PUMCH Dementia Longitudinal Cohort Study
Study Details
Study Description
Brief Summary
The PUMCH Dementia Cohort is a hospital-based, observational study of Chinese elderly with cognitive impairment.
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
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Detailed Description
In China, the burden of dementia is increasing, which has a major impact on medical care, society, and the economy. In order to solve this important public health problem, a cohort study of cognitive impairment in the elderly should be carried out. We designed an age stratified dementia cohort and tried to to clarify the risk and prognostic factors, disease characteristics, cognitive evaluation, biomarkers, diagnosis, treatment of dementia and its subtypes in China. It is of great significance to establish a relatively comprehensive dementia database, improve the level of clinical diagnosis and treatment of cognitive impairment, and formulate prevention and treatment strategies for dementia.
Baseline data collection and cohort establishing: Detailed clinical information including demographic data, clinical history, past history and physical examination are collected. Formatted neuropsychological battery is used in all patients, including screening tests (MMSE, MoCA-PUMCH, ADL, HAD) and domain specific evaluation (Memory, executive function, visual spatial, calculation, language). Samples including serum, CSF, urine, skin, saliva are stored. Every patient is followed up every 6 months. Autopsy brain tissue will be collected if patients died.
The main contents of this study are following:
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Explore the relationship between lifestyles, stress and dementia.
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Assess risk factors for dementia.
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Evaluating behavioral and psychological symptoms of dementia.
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Improve the long-term follow-up cohort stratified by age and dementia type and construct the high standard information and sample bank.
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Explore biomarkers of different groups of dementia, incorporating neuropsychology, multi-model neuroimaging, metabolics and proteomics based fluid biomarkers as well as genetic biomarkers. Autopsy after clinical follow up help to verify the biomarkers.
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Establish and promote standardized and consistent biomarker detection methods.
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Dementia education and training.
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Use machine learning methods to establish computer-assisted dementia diagnosis system and evaluation system. Establish prediction models for the progression of dementia.
Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| Early onset dementia Dementia patients with onset age lower than 65y/o |
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| Late onset dementia Dementia patients with onset age between 65y/o and 85y/o |
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| Oldest old dementia Dementia patients with onset age older than 85y/o |
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| Cognitive normal control Normal Aging with normal cognitive function |
Outcome Measures
Primary Outcome Measures
- The incidence of dementia [Through study completion,an average of 10-20 years]
Through follow up of cognitive normal control ,to find the incidence of dementia in PUMCH cohort
- The relationship between lifestyles, stress (stressful events and their degree) and dementia [Through study completion,an average of 10 years]
Analysis of the relationship between lifestyles, stress and progression of dementia. Discover lifestyle factors (such as diet, residential environment, physical activity, hobbies, and sleep) and stress (stressful events and their degree) by using a questionnaire designed by PUMCH
- Risk factors for dementia [Through study completion,an average of 10-20 years]
Collect the risk factors in normal control and analysis the relationship after diagnosis of dementia
- Cognitive decline [Through study completion,an average of 10-20 years]
Use a systematic neuropsychological battery designed by PUMCH
- Functional decline [Through study completion,an average of 10-20 years]
Use Activity of Daily Living Scale（ADL）
- Changes in the Neuropsychiatric Index (NPI) [Through study completion,an average of 10 years]
In dementia patients, analysis their behavioral and psychological symptoms and the related factor. Discover the relationship between behavioral and psychological symptoms and biomarkers for dementia.
- Changes in the Hospital Anxiety and Depression scale (HAD) [Through study completion,an average of 10 years]
In dementia patients, analysis their behavioral and psychological symptoms and the related factor. Discover the relationship between behavioral and psychological symptoms and biomarkers for dementia.
- Changes in the Cornell Scale for dementia [Through study completion,an average of 10 years]
In dementia patients, analysis their behavioral and psychological symptoms and the related factor. Discover the relationship between behavioral and psychological symptoms and biomarkers for dementia.
- Tau and Beta-amyloid biomarkers in CSF [Through study completion,an average of 10 years]
Concentration ( pg/mL) of beta-amyloid, tau and phospho-tau in cerebrospinal fluid (CSF) of patients with dementia and controls
- Tau biomarkers in serum [Through study completion,an average of 10 years]
Concentration ( pg/mL) of tau in serum of patients with dementia and controls
- CSF collection for assessing new dementia biomarker [Through study completion,an average of 10 years]
Use collected CSF to assess new biomarkers.
