, being 23%, 38.5%, and 42.9% respectively, as compared to 100% amyloid positivity in AD. Using global SUVR, ROC analysis showed AUC of 0.868 and 0.588 in differentiating MCI from AD and MCI from OD respectively. CONCLUSION 18F-Flutemetamol SUVR differentiated MCI from AD with high efficacy (high negative predictive value), but much lower efficacy from OD. The major benefit of the test was to differentiate cognitively impaired patients (either SCD, MCI, or OD) without AD-related-amyloid-pathology from AD in the clinical setting, which was under-emphasized in the current guidelines proposed by Amyloid Imaging Task Force.
Collapse
Affiliation(s)
- Yi-Wen Bao
- Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Anson C M Chau
- Department of Medical Imaging, The University of Hong Kong (Shenzhen) Teaching Hospital , The University of Hong Kong, Hong Kong SAR, China
| | - Patrick Ka-Chun Chiu
- Division of Geriatrics, Department of Medicine, Queen Mary Hospital, Hong Kong SAR, China
| | - Yat Fung Shea
- Division of Geriatrics, Department of Medicine, Queen Mary Hospital, Hong Kong SAR, China
| | - Joseph S K Kwan
- Department of Brain Sciences, Imperial College London, London, United Kingdom
| | - Felix Hon Wai Chan
- Division of Geriatrics, Department of Medicine, Queen Mary Hospital, Hong Kong SAR, China
| | - Henry Ka-Fung Mak
- Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.,State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong SAR, China
| |
Collapse
|
23
|
Papanastasiou G, Rodrigues MA, Wang C, Heurling K, Lucatelli C, Salman RAS, Wardlaw JM, van Beek EJR, Thompson G. Pharmacokinetic modelling for the simultaneous assessment of perfusion and 18F-flutemetamol uptake in cerebral amyloid angiopathy using a reduced PET-MR acquisition time: Proof of concept. Neuroimage 2020; 225:117482. [PMID: 33157265 DOI: 10.1016/j.neuroimage.2020.117482] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Revised: 09/24/2020] [Accepted: 10/19/2020] [Indexed: 01/05/2023] Open
Abstract
PURPOSE Cerebral amyloid angiopathy (CAA) is a cerebral small vessel disease associated with perivascular β-amyloid deposition. CAA is also associated with strokes due to lobar intracerebral haemorrhage (ICH). 18F-flutemetamol amyloid ligand PET may improve the early detection of CAA. We performed pharmacokinetic modelling using both full (0-30, 90-120 min) and reduced (30 min) 18F-flutemetamol PET-MR acquisitions, to investigate regional cerebral perfusion and amyloid deposition in ICH patients. METHODS Dynamic18F-flutemetamol PET-MR was performed in a pilot cohort of sixteen ICH participants; eight lobar ICH cases with probable CAA and eight deep ICH patients. A model-based input function (mIF) method was developed for compartmental modelling. mIF 1-tissue (1-TC) and 2-tissue (2-TC) compartmental modelling, reference tissue models and standardized uptake value ratios were assessed in the setting of probable CAA detection. RESULTS The mIF 1-TC model detected perfusion deficits and 18F-flutemetamol uptake in cases with probable CAA versus deep ICH patients, in both full and reduced PET acquisition time (all P < 0.05). In the reduced PET acquisition, mIF 1-TC modelling reached the highest sensitivity and specificity in detecting perfusion deficits (0.87, 0.77) and 18F-flutemetamol uptake (0.83, 0.71) in cases with probable CAA. Overall, 52 and 48 out of the 64 brain areas with 18F-flutemetamol-determined amyloid deposition showed reduced perfusion for 1-TC and 2-TC models, respectively. CONCLUSION Pharmacokinetic (1-TC) modelling using a 30 min PET-MR time frame detected impaired haemodynamics and increased amyloid load in probable CAA. Perfusion deficits and amyloid burden co-existed within cases with CAA, demonstrating a distinct imaging pattern which may have merit in elucidating the pathophysiological process of CAA.
Collapse
Affiliation(s)
- Giorgos Papanastasiou
- Edinburgh Imaging Facility, Queen's Medical Research Institute, The University of Edinburgh, 47 Little France Crescent, Edinburgh EH16 4TJ, UK.
| | - Mark A Rodrigues
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Chengjia Wang
- Edinburgh Imaging Facility, Queen's Medical Research Institute, The University of Edinburgh, 47 Little France Crescent, Edinburgh EH16 4TJ, UK
| | | | - Christophe Lucatelli
- Edinburgh Imaging Facility, Queen's Medical Research Institute, The University of Edinburgh, 47 Little France Crescent, Edinburgh EH16 4TJ, UK
| | | | - Joanna M Wardlaw
- Edinburgh Imaging Facility, Queen's Medical Research Institute, The University of Edinburgh, 47 Little France Crescent, Edinburgh EH16 4TJ, UK; Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Edwin J R van Beek
- Edinburgh Imaging Facility, Queen's Medical Research Institute, The University of Edinburgh, 47 Little France Crescent, Edinburgh EH16 4TJ, UK
| | - Gerard Thompson
- Edinburgh Imaging Facility, Queen's Medical Research Institute, The University of Edinburgh, 47 Little France Crescent, Edinburgh EH16 4TJ, UK; Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| |
Collapse
|
24
|
Jun S, Kim H, Kim BS, Yoo BG, Lee WG. Quantitative Brain Amyloid Measures Predict Time-to-Progression from Amnestic Mild Cognitive Impairment to Alzheimer's Disease. J Alzheimers Dis 2020; 70:477-486. [PMID: 31256127 DOI: 10.3233/jad-190070] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND This study was designed to investigate factors that predict progression from amnestic mild cognitive impairment (aMCI) to probable Alzheimer's disease (AD). OBJECTIVE We studied the usefulness of quantitative assessment of amyloid burden measured by Florbetapir PET scan. METHODS The study cohort consisted of aMCI participants older than 65 and those with available Florbetapir PET scan at diagnosis from the ADNI database (http://adni.loni.usc.edu). To assess the prognostic impact of amyloid burden, a staging system based on the global SUVr of the PET scan was applied. We defined the stages as: stage I, negative amyloid scan; stage II, positive amyloid in 1st tertile; stage III, positive amyloid in 2nd tertile; and stage IV, positive amyloid in 3rd tertile. RESULTS Of 250 eligible aMCI subjects (age 74.1±5.4, female n = 105), 71 (28.4%) were diagnosed with probable AD within 3 years. Higher amyloid stages showed faster cognitive decline by Kaplan-Meier analysis. In multivariate Cox analysis, with stage I as a reference, the hazard ratio (HR) increased as the stage increased: stage II (HR, 4.509; p = 0.015), stage III (HR, 7.616; p = 0.001), and stage IV (HR, 9.421; p < 0.001). Along with amyloid stage, ApoE ɛ4 (HR, 1.943; p = 0.031), score of CDR-SB (HR, 1.845; p < 0.001) and ADAS 11 (HR, 1.144; p < 0.001), and hippocampal volume (HR, 0.002; p = 0.005) were also identified as predictors of dementia progression in aMCI subjects. CONCLUSIONS Large amyloid burden measured from amyloid PET scan could be a predictor of faster cognitive decline in aMCI patients.
