Clinical trial NCT05697588: Exploring the Predicting Biomarkers From Mild Cognitive Impairment to Dementia (EBMID)
Official title: Studies on Biomarkers for Mild Cognitive Impairment Conversion to Dementia
Study type: OBSERVATIONAL
Overall status: NOT_YET_RECRUITING
Conditions: Biomarkers
MCI Conversion to Dementia
Lead sponsor: Xuanwu Hospital, Beijing
Sponsor class: OTHER
Collaborators: name: Beihang University
name: Chinese PLA General Hospital
name: Chongqing Medical University
name: Tianjin Huanhu Hospital
name: The Affiliated Zhongshan Hospital of Dalian University
name: First Hospital of Shijiazhuang City
name: Jilin University
First posted: 2023-01-26
Enrollment: 900
Sex: ALL
Minimum age (years): 50
Maximum age (years): 85
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: This project will enroll about 900 patients with mild cognitive impairment (MCI), who meet the inclusion and exclusion criteria, including MCI due to AD (AD-MCI) \>350 participants, MCI due to frontotemporal dementia (FTD-MCI) \>150 participants, MCI due to dementia with Lewy bodies (DLB-MCI) \>150 participants, MCI due to vascular dementia (VaD-MCI) \>250 participants.

Brief summary: Mild cognitive impairment (MCI) represents a transitional stage between healthy aging and dementia, and affects more than 15% of the population over the age of 60 in China. About 15% patients with MCI could progress into dementia after two years and about one-third develop into dementia within five years, which will lead to suffering, as well as staggering economic and care burden. So, exploring the predicting biomarkers from MCI to dementia to identify and delay progression to dementia at an early stage is of great social and clinical significance. Some reports based on a single neural biomarker suggest that risk models can predict the conversion of MCI to dementia, but no widely recognized prediction models basing on multiple complex markers have been used in clinical practice. The objectives of this study are to outline the spectrum of MCI transforming into dementia through a 5-year prospective longitudinal cohort study; Secondly, screening biomarkers for MCI transmit to dementia are based on clinical symptoms, neuropsychology, neuroimaging, neuroelectrophysiology, and humoral markers tests data.

Detailed description: The 900 patients with MCI will be enrolled in this study, and data will be collected in the baseline including demographics, clinical symptoms, assessment of neuropsychology, neuroimaging, neuroelectrophysiology, blood samples, cerebrospinal fluid, etc. The changes of these data were dynamically observed through an annual follow-up for 5 years. According to the neuropsychological evaluation results of follow-up, the subjects were divided into MCI progression (MCI-P) and MCI stabilization (MCI-S). Difference in clinical phenotype, neuropsychology, electrophysiology, neuroimaging, and body fluid multi-omics indicators between the two subtypes were compared and analyzed. The neuropsychological testes in patients with MCI included some neuropsychological scales such as, Clinical Dementia Rating (CDR), Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), etc. Multi-model neuroimaging evaluation screen the candidate neuroimaging markers, including structure and functional brain magnetic resonance imaging (MRI), Diffusion tensor image (DTI), 18 F-2-fluro-D-deoxy-glucose-positron emission tomography (18F-FDG-PET)，Amyloid-PET and tau-PET. To exploring neuroelectrophysiology biomarkers collect the data on polysomnography, resting state electroencephalogram, and evoked potentials (P1, N1, P2, N2, etc.). ELISA, SIMOA and other analytical methods were used to detect the contents related to MCI conversion to dementia in the blood, cerebrospinal fluid, urine, saliva and feces. Using statistic and machine learning methods, the biomarkers and their combinations from MCI transmit to dementia could be obtained, and it can contribute to the construction of a risk prediction model and early warning evaluation system of MCI transmit to dementia.

Eligibility criteria: Inclusion Criteria:

* Male or female patients aged ≥50 and ≤85 years;

  * Meet the diagnostic criteria for dementia or MCI; ③ Neuropsychological score: MMSE 15-28 points, CDR≤1 point; ④ The patients and their families were informed and signed the informed consent.

Exclusion Criteria:

* There are other neurological diseases that can cause brain dysfunction (such as depression, brain tumors, Parkinson's disease disease, metabolic encephalopathy, encephalitis, multiple sclerosis, epilepsy, traumatic brain injury, normal intracranial pressure hydrocephalus, etc.);

  * There are other systemic diseases that can cause cognitive impairment (such as hepatic insufficiency, renal insufficiency, Thyroid dysfunction, severe anemia, folic acid or vitamin B12 deficiency, syphilis, HIV infection, alcohol and drug abuse, etc.);

    * Suffering from a disease that cannot cooperate with the completion of cognitive examination; ④ There are contraindications to nuclear magnetic resonance;

      * There is mental and neurodevelopmental delay; ⑥ refuse to draw blood; ⑦ Refuse to sign the informed consent.

Primary outcomes:
measure: Rate of change in global cognition as measured by Clinical Dementia Rating (CDR).
timeFrame: 5 years
measure: Rate of change in global cognition as measured by Mini-Mental State Examination (MMSE).
timeFrame: 5 years
measure: Rate of change in global cognition as measured by Montreal Cognitive Assessment (MoCA).
timeFrame: 5 years
measure: Rate of change in the severity of cognitive impairment as assessed by Alzheimer's Disease Assessment Scale-Cognitive section (ADAS-cog).
timeFrame: 5 years
measure: Rate of change in memory function as assessed by World Health Organization-Un-iversity of California, Los Angeles, auditory verbal learning test (WHO-UCLA AVLT).
timeFrame: 5 years
measure: Rate of change in language function as assessed by Boston Naming Test (BNT).
timeFrame: 5 years
measure: Rate of change in psychobehavioral symptoms as assessed by Neuropsychiatric Inventory (NPI).
timeFrame: 5 years
measure: Rate of change in activities of daily living as assessed by Alzheimer's Disease Cooperative Study-Activity of Daily Living (ADCS-ADL).
timeFrame: 5 years
Secondary outcomes:
measure: Rate of change in differential protein content as assessed by CSF and blood samples.
timeFrame: 5 years
measure: Rate of change in small molecule metabolite as assessed by stool and urine.
timeFrame: 5 years
measure: Rate of change in metagenomes as assessed by stool samples.
timeFrame: 5 years
measure: Rate of change in classical AD protein biomarkers as assessed by CSF and blood samples.
timeFrame: 5 years
measure: Rate of change in sleep apnea hypopnea as assessed by Standard night Polysomnography.
timeFrame: 5 years
measure: Rate of change in brain resting state activity as assessed by Resting state electroencephalogram (EEG).
timeFrame: 5 years
measure: Rate of change in brain stem damage as assessed by Evoked potentials (EPs).
timeFrame: 5 years
measure: Rates of change in brain structure using brain structure magnetic resonance imaging (sMRI).
timeFrame: 5 years
measure: Rates of change in brain function characteristics using brain functional MRI (fMRI).
timeFrame: 5 years
measure: Rates of change in white matter fiber bundle using Diffusion tensor image (DTI).
timeFrame: 5 years
measure: Rates of change in glucose metabolism as measured by 18F-FDG-PET.
timeFrame: 5 years
measure: Rates of change in amyloid deposition as measured by amyloid-PET
timeFrame: 5 years
measure: Rates of change in tau deposition as measured by tau-PET.
timeFrame: 5 years
Other outcomes:
Locations:
city: Beijing
country: China
facility: Xuan Wu Hospital of Capital Medical University
state: Beijing
Study officials:
affiliation: Xuan Wu Hospital of Capital Medical University
name: Cuibai Wei
role: PRINCIPAL_INVESTIGATOR
References: