Study on Biomarkers for Early Diagnosis of Alzheimer's Disease

Official title

Study on Body Fluid, Gene and Neuroimaging Biomarkers for Early Diagnosis of Alzheimer's Disease

Overview

The project of Bio-AD is a population- based cohort study among the elderly in China. The project includes not only Alzheimer's disease (AD including familial AD and sporadic AD), but also other clinical stage of AD, as well as elderly people with normal cognitive function. The project will collect, detect and screen the special biomarkers at different clinical stage of AD based on body fluid, gene and brain image. The standard and consistent assessment protocols are employed to obtain clinical, cognitive, genetic, neuroimaging and biospecimen data. The purpose of this project is to establish a panel of biomarkers which could be used to diagnose AD at the early stage, and to establish a risk prediction models for AD to predict the 5-years risk of the onset and progression of AD among elderly population in China.

Detailed description

1. Set up a large population- based cohort including AD, MCI, pre-MCI, other neurodegenerative diseases, and elderly individuals with normal cognitive function. 2. Collect the information of clinical and neuropsychological assessment, individual traits and social environmental factors, and neuroimaging data, as well as the biological samples, such as peripheral blood and cerebrospinal fluid. 3. Screen biomarkers with high specificity and sensitivity from peripheral blood, cerebrospinal fluid and neuroimaging to distinguish different clinical stages of AD at baseline. 4. Screen the AD-associated gene and their risk variants. 5. Establish a panel of AD-specific biomarkers for the preliminary development of diagnostic kit. 6. Identify AD-relevant factors and the special biomarkers to create a preliminary risk models to predict the onset and progression of AD. 7. Follow up the cohort for next 5 years and collect the multiple information and biological samples each year to validate and revise the risk prediction models and the diagnostic kit of AD.

Primary outcome measures

• A multiple diagnostic kit for early diagnosis of AD. [Time frame: An Average of 1 year]
• A 5-years risk prediction model for onset and progression of AD among elderly population in China. [Time frame: An Average of 1 year]

Secondary outcome measures (4)

• A panel of biomarker with high specificity and sensibility [Time frame: An Average of 1 year]
• AD-associated genes in Chinese. [Time frame: An Average of 1 year]
• Neuroimaging biomarkers for AD [Time frame: An Average of 1 year]
• Risks and protective factors for AD among elderly in China [Time frame: An Average of 1 year]

Eligibility criteria

Inclusion criteria

• Written informed consent obtained from participant or legal guardian prior to any study-related procedures.
• Aged 18 (inclusive) or older.
• Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision (DSM-IV-R). The diagnosis of AD is made using the National Institute of Neurologic and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association (NINCDS- ADRDA) or National Institute on Aging and the Alzheimer's Assocation (NIA-AA) criteria. A diagnosis of mild cognitive impairment (MCI) is assigned according to Petersen criteria. A diagnosis of pre-MCI group is assigned by β-Amyloid positive or APOE ε4 carrier or complains of cognitive impairment, but not up to MCI or cognitive impairment. Normal cognitive function assessed/evaluated by MMSE, CDR and other cognitive function scales.
• Follow up 5 years and collect the information.

Exclusion criteria

• Under age 18.
• Medical or psychiatric illness that would interfere in completing initial and follow-up visits.
• No one can serve as a study informant.
• With current or past neurological or psychiatric illnesses such as schizophrenia, epilepsy, brain tumors, severe head trauma and other diseases which can induce dementia.
• Refused to complete a cognitive test and provide biospecimen.
• With history of alcohol or drug abuse.

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: Yes

Study design

Observational model

Cohort

Study locations

China · 1 center

• Xuanwu Hospital of Capital Medical University — Beijing

Publications

• Jia L, Fu Y, Shen L, Zhang H, Zhu M, Qiu Q, Wang Q, Yan X, Kong C, Hao J, Wei C, Tang Y, Qin W, Li Y, Wang F, Guo D, Zhou A, Zuo X, Yu Y, Li D, Zhao L, Jin H, Jia J. PSEN1, PSEN2, and APP mutations in 404 Chinese pedigrees with familial Alzheimer's disease. Alzheimers Dement. 2020 Jan;16(1):178-191. doi: 10.1002/alz.12005. PMID 31914229
• Jia L, Quan M, Fu Y, Zhao T, Li Y, Wei C, Tang Y, Qin Q, Wang F, Qiao Y, Shi S, Wang YJ, Du Y, Zhang J, Zhang J, Luo B, Qu Q, Zhou C, Gauthier S, Jia J; Group for the Project of Dementia Situation in China. Dementia in China: epidemiology, clinical management, and research advances. Lancet Neurol. 2020 Jan;19(1):81-92. doi: 10.1016/S1474-4422(19)30290-X. Epub 2019 Sep 4. PMID 31494009
• Jia L, Qiu Q, Zhang H, Chu L, Du Y, Zhang J, Zhou C, Liang F, Shi S, Wang S, Qin W, Wang Q, Li F, Wang Q, Li Y, Shen L, Wei Y, Jia J. Concordance between the assessment of Abeta42, T-tau, and P-T181-tau in peripheral blood neuronal-derived exosomes and cerebrospinal fluid. Alzheimers Dement. 2019 Aug;15(8):1071-1080. doi: 10.1016/j.jalz.2019.05.002. PMID 31422798
• Qiu Q, Jia L, Wang Q, Zhao L, Jin H, Li T, Quan M, Xu L, Li B, Li Y, Jia J. Identification of a novel PSEN1 Gly111Val missense mutation in a Chinese pedigree with early-onset Alzheimer's disease. Neurobiol Aging. 2020 Jan;85:155.e1-155.e4. doi: 10.1016/j.neurobiolaging.2019.05.018. Epub 2019 May 31. PMID 31235344
• Shen L, Qin W, Wu L, Zhou A, Tang Y, Wang Q, Jia L, Jia J. Two novel presenilin-1 mutations (I249L and P433S) in early onset Chinese Alzheimer's pedigrees and their functional characterization. Biochem Biophys Res Commun. 2019 Aug 13;516(1):264-269. doi: 10.1016/j.bbrc.2019.05.185. Epub 2019 Jun 21. PMID 31235249
• Jia J, Li T, Yang J, Chen B, Qin W, Wei C, Song Y, Wang Q, Li Y, Jia L. Detection of plasma Abeta seeding activity by a newly developed analyzer for diagnosis of Alzheimer's disease. Alzheimers Res Ther. 2022 Feb 2;14(1):21. doi: 10.1186/s13195-022-00964-2. PMID 35109911
• Song Y, Quan M, Li T, Jia J. Serum Homocysteine, Vitamin B12, Folate, and Their Association with Mild Cognitive Impairment and Subtypes of Dementia. J Alzheimers Dis. 2022;90(2):681-691. doi: 10.3233/JAD-220410. PMID 36155508
• Gong M, Jia J. Contribution of blood-brain barrier-related blood-borne factors for Alzheimer's disease vs. vascular dementia diagnosis: A pilot study. Front Neurosci. 2022 Aug 8;16:949129. doi: 10.3389/fnins.2022.949129. eCollection 2022. PMID 36003963

Identifiers

NCT: NCT04575337 · Bio-AD

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