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| Name | Class |
|---|---|
| Hong Kong Center for Neurodegenerative Diseases | OTHER |
| Tung Wah College | OTHER |
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Population aging is reshaping societal dynamics and presents significant global challenges. By 2050, it is projected that 1.6 billion people worldwide will be over the age of 65. Given that aging is the primary risk factor for many common chronic diseases, reducing the burden of age-related illnesses and promoting healthy aging have become critical public health priorities. Notably, Hong Kong has one of the largest proportions of elderly and the highest life expectancy in the world. Dementia, particularly Alzheimer's disease (AD), is a multifaceted condition influenced by both biological and behavioral factors. There is a paucity of robust, community-based prospective data in ethnic Chinese populations that integrate clinical and cognitive measures with objective biomarkers and neuroimaging, especially at earlier stages such as mild cognitive impairment (MCI) and early AD. This community-based project aims to establish a cohort of elderly in Hong Kong, with longitudinal follow-up for 2-3 years. A key strength of this research is the incorporation of a panel of blood biomarkers, which will provide a less invasive and more affordable screening tool to identify Alzheimer's disease at a much earlier stage in the community. Additionally, through benchmark with MRI and PET imaging gold standard, these biomarkers have the potential to predict the conversion risk 1) from clinically normal to mild cognitive impairment and Alzheimer's disease (AD dementia); 2) from clinically MCI to Alzheimer's disease (MCI-AD dementia) or remain static; and differentiate non-AD dementia from Alzheimer's disease (dementia-AD). Collectively, these data will facilitate monitoring of aging processes and cognitive decline, help to identify candidate modifiable factors associated with resilience, and generate a de-identified, Chinese-specific resource to advance healthy aging in Hong Kong.
Introduction Population aging is a major global challenge with estimated 1.6 billion people will be over 65 by 2050. Aging is the main risk factor for many chronic diseases, including Alzheimer's disease (AD). Hong Kong features one of the world's largest proportions of older adults and highest life expectancy and therefore, Hong Kong will face a particular heavy burden on caring of elderly citizens with dementia. Hence, to better planning for caring the aging population within the community, there is a need for robust, community-based data integrating clinical, cognitive, biomarker, and neuroimaging metrics in ethnic Chinese populations. Research Objectives
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Cognitively normal (CN) | Participants with normal cognition |
| |
| Mild cognitive impairment (MCI) | Participants with MCI |
| |
| Dementia | Participants with dementia |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Observational | Other | Clinical profile, blood collection, cognitive assessment, MRI and PET imaging |
|
| Measure | Description | Time Frame |
|---|---|---|
| Blood biomarker (baseline) | Blood-based biomarkers provide a minimally invasive approach for detecting Alzheimer's disease-related pathology and for monitoring disease progression. Peripheral blood will be analyzed for a core panel that includes p tau217 and a multiplex 21 protein panel, with results generated under predefined quality control specifications. | Baseline |
| Follow up blood biomarker | Proportion of longitudinally selected participants who complete the repeat fasting blood collection; report completion rate and reasons for non-completion. | 24 to 36 months after baseline |
| Measure | Description | Time Frame |
|---|---|---|
| Change in MoCA from baseline to follow-up | Montreal Cognitive Assessment (MoCA), total score 0-30 (higher scores indicate better cognitive function; lower scores indicate worse function); mean change in MoCA total score is calculated based on the difference between MoCA scores at baseline and follow-up visits | Baseline to approximately 24-36 months |
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Inclusion Criteria:
Exclusion Criteria:
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Community elderly dwellings
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Nancy Ip, PhD | Contact | +852-23587304 | boip@ust.hk | |
| Kin Ying Mok, PhD | Contact | +852-23563164 | mok@ust.hk |
| Name | Affiliation | Role |
|---|---|---|
| Nancy Ip, PhD | Hong Kong University of Science and Technology | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Hong Kong University of Science and Technology | Recruiting | Hong Kong | China |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 34032364 | Background | Jiang Y, Zhou X, Ip FC, Chan P, Chen Y, Lai NCH, Cheung K, Lo RMN, Tong EPS, Wong BWY, Chan ALT, Mok VCT, Kwok TCY, Mok KY, Hardy J, Zetterberg H, Fu AKY, Ip NY. Large-scale plasma proteomic profiling identifies a high-performance biomarker panel for Alzheimer's disease screening and staging. Alzheimers Dement. 2022 Jan;18(1):88-102. doi: 10.1002/alz.12369. Epub 2021 May 25. | |
| 38183344 |
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blood
| Time to cognitive progression | Time from baseline to clinically adjudicated progression, defined as CN to MCI or dementia, or MCI to dementia, assessed over up to 36 months. | Baseline to approximately 24-36 months |
| Multimodal imaging data collection | Proportion of invited imaging-subset participants who complete planned baseline MRI and amyloid/tau PET according to protocol; repeat completion rate reported at follow-up. | Baseline (PET/MRI within 3-6 months of baseline blood) and repeat at approximately 24-36 months |
| Background |
| Jiang Y, Uhm H, Ip FC, Ouyang L, Lo RMN, Cheng EYL, Cao X, Tan CMC, Law BCH, Ortiz-Romero P, Puig-Pijoan A, Fernandez-Lebrero A, Contador J, Mok KY, Hardy J, Kwok TCY, Mok VCT, Suarez-Calvet M, Zetterberg H, Fu AKY, Ip NY. A blood-based multi-pathway biomarker assay for early detection and staging of Alzheimer's disease across ethnic groups. Alzheimers Dement. 2024 Mar;20(3):2000-2015. doi: 10.1002/alz.13676. Epub 2024 Jan 6. |
| ID | Term |
|---|---|
| D000544 | Alzheimer Disease |
| D060825 | Cognitive Dysfunction |
| D003704 | Dementia |
| ID | Term |
|---|---|
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
| D009422 | Nervous System Diseases |
| D024801 | Tauopathies |
| D019636 | Neurodegenerative Diseases |
| D019965 | Neurocognitive Disorders |
| D001523 | Mental Disorders |
| D003072 | Cognition Disorders |
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| ID | Term |
|---|---|
| D057832 | Watchful Waiting |
| ID | Term |
|---|---|
| D017063 | Outcome Assessment, Health Care |
| D010043 | Outcome and Process Assessment, Health Care |
| D011787 | Quality of Health Care |
| D006298 | Health Services Administration |
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