Collapse
Affiliation(s)
- Sungmin Jun
- Departement of Nuclear Medicine, Kosin University Gospel Hospital, University of Kosin College of Medicine, Busan, Republic of Korea
| | - Heeyoung Kim
- Departement of Nuclear Medicine, Kosin University Gospel Hospital, University of Kosin College of Medicine, Busan, Republic of Korea
| | - Bum Soo Kim
- Departement of Nuclear Medicine, Kosin University Gospel Hospital, University of Kosin College of Medicine, Busan, Republic of Korea
| | - Bong-Goo Yoo
- Departement of Neurology, Kosin University Gospel Hospital, University of Kosin College of Medicine, Busan, Republic of Korea
| | - Won Gu Lee
- Departement of Neurology, Kosin University Gospel Hospital, University of Kosin College of Medicine, Busan, Republic of Korea
| | | |
Collapse
|
25
|
Lauretani F, Ruffini L, Scarlattei M, Maggio M. Relationship between comprehensive geriatric assessment and amyloid PET in older persons with MCI. BMC Geriatr 2020; 20:337. [PMID: 32907545 PMCID: PMC7487621 DOI: 10.1186/s12877-020-01746-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2019] [Accepted: 08/30/2020] [Indexed: 01/23/2023] Open
Abstract
Background The association between amyloid deposition and cognitive, behavioral and physical performance in mild cognitive impairment (MCI) due to Alzheimer’s disease (AD) has been poorly investigated, especially in older persons. Methods We studied the in vivo correlation between the amyloid deposition at Positron Emission Tomography (amyloid-PET) and the presence of memory loss, reduced executive function, neuropsychiatric symptoms and physical performance in older persons with MCI. Amyloid-PET was performed with 18F-flutemetamol and quantitatively analyzed. Results We evaluated 48 subjects, 21 men and 27 women. We performed in each patient a comprehensive geriatric assessment (CGA) including Mini Mental State Examination (MMSE), Clock Drawing Test (CDT), Activity Daily Living (ADL), Instrumental Activity of Daily Living (IADL), Neuropsychiatric inventory (NPI) questionnaire, 15 Geriatric Depression Scale (GDS), Short Physical Performance Battery (SPPB) and Hand Grip strength. Then, each patient underwent amyloid-PET. Mean age of the enrolled subjects was 74.6 ± 7.8 years. All of these subjects showed preserved cognitive function at MMSE > 24, while 29 of 48 subjects (61.0%) had altered CDT. Mean NPI score was 6.9 ± 5.9. The mean value of SPPB score was 9.0 ± 2.6, while the average muscle strength of the upper extremities measured by hand grip was 25.6 ± 7.7 Kg. CT/MRI images showed cortical atrophic changes in 26 of the 48 examined subjects (54.0%), while cerebrovascular modifications were present in 31 subjects (64.5%). Pathological burden of amyloid deposits was detected in 25 of 48 (52.0%) patients with a mean value of global z-score of 2.8 (subjects defined as MCI due to AD). After stratifying subjects in subclasses of clinical alterations, more probability of pathological amyloid deposition was found in subjects with impaired CDT and higher NPI score (O.R. = 3.45 [1.01–11.2], p = 0.04), with both impaired CDT and low physical performance (O.R. = 5.80 [1.04–32.2], p = 0.04), with altered CDT and high NPI score (O.R. = 7.98 [1.38–46.0], p = 0.02), and finally in those subjects with altered CDT, high NPI and low physical performance (O.R. = 5.80 [1.05–32.2], p = 0.04). Conclusion Our findings support the recent hypothesis that amyloid deposition could be associated with multiple cerebral dysfunction, mainly affecting executive, behavioral and motor abilities.
Collapse
Affiliation(s)
- Fulvio Lauretani
- Department of Medicine and Surgery, University of Parma, Via Gramsci 14, 43100, Parma, Italy. .,Cognitive and Motoric Center, Medicine and Geriatric-Rehabilitation Department of Parma, University-Hospital of Parma, 43126, Parma, Italy.
| | - Livia Ruffini
- Nuclear Medicine Unit, University Hospital of Parma, Parma, Italy
| | - Maura Scarlattei
- Nuclear Medicine Unit, University Hospital of Parma, Parma, Italy
| | - Marcello Maggio
- Department of Medicine and Surgery, University of Parma, Via Gramsci 14, 43100, Parma, Italy.,Cognitive and Motoric Center, Medicine and Geriatric-Rehabilitation Department of Parma, University-Hospital of Parma, 43126, Parma, Italy
| |
Collapse
|
26
|
Hanseeuw BJ, Malotaux V, Dricot L, Quenon L, Sznajer Y, Cerman J, Woodard JL, Buckley C, Farrar G, Ivanoiu A, Lhommel R. Defining a Centiloid scale threshold predicting long-term progression to dementia in patients attending the memory clinic: an [ 18F] flutemetamol amyloid PET study. Eur J Nucl Med Mol Imaging 2020; 48:302-310. [PMID: 32601802 PMCID: PMC7835306 DOI: 10.1007/s00259-020-04942-4] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Accepted: 06/22/2020] [Indexed: 12/14/2022]
Abstract
PURPOSE To evaluate cerebral amyloid-β(Aβ) pathology in older adults with cognitive complaints, visual assessment of PET images is approved as the routine method for image interpretation. In research studies however, Aβ-PET semi-quantitative measures are associated with greater risk of progression to dementia; but until recently, these measures lacked standardization. Therefore, the Centiloid scale, providing standardized Aβ-PET semi-quantitation, was recently validated. We aimed to determine the predictive values of visual assessments and Centiloids in non-demented patients, using long-term progression to dementia as our standard of truth. METHODS One hundred sixty non-demented participants (age, 54-86) were enrolled in a monocentric [18F] flutemetamol Aβ-PET study. Flutemetamol images were interpreted visually following the manufacturers recommendations. SUVr values were converted to the Centiloid scale using the GAAIN guidelines. Ninety-eight persons were followed until dementia diagnosis or were clinically stable for a median of 6 years (min = 4.0; max = 8.0). Twenty-five patients with short follow-up (median = 2.0 years; min = 0.8; max = 3.9) and 37 patients with no follow-up were excluded. We computed ROC curves predicting subsequent dementia using baseline PET data and calculated negative (NPV) and positive (PPV) predictive values. RESULTS In the 98 participants with long follow-up, Centiloid = 26 provided the highest overall predictive value = 87% (NPV = 85%, PPV = 88%). Visual assessment corresponded to Centiloid = 40, which predicted dementia with an overall predictive value = 86% (NPV = 81%, PPV = 92%). Inclusion of the 25 patients who only had a 2-year follow-up decreased the PPV = 67% (NPV = 88%), reflecting the many positive cases that did not progress to dementia after short follow-ups. CONCLUSION A Centiloid threshold = 26 optimally predicts progression to dementia 6 years after PET. Visual assessment provides similar predictive value, with higher specificity and lower sensitivity. TRIAL REGISTRATION Eudra-CT number: 2011-001756-12.
Collapse
Affiliation(s)
- Bernard J Hanseeuw
- Institute of Neuroscience, Université Catholique de Louvain, Brussels, Belgium. .,Neurology Department, Saint-Luc University Hospital, Av. Hippocrate, 10, 1200, Brussels, Belgium. .,Gordon Center for Medical Imaging, Radiology Department, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
| | - Vincent Malotaux
- Institute of Neuroscience, Université Catholique de Louvain, Brussels, Belgium
| | - Laurence Dricot
- Institute of Neuroscience, Université Catholique de Louvain, Brussels, Belgium
| | - Lisa Quenon
- Neurology Department, Saint-Luc University Hospital, Av. Hippocrate, 10, 1200, Brussels, Belgium
| | - Yves Sznajer
- Genetics Department, Saint-Luc University Hospital, Brussels, Belgium
| | - Jiri Cerman
- Department of Neurology, Charles University, 2nd Faculty of Medicine and Motol University Hospital, Prague, Czech Republic
| | - John L Woodard
- Institute of Neuroscience, Université Catholique de Louvain, Brussels, Belgium.,Department of Psychology, Wayne State University, Detroit, MI, USA
| | | | | | - Adrian Ivanoiu
- Institute of Neuroscience, Université Catholique de Louvain, Brussels, Belgium.,Neurology Department, Saint-Luc University Hospital, Av. Hippocrate, 10, 1200, Brussels, Belgium
| | - Renaud Lhommel
- Institute of Neuroscience, Université Catholique de Louvain, Brussels, Belgium.,Nuclear Medicine Department, Saint-Luc University Hospital, Brussels, Belgium.,Institute of Experimental and Clinical Research, Université Catholique de Louvain, Brussels, Belgium
| |
Collapse
|
27
|
Franzmeier N, Koutsouleris N, Benzinger T, Goate A, Karch CM, Fagan AM, McDade E, Duering M, Dichgans M, Levin J, Gordon BA, Lim YY, Masters CL, Rossor M, Fox NC, O'Connor A, Chhatwal J, Salloway S, Danek A, Hassenstab J, Schofield PR, Morris JC, Bateman RJ, Ewers M. Predicting sporadic Alzheimer's disease progression via inherited Alzheimer's disease-informed machine-learning. Alzheimers Dement 2020; 16:501-511. [PMID: 32043733 PMCID: PMC7222030 DOI: 10.1002/alz.12032] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2019] [Revised: 10/21/2019] [Accepted: 11/25/2019] [Indexed: 11/22/2022]
Abstract
Introduction: Developing cross-validated multi-biomarker models for the prediction of the rate of cognitive decline in Alzheimer’s disease (AD) is a critical yet unmet clinical challenge. Methods: We applied support vector regression to AD biomarkers derived from cerebrospinal fluid, structural magnetic resonance imaging (MRI), amyloid-PET and fluorodeoxyglucose positron-emission tomography (FDG-PET) to predict rates of cognitive decline. Prediction models were trained in autosomal-dominant Alzheimer’s disease (ADAD, n = 121) and subsequently cross-validated in sporadic prodromal AD (n = 216). The sample size needed to detect treatment effects when using model-based risk enrichment was estimated. Results: A model combining all biomarker modalities and established in ADAD predicted the 4-year rate of decline in global cognition (R2 = 24%) and memory (R2 =25%) in sporadic AD. Model-based risk-enrichment reduced the sample size required for detecting simulated intervention effects by 50%–75%. Discussion: Our independently validated machine-learning model predicted cognitive decline in sporadic prodromal AD and may substantially reduce sample size needed in clinical trials in AD.
Collapse
Affiliation(s)
- Nicolai Franzmeier
- Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-Universität LMU, Munich, Germany
| | - Nikolaos Koutsouleris
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-Universität LMU, Munich, Germany
| | - Tammie Benzinger
- Department of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA.,Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Alison Goate
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Ronald M. Loeb Center for Alzheimer's Disease, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Celeste M Karch
- Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, Missouri, USA.,Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, Missouri, USA.,Department of Psychiatry, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Anne M Fagan
- Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, Missouri, USA.,Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, Missouri, USA.,Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Eric McDade
- Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, Missouri, USA.,Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Marco Duering
- Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-Universität LMU, Munich, Germany
| | - Martin Dichgans
- Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-Universität LMU, Munich, Germany.,Munich Cluster for Systems Neurology, Munich, Germany.,German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Johannes Levin
- Munich Cluster for Systems Neurology, Munich, Germany.,German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.,Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Brian A Gordon
- Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, Missouri, USA.,Mallinckrodt Institute of Radiology, Washington University, St. Louis, Missouri, USA.,Department of Psychological and Brain Sciences, Washington University, St. Louis, Missouri, USA
| | - Yen Ying Lim
- The Florey Institute, The University of Melbourne, Parkville, Victoria, Australia
| | - Colin L Masters
- The Florey Institute, The University of Melbourne, Parkville, Victoria, Australia
| | - Martin Rossor
- Dementia Research Centre, University College London, Queen Square, London, UK
| | - Nick C Fox
- Dementia Research Centre, University College London, Queen Square, London, UK
| | - Antoinette O'Connor
- Dementia Research Centre, University College London, Queen Square, London, UK
| | - Jasmeer Chhatwal
- Massachusetts General Hospital, Department of Neurology, Harvard Medical School, Boston, Massachusetts, USA
| | - Stephen Salloway
- Department of Neurology, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Adrian Danek
- Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Jason Hassenstab
- Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, Missouri, USA.,Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA.,Department of Psychological and Brain Sciences, Washington University, St. Louis, Missouri, USA
| | - Peter R Schofield
- Neuroscience Research Australia, Randwick, New South Wales, Australia.,School of Medical Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | - John C Morris
- Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, Missouri, USA.,Department of Psychiatry, Washington University in St. Louis, St. Louis, Missouri, USA.,Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Randall J Bateman
- Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, Missouri, USA.,Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | -
- ADNI Consortium members are listed in the appendix
| | -
- DIAN Consortium members are listed in the appendix
| | - Michael Ewers
- Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-Universität LMU, Munich, Germany
| |
Collapse
|
28
|
Tolar M, Abushakra S, Sabbagh M. The path forward in Alzheimer's disease therapeutics: Reevaluating the amyloid cascade hypothesis. Alzheimers Dement 2020; 16:1553-1560. [PMID: 31706733 DOI: 10.1016/j.jalz.2019.09.075] [Citation(s) in RCA: 157] [Impact Index Per Article: 39.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Development of disease-modifying treatments for Alzheimer's disease (AD) has been challenging, with no drugs approved to date. The failures of several amyloid-targeted programs have led many to dismiss the amyloid beta (Aβ) hypothesis of AD. An antiamyloid antibody aducanumab recently showed modest but significant efficacy in a phase 3 trial, providing important validation of amyloid as a therapeutic target. However, the inconsistent results observed with aducanumab may be explained by the limited brain penetration and lack of selectivity for the soluble Aβ oligomers, which are implicated as upstream drivers of neurodegeneration by multiple studies. Development of agents that can effectively inhibit Aβ oligomer formation or block their toxicity is therefore warranted. An ideal drug would cross the blood-brain barrier efficiently and achieve sustained brain levels that can continuously prevent oligomer formation or inhibit their toxicity. A late-stage candidate with these attributes is ALZ-801, an oral drug with a favorable safety profile and high brain penetration that can robustly inhibit Aβ oligomer formation. An upcoming phase 3 trial with ALZ-801 in APOE4/4 homozygous patients with early AD will effectively test this amyloid oligomer hypothesis.