- Serum collection for assessing new dementia biomarker [Through study completion,an average of 10 years]
Use collected serum to assess new biomarkers.
- Urine collection for assessing new dementia biomarker [Through study completion,an average of 10 years]
Use collected urine to assess new biomarkers.
- Skin collection for assessing new dementia biomarker [Through study completion,an average of 10 years]
Use collected skin for finding new biomarkers.
- Biomarker differences of dementia [Through study completion,an average of 10 years]
The differences of biomarkers in patients with different dementia.
- Incorporating age stratified biomarkers into the diagnosis of dementia [Through study completion,an average of 10 years]
Comparing the relationships between biomarkers and clinical presentations. Incorporate biomarkers into the accurate and early diagnosis of dementia
- Dementia education and training [Through study completion,an average of 10 years]
Observe the function of education and training in the treatment and care of dementia patients
- Dementia diagnosis system and evaluation system [Through study completion,an average of 10 years]
Use machine learning methods to establish computer-assisted dementia diagnosis system and evaluation system. Establish prediction models for the progression of dementia
Eligibility Criteria
Criteria
Inclusion Criteria:
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Neurodegenerative dementia diagnosis based on 2011 NIA-AA criteria of Dementia
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Fixed care giver and can follow up regularly
Exclusion Criteria:
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Not demented, including MCI
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Systemic severe diseases and severe vision or hearing problem effecting follow up and neuropsychological evaluation
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Without fixed care giver
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Reject informed consent
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Expected life shorter than 2 years
Contacts and Locations
Locations
| Site | City | State | Country | Postal Code | |
|---|---|---|---|---|---|
| 1 | Peking Union Medical College Hospital | Beijing | China |
Sponsors and Collaborators
- Peking Union Medical College Hospital
Investigators
- Principal Investigator: Chenhui Mao, Doctor, Peking Union Medical College Hospital
Study Documents (Full-Text)
None provided.More Information
Publications
- Jack CR Jr, Bennett DA, Blennow K, Carrillo MC, Dunn B, Haeberlein SB, Holtzman DM, Jagust W, Jessen F, Karlawish J, Liu E, Molinuevo JL, Montine T, Phelps C, Rankin KP, Rowe CC, Scheltens P, Siemers E, Snyder HM, Sperling R; Contributors. NIA-AA Research Framework: Toward a biological definition of Alzheimer's disease. Alzheimers Dement. 2018 Apr;14(4):535-562. doi: 10.1016/j.jalz.2018.02.018. Review.
- McKhann GM, Albert MS, Grossman M, Miller B, Dickson D, Trojanowski JQ; Work Group on Frontotemporal Dementia and Pick's Disease. Clinical and pathological diagnosis of frontotemporal dementia: report of the Work Group on Frontotemporal Dementia and Pick's Disease. Arch Neurol. 2001 Nov;58(11):1803-9.
- Norton S, Matthews FE, Barnes DE, Yaffe K, Brayne C. Potential for primary prevention of Alzheimer's disease: an analysis of population-based data. Lancet Neurol. 2014 Aug;13(8):788-94. doi: 10.1016/S1474-4422(14)70136-X. Erratum in: Lancet Neurol. 2014 Nov;13(11):1070.
- Olsson B, Lautner R, Andreasson U, Öhrfelt A, Portelius E, Bjerke M, Hölttä M, Rosén C, Olsson C, Strobel G, Wu E, Dakin K, Petzold M, Blennow K, Zetterberg H. CSF and blood biomarkers for the diagnosis of Alzheimer's disease: a systematic review and meta-analysis. Lancet Neurol. 2016 Jun;15(7):673-684. doi: 10.1016/S1474-4422(16)00070-3. Epub 2016 Apr 8. Review.
- Rosenberg A, Ngandu T, Rusanen M, Antikainen R, Bäckman L, Havulinna S, Hänninen T, Laatikainen T, Lehtisalo J, Levälahti E, Lindström J, Paajanen T, Peltonen M, Soininen H, Stigsdotter-Neely A, Strandberg T, Tuomilehto J, Solomon A, Kivipelto M. Multidomain lifestyle intervention benefits a large elderly population at risk for cognitive decline and dementia regardless of baseline characteristics: The FINGER trial. Alzheimers Dement. 2018 Mar;14(3):263-270. doi: 10.1016/j.jalz.2017.09.006. Epub 2017 Oct 19.
- PUMCH Dementia Cohort