Collapse
Affiliation(s)
| | | | - Marwan Sabbagh
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, USA
| |
Collapse
|
29
|
James HJ, Van Houtven CH, Lippmann S, Burke JR, Shepherd-Banigan M, Belanger E, Wetle TF, Plassman BL. How Accurately Do Patients and Their Care Partners Report Results of Amyloid-β PET Scans for Alzheimer's Disease Assessment? J Alzheimers Dis 2020; 74:625-636. [PMID: 32065790 PMCID: PMC7183243 DOI: 10.3233/jad-190922] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
BACKGROUND Amyloid-β PET scans will likely become an integral part of the diagnostic evaluation for Alzheimer's disease if Medicare approves reimbursement for the scans. However, little is known about patients' and their care partners' interpretation of scan results. OBJECTIVE This study seeks to understand how accurately patients with mild cognitive impairment (MCI) or dementia and their care partners report results of amyloid-β PET scans and factors related to correct reporting. METHODS A mixed-methods approach was used to analyze survey data from 1,845 patient-care partner dyads and responses to open-ended questions about interpretation of scan results from a sub-sample of 200 dyads. RESULTS Eighty-three percent of patients and 85% of care partners correctly reported amyloid-β PET scan results. Patients' higher cognitive function was associated with a small but significant decrease in the predicted probability of not only patients accurately reporting scan results (ME: -0.004, 95% CI: -0.007, -0.000), but also care partners accurately reporting scan results (ME: -0.006, 95% CI: -0.007, -0.001), as well as decreased concordance between patient and care partner reports (ME: -0.004, 95% CI: -0.007, -0.001). Content analysis of open-ended responses found that participants who reported the scan results incorrectly exhibited more confusion about diagnostic terminology than those who correctly reported the scan results. CONCLUSION Overall, patients with MCI or dementia showed high rates of accurate reporting of amyloid-β PET scan results. However, responses to questions about the meaning of the scan results highlight the need for improved provider communication, including providing written explanations and better prognostic information.
Collapse
Affiliation(s)
- Hailey J. James
- Department of Health Policy and Management, University of North Carolina, Chapel Hill, NC, USA
- Department of Population Health Sciences, Duke University, Durham, NC, USA
| | - Courtney Harold Van Houtven
- Department of Population Health Sciences, Duke University, Durham, NC, USA
- Health Services Research and Development in Primary Care, Durham Veterans Affairs Medical Center, Durham, NC, USA
| | - Steven Lippmann
- Department of Population Health Sciences, Duke University, Durham, NC, USA
| | - James R. Burke
- Department of Neurology, School of Medicine, Duke University, Durham, NC, USA
| | - Megan Shepherd-Banigan
- Department of Population Health Sciences, Duke University, Durham, NC, USA
- Health Services Research and Development in Primary Care, Durham Veterans Affairs Medical Center, Durham, NC, USA
| | - Emmanuelle Belanger
- Center for Gerontology and Healthcare Research, School of Public Health, Brown University, Providence, RI, USA
- Department of Health Services, Policy and Practice, School of Public Health, Brown University, Providence, RI, USA
| | - Terrie Fox Wetle
- Department of Health Services, Policy and Practice, School of Public Health, Brown University, Providence, RI, USA
| | - Brenda L. Plassman
- Department of Neurology, School of Medicine, Duke University, Durham, NC, USA
- Department of Psychiatry and Behavioral Sciences, School of Medicine, Duke University, Durham, NC, USA
| |
Collapse
|
30
|
Chandra A, Valkimadi PE, Pagano G, Cousins O, Dervenoulas G, Politis M. Applications of amyloid, tau, and neuroinflammation PET imaging to Alzheimer's disease and mild cognitive impairment. Hum Brain Mapp 2019; 40:5424-5442. [PMID: 31520513 PMCID: PMC6864887 DOI: 10.1002/hbm.24782] [Citation(s) in RCA: 111] [Impact Index Per Article: 22.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2019] [Revised: 07/29/2019] [Accepted: 08/18/2019] [Indexed: 02/06/2023] Open
Abstract
Alzheimer's disease (AD) is a devastating and progressive neurodegenerative disease for which there is no cure. Mild cognitive impairment (MCI) is considered a prodromal stage of the disease. Molecular imaging with positron emission tomography (PET) allows for the in vivo visualisation and tracking of pathophysiological changes in AD and MCI. PET is a very promising methodology for differential diagnosis and novel targets of PET imaging might also serve as biomarkers for disease-modifying therapeutic interventions. This review provides an overview of the current status and applications of in vivo molecular imaging of AD pathology, specifically amyloid, tau, and microglial activation. PET imaging studies were included and evaluated as potential biomarkers and for monitoring disease progression. Although the majority of radiotracers showed the ability to discriminate AD and MCI patients from healthy controls, they had various limitations that prevent the recommendation of a single technique or tracer as an optimal biomarker. Newer research examining amyloid, tau, and microglial PET imaging in combination suggest an alternative approach in studying the disease process.
Collapse
Affiliation(s)
- Avinash Chandra
- Neurodegeneration Imaging Group (NIG), Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London (KCL), London, UK
| | - Polytimi-Eleni Valkimadi
- Neurodegeneration Imaging Group (NIG), Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London (KCL), London, UK
| | - Gennaro Pagano
- Neurodegeneration Imaging Group (NIG), Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London (KCL), London, UK
| | - Oliver Cousins
- Neurodegeneration Imaging Group (NIG), Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London (KCL), London, UK
| | - George Dervenoulas
- Neurodegeneration Imaging Group (NIG), Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London (KCL), London, UK
| | - Marios Politis
- Neurodegeneration Imaging Group (NIG), Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London (KCL), London, UK
| |
Collapse
|
31
|
Müller EG, Edwin TH, Stokke C, Navelsaker SS, Babovic A, Bogdanovic N, Knapskog AB, Revheim ME. Amyloid-β PET-Correlation with cerebrospinal fluid biomarkers and prediction of Alzheimer´s disease diagnosis in a memory clinic. PLoS One 2019; 14:e0221365. [PMID: 31430334 PMCID: PMC6701762 DOI: 10.1371/journal.pone.0221365] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2019] [Accepted: 08/05/2019] [Indexed: 01/11/2023] Open
Abstract
Background Alzheimer’s disease (AD) remains a clinical diagnosis but biomarkers from cerebrospinal fluid (CSF) and more lately amyloid imaging with positron emission tomography (PET), are important to support a diagnosis of AD. Objective To compare amyloid-β (Aβ) PET imaging with biomarkers in CSF and evaluate the prediction of Aβ PET on diagnosis in a memory clinic setting. Methods We included 64 patients who had lumbar puncture and Aβ PET with 18F-Flutemetamol performed within 190 days. PET was binary classified (Flut+ or Flut-) and logistic regression analyses for correlation to each CSF biomarker; Aβ 42 (Aβ42), total tau (T-tau) and phosphorylated tau (P-tau), were performed. Cut-off values were assessed by receiver operating characteristic (ROC) curves. Logistic regression was performed for prediction of clinical AD diagnosis. We assessed the interrater agreement of PET classification as well as for diagnoses, which were made both with and without knowledge of PET results. Results Thirty-two of the 34 patients (94%) in the Flut+ group and nine of the 30 patients (30%) in the Flut- group had a clinical AD diagnosis. There were significant differences in all CSF biomarkers in the Flut+ and Flut- groups. Aβ42 showed the highest correlation with 18F-Flutemetamol PET with a cut-off value of 706.5 pg/mL, corresponding to sensitivity of 88% and specificity of 87%. 18F-Flutemetamol PET was the best predictor of a clinical AD diagnosis. We found a very high interrater agreement for both PET classification and diagnosis. Conclusions The present study showed an excellent correlation of Aβ42 in CSF and 18F-Flutemetamol PET and the presented cut-off value for Aβ42 yields high sensitivity and specificity for 18F-Flutemetamol PET. 18F-Flutemetamol PET was the best predictor of clinical AD diagnosis.
Collapse
Affiliation(s)
- Ebba Gløersen Müller
- Department of Nuclear Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- * E-mail:
| | - Trine Holt Edwin
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Geriatric Medicine, The Memory Clinic, Oslo University Hospital, Oslo, Norway
| | - Caroline Stokke
- Department of Diagnostic Physics, Oslo University Hospital, Oslo, Norway
- Department of Life Science and Health, Oslo Metropolitan University, Oslo, Norway
| | | | - Almira Babovic
- Department of Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Nenad Bogdanovic
- Department for Neurobiology, Caring Science and Society, Division of Clinical Geriatrics, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
| | - Anne Brita Knapskog
- Department of Geriatric Medicine, The Memory Clinic, Oslo University Hospital, Oslo, Norway
| | - Mona Elisabeth Revheim
- Department of Nuclear Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| |
Collapse
|
32
|
A deep learning model for early prediction of Alzheimer's disease dementia based on hippocampal magnetic resonance imaging data. Alzheimers Dement 2019; 15:1059-1070. [PMID: 31201098 DOI: 10.1016/j.jalz.2019.02.007] [Citation(s) in RCA: 98] [Impact Index Per Article: 19.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2018] [Revised: 02/14/2019] [Accepted: 02/25/2019] [Indexed: 02/04/2023]
Abstract
INTRODUCTION It is challenging at baseline to predict when and which individuals who meet criteria for mild cognitive impairment (MCI) will ultimately progress to Alzheimer's disease (AD) dementia. METHODS A deep learning method is developed and validated based on magnetic resonance imaging scans of 2146 subjects (803 for training and 1343 for validation) to predict MCI subjects' progression to AD dementia in a time-to-event analysis setting. RESULTS The deep-learning time-to-event model predicted individual subjects' progression to AD dementia with a concordance index of 0.762 on 439 Alzheimer's Disease Neuroimaging Initiative testing MCI subjects with follow-up duration from 6 to 78 months (quartiles: [24, 42, 54]) and a concordance index of 0.781 on 40 Australian Imaging Biomarkers and Lifestyle Study of Aging testing MCI subjects with follow-up duration from 18 to 54 months (quartiles: [18, 36, 54]). The predicted progression risk also clustered individual subjects into subgroups with significant differences in their progression time to AD dementia (P < .0002). Improved performance for predicting progression to AD dementia (concordance index = 0.864) was obtained when the deep learning-based progression risk was combined with baseline clinical measures. DISCUSSION Our method provides a cost effective and accurate means for prognosis and potentially to facilitate enrollment in clinical trials with individuals likely to progress within a specific temporal period.
Collapse
|
33
|
Rabinovici GD, Gatsonis C, Apgar C, Chaudhary K, Gareen I, Hanna L, Hendrix J, Hillner BE, Olson C, Lesman-Segev OH, Romanoff J, Siegel BA, Whitmer RA, Carrillo MC. Association of Amyloid Positron Emission Tomography With Subsequent Change in Clinical Management Among Medicare Beneficiaries With Mild Cognitive Impairment or Dementia. JAMA 2019; 321:1286-1294. [PMID: 30938796 PMCID: PMC6450276 DOI: 10.1001/jama.2019.2000] [Citation(s) in RCA: 351] [Impact Index Per Article: 70.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
IMPORTANCE Amyloid positron emission tomography (PET) detects amyloid plaques in the brain, a core neuropathological feature of Alzheimer disease. OBJECTIVE To determine if amyloid PET is associated with subsequent changes in the management of patients with mild cognitive impairment (MCI) or dementia of uncertain etiology. DESIGN, SETTING, AND PARTICIPANTS The Imaging Dementia-Evidence for Amyloid Scanning (IDEAS) study was a single-group, multisite longitudinal study that assessed the association between amyloid PET and subsequent changes in clinical management for Medicare beneficiaries with MCI or dementia. Participants were required to meet published appropriate use criteria stating that etiology of cognitive impairment was unknown, Alzheimer disease was a diagnostic consideration, and knowledge of PET results was expected to change diagnosis and management. A total of 946 dementia specialists at 595 US sites enrolled 16 008 patients between February 2016 and September 2017. Patients were followed up through January 2018. Dementia specialists documented their diagnosis and management plan before PET and again 90 (±30) days after PET. EXPOSURES Participants underwent amyloid PET at 343 imaging centers. MAIN OUTCOMES AND MEASURES The primary end point was change in management between the pre- and post-PET visits, as assessed by a composite outcome that included Alzheimer disease drug therapy, other drug therapy, and counseling about safety and future planning. The study was powered to detect a 30% or greater change in the MCI and dementia groups. One of 2 secondary end points is reported: the proportion of changes in diagnosis (from Alzheimer disease to non-Alzheimer disease and vice versa) between pre- and post-PET visits. RESULTS Among 16 008 registered participants, 11 409 (71.3%) completed study procedures and were included in the analysis (median age, 75 years [interquartile range, 71-80]; 50.9% women; 60.5% with MCI). Amyloid PET results were positive in 3817 patients with MCI (55.3%) and 3154 patients with dementia (70.1%). The composite end point changed in 4159 of 6905 patients with MCI (60.2% [95% CI, 59.1%-61.4%]) and 2859 of 4504 patients with dementia (63.5% [95% CI, 62.1%-64.9%]), significantly exceeding the 30% threshold in each group (P < .001, 1-sided). The etiologic diagnosis changed from Alzheimer disease to non-Alzheimer disease in 2860 of 11 409 patients (25.1% [95% CI, 24.3%-25.9%]) and from non-Alzheimer disease to Alzheimer disease in 1201 of 11 409 (10.5% [95% CI, 10.0%-11.1%]). CONCLUSIONS AND RELEVANCE Among Medicare beneficiaries with MCI or dementia of uncertain etiology evaluated by dementia specialists, the use of amyloid PET was associated with changes in clinical management within 90 days. Further research is needed to determine whether amyloid PET is associated with improved clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT02420756.
Collapse
Affiliation(s)
- Gil D. Rabinovici
- Memory and Aging Center, Department of Neurology, University of California, San Francisco
- Associate Editor, JAMA Neurology
| | - Constantine Gatsonis
- Center for Statistical Sciences, Brown University School of Public Health, Providence, Rhode Island
- Department of Biostatistics, Brown University School of Public Health, Providence, Rhode Island
| | | | - Kiran Chaudhary
- Memory and Aging Center, Department of Neurology, University of California, San Francisco
| | - Ilana Gareen
- Center for Statistical Sciences, Brown University School of Public Health, Providence, Rhode Island
- Department of Epidemiology, Brown University School of Public Health, Providence, Rhode Island
| | - Lucy Hanna
- Center for Statistical Sciences, Brown University School of Public Health, Providence, Rhode Island
| | | | - Bruce E. Hillner
- Department of Medicine, Virginia Commonwealth University, Richmond
| | | | - Orit H. Lesman-Segev
- Memory and Aging Center, Department of Neurology, University of California, San Francisco
| | - Justin Romanoff
- Center for Statistical Sciences, Brown University School of Public Health, Providence, Rhode Island
| | - Barry A. Siegel
- Edward Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri
| | - Rachel A. Whitmer
- Division of Research, Kaiser Permanente, Oakland, California
- Department of Public Health Sciences, University of California, Davis
| | | |
Collapse
|
34
|
Leuzy A, Savitcheva I, Chiotis K, Lilja J, Andersen P, Bogdanovic N, Jelic V, Nordberg A. Clinical impact of [ 18F]flutemetamol PET among memory clinic patients with an unclear diagnosis. Eur J Nucl Med Mol Imaging 2019; 46:1276-1286. [PMID: 30915522 PMCID: PMC6486908 DOI: 10.1007/s00259-019-04297-5] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2018] [Accepted: 02/25/2019] [Indexed: 12/11/2022]
Abstract
Purpose To investigate the impact of amyloid PET with [18F]flutemetamol on diagnosis and treatment management in a cohort of patients attending a tertiary memory clinic in whom, despite extensive cognitive assessment including neuropsychological testing, structural imaging, CSF biomarker analysis and in some cases [18F]FDG PET, the diagnosis remained unclear. Methods The study population consisted of 207 patients with a clinical diagnosis prior to [18F]flutemetamol PET including mild cognitive impairment (MCI; n = 131), Alzheimer’s disease (AD; n = 41), non-AD (n = 10), dementia not otherwise specified (dementia NOS; n = 20) and subjective cognitive decline (SCD; n = 5). Results Amyloid positivity was found in 53% of MCI, 68% of AD, 20% of non-AD, 20% of dementia NOS, and 60% of SCD patients. [18F]Flutemetamol PET led, overall, to a change in diagnosis in 92 of the 207 patients (44%). A high percentage of patients with a change in diagnosis was observed in the MCI group (n = 67, 51%) and in the dementia NOS group (n = 11; 55%), followed by the non-AD and AD (30% and 20%, respectively). A significant increase in cholinesterase inhibitor treatment was observed after [18F]flutemetamol PET (+218%, 34 patients before and 108 patients after). Conclusion The present study lends support to the clinical value of amyloid PET in patients with an uncertain diagnosis in the tertiary memory clinic setting.
Collapse
Affiliation(s)
- Antoine Leuzy
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics Center for Alzheimer Research, Karolinska Institutet, Neo, 7th floor, 141 83, Huddinge, Sweden
| | - Irina Savitcheva
- Medical Radiation Physics and Nuclear Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Konstantinos Chiotis
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics Center for Alzheimer Research, Karolinska Institutet, Neo, 7th floor, 141 83, Huddinge, Sweden
| | - Johan Lilja
- Department of Surgical Sciences, Radiology, Nuclear Medicine and PET, Uppsala University, Uppsala, Sweden.,Hermes Medical Solutions, Stockholm, Sweden
| | - Pia Andersen
- Clinic for Cognitive Disorders, Theme Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Nenad Bogdanovic
- Clinic for Cognitive Disorders, Theme Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Vesna Jelic
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics Center for Alzheimer Research, Karolinska Institutet, Neo, 7th floor, 141 83, Huddinge, Sweden.,Clinic for Cognitive Disorders, Theme Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Agneta Nordberg
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics Center for Alzheimer Research, Karolinska Institutet, Neo, 7th floor, 141 83, Huddinge, Sweden. .,Clinic for Cognitive Disorders, Theme Aging, Karolinska University Hospital, Stockholm, Sweden.
| |
Collapse
|
35
|
Farrar G, Molinuevo JL, Zanette M. Is there a difference in regional read [ 18F]flutemetamol amyloid patterns between end-of-life subjects and those with amnestic mild cognitive impairment? Eur J Nucl Med Mol Imaging 2019; 46:1299-1308. [PMID: 30863934 PMCID: PMC6486895 DOI: 10.1007/s00259-019-04282-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2018] [Accepted: 02/04/2019] [Indexed: 02/04/2023]
Abstract
PURPOSE Visual interpretation of PET [18F]flutemetamol images relies on systematic review of five brain regions and is considered positive when an elevated signal is observed in at least one region. Amnestic mild cognitive impairment (aMCI) is an early clinical presentation of Alzheimer's disease (AD); hence it is of interest to determine if the pattern of visually read regional positivity between end-of-life (EoL) patients with and without dementia and aMCI patients is different. METHODS A total of 180 EoL patients with and without dementia (mean age 81 years, range 59 to 95 years) and 232 aMCI patients (mean age 71 years, range 53 to 91 years) were scanned following intravenous administration of 185-370 MBq [18F]flutemetamol. Images from both studies were read by two groups of five blinded readers who independently classified each of the five regions as either positive or negative. The majority interpretation made by at least three of the five readers was used as the imaging endpoint and compared with a composite standardized uptake value ratio (SUVR) analysis using a predetermined threshold. RESULTS Amyloid-positive images from 71 of 106 EoL patients coming to autopsy and from 97 aMCI patients were included. In the images from the EoL patients widespread deposition of amyloid was observed, with 76% of the images positive in all five regions and a further 20% positive in four regions. In the images from the aMCI patients, similar results were observed with 87% of the images positive in five regions and a further 5% positive in four regions. The mean SUVR of these positively read images was 2.24 (range 1.48 to 3.14) and 2.08 (range 1.28 to 3.04) in the autopsy and aMCI groups, respectively. There was 95.3% agreement between the visual reading and SUVR quantitation in the aMCI group and 90.4% agreement in the autopsy group. CONCLUSION Patients with aMCI showed a similar distribution of amyloid deposition determined by both visual reading and SUVR to that observed in patients with and without dementia coming to autopsy. Most of the aMCI patients, who are already within the AD continuum, had widespread amyloid deposition in terms of amount and topographical progression. Attempts to observe potential initial signs of amyloid deposition should focus on populations earlier in the dementia spectrum such as patients with subjective cognitive decline or even at-risk subjects with earlier stages of disease.
Collapse
Affiliation(s)
| | - José Luis Molinuevo
- Barcelona Beta Brain Research Center, Pasqual Maragall Foundation and Hospital Clinic I Universitari, IDIBAPS, Barcelona, Spain
| | | |
Collapse
|
36
|
Cox CG, Ryan B A MM, Gillen DL, Grill JD. A Preliminary Study of Clinical Trial Enrollment Decisions Among People With Mild Cognitive Impairment and Their Study Partners. Am J Geriatr Psychiatry 2019; 27:322-332. [PMID: 30522811 PMCID: PMC6387840 DOI: 10.1016/j.jagp.2018.10.016] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/14/2018] [Revised: 10/27/2018] [Accepted: 10/31/2018] [Indexed: 11/25/2022]
Abstract
OBJECTIVE All Alzheimer disease (AD) clinical trials, including those enrolling patients with mild cognitive impairment (MCI), require dyadic participation. The purpose of this study was to elucidate how people with MCI and their study partners decide whether to enroll in clinical trials. METHODS This was a mixed methods interview study. We interviewed patient participants with a consensus research diagnosis of MCI and their study partners. Interviews examined how dyads decide whether to enroll in a clinical trial and whether AD biomarker testing affects willingness to enroll. RESULTS Though most MCI patients and study partners would decide in partnership whether to enroll in a clinical trial, agreement was lower among nonspousal, compared with spousal, dyads. Deterrents to enrollment included concerns about patient safety and inconvenience, especially for study partners. Motivators to enrollment included altruism, the desire to contribute to research, hope for patient benefit, and the desire to learn more about the patient's condition. When asked open-ended questions about motivators to enroll in trials, few patients cited access to biomarker testing specifically, though most expressed a desire to undergo biomarker testing when asked directly. CONCLUSION Spousal and nonspousal MCI dyads may approach clinical trial decisions differently. Future research should investigate how AD biomarker testing affects participants' willingness to enroll in trials.
Collapse
Affiliation(s)
- Chelsea G Cox
- Institute for Memory Impairments and Neurological Disorders (CGC, DLG, JDG), University of California, Irvine, Irvine, CA
| | - Mary M Ryan B A
- the Department of Statistics (MMR, DLG), University of California, Irvine, Irvine, CA
| | - Daniel L Gillen
- Institute for Memory Impairments and Neurological Disorders (CGC, DLG, JDG), University of California, Irvine, Irvine, CA; the Department of Statistics (MMR, DLG), University of California, Irvine, Irvine, CA
| | - Joshua D Grill
- Institute for Memory Impairments and Neurological Disorders (CGC, DLG, JDG), University of California, Irvine, Irvine, CA; the Department of Psychiatry and Human Behavior (JDG), University of California, Irvine, Irvine, CA; the Department of Neurobiology and Behavior (JDG), University of California, Irvine, Irvine, CA; Institute for Clinical and Translational Science (JDG), University of California, Irvine, Irvine, CA.
| |
Collapse
|
37
|
Prato FS, Pavlosky WF, Foster SC, Thiessen JD, Beaujot RP. Screening for Dementia Caused by Modifiable Lifestyle Choices Using Hybrid PET/MRI. J Alzheimers Dis Rep 2019; 3:31-45. [PMID: 30842996 PMCID: PMC6400112 DOI: 10.3233/adr-180098] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/19/2018] [Indexed: 12/19/2022] Open
Abstract
Significant advances in positron emission tomography (PET) and magnetic resonance imaging (MRI) brain imaging in the early detection of dementia indicate that hybrid PET/MRI would be an effective tool to screen for dementia in the population living with lifestyle risk factors. Here we investigate the associated costs and benefits along with the needed imaging infrastructure. A demographic analysis determined the prevalence of dementia and its incidence. The expected value of the screening program was calculated assuming a sensitivity and specificity of 0.9, a prevalence of 0.1, a QALY factor of 0.348, a willingness to pay $114,000 CAD and the cost per PET/MRI scan of $2,000 CAD. It was assumed that each head PET/MRI could screen 3,000 individuals per year. The prevalence of dementia is increasing by almost two-fold every 20 years due to the increased population at ages where dementia is more prevalent. It has been shown that a five-year delay in the incidence of dementia would decrease the prevalence by some 45%. In Canada, a five-year delay corresponds to a health care savings of $27,000 CAD per subject per year. The expected value for screening was estimated at $23,745 CAD. The number of subjects to be screened per year in Canada, USA, and China between 60 and 79 was 11,405,000. The corresponding number of head-only hybrid PET/MRI systems needed is 3,800. A brain PET/MRI screening program is financially justifiable with respect to health care costs and justifies the continuing development of MRI compatible brain PET technology.
Collapse
Affiliation(s)
- Frank S. Prato
- Department of Medical Biophysics, Western University, London, ON, Canada
- Lawson Health Research Institute, London, ON, Canada
- Department of Medical Imaging, Western University, London, ON, Canada
| | - William F. Pavlosky
- Lawson Health Research Institute, London, ON, Canada
- Department of Medical Imaging, Western University, London, ON, Canada
| | | | - Jonathan D. Thiessen
- Department of Medical Biophysics, Western University, London, ON, Canada
- Lawson Health Research Institute, London, ON, Canada
- Department of Medical Imaging, Western University, London, ON, Canada
| | | |
Collapse
|
38
|
Petersen RC, Lundt ES, Therneau TM, Weigand SD, Knopman DS, Mielke MM, Roberts RO, Lowe VJ, Machulda MM, Kremers WK, Geda YE, Jack CR. Predicting Progression to Mild Cognitive Impairment. Ann Neurol 2019; 85:155-160. [PMID: 30521086 PMCID: PMC6504922 DOI: 10.1002/ana.25388] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2018] [Revised: 11/30/2018] [Accepted: 12/03/2018] [Indexed: 12/31/2022]
Abstract
Despite much attention to the use of biomarkers for predicting Alzheimer disease, little information is available at the individual level. We used the population-based Mayo Clinic Study of Aging to estimate absolute risk of cognitive impairment by biomarker group. Risk increased with age and any biomarker abnormality. For example, a 75-year-old with abnormal amyloid and cortical thinning biomarkers has about a 20% chance of cognitive impairment by age 80 years, whereas with normal biomarkers the chance is <10%. Persons with only one abnormal biomarker had similar intermediate risks. ANN NEUROL 2019;85:155-160.
Collapse
Affiliation(s)
- Ronald C. Petersen
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Emily S. Lundt
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Terry M. Therneau
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | | | | | | | | | - Val J. Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Mary M. Machulda
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Walter K. Kremers
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Yonas E. Geda
- Department of Psychiatry and Psychology, Mayo Clinic, Phoenix, AZ, USA
| | | |
Collapse
|
39
|
Westwood S, Baird AL, Hye A, Ashton NJ, Nevado-Holgado AJ, Anand SN, Liu B, Newby D, Bazenet C, Kiddle SJ, Ward M, Newton B, Desai K, Tan Hehir C, Zanette M, Galimberti D, Parnetti L, Lleó A, Baker S, Narayan VA, van der Flier WM, Scheltens P, Teunissen CE, Visser PJ, Lovestone S. Plasma Protein Biomarkers for the Prediction of CSF Amyloid and Tau and [ 18F]-Flutemetamol PET Scan Result. Front Aging Neurosci 2018; 10:409. [PMID: 30618716 PMCID: PMC6297196 DOI: 10.3389/fnagi.2018.00409] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2018] [Accepted: 11/28/2018] [Indexed: 01/01/2023] Open
Abstract
Background: Blood biomarkers may aid in recruitment to clinical trials of Alzheimer's disease (AD) modifying therapeutics by triaging potential trials participants for amyloid positron emission tomography (PET) or cerebrospinal fluid (CSF) Aβ and tau tests. Objective: To discover a plasma proteomic signature associated with CSF and PET measures of AD pathology. Methods: Liquid chromatography-tandem mass spectrometry (LC-MS/MS) based proteomics were performed in plasma from participants with subjective cognitive decline (SCD), mild cognitive impairment (MCI), and AD, recruited to the Amsterdam Dementia Cohort, stratified by CSF Tau/Aβ42 (n = 50). Technical replication and independent validation were performed by immunoassay in plasma from SCD, MCI, and AD participants recruited to the Amsterdam Dementia Cohort with CSF measures (n = 100), MCI participants enrolled in the GE067-005 study with [18F]-Flutemetamol PET amyloid measures (n = 173), and AD, MCI and cognitively healthy participants from the EMIF 500 study with CSF Aβ42 measurements (n = 494). Results: 25 discovery proteins were nominally associated with CSF Tau/Aβ42 (P < 0.05) with associations of ficolin-2 (FCN2), apolipoprotein C-IV and fibrinogen β chain confirmed by immunoassay (P < 0.05). In the GE067-005 cohort, FCN2 was nominally associated with PET amyloid (P < 0.05) replicating the association with CSF Tau/Aβ42. There were nominally significant associations of complement component 3 with PET amyloid, and apolipoprotein(a), apolipoprotein A-I, ceruloplasmin, and PPY with MCI conversion to AD (all P < 0.05). In the EMIF 500 cohort FCN2 was trending toward a significant relationship with CSF Aβ42 (P ≈ 0.05), while both A1AT and clusterin were nominally significantly associated with CSF Aβ42 (both P < 0.05). Conclusion: Associations of plasma proteins with multiple measures of AD pathology and progression are demonstrated. To our knowledge this is the first study to report an association of FCN2 with AD pathology. Further testing of the proteins in larger independent cohorts will be important.
Collapse
Affiliation(s)
- Sarah Westwood
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Alison L. Baird
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Abdul Hye
- Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kigndom
- Biomedical Research Unit for Dementia, NIHR Biomedical Research Centre for Mental Health, South London and Maudsley NHS Foundation Trust, London, United Kingdom
| | - Nicholas J. Ashton
- Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kigndom
- Biomedical Research Unit for Dementia, NIHR Biomedical Research Centre for Mental Health, South London and Maudsley NHS Foundation Trust, London, United Kingdom
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | | | - Sneha N. Anand
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Benjamine Liu
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Danielle Newby
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Chantal Bazenet
- Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kigndom
| | - Steven J. Kiddle
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- MRC Biostatistics Unit, Cambridge Biomedical Campus, Cambridge Institute of Public Health, University of Cambridge, Cambridge, United Kingdom
| | - Malcolm Ward
- Proteomics Facility, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
| | - Ben Newton
- GE Healthcare Life Sciences Core Imaging, London, United Kingdom
| | - Keyur Desai
- Biosciences, GE Global Research, Niskayuna, NY, United States
| | | | - Michelle Zanette
- GE Healthcare Life Sciences Core Imaging, Marlborough, MA, United States
| | - Daniela Galimberti
- Neurodegenerative Diseases Unit, Centro Dino Ferrari, University of Milan, Milan, Italy
- Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Lucilla Parnetti
- Center for Memory Disorders and Laboratory of Clinical Neurochemistry, Neurology Clinic, University of Perugia, Perugia, Italy
| | - Alberto Lleó
- Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Susan Baker
- Janssen Neuroscience Research & Development, Titusville, NJ, United States
| | - Vaibhav A. Narayan
- Janssen Neuroscience Research & Development, Titusville, NJ, United States
| | - Wiesje M. van der Flier
- Department of Neurology, Alzheimer Centre, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, Netherlands
- Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, Netherlands
| | - Philip Scheltens
- Department of Neurology, Alzheimer Centre, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, Netherlands
| | - Charlotte E. Teunissen
- Department of Clinical Chemistry, Neurochemistry Lab and Biobank, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, Netherlands
| | - Pieter Jelle Visser
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Simon Lovestone
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| |
Collapse
|